text
stringlengths 87
880k
| pmid
stringlengths 1
8
| accession_id
stringlengths 9
10
| license
stringclasses 2
values | last_updated
stringlengths 19
19
| retracted
stringclasses 2
values | citation
stringlengths 22
94
| decoded_as
stringclasses 2
values | journal
stringlengths 3
48
| year
int32 1.95k
2.02k
| doi
stringlengths 3
61
| oa_subset
stringclasses 1
value |
|---|---|---|---|---|---|---|---|---|---|---|---|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science 10.1289/ehp.6367ehp0112-00169715579416ResearchArticlesUse of Pharmacokinetic Modeling to Design Studies for Pathway-Specific Exposure Model Evaluation Hu Ye 1Akland Gerry G. 1Pellizzari Edo D. 1Berry Maurice R. 2Melnyk Lisa Jo 21Analytical and Chemical Sciences, Research Triangle Institute, Research Triangle Park, North Carolina, USA2National Exposure Research Laboratory, U.S. Environmental Protection Agency, Cincinnati, Ohio, USAAddress correspondence to Y. Hu, Analytical and Chemical Sciences, Research Triangle Institute, P.O. Box 12194, Research Triangle Park, NC 27709 USA. Telephone: (919) 541-8799. Fax: (919) 541-7208. E-mail:
[email protected] work is partially supported by the internal fund of Research Triangle Institute (RTI). The U.S. Environmental Protection Agency through its Office of Research and Development has also partially funded and collaborated in the research described herein under contract 68-D99-012 to RTI. It has been subjected to agency review and approved for publication. Mention of trade names or commercial products does not constitute an endorsement or recommendation for use.
The authors declare they have no competing financial interests.
12 2004 16 8 2004 112 17 1697 1703 1 4 2003 16 8 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Validating an exposure pathway model is difficult because the biomarker, which is often used to evaluate the model prediction, is an integrated measure for exposures from all the exposure routes and pathways. The purpose of this article is to demonstrate a method to use pharmacokinetic (PK) modeling and computer simulation to guide the design of field studies to validate pathway models. The children’s dietary intake model is discussed in detail as an example. Three important aspects are identified for a successful design to evaluate the children’s dietary intake model: a) longitudinally designed study with significant changes in the exposure for the route/pathway of interest, b) short biologic half-life of the selected chemical, and c) surface loading of the selected chemical at sufficient levels. Using PK modeling to guide a study design allowed a path-specific exposure model to be evaluated using urinary metabolite biomarkers.
dietary intakeexposurepesticidepharmacokinetic (PK) modelingstudy design
==== Body
Modeling is often the only cost-effective tool for making exposure and risk assessments; however, an evaluation of such modeling is difficult, especially if it is for a pathway-specific model such as a dietary exposure model. A biomarker, such as urinary metabolite, which is often used to evaluate a model prediction, is an integrated measure of exposures from all routes, including inhalation, ingestion, and dermal. Biomarkers also have inherent problems such as large intra- and interindividual variabilities and unclear metabolic pathways. These uncertainties complicate the interpretation of biomarker measurements relative to the routes responsible for the exposures. Furthermore, the detection limits for urinary metabolite biomarkers are often not low enough to obtain a measurement, producing a substantial number of nonmeasurable observations, which make model validation impossible.
Despite these problems, the demand for model evaluation is increasing (Oreskes 1998). Biomarkers have been used to evaluate various exposure models, such as a lead exposure model (Zaragoza and Hogan 1998), a dietary cadmium model (Choudhury et al. 2001), and a dietary methyl mercury intake model (Ponce et al. 1998). In all these studies, however, pharmacokinetic (PK) modeling was used to provide interpretations for exposure and biomarker measurement. The potential of PK modeling in guiding a study design for model evaluation was not explored.
One of the problems in children’s exposure studies is assessing dietary exposure. Because children touch foods with their hands, excess dietary intake could result from hand-to-food, surface-to-food, and hand-to-surface-to-food contacts in contaminated homes (Melnyk et al. 2000). No direct method to measure this excess exposure is available, so a dietary intake model was developed (Akland et al. 2000).
Because the children’s dietary intake model is pathway specific, evaluating it has considerable challenges. PK modeling makes the evaluation possible. Unlike other model evaluation efforts, here we used PK modeling to guide the design of a field study to evaluate a pathway-specific model using urinary metabolites measured in overnight voids. The children’s dietary intake model for pesticide exposure is used as an example. The principle of using PK modeling for study design, however, should be applicable in other similar cases.
Materials and Methods
Conceptual model.
A simplified, single-compartment model that can be used in the design of a field study is shown in Figure 1. In a single-compartment model, the body receives exposures from three major routes: inhalation, ingestion, and dermal. The ingestion route receives exposures from two pathways: dietary ingestion and nondietary ingestion (caused by hand-to-mouth or object-to-mouth activities). The body eliminates the exposure through urine and other biologic routes, such as exhaled air, feces, and other body fluids.
To demonstrate how a specific pathway model can be evaluated using an overnight urine void, a hypothetical scenario (shown in Figure 2) is presented here. In this hypothetical case, a child receives discrete and varying amounts of dietary exposure, Pdietary (micrograms), from the meals (see Table 1 for a list of all terms used in this article). A child also receives a simplified constant rate for inhalation exposure, Rinhalation (micrograms per minute), assuming the child spends most of the time indoors (Lambert et al. 1993). In addition, the child receives a fairly constant nondietary ingestion exposure, Rnondietary (micrograms per minute), from hand-to-mouth or object-to-mouth activities that occur when the child is awake during the day. Finally, the child receives a constant rate of dermal exposure, Rdermal (micrograms per minute), during the day until he or she is bathed. The exposure amount and rates can be expressed as follows:
Here Pbreakfast, Plunch, and Pdinner are the amount of dietary intake from breakfast, lunch, and dinner, respectively, and T1, T2, and T3 are the timing of the meals. Edermal is the rate of dermal exposure before bathing, and T4 is the time when the child is bathed. Enondietary is the rate of nondietary exposure before bed, and T5 is the time when the child goes to the bed. Einhalation is the constant rate of inhalation exposure.
Assuming immediate and 100% absorption through all routes for a single-compartment linear model, the change in the amount of pollutant over time in the compartment can be expressed as follows:
where Pt is the amount of pollutant in the compartment, and k is the first-order biologic elimination constant, calculated by 0.693/T1/2 (T1/2 is the biologic half-life) (Schoenwald 2001). RT is the sum of Rinhalation, Rnondietary, and Rdermal. Dietary exposures from the three meals can be viewed as additional multiple bolus intake at times T1, T2, and T3.
Using the principle of superposition (Schoenwald 2001), the solution to Equation 1 can be expressed as follows:
The amount of pollutant metabolite eliminated into overnight void from 2000 hr to 0800 hr is:
where α is the fraction of pollutant that is eliminated via urine, k is the first-order biologic elimination constant, Pt is the amount of pollutant in the compartment, Mpollutant is the molecular weight of the pollutant, and Mmetabolite is the molecular weight of the urinary metabolite. Applying Equation 2 to Equation 3, the amount of metabolite in overnight urine, Yovernight, becomes
Equation 4 demonstrates that the amount of metabolite in overnight urine is an additive result of exposure from dietary ingestion, nondietary ingestion, inhalation, and dermal exposure. Therefore, if we design a study in which exposure from a specific route is varied while exposures from other routes remain the same, we will be able to investigate the exposure through this particular route. For example, if we alternate only daily dietary exposure status—that is, let the subject have dietary exposure on “dietary exposure day” (when dietary exposures are Pbreakfast, Plunch, and Pdinner) followed by “no dietary exposure day” (when dietary exposures Pbreakfast = Plunch = Pdinner = 0)—and let the exposures from other routes/pathways remain the same, then the difference of the urinary metabolites between these 2 days is a function only of dietary exposure because exposures from other routes/pathways can be canceled out. Equation 5 shows the difference in the amount of urinary metabolites measured in overnight voids after the dietary-exposure day and the no-dietary-exposure day:
Equation 5 indicates that if ΔY—the metabolite difference between overnight voids after the dietary-exposure day and the no-dietary-exposure day—is large enough to be measured, it can be used to evaluate dietary exposure differences on these days. It also indicates that to make the evaluation possible, the dietary exposures on the dietary-exposed day also need to be large; the biologic half-life of the chemical, T1/2, needs to be short because k is proportional to 1/T1/2; and a substantial fraction of the metabolites should be eliminated through the urinary pathway.
In reality, however, dietary exposure is hardly zero on the dietary exposure days, because pesticide residues in foods are inevitable. Nonetheless, with a careful design, the pesticide residue can be canceled out and the strategy can still be used, as demonstrated in the following evaluation of the children’s dietary intake model.
Children’s dietary intake model.
The major problem of assessing children’s dietary exposure is that young children often touch foods with their hands before consumption, thereby increasing contamination of the food and their intake of contaminants through the diet (Melnyk et al. 2000). Because direct methods for sampling the foods as they enter the mouths of young children are not available, a deterministic dietary intake model was developed (Akland et al. 2000). In this model, three terms are considered: a) the original contaminant residue on the food before handling (term 1), b) surface-to-food contamination as the food comes in contact with contaminated surfaces (term 2), and c) surface-to-hand-to-food contamination as the child touches the contaminated surfaces and then handles and eats foods (term 3). Term 1 has also been referred to as “direct dietary ingestion,” and terms 2 and 3 as “indirect dietary ingestion.” In this model, it is assumed that the activity parameters (AS/F, AH/F, and AS/H) are determined by food types and individual child, and transfer efficiencies (TS/F, TH/F, and TS/H) are determined by food types, surface types, and the chemical properties of the contaminants.
Details of the children’s dietary intake model have been discussed previously (Akland et al. 2000). The following is the model for a specific food item consumed after multiple touches by hands and/or surfaces.
where, assuming the pollutant of interest is a pesticide, Pfood is the dietary intake of a pesticide for one food (micrograms), U is the pesticide residue concentration (micrograms pesticide per gram food), WT is the total amount of the individual food consumed (grams), LS is the loading of the contaminant on the surface (micrograms pesticide per square centimeter), FS is the food surface area that comes in contact with the contaminated surface (square centimeters), TS/F is the surface-to-food mass transfer efficiency (dimensionless), AS/F is the surface-to-food contact frequencies, TS/H is the surface-to-hand mass transfer efficiency (dimensionless), AS/H is the surface-to-hand contact frequencies, TH/F is the hand-to-food mass transfer efficiency (dimensionless), AH/F is the hand-to-food contact frequency, HS is the total hand surface area (square centimeters), and PH is the proportion of hand surface area in contact with contaminated food. Total dietary exposure for a meal is therefore
Laboratory experiments have demonstrated measurable surface-to-food, surface-to-hand, and hand-to-food pesticide transfers (Akland et al. 2000; Edwards and Lioy 1999). Using the children’s dietary intake model Equation 6, Akland et al. (2000) estimated that the extra pesticide intake resulting from young children’s eating behaviors, terms 2 and 3, could account for up to 80% of total dietary intake if the surface loading of pesticide residue is 5 ng/cm2 or higher (Akland et al. 2000).
If proved, this result would have profound implications in pesticide regulation and exposure mitigation. However, as shown in Equation 6, the model prediction was based upon the estimation of food surfaces, the surface pesticide loading, the transfer efficiencies, and observation of children’s eating behaviors. A natural question for the model prediction is whether this model estimation is reasonable.
Using PK modeling to design a field study: children’s dietary intake model as an example.
General concept for design.
The children’s dietary intake model is a pathway model. Exposures from other routes/pathways (e.g., nondietary ingestion, inhalation, and dermal exposure) also contribute to the total urinary pesticide metabolite measurements. Therefore, using urinary biomarker measurements to evaluate the dietary intake model is difficult. To circumvent the problem, the strategy demonstrated in Equation 5 can be followed, as outlined below.
According to the children’s dietary intake model Equation 6, the dietary exposure consists of three terms: residue in food before handling (term 1), surface-to-food transfer (term 2), and surface-to-hand-to-food transfer (term 3). On a day when the child is allowed to eat in an unrestricted normal setting, the child receives environmental exposures through inhalation, dietary ingestion, nondietary ingestion, and dermal exposure, and the dietary exposure includes term 1 + term 2 + term 3. Suppose we restrict a child with clean hands to a clean area and require the same foods to be eaten as on the normal day; then term 2 + term 3 are artificially forced to be approximately zero and only term 1 remains. For the convenience of discussion, henceforth the day when the child is restricted to a clean area with clean hands is referred to as “nonexposed day,” and the day when the child is allowed to eat at regular places with uncleaned hands is referred to as “exposed day.” Note that on the nonexposed day, the child still receives inhalation, nondietary ingestion, and dermal exposures. On both the exposed day and the nonexposed day, the child receives the same term 1 because the same foods are eaten on both days. The exposures the child does not receive on the nonexposed day are the surface-to-food transfer (term 2) and surface-to-hand-to-food transfer (term 3).
Theoretically, if inhalation, nondietary ingestion, and dermal exposures can be kept approximately the same on the exposed day and the nonexposed day, then according to Equation 5, the difference in the amount of urinary metabolites in overnight voids after the exposed day and the nonexposed day is a function of terms 2 and 3:
Compared with Equation 5, term 1 has been canceled out because the child’s diet is restricted so that the same foods were eaten on the exposed day and the nonexposed day. An effective method to maintain the same exposure on the exposed day and the nonexposed day for other exposure routes/pathways while alternating the exposure for the pathway of interest is to conduct the study longitudinally so that data from several exposed-day/nonexposed-day pairs can be collected from the same subjects. This way the participant can serve as his or her own control so that α and k can be assumed to be the same variable and behavior pattern variations can be kept at a minimum.
Computer simulation.
Equations 5 and 8 demonstrate how, in theory, a route/pathway exposure model can be evaluated with a study design using metabolites in overnight urinary voids where the exposure status of the route/pathway of interest is varied while the exposures from the other routes/pathways are kept the same. For field studies, the following questions are the keys for study design: How long should the half-life of a selected pesticide be? What is the minimum level of surface pesticide loading to produce a measurable metabolite concentration in the overnight void? What is the minimum level of surface pesticide loading to make indirect dietary ingestion a measurable quantity in overnight urine? Will exposures from other pathways “mask” the exposure caused by surface-to-food and surface-to-hand-to-food transfer? How large a sample size is needed?
An important assumption for the analytical solutions, Equations 5 and 8, is that exposures from inhalation, nondietary ingestion, and dermal remain constant. In reality, however, this may not be true. To investigate whether a varying inhalation–nondietary–dermal profile will mask the urinary metabolite difference caused by dietary exposure, which is the key to the study design, we need to let the exposure rates vary across time. To demonstrate, however, we only set nondietary ingestion exposure to vary across time because of its significance (Zartarian et al. 2000). Inhalation and dermal exposures remained constant.
The varying exposure rates make it impossible to use analytical solutions to Equations 5 and 8. Therefore, we conducted a computer simulation to answer the above questions needed for a field study. To conduct the computer simulation, we set all the input parameters at values for a likely scenario based upon published literature. The parameters of interest were then varied (one at a time) to observe their impact on the output variable (i.e., urinary metabolite concentration). Computer simulation was based upon numerical solution to Equation 3 using Euler’s method (Grossman 1986):
Details of the estimation/simulation of the exposure rates are given below.
For the inhalation exposure rate, exposure via inhalation per hour was estimated as follows:
where CA is the air concentration (micrograms per liter) and V is the ventilation rate for children (liters per hour).
The nondietary ingestion exposure rate mentioned here is the exposure incurred when children put contaminated hands or toys into their mouth. To simulate the varying profile, the time that a child is awake (assuming from 0800 hr to 2000 hr) was divided into equal time intervals. The nondietary exposures received in these time intervals were assumed to be normally distributed. The mean of the Rnondietary was calculated by the following formula:
where HS is the total hand/toy surface area (square centimeters), PHM is the proportion of total hand/toy surface area coming in contact with mouth, LH is the surface loading of the contaminant on the hand/toy (micrograms pesticide per square centimeter), and FrH/M is the frequency of mouthing activity during the time interval. Using published data, we estimated a mean of 0.0267 μg/min for Rnondietary. A standard deviation of 0.0179 μg/min was assumed so that > 50% of the simulated values were within one standard deviation (Table 2). Because nondietary ingestion exposure was unlikely when the child is asleep, we assumed zero nondietary exposures between 2000 hr and 0800 hr. The simulation of normally distributed Rnondietary for a 1-min time interval can be summarized in the following formula:
We ignored dermal exposure in the computer simulation for two reasons. First, exposure to diazinon (which was the pesticide of interest) through skin absorption has been reported in the literature to be minimal, although this may not be the case for other chemicals. Using radiolabeled diazinon in an acetone solution or lanolin grease on the forearm or abdomen, Wester et al. (1993) reported a total of only 2.2% skin absorption over 24 hr. Second, the purpose of the study was to guide study design rather than to establish a definitive relationship between exposure and metabolites.
Applying Equations 7, 10, and 12 to Equation 9, the model used to conduct the computer simulation was obtained. Table 2 lists the parameters used to estimate inhalation and nondietary intake.
Parameters for the children’s dietary intake model were obtained from a previous study (Akland et al. 2000). Table 3 demonstrates how to use the children’s dietary model to estimate exposure for three example foods: Cheerios, apple, and tortilla. In these examples, the pesticide residue was assumed to be 6 ng/g for all foods (National Research Council 1993). Parameters TS/H, AS/H, TH/F, AH/F, and PH were also estimated from the previous study (Akland et al. 2000). Because Cheerios are normally eaten with utensils, only term 1 is calculated for total dietary ingestion. Apple and tortilla, however, were estimated for terms 2 and 3, because these foods are normally handled by children. Other foods used to estimate a hypothetical child’s exposed day’s total dietary intake included rice (two tablespoons), chicken nuggets (four pieces), and ham (one slice). On the next unexposed day, only term 1 from the foods remained, and terms 2 and 3 were assumed to be zero. The examples shown in Table 3 demonstrate that by varying surface loading, different pesticide transfers are obtained. Therefore, the minimum level of surface pesticide loading to make indirect dietary ingestion a measurable quantity in overnight urine can be estimated.
Computer simulation was conducted using Microsoft Excel 2002 (Microsoft, Seattle, WA). Equations for calculating Rinhalation, Rnondietary, and Pdietary were keyed in, and variables of interest, such as biologic half-life, dust loading, air concentration, and nondietary intake, were set in such a way that they could be easily varied to conduct the simulation. The simulation results were also plotted using Microsoft Excel.
Sample size calculation.
Once the results from the simulation were obtained, sample size was calculated based upon a one-sided t-test of hypothesis: Yovernight void after exposed day = Yovernight void after nonexposed day versus Yovernight void after exposed day > Yovernight void after nonexposed day (Kleinbaum et al. 1988).
Results
Urinary measurements and biologic half-life.
Figure 3 shows the urinary metabolite measurements in overnight voids as point estimates (when the urine samples are collected at 0800 hr) after three exposed-day/nonexposed-day pairs with various lengths of biologic half-life of the selected chemical. The results indicated that the success of the validation depends heavily on the biologic half-life of the chosen chemical. If the chemical has a relatively short half-life, as does malathion (3–4 hr; Lyon et al. 1987) or diazinon (~ 6 hr; Iverson et al. 1975), it is possible to detect a change in the urine metabolite concentration. The amount in the plasma also returns to nonexposed levels, which makes the evaluation of the model possible. However, if the biologic half-life is longer than 16 hr, a large sample size is required because the difference between urinary metabolites after exposed days and nonexposed days becomes small and the amount in the plasma is carried over from day to day with no recovery. When the biologic half-life is as long as or longer than 27 hr (e.g., chlorpyrifos), the chance of successful validation using the exposed-day/nonexposed-day design is even smaller because there is minimal difference in the urinary metabolite concentrations. Nonetheless, an alternative design, such as 1 exposed day followed by 2 nonexposed days to let the body further eliminate the metabolites, might be possible. This alternative design, however, substantially increases field difficulties because on the 2 non-exposed days the field team would need to ensure that no term 2 or term 3 intakes occur.
Pesticide loading.
Surface pesticide loading is the source for surface-to-food and surface-to-hand-to-food transfer. Results of variations in the surface loading and urinary metabolites for a compound with a biologic half-life of 8 hr are shown in Figure 4. The results indicate that even if the chemical’s half-life is short, a preferable loading of 4 ng/cm2 or above is still needed to generate observable differences in urinary metabolites in the overnight voids after the exposed day and the nonexposed day. This level of loading can be found after indoor pesticide application (Byrne et al. 1998). However, when the loading decreases to ≤ 1 ng/cm2, it is very difficult to see the differences in the urinary metabolite amount in overnight voids after exposed and nonexposed days. In the Minnesota Children’s Pesticide Exposure Study, the mean surface chlorpyrifos loading measured by a surface press ranged from 0.03 to 32.6 ng/cm2, with a mean of 0.48 ng/cm2 (Lioy et al. 2000). These results answer the question about exposure scenario: Households with surface pesticide loading > 4 ng/cm2 are preferred for efficient design, and houses that have frequent indoor pesticide applications are most likely to meet the criterion.
Impact of exposure from other routes/pathways.
Figure 5 attempts to answer whether exposure from nondietary ingestion will mask the dietary exposure and interfere with the validation process. As shown in Figure 5, when nondietary ingestion exposure is normally distributed with a mean ± SD of 1.6 ± 1.1 μg/hr, the mask effect is small enough to allow the biomarker differences caused by dietary exposure difference to be observed. However, when nondietary ingestion exposure reaches a mean of 3.2 μg/hr, the mask effect becomes obvious because the difference in urine metabolite concentrations becomes small and inconsistent. The 1.6 μg/hr nondietary ingestion exposure was calculated by assuming a mouthing frequency of 10/hr (Reed et al. 1999; Zartarian et al. 1997), which was high compared with the current U.S. Environmental Protection Agency default (Reed et al. 1999), and for each event the child mouths a 40-cm2 surface (hand or toy) with a relatively high pesticide loading of 4 ng/cm2. Because these assumptions reflect high-end exposure, we can safely assume that the average level of nondietary activity will not significantly interfere with the model validation process. Nonetheless, to conduct a successful study, the subjects selected into the study would preferably be children who do not have frequent mouthing activities, such as thumb sucking.
Similarly, we estimated the effect of inhalation exposure (Figure 6). The results indicate that inhalation exposure does not cause a large effect on the biomarker differences, even when the hypothetical air concentration was increased to 5 μg/m3, a level only seen immediately after indoor pesticide application (Akland et al. 2000).
Sample size.
Based upon a pesticide with a biologic half-life of 8 hr and assuming a variance of 2 due to measurement errors, a minimum sample size of five pairs of the exposed day and the nonexposed day would be required in homes with pesticide loading ≥ 4 ng/cm2 to achieve a power of 80% for detecting 3-μg urinary metabolite differences.
Discussion
Evaluating a pathway model is difficult because the biomarker measurements also have contributions from other exposure routes/pathways. Here we demonstrate that a thoughtful design guided by PK modeling can make the evaluation possible. The computer simulation for the children’s dietary intake model indicated three important aspects for a successful design: longitudinal design of the study, short half-life of the selected chemical, and high pesticide surface loading. Under normal circumstances, inhalation and nondietary ingestion exposure would not mask the dietary exposure as long as they can be kept nearly constant for the nonexposed day and the exposed day.
Using the results from the computer simulation, we selected diazinon and conducted a study with three children in homes with surface loading of > 4 ng/cm2. Each child was followed for at least 6 days, yielding three or more nonexposed-day/exposed-day pairs. The study results (unpublished data) indicated that this design was successful. Using PK modeling as a guidance, field efforts to collect data to evaluate the model can be well planned, and the cost can be substantially reduced.
In this study, we used a single-compartment PK model. The single-compartment model may not be as accurate as a multicompartment PK model in prediction, but it has a practical advantage—only two parameters are essential to build a model: the biologic half-life of the chemical and the proportion of the chemical eliminated in overnight void. In many cases, these parameters are the only information one can obtain from the literature. Because of this practical advantage, the single-compartment model was recently used again by other researchers to assess pesticide exposure based on urinary biomarkers (Rigas et al. 2001). Because the purpose of this modeling approach is to provide guidance for the design of field studies, it is perhaps not necessary to expend large efforts to develop a complicated model at the front end of the study design. Our field study also indicated that the single-compartment model was adequate for designing the model evaluation study we had conducted.
This article demonstrated the case of designing a study to appropriately capture data in order to evaluate a dietary exposure model. However, we envision a similar strategy being used in other situations, such as nondietary ingestion exposure models, dermal exposure models, or inhalation exposure models.
Figure 1 Single-compartment model for exposures from different pathways.
Figure 2 Exposure functions for a hypothetical child. (A) Hypothetical inhalation exposure. (B) Hypothetical dietary intake. (C) Hypothetical nondietary exposure. (D) Hypothetical dermal exposure.
Figure 3 Effect of biologic half-life on urinary measurements in the nonexposed-day/exposed-day design. (A) Half-life = 4 hr. (B) Half-life = 8 hr. (C) Half-life = 16 hr. (D) Half-life = 27 hr.
Figure 4 Effect of surface loading on urinary metabolite measurements in the nonexposed-day/exposed-day design. (A) Surface loading = 1 ng/cm2. (B) Surface loading = 2 ng/cm2. (C) Surface loading = 4 ng/cm2. (D) Surface loading = 8 ng/cm2.
Figure 5 Effect of nondietary exposure on urinary measurements in the nonexposed-day/exposed-day design. (A) Nondietary ∼ normal distribution, mean ± SD = 0.0266 ± 0.0179. (B) Nondietary ∼ normal distribution, mean ± SD = 0.0532 ± 0.0258.
Figure 6 Effect of inhalation exposure on urinary metabolite measurements in the nonexposed-day/exposed-day design. (A) Air concentration = 0.5 μg/m3. (B) Air concentration = 5 μg/m3.
Table 1 Notations.
Abbreviation Definition
α Fraction of pollutant that is eliminated through urine
AH/F Hand-to-food contact frequencies
AS/F Surface-to-food contact frequencies
AS/H Surface-to-hand contact frequencies
AH/M Hand (toy)-to-mouth contact frequencies
CA Air concentration (μg/L)
FrH/M Frequency of mouthing activity during a time interval of interest
FS Food surface area that comes in contact with the contaminated surface (cm2)
HS Total hand surface area (cm2)
k First-order elimination rate constant
LH Loading of contaminant on hand/toy (μg contaminant/cm2)
LS Loading of contaminant on surface (μg contaminant/cm2)
Mmetabolite Molecular weight of urinary metabolite
Mpollutant Molecular weight of pollutant compound
Pbreakfast Amount of pollutant in breakfast (μg)
Plunch Amount of pollutant in lunch (μg)
Pdinner Amount of pollutant in dinner (μg)
Pfood Amount of pollutant in one food (μg)
Pmeal Amount of pollutant in one meal (μg)
Pdietary Amount of dietary exposure received from all meals (μg)
PH Proportion of hand surface area in contact with contaminated food
PHM Proportion of total hand/toy surface area coming in contact with mouth
Pt Amount of pollutant in the compartment (μg)
Rdermal Dermal exposure rate (μg/hr)
Rinhalation Inhalation exposure rate (μg/hr)
Rnondietary Nondietary ingestion exposure rate (μg/hr)
RT Sum of Rinternal, Rinhalation, and Rnondietary
T1 Timing for breakfast
T2 Timing for lunch
T3 Timing for dinner
T4 Timing for bath
T5 Timing when child goes to bed
TH/F Hand-to-food transfer efficiencies
TS/F Surface-to-food transfer efficiencies
TS/H Surface-to-hand transfer efficiencies
U Pollutant residue in food (μg/g)
V Ventilation rate for children (L/hr)
WT Total amount of food consumed (g)
Yovernight Amount of urinary metabolite in overnight void
Yovernight void after exposure day Amount of urinary metabolite in overnight void after exposed day
Yovernight void after nonexposure day Amount of urinary metabolite in overnight void after nonexposed day
Table 2 Parameters for inhalation and nondietary ingestion exposures.
Type of distribution used in simulation Variable (reference)
Inhalation exposure Constant V = 4.2 L/min
CA = 0.5 μg/m3 (Byrne et al. 1998)
Nondietary exposure Normal distribution with mean ± SD = 0.0267 ± 0.1795 μg/min for 0800–2000 hr; 0 for 2000–0800 hr HS = 200 cm2
PHM = 0.2
LH = 4 ng/cm2 (Byrne et al. 1998; Lu and Fenske 1999)
FrH/M = 10/hr (Reed et al. 1999; Zartarian et al. 1997)
Table 3 Parameters used to calculate dietary intake from Cheerios, apple, and tortilla (Akland et al. 2000).
Parameters Parameter values Dietary intake
Cheerios (half bowl)
Term 1a
R 0.006 μg/g
FT 30 g Term 1 = 0.18 μg
Pbreakfast = term 1 = 0.18 μg
Apple (1/3 apple)
Term 1
R 0.006 μg/g
FT 80 g Term 1 = 0.48
Term 2b
FS 100 cm2
LS 0.004 μg/cm2
TS/F 0.5
AS/F 1 Term 2 = 0.2
Term 3c
LS 0.004 μg/cm2
TS/H 0.4
AS/H 10
TH/F 0.03
AH/F 10
HS 200 cm2
PH 0.9 Term 3 = 0.86
Plunch = term 1 + term 2 + term 3 = 1.54
Tortilla (half of a tortilla)
Term 1
R 0.006 μg/g
FT 65 g Term 1 = 0.39
Term 2
FS 200 cm2
LS 0.004 μg/cm2
TS/F 0.5 (chair-food)
AS/F 1 Term 2 = 0.4
Term 3
LS 0.004 μg/cm2
TS/H 0.5
AS/H 20
TH/F 0.03
AH/F 20
HS 200 cm2
PH 0.9 Term 3 = 4.32
Pdinner = term 1 + term 2 + term 3 = 5.11
Using model Equation 10 to estimate dietary intake for apple.
a Term 1 = 0.006 (μg/g) × 30 (g) = 0.18 μg.
b Term 2 = 100 (cm2) × 0.004 (μg/cm2) × 0.5 × 1 = 0.2 μg.
c Term 3 = 0.004 (μg/cm2) × 0.4 × 10 × 0.03 × 10 × 200 (cm2) × 0.9 = 0.86 μg.
==== Refs
References
Akland GG Pellizzari ED Hu Y Roberds M Rohrer CA Leckie JO 2000 Factors influencing total dietary exposures of young children J Expo Anal Environ Epidemiol 10 710 722 11138663
Byrne SL Shurdut BA Saunders DG 1998 Potential chlorpyrifos exposure to residents following standard crack and crevice treatment Environ Health Perspect 106 725 731 9799188
Choudhury H Harvey T Thayer WC Lockwood TF Stiteler WM Goodrum PE 2001 Urinary cadmium elimination as a biomarker of exposure for evaluating a cadmium dietary exposure—biokinetics model J Toxicol Environ Health A 63 321 350 11471865
Edwards RD Lioy PJ 1999 The EL sampler: a press sampler for the quantitative estimation of dermal exposure to pesticides in housedust J Expo Anal Environ Epidemiol 9 521 529 10554154
Iverson F Grant D Lacroix J 1975 Diazinon metabolism in the dog Bull Environ Contam Toxicol 13 611 618 1148418
Kleinbaum D Kupper L Muller K 1988. Applied Regression Analysis and Other Multivariable Methods. Boston:PWS-KENT.
Lambert WE Samet JM Hunt WC Skipper BJ Schwab M Spengler JD 1993 Nitrogen dioxide and respiratory illness in children. Part II: Assessment of exposure to nitrogen dioxide Res Rep Health Eff Inst 58 33 50 8240759
Lioy PJ Edwards RD Freeman N Gurunathan S Pellizzari E Adgate JL 2000 House dust levels of selected insecticides and a herbicide measured by the EL and LWW samplers and comparisons to hand rinses and urine metabolites J Expo Anal Environ Epidemiol 10 327 340 10981727
Lu C Fenske RA 1999 Dermal transfer of chlorpyrifos residues from residential surfaces: comparison of hand press, hand drag, wipe, and polyurethane foam roller measurements after broadcast and aerosol pesticide applications Environ Health Perspect 107 463 467 10339446
Lyon J Taylor H Ackerman B 1987 A case report of intravenous malathion injection with determination of serum half-life J Toxicol Clin Toxicol 25 243 249 3612901
Melnyk LJ Berry MR Sheldon LS Freeman NC Pellizzari ED Kinman RN 2000 Dietary exposure of children in lead-laden environments J Expo Anal Environ Epidemiol 10 723 731 11138664
National Research Council 1993. Pesticides in the Diets of Infants and Children. Washington, DC:National Academies Press.
Oreskes N 1998 Evaluation (not validation) of quantitative models Environ Health Perspect 106 suppl 6 1453 1460 9860904
Ponce RA Bartell SM Kavanagh TJ Woods JS Griffith WC Lee RC 1998 Uncertainty analysis methods for comparing predictive models and biomarkers: a case study of dietary methyl mercury exposure Regul Toxicol Pharmacol 28 96 105 9927559
Reed KJ Jimenez M Freeman NC Lioy PJ 1999 Quantification of children’s hand and mouthing activities through a videotaping methodology J Expo Anal Environ Epidemiol 9 513 520 10554153
Rigas ML Okino MS Quackenboss JJ 2001 Use of a pharmacokinetic model to assess chlorpyrifos exposure and dose in children, based on urinary biomarker measurements Toxicol Sci 61 374 381 11353146
Schoenwald R 2001. Pharmacokinetic Principles of Dosing Adjustments. Lancaster, PA:Technomic.
Wester RC Sedik L Melendres J Logan F Maibach HI Russell I 1993 Percutaneous absorption of diazinon in humans Food Chem Toxicol 31 569 572 8349202
Zaragoza L Hogan K 1998 The integrated exposure uptake biokinetic model for lead in children: independent validation and verification Environ Health Perspect 106 suppl 6 1551 1556 9860914
Zartarian VG Ferguson AC Ong CG Leckie JO 1997 Quantifying videotaped activity patterns: video translation software and training methodologies J Expo Anal Environ Epidemiol 7 535 542 9306236
Zartarian VG Ozkaynak H Burke JM Zufall MJ Rigas ML Furtaw EJ 2000 A modeling framework for estimating children’s residential exposure and dose to chlorpyrifos via dermal residue contact and nondietary ingestion Environ Health Perspect 108 505 514 10856023
|
15579416
|
PMC1253662
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2004 Dec 16; 112(17):1697-1703
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.6367
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science 10.1289/ehp.7224ehp0112-00170415579417ResearchArticlesAssociation of Chromosomal Alterations with Arsenite-Induced Tumorigenicity of Human HaCaT Keratinocytes in Nude Mice Chien Chia-Wen 1Chiang Ming-Chang 2Ho I-Ching 3Lee Te-Chang 131Institute of Biopharmaceutical Science, National Yang Ming University, Taipei, Taiwan, Republic of China2Department of Life Science, National Central University, Taoyuan, Taiwan, Republic of China3Institute of Biomedical Sciences, Academia Sinica, Taipei, Taiwan, Republic of ChinaAddress correspondence to T.-C. Lee, Institute of Pharmaceutical Science, National Yang Ming University, Pei-Tou, Taipei 112, Taiwan, Republic of China. Telephone: 886-2-28267300. Fax: 886-2-28237583. E-mail:
[email protected] thank Y.-J. Chen (Molecular Cytogenetics Laboratory) and C.-W. Chi (Molecular Pathology Laboratory, Genome Research Center, National Yang-Ming University) for their excellent technical assistance on comparative genomic hybridization and pathologic examination.
This work was supported by grants from the National Science Council of Taiwan (NSC 90-2318-B-010-006-M51, 91-3112-B-010-006, 92-3112-B-010-019).
The authors declare they have no competing financial interests.
12 2004 27 7 2004 112 17 1704 1710 3 5 2004 27 7 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Inorganic arsenic is a well-documented human carcinogen. Chronic low-dose exposure to inorganic arsenic is associated with an increased incidence of a variety of cancers, including skin, lung, bladder, and liver cancer. Because genetic alterations often occur during cancer development, the objective of this study was to explore what types of genetic alterations were induced by chronic exposure of human HaCaT cells to arsenic. After 20 passages in the presence of inorganic trivalent arsenite at concentrations of 0.5 or 1 μM, HaCaT cells had higher intracellular levels of glutathione, became more resistance to arsenite, and showed an increased frequency of micronuclei. Furthermore, the previously nontumorigenic HaCaT cells became tumorigenic, as shown by subcutaneous injection into Balb/c nude mice. Cell lines derived from the tumors formed by injection of arsenite-exposed HaCaT cells into nude mice expressed higher levels of keratin 6, a proliferation marker of keratinocytes, than did parental HaCaT cells, whereas the expression of keratins 5, 8, and 10 was significantly decreased. Comparative genomic hybridization demonstrated chromosomal alterations in the 11 cell lines derived from these tumors; all 11 showed significant loss of chromosome 9q, and seven showed significant gain of chromosome 4q. The present results show that long-term exposure to low doses of arsenite transformed nontumorigenic human keratinocytes to cells that were tumorigenic in nude mice and that chromosomal alterations were observed in all cell lines established from the tumors.
arsenitechromosomal alterationscomparative genomic hybridizationHaCaT cellstumorigenicity
==== Body
Arsenic is ubiquitous in nature and is released into the environment via industrial processes and agricultural and medical applications (Chan and Huff 1997). Because of the natural distribution, drinking water is the most common source of arsenic exposure for the general population (Gebel 2000), and millions of people worldwide suffer from arsenic intoxication caused by drinking arsenic-contaminated water (National Research Council 2001). Epidemiologic studies have shown a strong association between chronic arsenic exposure and various adverse health effects, including cardiovascular diseases, neurologic defects, and cancers of the lung, skin, bladder, liver, and kidney (Calderon et al. 2001; Chen et al. 1985, 1995; Chiou et al. 2001; Smith et al. 1992). Although the processes involved in arsenic carcinogenesis remain an enigma, a variety of mechanisms, both genotoxic and nongenotoxic, have been proposed to explain the carcinogenicity of arsenic at the cellular and molecular levels (Kitchin 2001; Rossman 2003).
A risk of arsenic-induced chronic diseases, such as cancer and cardiovascular diseases, is clearly associated with prolonged exposure to low doses of arsenic. Several studies have shown that low doses of inorganic arsenic compounds stimulate the proliferation of mammalian cells (Barchowsky et al. 1999; Germolec et al. 1996; Lee et al. 1985b). Furthermore, long-term exposure to low concentrations of arsenic causes increased neoplastic transformation of murine JB6 Cl41 cells (Huang et al. 1999), blast transformation of human lymphocytes (Meng and Meng 2000), and malignant transformation (tumors formed on injection of arsenic-transformed cells into nude mice) of the rat liver epithelial cell line TRL 1215 (Zhao et al. 1997), the human prostate epithelial cell line RWPE-1 (Achanzar et al. 2002), and the human osteosarcoma cell line TE85 (Mure et al. 2003). Long-term exposure to low doses of arsenite also results in increased tolerance of acute arsenic exposure (Romach et al. 2000) and the aberrant expression of genes involved in the regulation of a variety of cellular functions, including signal transduction, the stress response, apoptosis, and cell proliferation (Chen et al. 2001a, 2001b; Vogt and Rossman 2001). These studies strongly suggest that chronic exposure to low levels of arsenic can produce cellular changes that promote arsenic-induced cell transformation or tumor development.
Over the past few decades, numerous genetic alterations affecting growth-controlling genes have been identified in neoplastic cells, providing persuasive evidence for the genetic basis of human cancer (Lengauer et al. 1998). All tumors contain genetic alterations, including subtle changes in DNA sequences, gene amplification, and gross chromosome losses, gains, translocations, and aneuploidy (Cahill et al. 1999; Schar 2001). Tumors exhibiting abnormal karyotypes involving either chromosomal rearrangement and/or aneuploidy are classified as chromosomal instability tumors (Bardelli et al. 2001). Although arsenic-induced malignant transformation has been shown to be associated with DNA hypomethylation (Zhao et al. 1997), increased matrix metalloproteinase-9 secretion (Achanzar et al. 2002), and delayed mutagenesis (Mure et al. 2003), how arsenic induces genetic and epigenetic alterations during cancer development remains to be elucidated. Treatment with inorganic trivalent arsenite results in the formation of DNA single-strand breaks (Lynn et al. 1997) and in gene amplification (Lee et al. 1988; Yih and Lee 2000). Although inorganic arsenic compounds are ineffective in inducing point mutation in a variety of cultured cell systems (Oberley et al. 1982; Rossman et al. 1980), they cause chromosomal damage in a variety of in vitro (Hei et al. 1998; Jha et al. 1992; Lee et al. 1985a) and in vivo systems (Gonsebatt et al. 1997). Inorganic arsenic is generally accepted as a clastogenic agent.
We recently reported that treatment with inorganic trivalent arsenite increases the frequency of micronuclei (MN) and aneuploidy in human fibroblasts (Yih et al. 1997). These arsenite-treated human fibroblasts were also shown to have an unstable karyotype but an increased life span (Yih et al. 1997). To explore the association of chromosomal alterations with arsenic-induced tumorigenicity in epithelial cells, an immortalized but nontumorigenic human skin keratinocyte cell line, HaCaT (Boukamp et al. 1988), was exposed to low-dose inorganic trivalent arsenite for a long period. Conversion of the cells from nontumorigenic to tumorigenic was demonstrated by injection of arsenite-exposed cells into nude mice. Chromosomal alterations in the cell lines established from the resulting tumors were analyzed using the comparative genomic hybridization (CGH) technique, which permits the rapid detection and mapping of DNA sequence copy number differences between a normal and an abnormal genome (Kallioniemi et al. 1992). Our results demonstrate that tumor cell lines derived from tumors induced by injection with arsenite-treated cells show chromosomal alterations.
Materials and Methods
Cell culture and treatment.
HaCaT cells, kindly provided by N.E. Fusenig (German Cancer Research Center, Heidelberg, Germany), were routinely grown in Dulbecco’s modified Eagle medium (GIBCO, Grand Island, NY, USA) supplemented with 10% fetal bovine serum (GIBCO), 1% glutamine, and antibiotics (100 U/mL penicillin and 100 μg/mL streptomycin) (Boukamp et al. 1988). For long-term exposure of HaCaT cells to arsenite, 5 × 105 cells were plated onto a 100-mm Petri dish and were fed with medium containing various concentrations of sodium arsenite (0, 0.5, and 1 μM). Every 4 days, the cells, grown to near confluence, were subcultured, replated at the same cell density, and fed with arsenite at the same concentration. Subculturing was continued for 20 passages, and the accumulated population doublings during these 20 passages were calculated. HaCaT cells that had been exposed to 0, 0.5, or 1 μM sodium arsenite for 20 passages were designated as A0, A1, or A2 cells, respectively.
Cytotoxicity assay.
We determined the cytotoxicity of arsenite using the colony-forming assay or the sulforhodamine B (SRB) assay. The colony-forming assay was performed as described previously (Ho and Lee 1999). In brief, the HaCaT cells were treated with various concentrations of sodium arsenite for 24 hr and replated at 200 cells per 60-mm dish in triplicate. Then, after incubation for 10 days, the colonies were fixed, stained, and counted under a dissection microscope. The SRB assay (Skehan et al. 1990) was performed using 96-well microplates and a density of 1,000 HaCaT cells/well. After addition of sodium arsenite, the microplates were incubated for 72 hr, and then the cells were fixed for 1 hr with ice-cold 50% trichloroacetic acid and stained for 30 min with 0.4% (wt/vol) SRB in 1% acetic acid solution. After extensive washes with distilled water, the bound SRB was extracted with 100 μL 10-mM unbuffered Tris-base solution and measured using a 96-well plate reader (Bio-Rad model 550; Bio-Rad, Hercules, CA). The survival curves were plotted by expressing the absorbance of treated wells as a percentage of that of control wells, and the inhibitory concentration 50% (IC50) values were calculated by linear regression.
Glutathione determination.
Cellular glutathione (GSH) levels in logarithmically growing cells were determined as described by Cohn and Lyle (1966).
Cytokinesis-block MN assay.
We used the method of Fenech and Morley (1989) with slight modifications to analyze the frequency of arsenite-induced MN. In brief, A0, A1, and A2 cells were incubated for 30 hr with 2 μg/mL cytochalasin B and then treated for 150 sec with hypotonic solution (0.05% KCl). After fixation for 8 min in a 20:1 (vol/vol) mixture of methanol and acetic acid, the cells were stained for 10 min with 5% (vol/vol) Giemsa solution, and then the number of MN was scored in 1,000 binucleate cells; under the conditions used, the frequency of binucleate cells was 500–600 per 1,000 cells.
Tumorigenicity test and establishment of tumor cell lines.
Male Balb/c nude mice 4–6 weeks of age, obtained from the National Laboratory Animal Center (Taipei, Taiwan), were injected subcutaneously with 3 × 106 A0, A1, or A2 cells in 100 μL of phosphate-buffered saline (PBS), pH 7.4, at each of two sites on either side of the back. Five animals were used per cell line and were maintained on regular food and water. To monitor tumor formation, we measured the longest and shortest diameters of the tumors weekly, starting when the tumor was first apparent. At the end of the experiment, the tumors were excised, and then part of the tumor tissue was fixed in buffered formalin for histologic examination, and another part was washed with PBS, minced, digested with collagenase type IV, and seeded in a Petri dish to establish tumor cell lines. Three cell lines, designated T1, T2, and T3, were established from the A1-derived tumors, and two lines, T4 and T5, from A2-derived tumors. To confirm their tumorigenicity, we injected 3 × 106 T1 and T4 cells in 100 μL of PBS into Balb/c nude mice and monitored tumor formation as described above. Two further cell lines, designated T1R1 and T1R2, and four other cell lines, designated T4R1–T4R4, were established from the T1- and T4-induced tumors, respectively. In a separate experiment to see if arsenic enhanced tumor progression, five other cell lines, T4A1–T4A5, were derived from tumors in T4-injected Balb/c nude mice that were also given arsenite-containing water (30–50 ppb) from 1 week before injection until the end of the experiment.
Western blotting analysis of keratins.
Logarithmically growing cells were scraped from culture dishes using a rubber policeman, lysed immediately in electrophoretic sample buffer, and heated at 95°C for 10 min (Laemmli 1970). Protein concentrations were determined by the Bio-Rad protein assay (Bio-Rad). An aliquot containing 10–20 μg protein was loaded onto a 10% sodium dodecyl sulfate–polyacrylamide gel, and then, after electrophoretic separation, the proteins were transferred onto a polyvinylidene difluoride membrane using a semidry electrotransfer system (ATTO, Tokyo, Japan). After blocking with 5% milk in PBS containing 0.2% Tween 20 for 1 hr at room temperature, the membranes were reacted with primary antibodies against keratin 5/8, 6, 7/17, 10, 14, or 18 (Santa Cruz Biotechnology, Santa Cruz, CA, USA) and horseradish peroxidase–conjugated secondary antibody (Organon Teknika-Cappel, Turnhout, Belgium) as previously described (Yih and Lee 2000). Keratins were then visualized using an enhanced chemiluminescence system according to the manufacturer’s instructions (Pierce, Rockford, IL, USA).
Chromosomal alteration analysis by CGH.
CGH was performed essentially as described by Kallioniemi et al. (1992) on normal male human lymphocyte metaphase spreads. DNA isolated from control HaCaT cells or cells derived from arsenite-induced tumors was labeled via nick translation with Spectrum red–2′-deoxyuridine 5′-triphosphate (dUTP) and fluorescein isothiocyanate-dUTP, respectively (Vysis, Downers Grove, IL, USA) and the 500–3,000 bp products were used as the probe for CGH. After hybridizing the probe with the spreads for 48–72 hr at 37°C, the slides were washed and counterstained with 4′,6′-diamidino-2′-phenylindole, and then metaphases were examined under a Zeiss Axioskop microscope equipped with appropriate epifluorescence filters and a charge-coupled device camera (SenSys; Photometrics, Tucson, AZ, USA) controlled by the SmartCapture program (Vysis). The filter system (Chroma Technology, Brattleboro, VT, USA) consisted of a triple-bandpass beam splitter and a triple-bandpass computer-controlled filter wheel (Ludl Electronic Products, Hawthorne, NY, USA). Image acquisition, profile generation, and analysis were performed using the Quips XL genetics workstation system (Vysis). After karyotyping, we calculated the green-to-red ratio profiles down the axis of each chromosome. Data from 10 captured metaphases were used to generate a mean profile ± 1 SD per hybridization. Threshold values of 1.2 and 0.8 were set to identify the presence of gains and losses, respectively. To avoid bias due to possible different affinities of the fluorochromes for the DNA, we repeated the hybridization experiment using the same DNA samples from HaCaT cells and arsenite-induced tumor cells, but with the fluorochromes reversed, and used the results from the two hybridizations to determine the gains and losses.
Results
Increased intracellular GSH levels and arsenite resistance in long-term arsenite-exposed cells.
When the colony-forming assay was performed on HaCaT cells treated with arsenite for 24 hr, the value of IC50 was 8.7 μM. In a pilot study, 0.5 or 1 μM arsenite did not affect HaCaT cell proliferation. We therefore exposed HaCaT cells continuously for 20 passages to 0, 0.5, or 1 μM arsenite and designated the final cell populations as A0, A1, and A2 cells, respectively. At the doses used, arsenite did not significantly affect the growth rate of HaCaT cells; the accumulated population doublings ranged from 58 to 67 (Figure 1A). However, when the A0, A1, and A2 cells were then exposed to higher concentrations of sodium arsenite (0–16 μM) for 72 hr, the IC50 values for arsenite, examined using the SRB assay, were 2.2 ± 0.3, 3.2 ± 0.4, and 3.7 ± 0.5 μM, respectively (Figure 1B). The IC50 values for the A1 and A2 cells were significantly higher than that for A0 cells, showing that the A1 and A2 cells were more resistant to arsenite. Consistent with previous reports showing that elevated GSH levels are frequently associated with arsenic resistance (Brambila et al. 2002; Lee et al. 1989), intracellular GSH levels in A1 and A2 cells were significantly higher than those in A0 cells (Figure 1C).
Increased MN formation in long-term arsenite-exposed cells.
MN, which generally result from the loss of whole chromosomes or chromosome fragments, are frequently used to monitor chromosomal damage and/or instability in in vitro and in vivo systems (Fenech 2000). We examined the frequency of MN in A0, A1, and A2 cells immediately after exposure to arsenite for 20 passages by using the cytokinesis-block MN technique. As shown in Figure 1D, the frequency of MN in A1 and A2 cells was significantly higher than that in A0 cells, indicating that long-term exposure to low doses of arsenite resulted in increased chromosomal damage.
Tumorigenicity of HaCaT cells after long-term exposure to a low dose of arsenite.
We examined the tumorigenicity of A0, A1, and A2 cells by injecting the cells into Balb/c nude mice. As shown in Figure 2, no tumor growth was seen after injection of A0 cells, whereas tumors were seen 2 months after injection of A1 or A2 cells. As summarized in Table 1, tumors were formed at five or seven of the 10 sites injected with A1 or A2 cells, respectively. Histologic examination of the tumors revealed the formation of a multilayered, hyperproliferative, keratinizing epithelium (Figure 3A,B). When two tumor cell lines, T1 and T4—derived, respectively, from tumors induced by injection with A1 or A2 cells—were reinjected into nude mice to confirm their tumorigenicity, tumors were rapidly formed within 2 weeks at almost all injection sites (Figure 2D, Table 1). Their histologic phenotypes were clearly more malignant than those formed after injection with A1 or A2 cells (Figure 3C,D). When T4 cells were injected into nude mice given arsenite-containing water from 1 week before injection until the end of the experiment, the number of tumors formed and the rate of tumor formation were the same as in similarly injected nude mice given arsenite-free water (data not shown), showing that the continued presence of arsenite did not enhance tumor progression.
Altered keratin expression in long-term arsenite-exposed cells and cell lines derived from arsenite-induced tumors.
Keratins are components of intermediate filaments and play an essential role in cytoskeleton formation (Morley and Lane 1994). They are involved in a variety of cell functions, and alterations in keratin expression are closely associated with tumor progression (Chu and Weiss 2002). With Western blotting, the levels of keratins 5, 6, 7, 8, 10, and 17 were significantly decreased in A1 and A2 cells compared with A0 cells (Figure 4A), whereas levels of keratins 14 and 18 remained relatively constant. A significant decrease in levels of keratins 5, 8, and 10 was also observed in all cell lines established from tumors (Figure 4B). The expression of these keratins in T1R2 and T4R2 cells was in general lower than that in the parental T1 and T4 cells. The levels of keratins 7, 14, 17, and 18 did not change in these cell lines, whereas, because of the very low levels in A0 cells, the levels of keratin 6, a proliferation marker, were markedly increased (Figure 4B).
Identification of chromosomal alterations in cell lines derived from long-term arsenite-exposed cells.
To evaluate the presence of genetic changes in arsenite-induced tumors, we performed CGH analysis to analyze DNA sequence copy number changes in cell lines derived from tumors produced by injection with A1 or A2 cells or cell lines derived from the resulting tumors. The major changes found in these cell lines were gain of chromosome 4q and loss of chromosome 9q (Figure 5A). Other regions occasionally showing gain and loss of chromosome regions are summarized in Figure 5A. In a detailed comparison (Figure 5B), all five tumor cell lines established from A1 and A2 cells (lines T1–T5) showed gain of chromosome 4q and loss of a large region of chromosome 9q. However, although all six of the cell lines derived from tumors formed by injection with T4 cells showed loss of chromosome 9q, only two (lines T4R4 and T4A1) showed gain of chromosome 4q. These results show that 9q12–22 was lost in all these cell lines and that chromosomal alteration, particularly loss of chromosome 9q, was a common event in tumor cells derived from arsenite-exposed HaCaT cells.
Discussion
Chronic arsenic exposure results in skin pathology, including hyperkeratosis, pigmentation changes, Bowen’s disease, basal cell carcinomas, and squamous cell carcinomas (Centeno et al. 2002). In the present study, we demonstrated that long-term low-dose exposure to sodium arsenite converted the nontumorigenic human keratinocyte HaCaT cell line into cells that were tumorigenic in nude mice. Histology of the tumors caused by injection of arsenite-treated HaCaT cells showed epithelial hyperplasia, mild dysplasia, severe dysplasia, and invasive carcinoma. These phenotypes are similar to arsenic-induced skin pathology. These results showing the induction of neoplastic transformation by long-term exposure of nontumorigenic cells to low doses of arsenite are consistent with those of several other studies using different cell systems (Achanzar et al. 2002; Huang et al. 1999; Mure et al. 2003; Zhao et al. 1997).
Consistent with several previous reports (Brambila et al. 2002; Lee et al. 1989; Romach et al. 2000), we showed that long-term exposure of HaCaT cells to low doses of arsenite resulted in an increase in intracellular GSH levels and resistance to arsenite challenge. These results also suggested that the insults produced by low-dose arsenite stress modulated the cellular biochemistry to adapt to the growth environment. Because acquisition of a survival advantage is crucial for the development of cancer (Hanahan and Weinberg 2000), long-term exposure to arsenite, even at low doses, warrants concern.
In in vitro systems, arsenite induces MN in a variety of cells (Eastmond and Tucker 1989; Liu and Huang 1997; Wang and Huang 1994). Both low-dose and high-dose exposure to arsenite induces MN formation (Yih and Lee 1999), but low-dose treatment results mainly in kinetochore-positive (K+) MN, whereas high-dose treatment results mainly in K-negative MN. K+ MN are usually caused by failure of the whole chromosome to segregate into daughter cells, and agents inducing aneuploidy by interfering with spindle formation often induce K+ MN formation (Eastmond and Tucker 1989). Thus, low-dose arsenite may be considered an aneugen. In fact, an increased frequency of MN has been demonstrated in exfoliated bladder cells, buccal cells, sputum cells, and lymphocytes from arsenic-exposed populations (Rossman 2003). The increased frequency of MN seen in A1 and A2 cells in this study shows that long-term exposure to low-dose arsenite can cause chromosomal damage. Because chromosomal alterations are a general manifestation of tumors (Cahill etal. 1999; Schar 2001), the effects of arsenic-induced chromosomal damage may play a role in arsenic tumorigenesis.
Keratins are the major structural proteins in epithelial cells and consist of a family of proteins (Morley and Lane 1994). Several human genetic diseases provide evidence that keratins function to protect cells from mechanical and nonmechanical stresses that result in cell death (Fuchs and Cleveland 1998; Ma et al. 2001). The expression of keratins is affected by cellular differentiation, environmental stimuli, and diseases (Morley and Lane 1994). Progressive alterations in keratin expression are closely associated with the development of a variety of tumors (Chu and Weiss 2002). In our present study, long-term exposure of HaCaT cells to low-dose arsenite caused a reduction in the levels of keratins 5, 6, 7, 8, 10, and 17, and the cell lines derived from tumors induced by injection with arsenite-treated cells had a similar pattern of expression of keratins, except that the levels of keratins 7 and 17 were unchanged and keratin 6 levels were significantly increased in the tumor cell lines. These results show that long-term arsenite exposure can alter regulation of keratin expression. Levels of keratin 6, a marker of hyperproliferative keratinocytes (Tomic-Canic et al. 1998), are increased during wound healing, psoriasis, and other inflammatory disorders (Tomic-Canic et al. 1998). Furthermore, increased levels of keratins 6 and 16 have been reported in arsenic-induced Bowen’s disease, and increased levels of keratins 6, 16, and 17 are seen in arsenic-induced squamous cell carcinoma and basal cell carcinoma (Yu et al. 1993). The increased keratin 6 expression seen in tumor cell lines derived from long-term arsenite-exposed HaCaT cells suggests that keratin 6 is a good proliferation marker for arsenite-induced carcinogenesis.
Using CGH analysis, we demonstrated genetic changes in cells exposed to low-dose arsenite for a long time. Because gain of chromosome 4q and loss of 9q were observed in most of the cell lines established, these non-random changes are possibly important genetic events in arsenic tumorigenesis. However, although gain of chromosome 4q was seen in all five lines cells derived from A1- and A2-induced primary tumors (lines T1–T5), it was only seen in two (T4R4 and T4A1) of six cell lines derived from T4-induced secondary tumors. This suggests that gain of chromosome 4q might not be crucial for arsenite-induced tumorigenicity. On the other hand, loss of chromosome 9q was consistently observed in all primary and secondary tumor cell lines established in this study, suggesting that it plays an essential role in arsenite-induced tumorigenicity. Deletion of all or part of chromosome 9q is seen in tumors from patients exposed to arsenic (Moore et al. 2002). As reported by Boukamp et al. (1997), HaCaT cells are spontaneously immortalized human skin keratinocytes and remain nontumorigenic up to 300 passages (Boukamp et al. 1997). Because translocations and deletions occurred during late passages, the presence of rare tumorigenic variants in A0 cells warrants our concern. However, it is unlikely because the sustained nontumorigenic phenotype of HaCaT cells during long-term propagation is well associated with their preserved chromosomal balance demonstrated by karyotypic and CGH analysis (Boukamp et al. 1997).
The association of chromosomal alterations with cancer development is a complicated issue. Gain of chromosome 4q or loss of 9q has been found in a variety of cancers, including skin, bladder, and lung cancers (Hartmann et al. 2002; Merlo et al. 1994; Popp et al. 2000), but other studies found an association between loss of chromosome 4q or gain of 9q and cancer development (Balsara et al. 2001; Jin et al. 2001). These studies indicate the presence of both tumor suppressor genes and oncogenes on these chromosomal regions. The genes for chemokine ligands 1, 2, and 3 are localized on chromosome 4q (Haskill et al. 1990) and are considered oncogenes because of their growth stimulatory activity. Two putative tumor suppressor genes, deleted in bladder cancer 1 (DBC1) and deleted in esophageal cancer 1 (DEC1), are localized on chromosomal 9q. Loss of heterozygosity of DBC1 is seen in some bladder cancers (Habuchi et al. 1998), whereas DEC1 expression is reduced or absent in esophageal squamous cell carcinomas (Nishiwaki et al. 2000). The expression of these genes and its relationship to arsenic carcinogenesis require further investigation.
In conclusion, our results demonstrate that long-term exposure to low doses of arsenite can cause genetic instability and lead to conversion of nontumorigenic human epithelial cells into cells that are tumorigenic in nude mice. However, the oncogenes and/or tumor suppressor genes involved in arsenic-induced carcinogenesis require further investigation.
Figure 1 Effects of long-term sodium arsenite treatment on accumulated population doubling, arsenic resistance, intracellular GSH levels, and MN frequency. (A) HaCaT cells continuously treated for 20 passages with 0, 0.5, or 1 μM sodium arsenite and then designated as A0, A1, and A2 cells. (B) A0, A1, and A2 cells treated with different concentrations of sodium arsenite for 72 hr, and cell survival determined using the SRB assay and the IC50 values calculated by linear regression. (C) Intracellular GSH levels in A0, A1, and A2 cells. (D) MN analysis performed on A0, A1, and A2 cells. In (B–D), the data are the means ± SD for three independent experiments. *p < 0.05 by Student’s t-test (C) and by Fisher’s exact test (D).
Figure 2 Growth curves of tumors formed in nude mice by subcutaneous injection of A0, A1, A2, or T4 cells. Tumor size (longest × shortest2 diameter × 0.5 in mm3), measured once a week starting 1 month (A0–A2 cells) or 2 weeks (T4 cells) after injection, is plotted against time. (A) A0 cells. (B) A1 cells. (C) A2 cells. (D) T4 cells. The horizontal lines indicate 30 mm3, and a tumor size greater than this was considered tumor formation in Table 1.
Figure 3 Histologic examination of tumors formed in nude mice. Tumors showing a hyperplastic stratified epithelium with prominent parakeratosis formed by injection of A1 cells (A) or A2 cells (B). Tumors with more malignant characteristics formed by injection of cell lines T1 (C) or T4 (D). Bars = 50 μm.
Figure 4 Western blotting analysis of keratins in arsenite-exposed cells and cell lines derived from tumors induced by injection of arsenite-treated cells. (A) Keratin levels in A0, A1, and A2 cells. (B) Keratin levels in cell lines derived either from tumors induced by injection of arsenite-treated cells (T1 and T4) or from those induced by injection of lines T1 or T4 (T1R2 and T4R2). β-Actin was used as the loading control and to normalize the keratin expression levels. The normalized expression level in each cell type was then compared with that in A0 cells. The data are the means ± SD for three independent experiments. *p < 0.05 by Student’s t-test.
Figure 5 CGH analysis of cell lines derived from arsenite-induced tumors. (A) All cell lines were compared with HaCaT cells. Chromosomal loss is indicated by a line to the left of each chromosome, and a gain by a line to the right. The entire X and Y chromosomes were excluded from analysis. (B) Chromosomal gain at the 4q region and loss at the 9q region in individual cell lines. Lines T1–T5 were derived from tumors induced in mice injected with A1 or A2 cells, whereas the other six lines were from tumors induced by injection of T4 cells.
Table 1 Tumorigenicity of arsenite-exposed cells and cell lines derived from arsenite-induced tumors after subcutaneous injection into nude mice.
Cellsa Days No. of tumors/no. of injections (%) Tumor size (mm3)b
A0 128 0/10 (0)
A1 5/10 (50) 68.3 (36.5–174.1)
A2 7/10 (70) 119.0 (42.1–314.1)
T1 35 4/4 (100) 146.5 (105.4–185.6)
T4 94 8/10 (80) 413.2 (78.9–1242.8)
a A0, A1, and A2, final cell lines after treatment with 0, 0.5, or 1 μM sodium arsenite, respectively, for 20 passages; T1 and T4, cell lines derived from tumors induced by injection with A1 cells or A2 cells, respectively.
b Tumor size = longest × shortest2 diameter (in mm) × 0.5.
==== Refs
References
Achanzar WE Brambila EM Diwan BA Webber MM Waalkes MP 2002 Inorganic arsenite-induced malignant transformation of human prostate epithelial cells J Natl Cancer Inst 94 1888 1891 12488483
Balsara BR Pei J De Rienzo A Simon D Tosolini A Lu YY 2001 Human hepatocellular carcinoma is characterized by a highly consistent pattern of genomic imbalances, including frequent loss of 16q23.1–24.1 Genes Chromosomes Cancer 30 245 253 11170281
Barchowsky A Roussel RR Klei LR James PE Ganju N Smith KR 1999 Low levels of arsenic trioxide stimulate proliferative signals in primary vascular cells with activating stress effector pathways Toxicol Appl Pharmacol 159 65 75 10448126
Bardelli A Cahill DP Lederer G Speicher MR Kinzler KW Vogelstein B 2001 Carcinogen-specific induction of genetic instability Proc Natl Acad Sci USA 98 5770 5775 11296254
Boukamp P Petrussevska RT Breitkreutz D Hornung J Markham A Fusenig NE 1988 Normal keratinization in a spontaneously immortalized aneuploid human keratinocyte cell line J Cell Biol 106 761 771 2450098
Boukamp P Popp S Altmeyer S Hülsen A Fasching C Cremer T 1997 Sustained nontumorigenic phenotype correlates with a largely stable chromosome content during long-term culture of the human keratinocyte line HaCaT Genes Chromosomes Cancer 19 201 214 9258654
Brambila EM Achanzar W Qu W Webber MM Waalkes MP 2002 Chronic arsenic-exposed human prostate epithelial cells exhibit stable arsenic tolerance: mechanistic implications of altered cellular glutathione and glutathione S -transferase Toxicol Appl Pharmacol 183 99 107 12387749
Cahill DP Kinzler KW Vogelstein B Lengauer C 1999 Genetic instability and darwinian selection in tumors Trends Cell Biol 9 M57 M60 10611684
Calderon J Navarro ME Jimenez-Capdeville ME Santos-Diaz MA Golden A Rodriguez-Leyva I 2001 Exposure to arsenic and lead and neuropsychological development in Mexican children Environ Res 85 69 76 11161656
Centeno JA Mullick FG Martinez L Page NP Gibb H Longfellow D 2002 Pathology related to chronic arsenic exposure Environ Health Perspect 110 883 886 12426152
Chan PC Huff J 1997 Arsenic carcinogenesis in animals and in humans: mechanistic, experimental, and epidemiological evidence Environ Carcinog Ecotox Rev C15 83 122
Chen CJ Chuang YC Lin TM Wu HY 1985 Malignant neoplasms among residents of a blackfoot disease-endemic area in Taiwan: high-arsenic artesian well water and cancer Cancer Res 45 5895 5899 4053060
Chen CJ Hsueh YM Lai MS Shyu MP Chen SY Wu MM 1995 Increased prevalence of hypertension and long-term arsenic exposure Hypertension 25 53 60 7843753
Chen H Liu J Merrick BA Waalkes MP 2001a Genetic events associated with arsenic-induced malignant transformation: applications of cDNA microarray technology Mol Carcinog 30 79 87 11241755
Chen H Liu J Zhao CQ Diwan BA Merrick BA Waalkes MP 2001b Association of c-myc overexpression and hyperpro-liferation with arsenite-induced malignant transformation Toxicol Appl Pharmacol 175 260 268 11559025
Chiou HY Chiou ST Hsu YH Chou YL Tseng CH Wei ML 2001 Incidence of transitional cell carcinoma and arsenic in drinking water: a follow-up study of 8,102 residents in an arseniasis-endemic area in northeastern Taiwan Am J Epidemiol 153 411 418 11226969
Chu PG Weiss LM 2002 Keratin expression in human tissues and neoplasms Histopathology 40 403 439 12010363
Cohn VH Lyle J 1966 A fluorometric assay for glutathione Anal Biochem 14 434 440 5944947
Eastmond DA Tucker JD 1989 Identification of aneuploidy-inducing agents using cytokinesis-blocked human lymphocytes and an antikinetochore antibody Environ Mol Mutag 13 34 43
Fenech M 2000 The in vitro micronucleus technique Mutat Res 455 81 95 11113469
Fenech M Morley AA 1989 Kinetochore detection in micro-nuclei: an alternative method for measuring chromosome loss Mutagenesis 4 98 104 2659933
Fuchs E Cleveland DW 1998 A structural scaffolding of intermediate filaments in health and disease Science 279 514 519 9438837
Gebel T 2000 Confounding variables in the environmental toxicology of arsenic Toxicology 144 155 162 10781883
Germolec DR Yoshida T Gaido K Wilmer JL Simeonova PP Kayama F 1996 Arsenic induces overexpression of growth factors in human keratinocytes Toxicol Appl Pharmacol 141 308 318 8917704
Gonsebatt ME Vega L Salazar AM Montero R Guzman P Blas J 1997 Cytogenetic effects in human exposure to arsenic Mutat Res 386 219 228 9219560
Habuchi T Luscombe M Elder PA Knowles MA 1998 Structure and methylation-based silencing of a gene (DBCCR1 ) within a candidate bladder cancer tumor suppressor region at 9q32-q33 Genomics 48 277 288 9545632
Hanahan D Weinberg RA 2000 The hallmarks of cancer Cell 100 57 70 10647931
Hartmann A Schlake G Zaak D Hungerhuber E Hofstetter A Hofstaedter F 2002 Occurrence of chromosome 9 and p53 alterations in multifocal dysplasia and carcinoma in situ of human urinary bladder Cancer Res 62 809 818 11830537
Haskill S Peace A Morris J Sporn SA Anisowicz A Lee SW 1990 Identification of three related human GRO genes encoding cytokine functions Proc Natl Acad Sci USA 87 7732 7736 2217207
Hei TK Liu SX Waldren C 1998 Mutagenicity of arsenic in mammalian cells: role of reactive oxygen species Proc Natl Acad Sci USA 95 8103 8107 9653147
Ho IC Lee TC 1999 Sodium arsenite enhances copper accumulation in human lung adenocarcinoma cells Toxicol Sci 47 176 180 10220854
Huang C Ma WY Li J Goranson A Dong Z 1999 Requirement of Erk, but not JNK, for arsenite-induced cell transformation J Biol Chem 274 14595 14601 10329651
Jha AN Noditi M Nilsson R Natarajan AT 1992 Genotoxic effects of sodium arsenite on human cells Mutat Res 284 215 221 1281272
Jin Y Martins C Salemark L Persson B Jin C Miranda J 2001 Nonrandom karyotypic features in basal cell carcinomas of the skin Cancer Genet Cytogenet 131 109 119 11750050
Kallioniemi A Kallioniemi OP Sudar D Rutovitz D Gray JW Waldman F 1992 Comparative genomic hybridization for molecular cytogenetic analysis of solid tumors Science 258 818 821 1359641
Kitchin KT 2001 Recent advances in arsenic carcinogenesis: modes of action, animal model systems, and methylated arsenic metabolites Toxicol Appl Pharmacol 172 249 261 11312654
Laemmli UK 1970 Cleavage of structural proteins during the assembly of the head of bacteriophage T4 Nature 227 680 685 5432063
Lee TC Huang RY Jan KY 1985a Sodium arsenite enhances the cytotoxicity, clastogenicity, and 6-thioguanine-resistant mutagenicity of ultraviolet light in Chinese hamster ovary cells Mutat Res 148 83 89 3969080
Lee TC Oshimura M Barrett JC 1985b Comparison of arsenic-induced cell transformation, cytotoxicity, mutation and cytogenetic effects in Syrian hamster embryo cells in culture Carcinogenesis 6 1421 1426 3840060
Lee TC Tanaka N Lamb PW Gilmer TM Barrett JC 1988 Induction of gene amplification by arsenic Science 241 79 81 3388020
Lee TC Wei ML Chang WJ Ho IC Jan KY Huang H 1989 Elevation of glutathione levels and glutathione S -transferase activity in arsenic-resistant Chinese hamster ovary cells In Vitro Cell Dev Biol 25 442 448 2732199
Lengauer C Kinzler KW Vogelstein B 1998 Genetic instabilities in human cancers Nature 396 643 649 9872311
Liu YC Huang H 1997 Involvement of calcium-dependent protein kinase C in arsenite-induced genotoxicity in Chinese hamster ovary cells J Cell Biochem 64 423 433 9057100
Lynn S Lai H-T Gurr J-R Jan KY 1997 Arsenite retards DNA break rejoining by inhibiting DNA ligation Mutagenesis 12 353 358 9379914
Ma L Yamada S Wirtz D Coulombe PA 2001 A “hot-spot” mutation alters the mechanical properties of keratin filament networks Nature Cell Biol 3 503 506 11331879
Meng ZQ Meng NY 2000 Effects of arsenic on blast transformation and DNA synthesis of human blood lymphocytes Chemosphere 41 115 119 10819187
Merlo A Gabrielson E Mabry M Vollmer R Baylin SB Sidransky D 1994 Homozygous deletion on chromosome 9p and loss of heterozygosity on 9q, 6p, and 6q in primary human small cell lung cancer Cancer Res 54 2322 2326 8162574
Moore LE Smith AH Eng C Kalman D DeVries S Bhargava V 2002 Arsenic-related chromosomal alterations in bladder cancer J Natl Cancer Inst 94 1688 1696 12441324
Morley SM Lane EB 1994. The keratinocyte cytoskeleton. In: The Keratinocyte Handbook (Leigh IM, Lane B, Watt FM, eds). Cambridge:Cambridge University Press, 293–322.
Mure K Uddin AN Lopez LC Styblo M Rossman TG 2003 Arsenite induces delayed mutagenesis and transformation in human osteosarcoma cells at extremely low concentration Environ Mol Mutag 41 322 331
National Research Council 2001. Arsenic in Drinking Water. 2001 Update. Washington, DC:National Academies Press.
Nishiwaki T Daigo Y Kawasoe T Nakamura Y 2000 Isolation and mutational analysis of a novel human cDNA, DEC1 (deleted in esophageal cancer 1), derived from the tumor suppressor locus in 9q32 Genes Chromosomes Cancer 27 169 176 10612805
Oberley TJ Piper CE McDonald DS 1982 Mutagenicity of metal salts in the L5178Y mouse lymphoma assay J Toxicol Environ Health 9 367 376 7097791
Popp S Waltering S Holtgreve-Grez H Jauch A Proby C Leigh IM 2000 Genetic characterization of a human skin carcinoma progression model: from primary tumor to metastasis J Invest Dermatol 115 1095 1103 11121147
Romach EH Zhao CQ Del Razo LM Cebrian ME Waalkes MP 2000 Studies on the mechanisms of arsenic-induced self tolerance developed in liver epithelial cells through continuous low-level arsenite exposure Toxicol Sci 54 500 508 10774833
Rossman TG 2003 Mechanism of arsenic carcinogenesis: an integrated approach Mutat Res 533 37 65 14643412
Rossman TG Stone D Molina M Troll W 1980 Absence of arsenite mutagenicity in E. coli and Chinese hamster ovary cells Environ Mutag 2 371 379
Schar P 2001 Spontaneous DNA damage, genome instability, and cancer—when DNA replication escapes control Cell 104 329 332 11239390
Skehan P Storeng R Scudiero D Monks A McMahon J Vistica D 1990 New colorimetric cytotoxicity assay for anti-cancer-drug screening J Natl Cancer Inst 82 1107 1112 2359136
Smith AH Hopenhayn-Rich C Bates MN Goeden HM Hertz-Picciotto I Duggan HM 1992 Cancer risks from arsenic in drinking water Environ Health Perspect 97 259 267 1396465
Tomic-Canic M Komine M Freedberg IM Blumenberg M 1998 Epidermal signal transduction and transcription factor activation in activated keratinocytes J Dermatol Sci 17 167 181 9697045
Vogt BL Rossman TG 2001 Effects of arsenite on p53, p21 and cyclin D expression in normal human fibroblasts—a possible mechanism for arsenite’s comutagenicity Mutat Res 478 159 168 11406180
Wang TS Huang H 1994 Active oxygen species are involved in the induction of micronuclei by arsenite in XRS-5 cells Mutagenesis 9 253 257 7934966
Yih LH Ho IC Lee TC 1997 Sodium arsenite disturbs mitosis and induces chromosome loss in human fibroblasts Cancer Res 57 5051 5059 9371502
Yih LH Lee TC 1999 Effects of exposure protocols on induction of kinetochore-plus and -minus micronuclei by arsenite in diploid human fibroblasts Mutat Res 440 75 82 10095130
Yih LH Lee TC 2000 Arsenite induces p53 accumulation through an ATM-dependent pathway in human fibroblasts Cancer Res 60 6346 6352 11103796
Yu HS Chiou KS Chen GS Yang RC Chang SF 1993 Progressive alterations of cytokeratin expression in the process of chronic arsenism J Dermatol 20 741 745 7509818
Zhao CQ Young MR Diwan BA Coogan TP Waalkes MP 1997 Association of arsenic-induced malignant transformation with DNA hypomethylation and aberrant gene expression Proc Natl Acad Sci USA 94 10907 10912 9380733
|
15579417
|
PMC1253663
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec 27; 112(17):1704-1710
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7224
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science 10.1289/ehp.7293ehp0112-00171115579418ResearchArticlesIs Bone Mineral Composition Disrupted by Organochlorines in East Greenland Polar Bears (Ursus maritimus)? Sonne Christian 12Dietz Rune 1Born Erik W. 3Riget Frank F. 1Kirkegaard Maja 1Hyldstrup Lars 4Letcher Robert J. 5Muir Derek C. G. 61National Environmental Research Institute, Department of Arctic Environment, Roskilde, Denmark2Department of Basic Animal and Veterinary Sciences, Royal Veterinary and Agricultural University, Frederiksberg, Denmark3Greenland Institute of Natural Resources, Nuuk, Greenland, Denmark4University Hospital of Hvidovre, Hvidovre, Denmark5Great Lakes Institute for Environmental Research, University of Windsor, Windsor, Ontario, Canada6National Water Research Institute, Environment Canada, Burlington, Ontario, CanadaAddress correspondence to C. Sonne, National Environmental Research Institute, Department of Arctic Environment, Frederiksborgvej 399, DK4000 Roskilde, Denmark. Telephone: 45-46-30-19-54. Fax: 45-46-30-19-14. E-mail:
[email protected] thank J. Brønlund and local hunters for organizing sampling in East Greenland, the Zoological Museum of Copenhagen for skull maceration and preparation support, and P.M. Lind and three anonymous reviewers for their comments on the manuscript.
Financial support was provided by the Danish Cooperation for Environment in the Arctic and the Commission for Scientific Research in Greenland.
The authors declare they have no competing financial interests.
12 2004 13 9 2004 112 17 1711 1716 28 5 2004 13 9 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. We analyzed bone mineral density (BMD) in skulls of polar bears (Ursus maritimus) (n = 139) from East Greenland sampled during 1892–2002. Our primary goal was to detect possible changes in bone mineral content (osteopenia) due to elevated exposure to organochlorine [polychlorinated biphenyls (PCBs), dichlorodiphenyl trichloroethane (DDT) and its metabolites, chlordanes (CHLs), dieldrin, hexacyclohexanes, hexachlorobenzene] and polybrominated diphenyl ether (PBDE) compounds. To ensure that the BMD value in skull represented the mineral status of the skeletal system in general, we compared BMD values in femur and three lumbar vertebrae with skull in a subsample. We detected highly significant correlations between BMD in skull and femur (r = 0.99; p < 0.001; n = 13) and skull and vertebrae (r = 0.97; p < 0.001; n = 8). BMD in skulls sampled in the supposed pre-organochlorine/PBDE period (1892–1932) was significantly higher than that in skulls sampled in the supposed pollution period (1966–2002) for subadult females, subadult males, and adult males (all, p < 0.05) but not adult females (p = 0.94). We found a negative correlation between organochlorines and skull BMD for the sum of PCBs (∑PCB; p < 0.04) and ∑CHL (p < 0.03) in subadults and for dieldrin (p < 0.002) and ∑DDT (p < 0.02) in adult males; indications for ∑PBDE in subadults were also found (p = 0.06). In conclusion, the strong correlative relationships suggest that disruption of the bone mineral composition in East Greenland polar bears may have been caused by organochlorine exposure.
BMDbone mineral densitychlordaneDDTdieldrinendocrine disruptionosteoporosisPCBspolar bearpolychlorinated biphenylsUrsus maritimus
==== Body
Bone mineral composition in mammals is based on a complex set of interrelated mechanisms and is influenced by various nutritional and environmental factors (e.g., Ganong 1991; Johansson and Melhus 2001; Johansson et al. 2002; Leder et al. 2001; Michaelsson et al. 2003; Promislow et al. 2002; Sarazin et al. 2000). Furthermore, environmental stressors such as exposure to harmful chemicals, starvation, temperature extremes, and noise have been shown to disrupt bone mineral composition in laboratory mammals (Brandt and Siegel 1978; Doyle et al. 1977; Mooney et al. 1985; Nilsson 1994; Siegel and Doyle 1975a, 1975b; Siegel et al. 1977, 1992; Siegel and Mooney 1987). The pathogenesis of stress-induced bone mineral changes is an activation of the hypophyseal–adrenal/thyroid axis, leading to enhanced parathyroid and cortisol hormone secretion, increased bone resorption, and decreased bone formation (Colborn et al. 1993; Damstra et al. 2002; Feldman 1995; Ganong 1991; Selye 1973). Other hypotheses on disruption of bone mineral status include altered mitotic rates, changes in local subcellular calcium transport, and decreased protein synthesis (Siegel and Mooney 1987).
Organochlorines such as polychlorinated biphenyls (PCBs), dichlorodiphenyl trichloroethane (DDT), chlordanes (CHLs), hexacyclohexanes (HCHs), dieldrin, hexachlorobenzene (HCB), polybrominated diphenyl ethers (PBDEs), and aryl hydrocarbon receptor (AhR)–active organochlorines (e.g., polychlorinated dibenzo-p-dioxins, dibenzofurans, and non-ortho-chlorine–substituted PCBs) are all lipophilic (low degradable) chemicals, pesticides, or unwanted chemical by-products (e.g., de March et al. 1998). In general, the presence of such compounds in the arctic marine environment is the result of long-range atmospheric transport from lower-latitude sources in more industrial areas of the world, where outputs and use of, for example, PCB peaked in the 1960s (de March et al. 1998). Because of their lipophilicity, organochlorines and PBDEs persist in the environment [Arctic Monitoring and Assessment Programme (AMAP) 2004; Colborn et al. 1993; Damstra et al. 2002; de March et al. 1998]. In polar bears, organochlorines are consequently transferred transplacentally from mother to fetus and via lactation, resulting in fetal and neonatal exposures that have the potential for adverse health effects, for example, on growth and development (Bernhoft et al. 1997; Birnbaum 1994; Polischuk et al. 1995, 2002).
In humans, PCB and DDT and its metabolites have been associated with low bone mineral density (BMD) (Alveblom et al. 2003; Beard and et al. 2000; Glynn et al. 2000) through their action as exogenous agonists and antagonists to naturally endogenous hormones (Damstra et al. 2002). Various organochlorines have also been linked to periodontitis and osteoporosis in marine fish and mammal wildlife (Bengtsson et al. 1985; Bergman et al. 1992; de Guise et al. 1995; Lind et al. 2003, 2004; Mortensen et al. 1992; Schandorff 1997; Zakharov and Yablokov 1990) and in the laboratory (Fernie et al. 2003; Jamsa et al. 2001; Lind et al. 1999, 2000a, 2000b; Render et al. 2000a, 2000b, 2001; Singh et al. 2000; Valentine and Soulé 1973). In various mammalian wildlife [e.g., gray seal (Halichoerus grypus), ringed seal (Phoca hispida), harbor seal (Phoca vitulina), and alligator (Alligator mississippiensis)], osteopenia and macroscopic pathology have been examined in bone during distinct periods of exposure to anthropogenic pollutants (Bergman et al. 1992; Lind et al. 2003, 2004; Mortensen et al. 1992, Schandorff 1997; Sonne-Hansen et al. 2002; Zakharov and Yablokov 1990). The studies showed relationships between organochlorines and exostosis, periodontitis, loss of alveolar bone structures, osteoporosis, widening of the canine opening, and enlargement of the foramen mentalia.
Polar bears from East Greenland, Svalbard, and the Kara Sea carry higher loads of organochlorines than do polar bears elsewhere in the Arctic due to the different atmospheric transport routes (AMAP 2004; de March et al. 1998; Lie et al. 2003; Norstrom et al. 1998). Subsequently, the organochlorines up-concentrate in the blubber of ringed seal (P. hispida) and bearded seal (Erignathus barbatus), which is the primary food of the polar bear (AMAP 2004; de March et al. 1998; Lie et al. 2003; Norstrom et al. 1998). Recent studies of polar bears from Svalbard have indicated that high levels of organochlorines negatively affect levels of retinol (vitamin A) and thyroid hormones (Braathen et al. 2004; Skaare et al. 2001) and possibly also negatively affect cortisols, sex steroids, and reproductive organs (female pseudohermaphrodites), although these latter mechanisms are not clearly understood (Haave et al. 2003; Oskam et al. 2003, 2004; Sonne et al., in press; Wiig et al. 1998). Other studies have associated high levels of organochlorines with low levels of IgG, suggesting possible immunotoxic effects on the IgG levels (Bernhoft et al. 2000; Lie E, Larsen HJS, Larsen S, Johansen GM, Derocher AE, Lunn NJ, et al., unpublished data). Overall, these studies support the notion that organochlorines may cause disruption and thereby potentially affect bone mineral composition.
To determine whether exposure to organochlorines and PBDEs may have adversely affected bone mineral composition in polar bears, we compared BMD in skulls of 41 individual polar bears collected in East Greenland during the supposed prepolluted period (1892–1932) with 98 polar bear skulls collected during the supposed polluted period (1966–2002). Furthermore, we examined a subset of 58 of the individuals collected during the pollution period to determine if BMD was related to body burden of various organochlorines and PBDEs.
Materials and Methods
Sampling and age estimation.
We studied a total of 139 East Greenland polar bear skulls sampled between Skjoldungen at 63°15′N and Danmarks Havn at 76°30′N during 1892–2002. The age determination was carried out by counting the cementum growth layer groups (GLGs) of the lower left incisor (I3) after decalcification, thin sectioning (14 μm), and staining (toluidine blue) using the method described by, for example, Hensel and Sorensen (1980) and Dietz et al. (1991). For analyses, the individuals were then categorized into adult males (≥6 years of age), adult females (≥5 years), and subadults (others) (e.g., Rosing-Asvid et al. 2002). Regarding skull samples from 1892–1987, the sex was available from the expedition files, and in case of absence of this information (n = 9), the determination was based on skull morphology.
Osteodensitometry.
X-Ray osteodensitometry was applied to detect osteopenia (osteoporosis) by use of an X-ray bone densitometer (model XR 26; Norland Corporation, Fort Atkinson, WI, USA), which determined the BMD (calcium phosphate, hydroxyapatite) using dual X-ray absorptiometry (DXA). The skulls were scanned in “research” mode (speed, 60 mm/sec; resolution, 3.0 × 3.0 mm; width, 24.9 cm) and analyzed using XR software (revision 2.4; Norland Corporation), which generated a picture of the bone segment and calculated the BMD of hydroxyapatite in grams per square centimeter (Figure 1).
To ensure that BMD in the skull represents the mineral status of the skeletal system in general, a study was conducted where the BMD of the skull, one femur, and three lumbar vertebrae were compared in a subset of 13 free-ranging polar bears (3 subadults, 2 adult females, and 8 adult males) from Svalbard and East Greenland. The DXA scanner was calibrated daily using a phantom with known mineral density. In addition, the precision was tested by a 10× rescanning (mean ± SD, 521.96 ± 0.60 g/cm2), which from the formula [1 − (SD/mean) × 100%] gives a precision of 99.88%. Fragmentation and loss of tooth material caused by handling and lead shot were thought to be a problem. A double determination of the BMD in 2 skulls (numbers 5483 and 2891) with and without incisors, canines, premolars, and molars showed that loss of half or more of the material of the large canines altered the result significantly. Because the canines in the material were not fragmented to such a degree, we did not consider fragmentations a problem.
Contaminant analyses.
Polar bear subcutaneous adipose tissue samples (n = 58) were analyzed for PCBs, DDT and its metabolites, HCHs, CHLs, HCB, dieldrin, and PBDEs as described elsewhere (Dietz et al. 2004; Luross et al. 2002; Sandala et al. 2004). The sum of PCBs (∑PCB) is the total concentrations of the 51 individual or coeluting congeners (if detected): PCBs 31/28, 52, 49, 44, 42, 64/71, 74, 70, 66/95, 60, 101/84, 99, 97, 87, 110, 151, 149, 118, 146, 153, 105, 141, 179, 138, 158, 129/178, 182/187, 183, 128, 174, 177, 171/202/156, 200, 172, 180, 170/190, 201, 203/196, 195, 194, and 206. ∑DDT is the sum of 4,4′-DDT, 4,4′-DDD (dichlorodiphenyldichloroethane), and 4,4′-DDE (dichlorodiphenyldichloroethylene). ∑HCH is the sum of the α-, β-, and γ-hexachlorocyclohexane. ∑CHL is the total concentration of oxychlordane, trans-chlordane, nonachlor III (MC6), trans-nonachlor, cis-nonachlor, and heptachlor epoxide. ∑PBDE concentration is the total of 35 individual or coeluting congeners (if detected): PBDE numbers 10, 7, 11, 8, 12/13, 15, 30, 32, 28/33, 35, 37, 75, 71, 66, 47, 49, 77, 100, 119, 99, 116, 85, 155/126, 105, 154, 153, 140, 138, 166, 183, 181, and 190 (Muir DCG, Dietz R, Riget FF, Sonne C, Letcher RJ, Born EWB, unpublished data). All contaminant data are given in nanograms per gram lipid weight (l.w.).
Statistics.
The BMD showed no deviation from normality (Shapiro-Wilk test), whereas contaminant data were log-transformed (base e) before analyses in order to meet the criteria of normality and homogeneity of the variance. The significance level was set to p ≤0.05, and a significance level of 0.05 < p ≤0.10 was considered a trend. First, we tested the condy-lobasal skull length versus age within each group (i.e., subadults of both sexes, adult females, and adult males) in an analysis of covariance (ANCOVA) with skull length as a dependent variable, periods (before and after 1960 respectively) as class variables, age as a covariable, and their first-order interaction links (age × period). The result from this analysis showed that the relationship of skull length versus age was the same in the two periods, which justified the use of non-length-corrected skull BMD in the further analyses (all, p > 0.26). Second, the relationship of BMD versus age was tested by a linear regression analyses (BMD as a dependent variable and age as an independent variable) for subadults of both sexes, adult females, and adult males. To test for period differences, we used an ANCOVA with BMD as a dependent variable, age/sex (subadult females, subadult males, adult females, and adult males) and period (before and after 1960 respectively) as class variables, age as a covariable, and the first-order interaction links (age × period, age × age/sex, and age/sex × period) between these variables. The model was successively reduced for nonsignificant interactions (p > 0.05) judged from the type III sum of squares, and the significance of the remaining factors was evaluated from the final model (least square means). A temporal trend over the entire period 1892–2002 was analyzed by a multiple regression analysis with skull BMD as the dependent variable and the individual age and year of kill as explanatory variables for subadults of both sexes, adult females, and adult males, respectively (the relationship was evaluated from the parameter estimate, r2, and p-value). The relationship between age/sex groups and contaminants was analyzed within a one-way analysis of variance on the log-transformed contaminant data, and significant results were tested by Tukey’s post hoc test. The skull BMD versus contaminant (∑PCB, ∑DDT, ∑CHL, HCB, ∑HCH, dieldrin, and ∑PBDE) relationships were explored by multiple regressions with skull BMD as the dependent variable and the age and contaminant concentrations as explanatory variables within age/sex groups (subadults of both sexes, adult females, and adult males). Finally, the relationship between levels of contaminants and BMD was evaluated from the parameter estimate, r2, and p-value.
Results
We found a highly significant correlation between BMD in skull and femur (r = 0.99; p < 0.001; n = 13), and skull and vertebrae (r = 0.97; p < 0.001; n = 8). These results justified the use of BMD measurements in skull to reflect the status of the skeletal system, although information on body conditions and nutritional stressors, relevant for osteoblastic and osteoclastic activity, was not available.
Skull BMD and age/sex differences.
BMD was analyzed in 139 skulls representing the period 1892–2002, and consisted of 64 subadults, 40 adult females and 35 adult males. The BMD increased with age in subadults (p < 0.001) but not adults (both, p > 0.05; Figure 2). BMD differed between males and females (p < 0.01) in the order subadult females < subadult males < adult females < adult males. Furthermore, BMD in females 14–23 years of age seemed to decline significantly with age (p < 0.04).
Period differences and temporal trends in skull BMD.
Forty-one skulls were available from the supposed prepollution period (1892–1932) and 98 from the supposed pollution period (1966–2002) (Table 1). BMD in skulls sampled in the pollution period was significantly lower than BMD sampled in skulls from the prepollution period for subadults and adult males (p < 0.05) but not for adult females (p > 0.9) (Table 1). In addition, the multiple regression analyses of BMD versus individual age and year of kill (1892–2002) showed that BMD decreased over the entire period in adult males (p < 0.01), and a similar trend was found for subadults (p = 0.07) (Table 2). There was no BMD time trend for adult females (p > 0.5).
Skull BMD and contaminants.
The range and variation of organochlorine and PBDE contaminants (nanograms per gram l.w.) in the 58 polar bears sampled during 1999–2001 are presented in Table 3. Levels of ∑DDT, dieldrin, ∑HCH, and ∑PBDE were not different between subadults, adult females, and adult males (all, p > 0.07). However, levels of ∑PCB were higher in adult males when compared with adult females (p ≤0.05). Additional information on the relationship between organochlorines and age, sex, and season in East Greenland polar bears from 1999 through 2002 has been published by Dietz et al. (2004) and Sandala et al. (2004).
BMD was found to be negatively correlated with levels of ∑PCB (p < 0.04) and ∑CHL in subadults (p < 0.03), whereas BMD was negatively correlated with ∑DDT (p < 0.02) and dieldrin (p < 0.002) in adult males (Table 4). In addition, a trend of ∑PBDE being negatively correlated to BMD in subadults was found (p = 0.06), whereas no significant relations were found for adult females (Table 4).
Discussion
BMD and age/sex differences.
The high correlation in BMD between skull and femur and vertebrae, respectively, is useful because skull samples of polar bears (and other mammals) are present at national zoological museums all over the world, which makes various time-trend bone studies possible. Our results clearly show that skull BMD increased more rapidly in subadults compared with adults, in accordance with previous studies of ringed seals from Northwest Greenland (Sonne-Hansen et al. 2002). Female polar bears usually give birth to two cubs every third year (December) and mobilize and transfer large amounts of calcium and phosphate during gestation and during the postpartum (suckling) period, which lasts up to 2 years (Ramsay and Stirling 1988). In this period, calcium is used for fetal skeletal production and maintenance of the mother’s and offspring’s calcium phosphate homeostasis (Ramsay and Stirling 1988). Because the female polar bear mobilizes these large amounts of calcium and phosphate, adult females are expected to have a lower BMD compared with adult males. Such a difference was also found in the present study. Similar differences have been found in humans (e.g., Van Langendonck et al. 2002). As suggested for humans, the marked difference in BMD between the sexes could be the result of a higher muscle mass and strength in males, leading to higher biomechanical loading of the bone. This would lead to increased bone formation through the stimulation of the mechanotransduction system in the osteocytes (Van Langendonck et al. 2002).
Earlier studies show that sufficient levels of sex steroids (estrogens and androgens) are important in the development of the human cortical bone structures in boys, girls, teenagers, adults, and the elderly (Hampson et al. 2002; Juul 2001; Leder et al. 2001; Szulc et al. 2001). On the other hand, high levels of estrogen-active substances (intrinsic, extrinsic) stimulate the expression of secondary sexual characteristics (Hampson et al. 2002; Juul 2001; Leder et al. 2001; Szulc et al. 2001). Therefore, growth delay and osteopenia (osteoporosis) have been associated with hypogonadism and lower estrogen levels in both sexes (Leder et al. 2001; Nelson 2003; Szulc et al. 2001). The age-related decrease in BMD in females in the present study was probably associated with a menopause phase after 15 years of age, but this requires a larger sample size (Figure 2) (Derocher and Stirling 1994).
Period differences and temporal trends in skull BMD.
In both analyses of subadults of both sexes and adult males, the individuals from the prepollution period had a higher skull BMD compared with those from the polluted period. These results suggest that there is a linkage between decreased BMD for bears from the polluted period and exposure to environmental stressors compared with bears in the prepollution period. Two major environmental stressors could be linked to mineral loss in polar bear skulls: anthropogenic organochlorine compounds and PBDEs and/or climate oscillations (AMAP 2004; de March et al. 1998; Førland et al. 2002). Concentrations of, for example, ∑PCB in the adipose tissue of East Greenland polar bears have, over the last four decades, reached levels that can elicit adverse biological effects on immunologic parameters and vitamin A levels, which may be linked to the present decrease in skull BMD (stress) (AMAP 2004; de March et al. 1998). However, during the same period global warming has resulted in a reduction in the ice coverage in the East Greenland area (Comiso 2002; Rothcock et al. 1999). Although population ecology has not been studied in East Greenland, the situation is probably similar for polar bears from the Hudson Bay area in Canada (Stirling et al. 1999). A reduction of the sea ice in the Hudson Bay area has reduced the bears’ access to ringed seals, resulting in reduced body condition and lowered natality in the polar bears (Stirling et al. 1999).
Temporal differences with respect to potential effects of PCB and DDT exposure on periodontitis and osteoporosis in gray seal and harbor seal was investigated by Bergman et al. (1992), Mortensen et al. (1992), and Schandorff (1997). They found exostosis and periodontitis, often with substantial loss of alveolar bone in mandible and maxilla (osteoporosis). These changes could have been caused by hormonal imbalance potentially induced by PCBs and by DDT and its metabolites, with malformation of the calcium helix structures around the collagen matrix (DeLillis 1989). These results are further supported by the investigations of Render et al. (2000a, 2000b, 2001). However, it must be noted that the ranges of ∑PCB and ∑DDT levels in the seals were orders of magnitude higher compared with levels in the present polar bears (Blomkvist et al. 1992).
Lind et al. (2003) investigated the BMD in the male gray seals (n = 43) reported by Bergman et al. (1992). The method used was peripheral quantitative computed tomography, which made it possible to distinguish between cortical and trabecular bone in os mandibularis and os radius, respectively (DXA scanning used in the present study gives the average of trabecular and cortical bone density). Three sample groups of seals were compared: 1850–1955 (no pollution), 1965–1985 (high pollution), and 1986–1997 (fairly low pollution). They found that radius trabecular BMD was significantly higher in the fairly low pollution period (1986–1997) compared with the high pollution period (1965–1985), whereas mandible cortical BMD was significantly lower in the fairly low pollution period (1986–1997) compared with the no-pollution period (1850–1955). Our study of BMD in East Greenland polar bears supports the findings of Lind et al. (2003).
BMD levels and contaminants.
Bone density expresses the bone mineral composition determined by the activity of osteoblastic bone formation and osteoclastic bone resorption, which is regulated by androgens and estrogens through cytokines (Manolagas and Jilka 1995; Manolagas et al. 1995). Studies on Svalbard have shown that PCBs may negatively influence plasma cortisol, estrogen, and testosterone levels (Haave et al. 2003; Oskam et al. 2003, 2004) and plasma retinol and thyroid hormone levels in polar bears (Braathen et al. 2004; Skaare et al. 2001). These studies all indicate that organochlorines in Svalbard polar bears (and likely also East Greenland bears, because the organohalogen compound levels are comparable) potentially affect endocrine homeostasis, which again may lead to bone mineral loss (osteoporosis). Another polar bear study from Svalbard associated high levels of organochlorines with low levels of IgG, suggesting possible immunotoxic effects (Bernhoft et al. 2000; Lie E, Larsen HJS, Larsen S, Johansen GM, Derocher AE, Lunn NJ, et al., unpublished data). This potential effect may lower the immune response and enhance stress with increased cortisol levels, which potentially affects the bone mineral composition (osteoporosis).
The present study indicated that high concentrations of ∑PCB and ∑CHL are associated with reduced skull BMD in subadults and that ∑DDT and dieldrin are associated with reduced skull BMD in adult males. These BMD relationships with ∑PCB, ∑CHL, ∑DDT, and dieldrin concentrations in subadults of both sexes and adult males may suggest endocrine-related effects (e.g., AMAP 2002; Birnbaum 1994; Damstra et al. 2002; de March et al. 1998; Lind et al. 2003, 2004). For example, PCBs and DDT and its metabolites have shown in vitro and in vivo to be weak agonists/antagonists of estrogen-receptor–mediated activity; organochlorine-mediated induction of cytochrome P450 isozyme activity can affect circulating sex hormone levels (e.g., estrogens) (Navas and Segner 1998), and this is also of relevance in the polar bear (e.g., Letcher et al. 1996). Relationships between 4,4′-DDE concentrations and BMD in humans have been reported (Beard et al. 2000; Glynn et al. 2000). Glynn et al. (2000) found significant negative correlations between 4,4′-DDE and BMD in 68 sedentary women (where concentrations are lower compared with the present polar bears) and concluded that 4,4′-DDE may also have a negative effect on BMD in men (with contaminant levels comparable with those found in the polar bears). Lind et al. (2004) investigated the relationship between DDT and its metabolites and bone composition in juvenile female American alligators (Alligator mississippiensis) in Lake Apopka, Florida. Compared with data from a nonpolluted reference alligator subpopulation, the tibial trabecular BMD was increased, and the authors suggested that environmental estrogenic compounds (e.g., DDT and its metabolites) disrupted the normal bone remodeling process (inhibition of osteoclast activity), which had resulted in increased BMD.
Guo et al. (1994) found that children (n = 25) of primiparous PCB-contaminated mothers (Yu-Cheng rice oil disease) were significantly smaller and had less total lean mass and less soft tissue mass but not lower BMD compared with a control group. The PCB levels in the children (serum) were 10.3 ng/g l.w., which is lower than the levels in polar bears in the present study. Alveblom et al. (2003) investigated the incidence of osteoporotic fractures in fishermen and their wives from the Baltic Sea (high pollution) and compared these with fishermen from the west coast of Sweden (low pollution) as controls. For vertebral fractures, there was a significantly higher incidence rate ratio for east coast (Baltic) women compared with west coast women, and a similar but nonsignificant tendency was found for men. The PCB concentration (10 congeners) was 2,000 ng/g l.w. (serum), which was significantly higher compared with the west coast population but lower compared with the range in the subcutaneous adipose tissue of East Greenland polar bears. These environmental studies support the findings of negative associations between PCBs/DDT and BMD levels in East Greenland polar bears.
In the present study, we observed a negative correlation between ∑PBDE concentrations in adipose tissue and BMD in subadults. Disturbances in thyroid function and developmental toxicity (histopathology) have been shown to be associated with PBDEs in laboratory rats (e.g., de Wit 2002) as well as in polar bears from Svalbard (Braathen et al. 2004; Skaare et al. 2001).
Conclusions
Skull BMD increased with age in subadults and was higher in males than in females at all ages. For adult females from 14 years of age, a menopausal BMD decrease was indicated, but further examination requires a larger sample size. BMD in skulls from subadult females, subadult males, and adult males sampled in the supposed pollution period (1966–2002) was significantly lower than BMD in skulls from the period before supposed pollution with organochlorine and PBDE compounds (1892–1932). Furthermore, correlative relationships suggest that ∑PCB, ∑CHL, dieldrin, and ∑DDT exposure negatively influenced BMD in skulls from subadults of both sexes and adult males.
Correction
In the manuscript originally published online, the years 1892–1960 and 1961–2002 were used to represent the pre- and post-organochlorine/PBDE periods, respectively. These years have been changed throughout to reflect the years in which the skulls were actually collected (1892–1932 and 1966–2002).
Figure 1 DXA scanning image of a 12-year-old female East Greenland polar bear skull sampled in 1972. Note the high-density areas of cortical bone tissue and the lower density areas of trabecular bone tissue.
Figure 2 BMD (g/cm2) in skulls from East Greenland polar bears versus individual age.
Table 1 Skull BMD [g/cm2 ± SD (n)] for subadult and adult East Greenland polar bears from 1892 to 2002.
Period Variable Subadult females Subadult males Adult females Adult males
1892–1932 BMD 1.67 ± 0.37 (7) 2.22 ± 0.19 (5) 1.99 ± 0.13 (9) 2.73 ± 0.21 (20)
Age 2.6 ± 1.3 (7) 4.4 ± 1.3 (5) 12.7 ± 3.7 (9) 11.5 ± 4.5 (20)
1966–2002 BMD 1.55 ± 0.3* (17) 1.85 ± 0.32* (35) 1.98 ± 0.13 (31) 2.49 ± 0.24** (15)
Age 2.8 ± 1 (17) 3.2 ± 1.1 (35) 12.1 ± 6.3 (31) 10.7 ± 5.5 (15)
Data are divided into two periods: 1892–1932 (supposed organochlorine and PBDE nonpolluted) and 1966–2002 (supposed organochlorine and PBDE polluted). BMD (g/cm2) was obtained by DXA scanning of the entire skull, and age (years) was obtained by counting the GLG of the lower I3 tooth.
* p ≤0.05 and
** p ≤0.01 significantly lower during 1966–2002 compared with the 1892–1932 period for the given age/sex group.
Table 2 Significant results from the multiple regression analyses of skull BMD versus age and year of kill in East Greenland polar bears during 1892–2002.
Age/sex group Equation r2 page pyok No.
Subadults BMD = 0.193 × age − 0.00254 × yok + 6.3 0.64 < 0.001 0.07* 64
Adult males BMD = 0.014 × age − 0.00324 × yok + 8.8 0.31 0.2 < 0.01** 35
yok, year of kill. The equation is given as [BMD = A × age + B × yok + C], with BMD (g/cm2) as the dependent variable and age (years) and yok (1892–2002) as the explanatory variables. A, B, and C are specific parameter estimates; r2 is the regression coefficient of the model; page is the p-value for age; and pyok is the p-value for the year of kill.
* Nonsignificant trend of BMD decline over the entire period 1892–2002 at the 0.05 < p ≤0.10 level.
** Significant BMD decline over the entire period 1892–2002 at the p ≤0.01 level.
Table 3 Concentrations [mean ± SD (median), ng/g l.w.] of various contaminants in subcutaneous adipose tissue of 58 East Greenland polar bears sampled during 1999–2001.
Compound Subadults (n = 35) Adult females (n = 14) Adult males (n = 9)
∑PCB 6,597 ± 2,726 (6,089) 5,334 ± 2,150* (5,770) 8,637 ± 4,111* (8,280)
∑CHL 1,598 ± 884 (1,469) 1,379 ± 591 (1,353) 1,055 ± 517 (914)
∑DDT 392 ± 209 (376) 358 ± 149 (366) 481 ± 331 (496)
∑HCH 196 ± 68 (172) 195 ± 186 (151) 294 ± 210 (181)
Dieldrin 210 ± 100 (196) 174 ± 70 (154) 177 ± 81 (172)
HCB 99 ± 84 (70) 75 ± 82 (51) 51 ± 28 (48)
∑PBDE 62 ± 33 (53) 53 ± 17 (53) 52 ± 16 (49)
* Significant difference between adult females and males at the p ≤0.05 level.
Table 4 Significant results from the multiple regression analyses of skull BMD versus age and contaminant concentrations in East Greenland polar bears sampled during 1999–2001.
Age/sex group Equation r2 page pcont No.
Subadults BMD = 0.26 × age − 0.25 × [ln(∑PCB)] + 3.1 0.59 < 0.001 < 0.04** 35
BMD = 0.24 × age − 0.19 × [ln(∑CHL)] + 2.4 0.6 < 0.001 < 0.03** 35
BMD = 0.25 × age − 0.18 × [ln(∑PBDE)] + 1.69 0.58 < 0.001 0.06* 35
Adult males BMD = 0.02 × age − 0.17 × [ln(∑DDT)] + 3.4 0.69 > 0.08 < 0.02** 9
BMD = −0.005 × age − 0.37 × [ln(dieldrin)] + 4.5 0.85 0.43 < 0.002# 9
The equation is given as [BMD = A × age + B × ln(contaminant) + C], with BMD (g/cm2) as the dependent variable and age (years) and log-transformed contaminant concentration [ln(ng/g l.w.)] as the explanatory variables. A, B, and C are specific parameter estimates; r2 is the regression coefficient of the model; page is the p-value for age; and pcont is the p-value for contaminants.
* Nonsignificant trend of a negative correlation between BMD and ln(∑PBDE) at the 0.05 < p ≤0.10 level.
** Significant negative correlation between BMD and organochlorine contaminant group at the p ≤0.05 level.
# Significant negative correlation between BMD and organochlorine contaminant group at the p ≤0.01 level.
==== Refs
References
Alveblom AK Rylander L Johnell O Hagmar L 2003 Incidence of hospitalized osteoporotic fractures in cohorts with high dietary intake of persistent organic compounds Int Arch Occup Environ Health 76 246 248 12690500
AMAP 2004. Persistent Organic Pollutants in the Arctic. AMAP Assessment 2002. Oslo:Arctic Monitoring and Assessment Programme.
Beard J Marshall S Jong K Newton R Triplett-McBride T Humphries B 2000 1,1,1-Trichloro-2,2-bis (p -chlorophenyl)-ethane (DDT) and reduced bone mineral density Arch Environ Health 55 3 177 180 10908100
Bengtsson BE Bengtsson A Himberg M 1985 Fish deformities and pollution in some Swedish waters Ambio 14 32 35
Bergman A Olsson M Reiland S 1992 Skull bone lesions in the Baltic grey seal (Halichoerus grypus ) Ambio 21 517 519
Bernhoft A Skaare JU Wiig Ø Derocher AE Larsen HJS 2000 Possible immunotoxic effects of organochlorines in polar bears (Ursus maritimus) at Svalbard J Toxicol Environ Health A 57 7 561 574 10777247
Bernhoft A Wiig Ø Skaare JU 1997 Organochlorines in polar bears (Ursus maritimus ) at Svalbard Environ Pollut 96 159 175 15093456
Birnbaum LS 1994 Endocrine effects of prenatal exposure to PCBs, dioxins, and other xenobiotics: implications for policy and future research Environ Health Perspect 102 676 679 7895708
Blomkvist G Roos A Jensen S Bignert A Olsson M 1992 Concentrations of sDDT and PCB in seals from Swedish and Scottish waters Ambio 21 8 539 545
Braathen M Derocher AE Wiig Ø Sørmo EG Lie E Skaare JU Jenssen BM 2004 Relationships between PCBs and thyroid hormones and retinol in female and male polar bears Environ Health Perspect 112 826 833 15175168
Brandt M Siegel MI 1978 The effects of stress on cortical bone thickness in rodents Am J Phys Anthropol 49 31 34 677294
Colborn T Vom Saal FA Soto AM 1993 Developmental effects of endocrine-disrupting chemicals in wildlife and humans Environ Health Perspect 101 378 384 8080506
Comiso JC 2002 A rapidly declining perennial sea ice cover in the Arctic [Letter] Geophys Res Lett 29 1956
Damstra T Barlow S Bergman A Kavlock R Kraak GVD 2002. Global Assessment of the State-of-the-Science of Endocrine Disruptors. Geneva:World Health Organization.
de Guise S Lagace A Beland P Girard C Higgins R 1995 Nonneoplastic lesions in beluga whales (Delphinapterus leucas ) and other marine mammals from the St. Lawrence estuary J Comp Pathol 112 3 257 271 7560301
DeLillis RA 1989. The endocrine system. In: Robbins Pathological Basis of Disease (Cotran RS, Kumar V, Robbins SL, eds). Philadelphia:W.B. Saunders Co., 1205–1276.
de March BGE de Wit C Muir DCG Braune B Gregor DJ Norstrom RJ 1998. Persistent organic pollutants. In: AMAP Assessment Report: Arctic Pollution Issues. Oslo:Arctic Monitoring and Assessment Programme, 183–372.
Derocher AE Stirling I 1994 Age-specific reproductive performance of female polar bears (Ursus maritimus ) Can J Zool 234 Pt 4 527 536
de Wit CA 2002 An overview of brominated flame retardants in the environment Chemosphere 46 5 583 624 11999784
Dietz R Heide-Jørgensen MP Härkönen T Teilmann J Valentin N 1991 Age determination of European harbour seal (Phoca vitulina L.) Sarsia 76 17 21
Dietz R Riget FF Sonne C Letcher R Born EW Muir DCG 2004 Seasonal and temporal trends in polychlorinated biphenyls and organochlorine pesticides in East Greenland polar bears (Ursus maritimus ), 1990–2001 Sci Total Environ 331 107 124 15325144
Doyle WJ Kelley C Siegel MI 1977 The effects of audiogenic stress on the growth of long bones in the laboratory rat (Rattus norvegicus ) Growth 41 183 189 914053
Feldman EC 1995. Hyperadrenocorticism. In: Textbook of Veterinary Internal Medicine, Vol. 2 (Ettinger SJ, Feldman EC, eds). Philadelphia:W.B. Saunders Co., 1538–1578.
Fernie K Bortolotti G Drouillard K Smits J Marchant T 2003 Developmental toxicity of in ovo exposure to polychlorinated biphenyls: II. Effects of maternal or paternal exposure on second-generation nestling American kestrels Environ Toxicol Chem 22 11 2688 2694 14587909
Førland EJ Hanssen-Bauer I Jónsson T Kern-Hansen C Nordli PØ Tveito OE 2002 Twentieth-century variations in temperature and precipitation in the Nordic Arctic Polar Rec 38 206 203 210
Ganong WF 1991. Review of Medical Physiology. 15th ed. Norwalk, CT:Appleton & Lange.
Glynn AW Michaëlsson K Lind PM Wolk A Aune M Atuma S 2000 Organochlorines and bone mineral density in Swedish men from the general population Osteoporos Int 11 1036 1042 11256895
Guo YL Lin CJ Yao WJ Ryan JJ Hsu CC 1994 Musculoskeletal changes in children prenatally exposed to polychlorinated-biphenyls and related-compounds (Yu-Cheng children) J Toxicol Environ Health 41 1 83 93 8277528
Haave M Ropstad E Derocher AE Lie E Dahl E Wiig Ø 2003 Polychlorinated biphenyls and reproductive hormones in female polar bears at Svalbard Environ Health Perspect 111 431 436 12676595
Hampson G Bhargava N Cheung J Vaja S Seed PT Fogelman I 2002 Low circulating estradiol and adrenal androgens concentations in men on glucocorticoids: a potential contributory factor in steroid-induced osteoporosis Metabolis 51 11 1458 1462
Hensel RJ Sorensen FE 1980 Age determination of live polar bears Int Conf Bear Res Manage 4 93 100
Jamsa T Viluksela M Tuomisto JT Tuomisto J Tuukkanen J 2001 Effects of 2,3,7,8-tetrachlorodibenzo-p -dioxin on bone in two rats strains with different aryl hydrocarbon receptor structures J Bone Miner Res 16 10 1812 1820 11585345
Johansson S Lind PM Hakansson H Oxlund H Örberg J Melhus H 2002 Subclinical hypervitaminosis A causes fragile bones in rats Bone 31 6 685 689 12531562
Johansson S Melhus H 2001 Vitamin A antagonizes calcium response to vitamin D in man J Bone Miner Res 16 10 1899 1905 11585356
Juul A 2001 The effects of oestrogens on linear bone growth Hum Reprod Update 7 3 303 313 11392377
Leder BZ Smith MR Fallon MA Lee MLT Finkelstein JS 2001 Effects of gonadal steroid suppression on skeletal sensitivity to parathyroid hormone in men J Clin Endocr Metab 86 2 511 516 11158001
Letcher RJ Norstrom RJ Lin S Ramsay MA Bandiera SM 1996 Immunoquantification and microsomal monooxygenase activities of hepatic cytochromes P4501A and P4502B and chlorinated hydrocarbon contaminant levels in polar bear (Ursus maritimus ) Toxicol Appl Pharmacol 137 127 140 8661337
Lie E Bernhoft A Riget FF Belikov SE Boltunov AN Derocher AE 2003 Geographical distribution of organochlorine pesticides (OCPs) in polar bears (Ursus maritimus ) in the Norwegian and Russian Arctic Sci Total Environ 306 159 170 12699924
Lie E Larsen HJS Larsen S Johansen GM Derocher AE Lunn NJ 2004 Does high organochlorine (OC) exposure impair the resistance to infection in polar bears (Ursus maritimus )? Part I: Effect of OCs on the humoral immunity? J Toxicol Environ Health A 67 555 582
Lind PM Bergman A Olsson M Örberg J 2003 Bone mineral density in male Baltic grey seal Ambio 32 6 385 388 14627366
Lind PM Eriksen EF Sahlin L Edlund M Örberg J 1999 Effects of the antiestrogenic environmental pollutants 3,3’,4,4’,5-pentachlorobiphenyl (PCB-126) in rat bone and uterus: diverging effects in ovarectomized and intact animals Toxicol Appl Pharmacol 154 236 244 9931283
Lind PM Larsson S Johansson S Melhus H Wikström M Lindhe Ö 2000b Bone tissue composition, dimensions and strength in female rats given an increased dietary level of vitamin A or exposed to 3,3’4,4’5-pentachlorobiphenyl (PCB-126) alone or in combination with vitamin C Toxicology 151 11 23 11074296
Lind PM Larsson S Oxlund H Håkansson H Nyberg K Eklund T 2000a Change of bone tissue composition and impaired bone strength in rats exposed to 3,3’,4,4’,5-pentachlorobiphenyl (PCB126) Toxicology 150 41 51 10996662
Lind PM Milnes MR Lundberg R Bermudez D Örberg J Guillette LJ 2004 Abnormal bone composition in female juvenile American alligators from a pesticide-polluted lake (Lake Apopka, Florida) Environ Health Perspect 112 359 362 14998753
Luross JM Alaee M Sergeant DB Cannon CM Whittle DM Solomon KR 2002 Spatial distribution of polybrominated diphenyl ethers and polybrominated biphenyls in lake trout from the Laurentian Great Lakes Chemosphere 46 665 672 11999789
Manolagas SC Bellido T Jilka RL 1995 New insights into the cellular, biochemical and molecular basis of post-menopausal and senile osteoporosis: roles of IL-6 and gp130 Int J Immunopharmacol 17 2 109 116 7657404
Manolagas SC Jilka RL 1995 Bone marrow, cytokines, and bone remodeling. Emerging insights into the pathophysiology of osteoporosis N Engl J Med 332 5 305 311 7816067
Michaelsson K Lithell H Vessby B Melhus H 2003 Serum retinol levels and the risk of fracture New Engl J Med 348 4 287 294 12540641
Mooney MP Siegel MI Gest TR 1985 Prenatal stress and increased fluctuating asymmetry in the parietal bones of neonatal rats Am J Phys Anthropol 68 131 134 4061598
Mortensen PÅ Bergman A Bignert A Hansen HJ Härkönen T Olsson M 1992 Prevalence of skull lesions in harbour seals (Phoca vitulina ) in Swedish and Danish museum collections: 1835–1988 Ambio 21 520 524
Navas JM Segner H 1998 Antiestrogenic activity of anthropogenic and natural chemicals Environ Sci Pollut Res 5 75 82
Nelson HD 2003 Postmenopausal osteoporosis and estrogen Am Fam Physician 68 4 606 615 12952379
Nilsson JA 1994 Energetic stress and the degree of fluctuating asymmetry—implications for a long lasting, honest signal Evol Ecol 8 3 248 255
Norstrom RJ Belikov S Born EW Garner GW Malone B Olpienski S 1998 Chlorinated hydrocarbon contaminants in polar bears from eastern Russia, North America, Greenland and Svalbard: biomonitoring of Arctic pollution Arch Environ Contam Toxicol 35 2 354 367 9680529
Oskam IC Ropstad E Dahl E Lie E Derocher AE Wiig Ø 2003 Organochlorines affect the major androgenic hormone, testosterone, in male polar bears (Ursus maritimus ) at Svalbard J Toxicol Environ Health A 66 22 2119 2139 14710596
Oskam IC Ropstad E Lie E Derocher AE Wiig Ø Dahl E 2004 Organochlorines affect the steroid hormone cortisol in free-ranging polar bears (Ursus maritimus ) at Svalbard, Norway J Toxicol Environ Health A 67 959 977 15205038
Polischuk S Ramsay M Norstrom N 2002 Body burdens and tissue concentrations of organochlorines in polar bears (Ursus maritimus ) vary during seasonal fasts Environ Pollut 118 29 39 11996380
Polischuk SC Letcher RJ Norstrom RJ Ramsay MA 1995 Preliminary results of fasting on the kinetics of organochlorines in polar bears (Ursus maritimus ) Sci Total Environ 160/161 465 472 7892579
Promislow JHE Goodman-Gruen D Slymen DJ Barrett-Connor E 2002 Retinol uptake and bone mineral density in the elderly: the Rancho Bernardo Study J Bone Miner Res 17 8 1349 1358 12162487
Ramsay MA Stirling I 1988 Reproductive biology and ecology of female polar bears (Ursus maritimus ) J Zool (Lond) 214 601 634
Render JA Aulerich RJ Bursian SJ Nachreiner RF 2000a Proliferation of maxillary and mandibular periodontal squamous cells in mink fed 3,3’4,4’,5-pentachlorobiphenyl (PCB 126) J Vet Diagn Invest 12 5 477 479 11021441
Render JA Bursian SJ Rosenstein DS Aulerich RJ 2001 Squamous epithelial proliferation in the jaws of mink fed diets containing 3,3’4,4’,5-pentachlorobiphenyl (PCB 126) or 2,3,7,8-tetrachlorodibenzo-p -dioxin (TCDD) Vet Hum Toxicol 43 1 22 26 11205072
Render JA Hochstein JR Aulerich RJ Bursian SJ 2000b Proliferation of periodontal squamous epithelium in mink fed 2,3,7,8-tetrachlorodibenzo-p -dioxin (TCDD) Vet Hum Toxicol 42 2 85 86 10750171
Rosing-Asvid A Born EW Kingsley MCS 2002 Age at sexual maturity of males and timing of the mating season of polar bears (Ursus maritimus ) in Greenland Polar Biol 25 878 883
Rothcock DA Yu Y Maykut GA 1999 Thinning of the Arctic sea-ice cover Geophys Res Lett 26 23 3469 3472
Sandala GM Sonne-Hansen C Dietz R Muir DCG Valters K Bennett ER 2004 Methyl sulfone and hydroxylated PCB metabolites in adipose and whole blood of polar bear (Ursus maritimus ) from Scoresby Sound, Greenland Sci Total Environ 2004 331 125 141
Sarazin M Alexandre C Thomas T 2000 Influence on bone metabolism of dietary trace elements, protein, fat, carbohydrates and vitamins Joint Bone Spine 67 5 408 418 11143907
Schandorff S 1997 Developmental stability and skull lesions in the harbour seal (Phoca vitulina ) in the 19th and 20th centuries Ann Zool Fenn 34 151 166
Selye H 1973 The evolution of the stress concept Am Sci 61 692 699 4746051
Siegel MI Doyle WJ 1975a The differential effects of prenatal and postnatal audiogenic stress on fluctuating dental asymmetry J Exp Zool 191 211 214 1113068
Siegel MI Doyle WJ 1975b Stress and fluctuating limb asymmetry in various species of rodents Growth 39 363 369 1183854
Siegel MI Mooney MP 1987 Perinatal stress and increased fluctuating asymmetry of dental calcium in the laboratory rat Am J Phys Anthropol 73 267 270 3618757
Siegel MI Mooney MP Taylor AB 1992 Dental and skeletal reduction as a consequence of environmental stress Acta Zool Fenn 191 145 149
Siegel P Siegel MI Krimmer EC Doyle WJ Barry H 1977 Fluctuating dental asymmmetry as an indicator of the stressful prenatal effects of delta9 -tetrahydrocannabinol in the laboratory rat Toxicol Appl Pharmacol 42 339 344 595012
Singh S Casper RF Fritz PC Sukhu B Ganss B Girard B 2000 Inhibition of dioxin effects on bone formation in vitro by a newly described aryl hydrocarbon receptor antagonist, resveratrol J Endocrinol 167 1 183 195 11018766
Skaare JU Bernhoft A Wiig Ø Norum KR Haug E Eide DM 2001 Relationship between plasma levels of organochlorines, retinol and thyroid hormones from polar bears (Ursus maritimus ) at Svalbard J Toxicol Environ Health A 62 227 241 11245393
Sonne C Leifsson PS Dietz R Born EW Letcher RJ Kirkegaard M In press. Enlarged clitoris in wild polar bears (Ursus maritimus) can be misdiagnosed as pseudohermaphroditism. Sci Total Environ.
Sonne-Hansen C Dietz R Leifsson PS Hyldstrup L Riget FF 2002 Cadmium toxicity to ringed seals (Phoca hispida )—an epidemiological study of possible cadmium induced nephropathy and osteodystrophy in ringed seals (Phoca hispida ) from Qaanaaq in Northwest Greenland Sci Total Environ 295 167 181 12186285
Stirling I Lunn NJ Iacozza J 1999 Long-term trends in the population ecology of polar bears in western Hudson Bay in relation to climatic change Arctic 52 3 294 306
Szulc P Hofbauer LC Heufelder AE Roth S Delmas PDF 2001 Osteoprotegerin serum levels in men: correlation with age, estrogen and testosterone status J Clin Endocr Metab 86 7 3162 3165 11443182
Valentine DW Soulé M 1973 Effects of p,p ’-DDT on developmental stability of pectoral fin rays in the grunion (Leuresthes tenuis ) Nat Mar Fish Serv Fish Bull 71 921 925
Van Langendonck L Claessens AL Lefevre J Thomis M Philippaerts R Delvaux K 2002 Association between bone mineral density (DXA), body structure, and body composition in middle-aged men Am J Hum Biol 14 6 735 742 12400034
Wiig Ø Derocher AE Cronin MM Skaare JU 1998 Female pseudohermaphrodite polar bears at Svalbard J Wildlife Dis 34 4 792 796
Zakharov MZ Yablokov AV 1990 Skull asymmetry in the Baltic grey seal: effects of environmental pollution Ambio 19 5 266 269
|
15579418
|
PMC1253664
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2004 Dec 13; 112(17):1711-1716
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7293
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science 10.1289/ehp.7066ehp0112-00171715579419ResearchArticlesGIS Modeling of Air Toxics Releases from TRI-Reporting and Non-TRI-Reporting Facilities: Impacts for Environmental Justice Dolinoy Dana C. 1Miranda Marie Lynn 21Integrated Toxicology Program and2Children’s Environmental Health Initiative, Nicholas School of the Environment and Earth Sciences, Duke University, Durham, North Carolina, USAAddress correspondence to M.L. Miranda, Children’s Environmental Health Initiative, Nicholas School of the Environment and Earth Sciences, A134-LSRC, Box 90328, Duke University, Durham, NC 27708 USA. Telephone: (919) 613-8023. Fax: (919) 684-8741. E-mail:
[email protected] thank C. Bradshaw, J. Hamilton, J. Levy, and M.A. Overstreet for their help and guidance on this project.
This research was supported in part by funding from the National Institute of Environmental Health Sciences (ES10356).
The authors declare they have no competing financial interests.
12 2004 13 9 2004 112 17 1717 1724 3 3 2004 13 9 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. The Toxics Release Inventory (TRI) requires facilities with 10 or more full-time employees that process > 25,000 pounds in aggregate or use > 10,000 pounds of any one TRI chemical to report releases annually. However, little is known about releases from non-TRI-reporting facilities, nor has attention been given to the very localized equity impacts associated with air toxics releases. Using geographic information systems and industrial source complex dispersion modeling, we developed methods for characterizing air releases from TRI-reporting as well as non-TRI-reporting facilities at four levels of geographic resolution. We characterized the spatial distribution and concentration of air releases from one representative industry in Durham County, North Carolina (USA). Inclusive modeling of all facilities rather than modeling of TRI sites alone significantly alters the magnitude and spatial distribution of modeled air concentrations. Modeling exposure receptors at more refined levels of geographic resolution reveals localized, neighborhood-level exposure hot spots that are not apparent at coarser geographic scales. Multivariate analysis indicates that inclusive facility modeling at fine levels of geographic resolution reveals exposure disparities by income and race. These new methods significantly enhance the ability to model air toxics, perform equity analysis, and clarify conflicts in the literature regarding environmental justice findings. This work has substantial implications for how to structure TRI reporting requirements, as well as methods and types of analysis that will successfully elucidate the spatial distribution of exposure potentials across geographic, income, and racial lines.
air dispersion modelingair toxicsenvironmental justicegeographic information systems (GIS)Toxics Release Inventory (TRI)
==== Body
Temporal, spatial, and other special circumstances can result in disproportionate environmental exposures and may play a role in differential health outcomes. For example, numerous studies highlight the disparate impact of asthma and allergies on specific subsets of the population, including minorities and poor families, as well as people living in urban environments (Oliveti et al. 1996; Weitzman et al. 1990; Wissow et al. 1988). In addition, people of color are more likely to live in areas that fail to meet national ambient air quality standards. In 1990, 57% of whites, 65% of African Americans, and 80% of Hispanics lived in counties that exceeded one of the federal criteria air pollutant standards (Wernette and Nieves 1992). In addition, 12% of whites, 20% of African Americans, and 31% of Hispanics lived in counties that failed to meet the federal standard for three or more criteria air pollutants (Wernette and Nieves 1992).
The Toxics Release Inventory (TRI), created by the Emergency Planning and Community Right-to-Know Act (EPCRA 1986), requires manufacturing facilities with ≥ 10 full-time employees that process > 25,000 lb in aggregate or use > 10,000 lb of any one of the 650 TRI chemicals to report their releases and waste management strategies annually to the U.S. Environmental Protection Agency (U.S. EPA 2001a). In January 2001, the U.S. EPA lowered the reporting requirement for lead and lead compounds to 100 lb (U.S. EPA 2001b). Reporting requirements cover emissions from routine processing and/or accidental releases as well as chemicals managed as waste from businesses categorized in Standard Industrial Classification (SIC) codes 10, 12, 20–39, 49, and 51, including metal and coal mining, printing, chemical, paper, electronic, plastics, refining, metal, and other industries. Facilities that fail to report annual releases by 1 July each year are subject to fines of up to $27,500/day (U.S. EPA 2001c).
The purpose of EPCRA is 2-fold. First, it seeks to provide citizens with information on chemical releases and waste management activities in and around their neighborhood, thereby empowering them to hold companies accountable for their emissions (U.S. EPA 2001c). Second, it attempts to provide government agencies with data for research and policy development (U.S. EPA 2001c). Although it is an important advance in helping communities understand the local air toxics load, the TRI program suffers from at least three weaknesses. First, minimum reporting requirements do not require smaller industrial facilities to report. Theoretically, cumulative effects of smaller non-TRI-reporting facilities might outweigh the individual effect of larger (but fewer) TRI-reporting facilities. Second, the U.S. EPA’s TRI database (as well as TRI data organized and maintained by environmental interest groups) does not address environmental fate and transport of industry emissions using modeling and other analytical techniques. The characteristics of pollutant concentration distributions depend on a variety of factors, including media emitted, physical properties of the chemical, wind direction and speed, meteorologic conditions, and stack height. Finally, by reporting emissions at the county level, the TRI database fails to capture important highly localized equity impacts.
The analysis presented here develops a methodology to characterize releases inclusively by incorporating emissions from smaller, non-TRI-reporting facilities. In addition, the project is carried out at four geographic levels of resolution (ZIP code, census tract, census block group, and census block) to assess the importance of geographic resolution in analyzing air toxics emissions. In this article we model pollutant concentrations using dispersion modeling and geographic information systems (GIS) analysis and hypothesize that inclusive modeling of releases from TRI-reporting and smaller non-TRI-reporting facilities at finer levels of geographic resolution will change the distribution of exposure potential for people living in a given area and subsequently improve the quality of equity analysis.
Materials and Methods
Study area.
The analysis focuses on Durham County, North Carolina (USA), which represents a broad range of values across demographic, socioeconomic, and social indicators. Table 1 shows selected demographics for Durham County from 2000 Census data (U.S. Census Bureau 2003). Forty percent of Durham County residents are African American, and almost 8% are Hispanic (U.S. Census Bureau 2003). In addition, approximately 10% of residents are living in poverty, and almost 46% reside in rental properties (U.S. Census Bureau 2003). Compared with Durham County as a whole, the State of North Carolina, and the United States, central Durham has a higher percentage of minorities, higher percentage of families in poverty, higher percentage of children < 6 years of age in poverty, lower median household income, and higher percentage of renter-occupied housing (U.S. Census Bureau 2003). Figure 1 highlights the location of Durham County within North Carolina. The yellow box represents central Durham. Figure 2 depicts two demographic variables for Durham County (percent African American by 2000 census block and median household income by 2000 census block group). Note that areas within the yellow box (central Durham) are characterized with a higher percentage of African Americans and lower household median income.
Demographic data.
This project uses year 2000 demographic data from the U.S. Census Bureau. Census demographic information is available in four different geographic scales: ZIP code tabulation areas (ZCTAs), tracts, block groups, and blocks. ZIP codes and tracts designate the largest geographic areas. The most detailed and focused information is contained in blocks. Blocks are also combined into block groups, an intermediate category. Durham County contains 20 ZIP codes, 53 tracts, 129 census block groups, and 3,284 census blocks. Figure 3 depicts ZIP code, tract, block group, and block boundaries for Durham County.
Facility data.
Year 2000 TRI data were extracted from the U.S. EPA’s TRI Explorer (U.S. EPA 2002a) and uploaded into a GIS (ArcView 3.2; Environmental Systems Research Institute, Redlands, CA). TRI facility locations and emissions were geocoded to a base map using latitude and longitude. Facility location was cross-referenced against tax parcel data to ensure accurate geolocation. TRI data from 2000 indicate that North Carolina is home to 874 TRI sites, releasing > 126 million lb of contaminants to the air. Durham County is home to 16 of these sites, releasing > 48,000 lb of contaminants to the air.
Nonreporting facilities within TRI-reporting SIC codes were extracted from city marketing directories and imported into the GIS project. Facility locations were address-geocoded to the individual tax parcel unit. City marketing data (infoTYME version 4.1; Polk City Directories, Livonia, MI) contain countywide listings of business names, addresses, contact persons, employee range, and SIC codes. Year 2000 city marketing data (infoTYME Polk City Directories 2000) indicate that Durham County contains > 400 non-TRI-reporting industrial facilities classified in TRI-SIC reporting codes. Figure 4 maps facilities that were required to report to TRI and those in the same SIC codes that were not required to report to TRI in Durham County in 2000. Note that although only three of the TRI-reporting facilities are located in the low-income, predominantly minority communities of central Durham, most of the non-TRI-reporting, smaller facilities are situated in central Durham.
Selecting a base case.
Ideally, all SIC codes and pollutants subject to TRI guidelines would be evaluated in an aggregate model. However, to facilitate the development of the spatial methods described here, we selected a prototype SIC code and pollutant to model. On the basis of an evaluation of year 2000 air releases from several southern states, we selected a four-digit rather than two-digit SIC code as a base case. This selection criterion better supported the required modeling assumptions that a TRI facility within a defined SIC code releases a similar pollutant profile when compared with other TRI- and non-TRI-reporting facilities in the same SIC code.
Of the 16 TRI-reporting sites in Durham County, no two facilities were defined within one four-digit SIC code. Therefore, we based the prototype selection on quantity and type of air releases. We chose SIC code 2752, representing commercial lithographic printing, because it released one type of pollutant rather than multiple classes of pollutants. In addition, it ranked second within Durham County for total air releases. Within Durham County, SIC code 2752 contained one TRI-reporting and 36 non-TRI-reporting sites. The TRI-reporting site was located in southern Durham, whereas the 36 non-TRI code 2752 sites were spread throughout the county (Figure 5). The TRI-reporting site emitted “certain glycol ethers” as fugitive (rather than stack) releases to the air.
An evaluation of air emissions in six southern states with manufacturing facilities classified in SIC code 27 revealed wide variability among two-digit SIC codes. However, variability was low when facilities were restricted to four-digit SIC codes. For example, of the 16 facilities in the neighboring state of Virginia with two-digit SIC code 27 releasing TRI chemicals to the air in 2000, three were identified within four-digit SIC code 2752. All three facilities released “certain glycol ethers” or ethylene glycol to the air. In addition, for all three facilities, the overwhelming majority of the releases were identified as fugitive rather than stack.
Glycol ethers represent a bundle of chemicals used in many industries (including printing) as solvents (Environmental Defense 2002). According to 2000 TRI data, the TRI-reporting facility (PBM Graphics) in Durham County released 13,733 lb of “certain glycol ethers” to the air. All releases were classified as fugitive rather than point source. To determine the specific chemical used, we contacted PBM Graphics directly. According to PBM Graphics personnel, the company used ethylene glycol monobutyl ether in 2000. Ethylene glycol monobutyl ether is a nonphotoreactive volatile organic compound used as a solvent during printing processes. It is a suspected cardiovascular, blood, developmental, endocrine, gastrointestinal, kidney, neurologic, and respiratory toxicant [Environmental Defense 2002; New Jersey Department of Health and Senior Services (NJDHSS) 2001]. According to the CalTOX multimedia and multiexposure model, ethylene glycol monobutyl ether exposure potential is primarily through air (rather than settled materials) and induces health effects via inhalation and ingestion [State of California Department of Toxic Substances Control (SCDTSC) 2002]. The half-life of ethylene glycol monobutyl ether is approximately 16 hr in the air. Both the exposure properties and half-life make ethylene glycol monobutyl ether an appropriate pollutant for air dispersion modeling. Although other facilities within SIC code 2752 may emit different subtypes of “certain glycol ethers,” the exposure properties and half-lives of individual compounds do not vary significantly enough to invalidate modeled concentrations.
Emissions estimation algorithm.
Comparing TRI-reporting with non-TRI-reporting sites requires estimation of emissions from non-TRI-reporting facilities. Ideally, annual averages of production units would be used. However, number of employees can serve as a proxy when production units are not readily known. Therefore, we generated an employee-based emissions algorithm to impute emissions to non-TRI-reporting facilities. The general algorithm for computing the estimated emissions is as follows. Step 1 involves the calculation of a per-employee emissions rate for a chemical of concern (C1) based on data from all TRI-reporting facilities (F1, F2, F3, … , Fn). In step 2, emissions are imputed to non-TRI-reporting facilities by multiplying the per-employee emissions rate (based on the TRI-reporting facilities) by the number of employees working at each of the non-TRI-reporting facilities.
Using employees instead of production units fails to address how economies of scale might affect production patterns. However, the literature (Dasgupta et al. 2002; Little et al. 1987; U.S. EPA 2001a) indicates that smaller facilities tend to emit more pollution on a per unit of production basis than do larger units, so our imputed data likely underestimate emissions from non-TRI-reporting facilities. Therefore, if significant differences are noted between TRI-reporting models and inclusive TRI-reporting plus non-TRI-reporting sites, under this conservative approach the actual effect can be assumed to be greater.
To impute emissions for the 36 non-TRI-reporting facilities in code 2752, a per-employee emissions rate (based on emissions from PBM Graphics) was calculated. PBM Graphics employed approximately 375 employees in its printing facility in 2000. The reported emissions were 13,733 lb of glycol ethers, delivering an imputed emissions rate of 36.6 lb/employee. As a data check, several SIC code 2752 facilities in surrounding states had similar ratios of emissions per employee. We used city marketing directories (infoTYME Polk City Directories 2000) to ascertain the number of employees at the 36 non-TRI-reporting facilities. Using the per-employee emissions rate and the number of employees, we imputed air emissions for the 36 non-TRI-reporting facilities. Once the base-case methodology is developed, future analysis should include Monte Carlo simulations that vary the per-employee emissions rate across non-TRI-reporting facilities. Figure 5 depicts the 37 facilities in Durham County classified in SIC code 2752 and their corresponding imputed emissions. According to imputed emissions estimates, the 36 non-TRI-reporting facilities emitted a total of 22,156 lb/year.
ISC dispersion modeling.
Developed by the U.S. EPA (U.S. EPA 2002b), the industrial source complex (ISC) model is one of the most widely used and successful steady-state Gaussian-based air dispersion models. Major assumptions of Gaussian models include a) that the rate of plume diffusion is proportional to contaminant concentration, b) a constant emissions rate, c) a conservative pollutant (no chemical reactions or biodecay), d) relatively flat terrain, and e) perfect ground reflection. Because of these assumptions, Gaussian models are most appropriate for local applications within 50 km or 2,500 km2 (Masters 1998). Gaussian models incorporate two dispersion coefficients based on the standard deviations of the horizontal and vertical Gaussian distributions of the downwind plume dispersion (Masters 1998). The standard deviations or dispersion coefficients increase with distance downwind of the source. In addition to distance, the dispersion coefficients also consider atmospheric stability parameters that address qualitative descriptions of prevailing weather conditions such as season, time of day, and degree of cloud cover. Gaussian model output reports annual average concentration of pollutant for each defined receptor. Receptors are user-defined areas of interest and often include the geographic centroid of ZIP codes or census tracts or points on regular grids spanning a study region.
This analysis used the short-term ISC model, ISCST3 (U.S. EPA 2002b), which captures initial mixing phenomena at the source and is best suited for study areas less than 2,500 km2. Containing approximately 751 km2, Durham County falls well within this limitation. ISCST3 modeling allows for multiple source and receptor specifications and requires users to input a year’s worth of hourly meteorologic data from the National Weather Service (U.S. EPA 2002c). The modeling period was 1 January 2000 to 31 December 2000. Source emission rates were treated as constant over 1 year by converting the number of pounds released in calendar year 2000 to grams per second.
Input requirements.
Within ISCST3, sources may be specified as POINT (stack), AREA (storage piles or irregular shapes), or VOLUME (multiple vents or conveyor belts) types (U.S. EPA 1995). According to TRI Explorer and conversations with personnel from TRI and non-TRI-reporting sites in SIC code 2752, releases from printing lithography facilities are generally fugitive rather than point. The AREA rather than VOLUME type was selected in the ISCST3 model to control for differences in building size. The area of each building footprint (in square meters) was based on the area of PBM Graphics scaled to the number of employees. Furthermore, the AREA subtype is best suited for low-level releases with no plume rise (U.S. EPA 1995). Area emission rates based on the per-employee emissions algorithm were entered into ISCST3 in grams per second meter squared. An average release height of 5 m was specified for each source. Source coordinates were entered as universal transverse mercator (UTM) coordinates.
A year’s worth of hourly meteorologic data were compiled using the PCRAMMET meteorologic preprocessor program (U.S. EPA, Research Triangle Park, NC). Ground-level weather data were obtained from the Raleigh–Durham Airport surface station (approximately 3 miles southwest of Durham County). The anemometer height at the airport is approximately 10.1 m. Mixing height data from the National Climatic Data Center (U.S. EPA 2002c) were obtained for the closest station (Greensboro, NC), located approximately 50 miles west of Durham County. The twice-daily mixing height values were combined with hourly surface data using PCRAMMET to derive hourly interpolated mixing height values.
We defined receptors as the geographic centroid of four modeling units (ZIP code, census tract, census block group, and census block) in Durham County, North Carolina. For each geographic scale, receptor coordinates of the centroids were entered as UTM coordinates. The default receptor elevation of ground level was used. Areas adjacent to Durham County were not specified or analyzed in this study.
To control for pollutant fate and transport characteristics, the ISCST3 model allows users to input pollutant half-life and specify average land terrain across the study area of interest. As an initial exercise, default values for pollutant half-life and landscape terrain were first specified. The ISCST3 default pollutant half-life is 4 hr. However, the half-life of ethylene glycol monobutyl ether is 16 hr. When the default half-life was changed to 16 hr, we observed no significant changes in output results. The default ISCST3 landscape terrain is rural. Because the landscape of Durham County is variable, the models were also specified using an urban terrain. Results did not vary significantly based on rural versus urban specified landscape terrain.
Models.
To assess the importance of inclusive modeling of all emitters as well as the importance of geographic resolution, we specified eight ISCST3 models: 1a, TRI-reporting sites alone at ZIP code level (20 receptors); 1b, all emitters at ZIP code level (20 receptors); 2a, TRI-reporting sites alone at tract level (53 receptors); 2b, all emitters at tract level (53 receptors); 3a, TRI-reporting sites alone at block group level (129 receptors); 3b, all emitters at block group level (129 receptors); 4a, TRI-reporting sites alone at block level (3,824 receptors); 4b, all emitters at block level (3,824 receptors).
Each model run generated an average concentration of the pollutant in micrograms per cubic meter in a particular receptor grid for the entire year. Comparing run a with run b (e.g., comparing 1a and 1b) allows for determination of the importance of inclusive modeling—that is, whether including non-TRI-reporting facilities changes exposure potential across different demographic groups. Comparing runs 1–4 explores the importance of geographic resolution in analyzing contaminant distribution across demographic groups. Statistical and spatial analysis of pollutant concentration was based on model output and was not verified by collecting environmental samples.
Statistical and spatial analysis.
Using spatial and tabular tools within GIS, modeled emissions from the ISC dispersion models were aggregated into spatially referenced data sets and combined with underlying census demographic data. The combined data sets were imported into Microsoft Excel (Excel 2000; Microsoft, Seattle, WA) and STATA 8.0 (Stata Corp., College Station, TX) for statistical analysis.
Cumulative distribution functions.
Comparing means (or medians) of modeled concentration, as is the case in multivariate regression analysis, may overemphasize differences near the center of the concentration distribution. Many times, scientists and public health analysts are most concerned with areas of relatively high (or low) exposure risk (i.e., the tails of the distribution). Therefore, we used cumulative distribution functions (CDFs) to address disparate exposure potential across two groups. For illustrative purposes, the y-axis of a CDF curve represents the percentage of the population (from 0 to 100), and the x-axis represents exposure potential (e.g., interpolated monitoring site data or modeled concentration levels) (Lopez 2002).
We estimated the CDFs using techniques reported in Waller et al. (1999). CDFs were created for all four levels of geographic resolution (ZIP code, census tract, census block group, and census block), although only data for census block, the finest level of resolution, are presented here. Population data for each subpopulation of interest for each geographic level of resolution were determined using 2000 census data and GIS. Exposure values were assigned to each unit based on modeled concentration values for the corresponding geographic level of resolution.
Multivariate statistical analysis.
To access multiple demographic variables at once, multivariate statistical analysis was performed with STATA 8.0. All dependent variables were log-transformed to normalize right-skewed data.
Kriging.
Using the spatial analyst extension within ArcView version 3.2 GIS software, a set of contour lines representing predicted concentration of glycol ethers for the entire Durham County were developed. Using a built-in geostatistical program with user-defined parameters, ArcView software interpolates lines that represent locations with the same pollutant concentration magnitude. Although kriging the modeled data introduces an additional layer of uncertainty, the smoothed contour lines depict a more easily interpreted array of pollutant concentrations, which is extremely useful for neighborhood-level equity analyses and community outreach.
Results
The outcome variables of interest from the ISC dispersion modeling data sets are a) the annual average concentration (micrograms per cubic meter) of glycol ethers based on modeling of the TRI site alone and b) the annual average concentration (micrograms per cubic meter) of glycol ethers based on modeling of the TRI site plus non-TRI-reporting sites. Modeling was conducted at four geographic levels: ZIP code, census tract, census block group, and census block. The annual average concentrations were converted to nanograms per cubic meter to facilitate presentation and log transformation.
Table 2 presents descriptive statistics for the annual average concentration in ZIP codes, census tracts, census block groups, and census blocks. Dispersion modeling data range in concentration from 0.3 ng/m3 (TRI site alone, ZIP code level) to 821.05 ng/m3 (all sites together, census block level). The inclusion of non-TRI-reporting sites in the model increases the average concentration among ZIP codes from 1.5 to 4.9 ng/m3. Likewise, the inclusion of smaller non-TRI-reporting sites in the model increases the average concentration among census tracts from 2.7 to 10.3 ng/m3; for census block groups, from 3.0 to 10.2 ng/m3; and for census blocks, from 3.9 to 12.1 ng/m3.
Importance of inclusive modeling.
As shown in Figure 6, inclusive modeling of all facilities, accomplished by imputing emissions to non-TRI-reporting facilities in the same SIC code, rather than modeling of TRI sites alone, significantly alters the magnitude and spatial distribution of modeled air concentrations. Recall from Figure 2 that areas in southern Durham County have higher household median incomes and relatively low densities of minorities compared with central Durham, as measured by 2000 Census data (U.S. Census Bureau 2003). Note the northward drift of higher concentration contours (the deeper the red color, the higher the modeled concentration) into lower income, predominantly minority communities. Thus, incorporating the non-TRI-reporting facilities provides a substantially different perspective on exposure to contaminants across race and income lines.
For noninclusive modeling at each level of geographic resolution, major impacts occur within a few miles of the TRI site. For inclusive modeling of the TRI-reporting plus non-TRI-reporting facilities at each level of geographic resolution, major impacts are spread throughout Durham County and into adjacent counties (Chatham, Orange, and Wake). The aggregate effects of modeling multiple smaller non-TRI-reporting emissions in central Durham are of the same order of magnitude as the effects of the larger TRI site in southern Durham. Although non-TRI-reporting sites do not significantly affect exposure potential in areas with TRI facilities, they do affect exposure potential in areas at some distance from TRI facilities. This results partly from the size and specific locations of the reporting and non-TRI-reporting 2752 facilities and may not necessarily hold when generalized to other SIC codes.
Figure 7 depicts the CDF for African-American and white subpopulations modeled at the block level. Figure 7A represents exposure values for noninclusive modeling of air emissions for TRI-reporting facilities only. The CDF curves for African-American and white subpopulations exhibit a narrow gap, indicating that a slightly larger proportion of whites reside in blocks with lower exposure potentials. Figure 7B represents exposure potential values for inclusive modeling of air emissions from all emitters at the block level. Inclusive modeling produces a larger gap between the CDF curves for the African-American and white subpopulations. The increase in exposure disparity moving from noninclusive to inclusive modeling persists at the three coarser levels of geographic resolution (data not shown). However, the increased gap is most apparent at the census block level.
Figure 8 depicts the CDF curves for comparing adult and nonadult (< 18 years of age) subpopulations. Again, Figure 8A represents exposure values for noninclusive modeling of air emissions for TRI-reporting facilities only. The CDF curves for adults and nonadults overlap, indicating a lack of disparate exposure. Figure 8B represents exposure values for inclusive modeling of air emissions from all emitters. Unlike the CDF for race depicted in Figure 7, potential exposure disparities based on age do not appear to be sensitive to noninclusive versus inclusive modeling. CDFs were also estimated for persons < 5 versus > 5 years of age. Significant differences in exposure potential were not observed based on noninclusive versus inclusive modeling.
Importance of geographic resolution.
Comparing run 1 (ZIP code receptor) through run 4 (census block receptors) in Table 2 reveals that modeling receptors at a more refined geographic resolution alters the annual average concentrations of glycol ethers for both the TRI models alone and the inclusive all-sites models. The range of concentrations for the census block model is successively greater than the range of concentrations for the coarser geographic scale models. Because the same emissions are being spread over successively smaller areas, the wider range of concentrations at finer geographic scales is an intuitive result.
Figure 9 depicts kriging results with two contour maps representing annual average concentration of glycol ethers for Durham County, North Carolina (the deeper the blue color, the higher the modeled concentration). Both maps represent inclusive modeling of all emitters. However, Figure 9A depicts contours based on modeling sources and receptors at the coarser ZIP code level of geographic resolution, whereas Figure 9B represents modeling at the finer census block group level. As shown in Figure 9, modeling exposure receptors at finer geographic levels of resolution (i.e., census block group rather than ZIP code) reveals localized, neighborhood-level exposure hot spots that are not apparent at coarser geographic scales—note in particular the high concentration contours that appear in central Durham under this alternative modeling approach. Modeling finer geographic levels of resolution provides a substantially different perspective on exposure to contaminants across race and income lines. Unlike the contours at ZIP code level, the contours at census block group level highlight areas in central Durham, characterized by a higher percentage of minorities and a lower median household income, as potential hot spots for exposure.
To better summarize and assess whether modeling of air emissions at varying levels of geographic resolution affects the distribution of exposure potential, we performed multivariate statistical analysis on the relationship between concentration and race and income. We focus specifically on these two variables because of their ubiquitous use in equity analysis. Dependent variables of interest were the modeled concentrations at the four geographic levels of resolution (ZIP code, census tract, census block group, and census block).
Tables 3 and 4 summarize regression results across geographic scale. In Table 3, moving from top to bottom indicates stepping from coarser (ZIP code) to finer (census block) levels of geographic resolution. A positive sign indicates a positive coefficient on the regression coefficient, and S indicates significance at the 0.05 level. Likewise, a negative sign indicates a negative coefficient on the regression coefficient, and NS indicates lack of significance at the 0.05 level. Moving from top to bottom, both the income and minority variables become significant and of the expected sign. These results highlight the importance of spatial resolution in conducting equity analysis. Table 4 presents more detailed regression results from multivariate statistical analysis. Comparing the ZIP code with block models explores the importance of geographic resolution in analyzing contaminant distribution. The census block model, representing inclusive modeling of all emitting sites at a very refined geographic scale, indicates exposure potential disparities across both income and race.
Additional multivariate analyses including the relationships between modeled concentration and percent children, percent vacant housing, and percent receiving public assistance did not reveal any statistically significant trends (results not shown). In addition, percent minority appears to be the most relevant “race” variable based on the modeled data, and median household income appears to be the most important “income” variable based on the modeled data (results not shown).
Discussion and Conclusion
Previous air toxics and TRI studies have taken advantage of advances in spatial and statistical mapping software to assess how geographic levels of resolution affect environmental justice conclusions. Summarizing many existing geographic-based air toxics studies, Lopez (2002) explains that conclusions often differ depending on the geographic unit of analysis. For example, “micro-area” studies that observe areas with and without facilities conclude that race is not a significant predictor for site but that income may play a role. On the other hand, “meso-area” studies that expand the area of interest to include blocks adjacent to facilities often conclude that race is an important predictor for siting but income is not. Furthermore, results from “macro-level” studies that compare counties with other counties or states with other states have correlated industrial facility siting with large percentages of minorities and persons in poverty. However, the results may be confounded by urban/rural status and other trends. Other traditional environmental justice analysis of industrial siting has focused on the location of facilities and not on concentration distributions and subsequent exposure potential (Morello-Frosch et al. 2002).
Our study attempts to clarify conflicts in the literature regarding facility siting, exposure potential, and equity by developing methods for inclusive modeling of releases at fine levels of geographic resolution. Although the results described here are specific to emissions of glycol ethers from printing/lithography sites in Durham County in 2000, the method developed is relevant across time, space, and industries. This is one of the first studies to develop methods for characterizing and mapping releases from smaller, non-TRI-reporting facilities. The study methodology further characterizes pollutant distribution, fate, and transport by incorporating atmospheric dispersion modeling. The use of GIS as a platform for data storage, statistical analysis, and kriging remains an important cornerstone for conducting spatially based environmental justice research. In addition, although average and maximum annual average concentrations of the pollutant (Table 2) do not approach the noncancer levels of concern set by the California EPA (700,000 ng/m3) and the U.S. EPA (20,000 ng/m3) (Environmental Defense 2002), the methods developed and presented here represent an innovative prototype for contaminant analysis. A full characterization of exposure potential would take into consideration releases from other sources and adjacent counties.
In a recent article, Maantay (2002) attributes the failure of previous studies to address small polluters such as automobile repair shops to the lack of standardized and publicly available data sets on small polluters. Although there are several caveats to using employees to estimate facility emissions, we believe that the approach offers a sound and creative solution for addressing these data limitations. However, future studies adopting this mechanism should perform some quality assurance techniques to ensure that number of employees reflects a representative proxy to production units and/or pollutant emissions.
The results indicate that the inclusive modeling of all facilities significantly alters the magnitude and spatial distribution of modeled air concentrations (Figure 6). Modeling all sites together rather than modeling TRI sites alone increases the magnitude of modeled concentrations—especially in areas with no TRI facilities. The red concentration contours depicted on the inclusive map are spatially correlated to high-minority and low-income neighborhoods presented in Figure 2. The same correlation is not observed for the TRI-reporting contours. In addition, the CDF curves indicate that inclusive facility modeling at fine levels of geographic resolution results in exposure disparities across race but not age (Figures 7 and 8).
As described above, a significant body of literature exists comparing varying levels of geographic resolution with different exposure potential outcomes (Glickman 2004; Lopez 2002; Maantay 2002; Sheppard et al. 1999). Intuitively, it makes sense that the finer the geographic resolution, the higher the predicted exposure concentration. In this analysis we attempted to build upon these studies by showing that the choice of geographic resolution significantly affects both the significance and trend of multivariate statistical analysis of underlying demographics. In our study, concentration gradients are substantially influenced by the resolution of the model, indicating that receptor choice is a significant modeling parameter and that localized equity impacts may be best represented at the block level.
These new methods significantly enhance the ability to model air toxics and perform equity analysis. They also clarify conflicts in the literature regarding environmental justice findings. In modeling air toxics, both the fate and transport literature and the mechanistic literature indicate that modeling inclusively at a refined geographic scale makes biologic sense. From a policy standpoint, then, it becomes critical to understand how reporting requirements and the design of spatial analyses can shape conclusions. This work, as it moves forward, will also have much to say about which facilities should be required to report to TRI, as well as how much reliability we can place on current TRI data. The 2001 drop in the reporting threshold for lead to 100 lb, which resulted in 251 additional facilities (> 5-fold increase) reporting lead processing in North Carolina, is one example of the impact reporting requirements have on what is known about emissions from local facilities. Future analysis will consider multiple contaminant exposures from multiple industries and explore the use of toxic equivalency factors to better analyze underlying justice concerns and exposure potential.
Figure 1 Durham county, North Carolina (USA).
Figure 2 Two demographic variables for Durham County: (A) median household income and (B) percent African American.
Figure 3 Boundaries for Durham County for (A) census tracts and census block groups and (B) census blocks and ZIP codes.
Figure 4 TRI-reporting and non-TRI-reporting facilities in all TRI SIC codes in Durham County. The yellow box represents central Durham.
Figure 5 TRI-reporting and non-TRI-reporting facilities in SIC Code 2752 (printing-lithography) and their estimated emissions of certain glycol ethers. The yellow box represents central Durham.
Figure 6 Modeled air emissions (ng/m3) of certain glycol ethers for (A) TRI-reporting and (B) non-TRI-reporting facilities.
Figure 7 CDF curves of modeled census-block–level exposure for African-American and white subpopulations for (A) TRI sites alone and (B) all emitters.
Figure 8 CDF curves of modeled census-block–level exposure for child and adult subpopulations for (A) TRI sites alone and (B) all emitters.
Figure 9 Modeled inclusive air emissions (ng/m3) of certain glycol ethers for all facilities at (A) the census tract and (B) the census block group level.
Table 1 Demographics of central Durham, Durham County, State of North Carolina, and United States.
Region Population (n) Hispanic (%) African American (%) Families in poverty (%) < 6 Years of age in poverty (%) Median household income Renter occupied (%)
Central Durham 57,690 12.5 60.5 22.2 37.8 $36,368 64.8
Durham County 223,314 7.6 39.5 9.8 19.9 $43,337 45.7
North Carolina 8,049,313 4.7 21.6 9.0 17.8 $39,184 30.6
United States 281,421,906 12.5 12.3 9.2 18.1 $41,994 33.8
Source: U.S. Census 2000 (U.S. Census Bureau 2003).
Table 2 Year 2000 annual average concentration of ethylene monobutyl ether (ng/m3) for Durham County.
Geographic resolution No. of receptors Model run Mean Median Maximum Minimum SD
ZIP code 20 1a: TRI alone 1.5 0.9 5.4 0.3 1.31
1b: all emitters 4.9 2.8 17.9 0.8 4.4
Census tract 53 2a: TRI alone 2.7 2.1 19.8 0.6 2.8
2b: all emitters 10.3 9.0 46.4 2.2 7.5
Census block 129 3a: TRI alone 3.0 2.2 28.2 0.5 3.3
group 3b: all emitters 10.2 9.1 49.4 1.6 7.0
Census block 3,824 4a: TRI alone 3.9 2.2 799.2 0.4 19.6
4b: all emitters 12.1 8.7 821.1 1.2 27.3
Table 3 Trends from the multivariate statistical analysis.
Geographic resolution Inclusive modeling
ZIP code Minority: +/S
Income: +/S
Census tract Minority: +/NS
Income: −/~S
Census block group Minority: +/S
Income: −/NS
Census block Minority: +/S
Income: −/S
Abbreviations: +, positive β-coefficient, positively proportional to pollutant concentration; −, negative β-coefficient, inversely proportional to pollutant concentration; NS, lack of significance at 0.05 level; S, significant at the 0.05 level; ~S, significant at the 0.10 level.
Table 4 Inclusive modeling regression results at four levels of geographic resolution (p-value) from multi-variate statistical analysis.
ZIP code coefficient Tract coefficient Block group coefficient Block coefficient
Constant −1.018 2.306 2.066 2.0245
Percent minority 0.0382 (0.0001)* 0.360 (0.212) 0.519 (0.011)* 0.622 (0.0001)*
Household median income 0.0000193 (0.022)* −7.89 × 10−6 (0.081) −4.03 × 10−6 (0.153) −3.55 × 10−6 (0.0001)*
Adjusted R2 0.50 0.15 0.13 0.11
* Significant at the 0.05 level.
==== Refs
References
Dasgupta S Lucas R Wheeler D 2002 Plant size, industrial air pollution, and local income: evidence from Mexico and Brazil Environ Dev Econ 7 2 365 381
EPCRA 1986. Emergency Planning and Community Right-to-Know Act. Public Law 42 U.S.C. 11001 et seq. Available: http://www.epa.gov/region5/defs/html/epcra.htm [accessed 22 October 2004].
Environmental Defense 2002. Glycol Ethers. New York: Environmental Defense. Available: http://www.scorecard.org/chemical-profiles/html/glycol_ethers.html [accessed 4 October 2002].
Glickman TS 2004. Evaluating Environmental Equity in Allegheny County. New York:Program for the Human Environment, Rockefeller University. Available: http://phe.rockefeller.edu/comm_risk/commrsk3.html [accessed 6 July 2004].
infoTYME Polk City Directories 2000. Durham City, NC. Livonia, MI:Polk City Directories.
Little IMD Mazumdar D Page JM 1987. Small Manufacturing Enterprises: A Comparative Study of India and Other Economies. New York:Oxford University Press.
Lopez R 2002 Segregation and black/white differences in exposure to air toxics in 1990 Environ Health Perspect 110 suppl 2 289 295 11929740
Maantay J 2002 Mapping environmental injustices: pitfalls and potential of geographic information systems in assessing environmental health and equity Environ Health Perspect 110 suppl 2 161 171 11929725
Masters G 1998. Air pollution. In: Introduction to Environmental Engineering and Science. Englewood Cliffs, NJ:Prentice Hall, 406–426.
Morello-Frosch R Pastor M Porras C Sadd J 2002 Environmental justice and regional inequity in Southern California: implications for future research Environ Health Perspect 110 suppl 2 149 154 11929723
NJDHSS 2001. Hazardous Substance Fact Sheet: 2-Butoxy Ethanol. Trenton, NJ:New Jersey Department of Health and Senior Services. Available: http://www.state.nj.us/health/eoh/rtkweb/0275.pdf [accessed 4 October 2002].
Oliveti J Kercsmar CM Redline S 1996 Pre- and perinatal risk factors for asthma in inner city African-American children Am J Epidemiol 143 6 570 577 8610674
SCDTSC 2002. CalTOX Model Description. Sacramento, CA:State of California Department of Toxic Substances Control. Available: http://www.dtsc.ca.gov/ScienceTechnology/ctox_model.html [accessed 10 October 2002].
Sheppard E Leitner H McMaster R Tian H 1999 GIS-based measures of environmental equity: exploring their sensitivity and significance J Expo Anal Environ Epidemiol 9 1 18 28 10189624
U.S. Census Bureau 2003. American FactFinder. Washington, DC:U.S. Census Bureau. Available: http://factfinder.census.gov/servlet/DatasetMainPageServlet?_lang=en&_ts=116506749456&_ds_name=DEC_2000_SF1_U&_program= [accessed 10 April 2003].
U.S. EPA 1995. User’s Guide for the Industrial Source Complex (ISC3) Dispersion Models. Research Triangle Park, NC:U.S. Environmental Protection Agency Office of Air Quality Planning and Standards. Available: http://www.epa.gov/scram001/userg/regmod/isc3v1.pdf [accessed 14 September 2004].
U.S. EPA 2001a. Toxics Release Inventory (TRI) Program. Washington, DC:U.S. Environmental Protection Agency. Available: http://www.epa.gov/tri/ [accessed 9 July 2001].
U.S. EPA 2001b. Emergency Planning and Community Right-to-Know Act—Section 313: Guidance for Reporting Releases and Other Waste Management Quantities of Toxic Chemicals: Lead and Lead Compounds. Washington, DC:U.S. Environmental Protection Agency. Available: http://www.epa.gov/tri/guide_docs/2001/lead_doc.pdf [accessed 6 September 2004].
U.S. EPA 2001c. TRI Guidance Documents. Washington, DC:U.S. Environmental Protection Agency Office of Environmental Information. Available: http://www.epa.gov/tri/guide_docs/#general [accessed 6 September 2004].
U.S. EPA 2002a. EPA TRI Explorer: Chemical Report. Washington, DC:U.S. Environmental Protection Agency. Available: http://www.epa.gov/triexplorer/ [accessed 12 October 2004].
U.S. EPA 2002b. Dispersion Models. Washington, DC:U.S. Environmental Protection Agency. Available: http://www.epa.gov/scram001/tt22.htm [accessed 14 September 2004].
U.S. EPA 2002c. Meteorological Data. Washington, DC:U.S. Environmental Protection Agency. Available: http://www.epa.gov/scram001/tt24.htm [accessed 12 Sepetember 2004].
Waller LA Louis TA Carlin BP 1999 Environmental justice and statistical summaries of differences in exposure distributions J Expo Anal Environ Epidemiol 9 1 56 65 10189627
Weitzman M Gortmaker S Sobol A 1990 Racial, social, and environmental risks for childhood asthma Am J Dis Child 144 11 1189 1194 2239856
Wernette D Nieves L 1992 Breathing polluted air EPA J 18 16 17
Wissow L Gittelsohn AM Szklo M Starfield B Mussman M 1988 Poverty, race, and hospitalization for childhood asthma Am J Public Health 78 7 777 782 3381951
|
15579419
|
PMC1253665
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec 13; 112(17):1717-1724
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7066
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science 10.1289/ehp.7209ehp0112-00172515579420ResearchArticlesLong-Term Exposure to Environmental Concentrations of the Pharmaceutical Ethynylestradiol Causes Reproductive Failure in Fish Nash Jon P. 123Kime David E. 1Van der Ven Leo T. M. 4Wester Piet W. 4Brion François 5Maack Gerd 3Stahlschmidt-Allner Petra 6Tyler Charles R. 31Animal and Plant Sciences, University of Sheffield, Sheffield, United Kingdom2Laboratory of Aquatic Ecology, Katholieke Universiteit Leuven, Leuven, Belgium3School of Biological Sciences, University of Exeter, Exeter, United Kingdom4Rijksinstituut voor volksgezondheid en mileu (RIVM), Bilthoven, The Netherlands5L’Institut national de L’environnement et des risque (INERIS), Verneuil-en-Halatte, France6Hessisches Landesamt für umwelt und geologie (HLUG), Wiesbaden, GermanyAddress correspondence to J.P. Nash, Laboratory of Aquatic Ecology, Katholieke Universiteit Leuven, 3000 Leuven, Belgium. Telephone: 32-16-323966. Fax: 32-16-324575. E-mail: jon @fishyone.netWe thank C. Spary, E. Saunders, B. McAllister, M. Skidmore, K. Van Look, and S. Holden for help with data collection and C. Kelly (CEFAS, Burnham-on-Crouch, UK) for the analytical chemistry. We also thank the reviewers for their useful comments.
This study was supported by grant GR3/10840 from the British Natural Environmental Research Council (D.E.K.), an EC Marie Curie fellowship (J.P.N.), and Exeter University (C.R.T.).
The authors declare they have no competing financial interests.
12 2004 4 11 2004 112 17 1725 1733 27 4 2004 22 10 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Heightened concern over endocrine-disrupting chemicals is driven by the hypothesis that they could reduce reproductive success and affect wildlife populations, but there is little evidence for this expectation. The pharmaceutical ethynylestradiol (EE2) is a potent endocrine modulator and is present in the aquatic environment at biologically active concentrations. To investigate impacts on reproductive success and mechanisms of disruption, we exposed breeding populations (n = 12) of zebrafish (Danio rerio) over multiple generations to environmentally relevant concentrations of EE2. Life-long exposure to 5 ng/L EE2 in the F1 generation caused a 56% reduction in fecundity and complete population failure with no fertilization. Conversely, the same level of exposure for up to 40 days in mature adults in the parental F0 generation had no impact on reproductive success. Infertility in the F1 generation after life-long exposure to 5 ng/L EE2 was due to disturbed sexual differentiation, with males having no functional testes and either undifferentiated or inter-sex gonads. These F1 males also showed a reduced vitellogenic response when compared with F0 males, indicating an acclimation to EE2 exposure. Depuration studies found only a partial recovery in reproductive capacity after 5 months. Significantly, even though the F1 males lacked functional testes, they showed male-pattern reproductive behavior, inducing the spawning act and competing with healthy males to disrupt fertilization. Endocrine disruption is therefore likely to affect breeding dynamics and reproductive success in group-spawning fish. Our findings raise major concerns about the population-level impacts for wildlife of long-term exposure to low concentrations of estrogenic endocrine disruptors.
ecotoxicologyendocrine disruptionethynylestradiolmating systemspopulation effectsreproductive successzebrafish
==== Body
Major worldwide attention has focused on the possibility that disruption of reproductive systems by endocrine-disrupting chemicals (EDCs) may be affecting the reproductive health of wildlife populations (Guillette and Gunderson 2001; Kime 1998; Tyler et al. 1998; Van Der Kraak 1998) and possibly, of humans (Colborn and Clement 1992; Ohtake et al. 2003). In fish, exposure to EDCs alters their reproductive physiology and morphology (Kime 1998; Tyler et al. 1998), resulting in, for example, the induction of female-specific proteins in male fish (Tyler and Routledge 1998), induction of gonopodia in females (Bortone and Davis 1994), reduced sperm counts (Haubruge et al. 2000), skewed sex ratios (Larsson et al. 2000), and prevalence of intersexuality (Jobling et al. 1998). Concern over the effects of EDCs on wildlife is driven by the hypothesis that disruption to the reproductive system may have serious deleterious consequences on the reproductive success of populations, but there is little evidence bearing on this expectation. An exception to this in a natural population is recent work on the roach (Rutilus rutilus); this study shows that sexual disruption (intersex) as a consequence of exposure to sewage treatment works effluents (STWs)—which contain a complex mixture of EDCs—results in gametes with reduced fertilizing capacity, as determined by in vitro studies (Jobling et al. 2002b). Direct population-level consequences of exposure to a specific EDC are known only for the antifouling agent tributyltin, which disrupts steroidogenesis, inducing an imposex condition that reduces reproductive success and causes localized extinctions in marine gastropods in the United Kingdom (Gibbs et al. 1991; Matthiessen and Gibbs 1998).
Many EDCs have a weak capacity to disrupt reproductive function. In contrast, natural steroidal estrogens control sexual differentiation and/or development in vertebrates and are potent modulators of sexual development and capacity (Bern 1992; Dawson 1998; Nagahama 1994; Strussmann and Nakamura 2002). Steroidal estrogens in effluents from STWs are believed to be responsible for, or contribute to, the feminized responses in some wild fish (Jobling et al. 1998, 2002a) and include the natural estrogens estradiol (E2) and estrone (E1) and the synthetic estrogen EE2, a component of the contraceptive pill (Desbrow et al. 1998; Tyler and Routledge 1998). In Europe, EE2 is present in effluents and surface waters at concentrations between 0.5 and 7 ng/L (Desbrow et al. 1998; Larsson et al. 1999; Ternes et al. 1999) but in some cases up to 50 ng/L (Ahern and Briggs 1989). A recent study of 139 streams in the United States found that 5.7% had concentrations > 5 ng/L (Kolpin et al. 2002a). In that study extremely high concentrations of EE2 up to 273 ng/L were reported at some riverine sites, but these figures may be overestimations and they are controversial (Kolpin et al. 2002b). EE2 concentrations are generally lower in surface waters than are natural steroidal estrogens, but the potency of EE2 in fish is 10- to 50-fold higher than that of E2 and E1
in vivo (Segner et al. 2003b; Thorpe et al. 2003) due to its longer half-life and tendency to bioconcentrate (650- and 10,000-fold in whole-body tissues and bile, respectively) (Lange et al. 2001; Larsson et al. 1999). In fish, for example, only 0.1 ng/L EE2 induces vitellogenin (VTG) yolk precursor (Purdom et al. 1994), 0.1–15 ng/L can affect normal sexual development and differentiation (Andersen et al. 2003; Metcalfe et al. 2001; van Aerle et al. 2002; Van den Belt et al. 2003; Weber et al. 2003), 2–10 ng/L can affect fecundity (Lange et al. 2001; Scholz and Gutzeit 2000; Van den Belt et al. 2002), 10 ng/L affects reproductive behavior (Balch et al. 2004), and 1–10 ng/L can reduce the fertilization success or viability of embryos from exposed adults (Hill and Janz 2003; Lange et al. 2001; Segner et al. 2003a). Thus, given its concentration in the environment, EE2 is potentially a major contributor to reproductive dysfunction in wild fish populations.
An overall aim of our research was to test whether there are any population-level consequences to reproductive dysfunction(s) induced by exposure to environmentally relevant levels of EDCs. Because of a number of compounding factors (e.g., larval dispersal, adult migration, etc.; Elliott et al. 2003) it is difficult to directly determine the population-level consequences of endocrine disruption on reproductive success in wild fish populations; even where it is possible to correlate levels of contamination with endocrine disruption and the consequential reproductive dysfunction with reproductive failure, this does not necessarily prove a direct cause-and-effect relationship. For these reasons, one approach to understanding the population-level consequences of reproductive dysfunction is to measure the impact of pollutants on reproductive success in model species bred under laboratory conditions (e.g., Balch et al. 2004; Hill and Janz 2003; Lange et al. 2001), an approach we have taken in our study. Reduced reproductive success may result from disruption of reproductive development, reduced female fecundity and male vitality, altered reproductive behavior, and/or disruption of the normal breeding dynamics. Little attention has been directed to the latter (Balch et al. 2004). To fully assess the potential of EDCs to disrupt reproduction, multigenerational full life-cycle exposures are needed that consider all relevant life stages and developmental end points; even where fish have been exposed over their whole life-cycle, the impact of any resulting reproductive dysfunction on their reproductive output has mostly been overlooked in earlier studies (Metcalfe et al. 2001; Van den Belt et al. 2003). A major goal of this study was to determine which stages or reproductive components are relatively most sensitive to endocrine disruption in terms of population-level impairment or failure to allow better priority and focus for future studies. We therefore determined impacts on reproductive success in fish populations over multiple generations and the mechanisms of reproductive impairment/failure investigated using environmentally relevant concentrations of EE2 and E2. Our chosen species for this work was the zebrafish because its short generation time facilitates the life-long and multigenerational chemical exposures; it is a group-spawner (a common breeding system in fish); and, most importantly, small populations will spawn naturally in the laboratory without any manipulation.
Materials and Methods
Fish culture and husbandry.
Wild-type zebrafish (Danio rerio, WIK strain; Max Plank Institute, Tubingen, Germany) maintained out-bred for three generations since capture were bred in our laboratory for one generation in clean freshwater before their use in this study. Adult fish were fed ad libitum twice daily on Artemia nauplii. Fry 5–12 days postfertilization (dpf) were fed a special fry diet and cultured rotifers, Brachionus calciflorus. Artemia nauplii were hatched in synthetic sea-water and rotifers reared in synthetic freshwater.
Populations were maintained and exposed to steroidal estrogens in 192 flow-through 18-L glass aquaria. An egg collection system allowed daily embryo collection without disturbance of the adult populations. Natural conditions were mimicked for optimal breeding; with a 13 hr light:11 hr dark photoperiod, artificial dawn/dusk, and water temperature of 28.5 ± 0.5°C (differences between tanks < 0.5°C throughout). Aquaria contained artificial weed for refuge and spawning substrate (glass marbles). Eggs were collected 1 hr after dawn. Embryos were maintained in 50 mL culture vessels modified for continuous flow-through before release into aquaria at 9 dpf.
Water quality and chemical dosing.
Tap water was filtered with activated charcoal and reverse osmosis (RO; Osmonics E625 with cellulose membranes; GE Water and Process Technologies, Trevose, PA, USA). RO water was reconstituted with Analar grade mineral salts to standardized synthetic freshwater, to concur with U.S. Environmental Protection Agency (EPA) guidelines (U.S. EPA 1986). Water was aerated and heated to 28.5°C in a reservoir before it was supplied to each aquarium at a rate of 9 L/day to provide an exchange of 3 L/g biomass/day (U.S. EPA 1986). Aquarium water was continuously monitored for temperature, pH, and conductivity and routinely measured for carbonate hardness, oxygen, chlorine, iron, ammonia, nitrate, nitrite, and periodically for 142 pollutants; all were within acceptable limits of U.S. EPA guidelines (U.S. EPA 1986). The chemical (and control) aquaria were dosed independently at 20 mL/hr by a medical dripper system fed from a 2.5-L glass aspirator, and dosing rates were checked twice daily. 17α-Ethynylestradiol [17α-ethinyl-1,3,5(10)-estratriene-3,17β-diol] and estradiol [1,3,5(10)-estratriene-3,17β-diol] were initially dissolved in 100% ethanol at 1 mg/mL and serially diluted with sterile (treated with ultraviolet radiation) distilled water to a final stock concentration of 50 ng/mL. Fresh final stocks were made every 10 days and stored at 5°C. Aspirators were refilled every fourth day. Nominal estrogen doses were 0.5, 5, and 50 ng/L for EE2 and 5 ng/L for E2. The ethanol concentrations administered to aquaria were < 0.05 μL/L. Steroids were extracted from 5 L water samples for the EE2 (0.5 and 5 ng/L only, because the 50 ng/L treatment was terminated at an early phase of experimentation) and E2 (5 ng/L) using solid-phase extraction and measured by gas chromatography-mass spectrometry (Kelly 2000), with a detection limit of 0.1 ng/L.
Impact of multigenerational estrogen exposure on reproductive success.
The main measures of reproductive success used in our study were the number of eggs produced by each population and the proportion of these eggs that were not viable at 14 hr post-fertilization (hpf; the mid-segmentation period) (Kimmel et al. 1995). The total reproductive success at 14 hpf was therefore the total number of viable embryos surviving to this stage. We used 14 hpf because infertile or dead embryos can be quickly differentiated from healthy embryos at this stage. Egg viability at 14 hpf was therefore a cumulative figure that includes the impact of unfertilized eggs plus embryo mortality during embryogenesis. Fertilization failure was differentiated from embryo mortality only in selected groups using time lapse videography to determine the mechanism(s) of reproductive failure.
At the begining of the study 720 adult (204 dpf) fish of mixed sex were randomly allocated to 60 aquaria (12 fish/aquarium) and acclimated for 14 days under egg collection conditions. Egg numbers and viability at 14 hpf were assessed in all groups in this F0 generation for 5 days before starting exposures. Tanks for the 12 replicates of the five treatments were randomly allocated using Latin square randomization in both vertical and horizontal gradients, and all experimentation was run blind of treatments. Steroid treatments were then initiated by flushing aquaria with 36 L estrogen-treated water 1 hr after spawning (day 0), and reproductive success was assessed over the following 15 days. The surviving F1 embryos were all reared to 100 hpf under continuous estrogen exposure, and the rate of embryo mortality/survival was assessed. We assessed the integrity of the surviving larvae, the proportion of embryos with developmental abnormalities, and the speed of development (proportion hatch and spine curvature) at 100 hpf as described by Kimmel et al. (1995). After the F0 generation had been exposed for a further 25 days (40 days of exposure total), we again assessed reproductive success (egg numbers and viability at 14 hpf), 100 hpf embryo mortality, and larval integrity of the resulting F1 offspring in eggs arising from 3 days of spawning. The surviving F1 embryos from these 3 days were then pooled within each replicate and reared to adulthood under continued exposure to form the F1 exposure generation. The age of the fish is stated as a single day postfertilization although, because the eggs were pooled over 3 days, the actual age may vary by up to an additional 48 hr. At 29 dpf, they were divided between two tanks (24 tanks/treatment) and maintained to 52 dpf, whereby survival and growth rates were determined. These fish were then pooled and randomly redistributed within treatments to provide 28 individuals/tank. At 72 and 124 dpf, populations were further reduced to 18 and 12 adults/tank, respectively. After the F1 generation had been exposed over their entire life time (210 dpf), their reproductive success was measured for 10 days. Any resulting F2 progeny were continually exposed to the estrogen treatments, and embryo survival/larval integrity was measured at 100 hpf.
Analysis of estrogenic disruption and reproductive failure.
Life-stage sensitivity, transgenerational impacts, and recovery from estrogen exposure.
To determine which life stage(s) were primarily responsible for any reproductive failure and to test for any trans-generational effects, we exposed different subgroups to various regimes of noncontinuous estrogen exposure. Eggs were collected over a 4-day period from each treatment group in the F0 generation 16–19 days after the start of exposure (i.e., after the main egg collection period on days 0–15). In this first subgroup, the eggs from six of the 12 replicate tanks from each treatment (0.5 and 5 ng/L EE2, 5 ng/L E2 and control) were removed from the continuous treatment 1 hpf and reared to 100 hpf in clean water. Egg numbers and viability to 14 hpf and embryo survival/integrity to 100 hpf were compared between the F0 parent-only exposure, the continuous F0/F1 exposure, and the unexposed control group. To test for any transgenerational effects of parental exposure on adult reproductive integrity in their offspring, we set up a second subgroup in which the F1 generation was reared to adulthood in clean water. Eggs were collected from the F0 generation over 5 days from five replicate tanks in each treatment group (0.5 and 5 ng/L EE2, 5 ng/L E2 and control) 29 days after the start of exposure. These fish were then reared to adulthood, when end points of reproductive success, adult health, and embryo survival were measured at the same time as the main multigenerational exposure experiment, as described above.
To examine the ability of fish to recover from the effects of estrogen treatments on sexual differentiation and gonadal development, we established a third subgroup in which the F1 generation was removed from the treatments at 75 dpf and reared to adulthood in clean water. In this subgroup, we set up three replicate populations of mixed sex juveniles from each treatment (0.5 and 5 ng/L EE2, 5 ng/L E2 and controls) using the excess fish removed from the main treatments at 75 dpf to reduce stocking densities; these fish were reared to adulthood in clean water. Reproductive success, adult health, and F2 embryo survival/integrity were measured in this subgroup at the same times as for the fish in the main multigenerational experiment.
Male replacement experiments.
To investigate the cause(s) of reproductive failure in the 5 ng/L EE2 treatment group after life-long exposure, males were removed from one-half of the replicate populations in the control group 20 days after embryo collection (240 dpf) to create an all-female group (n = 6) and leaving a mixed-sex control group (n = 6); we also replaced two EE2-exposed males with two control males in one-half of the replicate populations in the 5 ng/L EE2 exposure group to create two groups (n = 6), with or without additional healthy males. There was no dosing with EE2 during this phase of the experiment. The fish were acclimated, and egg numbers and egg viability were subsequently assessed over 5 days.
Adult health and growth.
In the F0 generation after 40 days of exposure, a total of 571 fish from 10 of the 12 replicates of each treatment were anesthetized, and weighed (wet weight, milligrams), and blood samples were collected from the caudal sinus. Gonads were dissected to determine gonadosomatic index (gonad weight as a percentage of body weight). Blood was centrifuged at 3,000 × g for 8 min and the hematocrit value measured in all samples. In the F1 generation (after full life-cycle exposure, 314 dpf), 284 adults from six replicate tanks in each of the remaining exposure groups (0.5 ng/L and 5 ng/L EE2 treatments with no F1 exposure; 0.5 and 5 ng/L EE2 and 5 ng/L E2 treatments with exposure stopped at 75 dpf in F 1 ) were weighed; we then collected blood samples and determined the hematocrit value. Whole fish were fixed in Bouin’s fixative and embedded in paraffin, and the gonad region was sectioned to 4 μm, stained, and analyzed by light microscopy. Histologic analysis was conducted blind of treatment and was undertaken in three independent laboratories.
Fertilization success, sperm quality.
Time-lapse image capture was used to assess whether reductions in egg viability were due to reduced fertilization success or embryo mortality at 14 hpf. Digital images of four developing embryos were taken every 5 min 1 to 24 hpf and repeated for > 10 days per treatment. To assess sperm quality in F1 controls and 5 ng/L EE2 treatments only, males were stripped manually of expressible milt 1 hr before dawn, and the activated sperm was examined using video microscopy (Kime et al. 1996).
Plasma vitellogenin and steroids.
Whole-blood VTG concentrations were measured by enzyme-linked immunosorbent assay (ELISA), as described by Brion et al. (2002), in all 12 adults from four and three replicate tanks within each treatment sampled in the F0 and F1 generations, respectively. We assayed E2 and 11-ketotestosterone (11-KT) by ELISA (Nash et al. 2000) in 2 individuals from each of the eight replicate groups in each treatment (n = 8) for the F0 generation only.
Statistical analyses.
Data were checked for normality using the Ryan-Joiner test and homogeneity of variance using Bartlett’s test. Data were transformed, where necessary, using square root (egg numbers and survival data), log10 (steroid levels), or arc sine of square root for proportion data (egg viability). When analyzing egg viability, we excluded data points for which egg numbers were < 4/tank (< 2%) because viability on low egg numbers biased the analysis disproportionately. We used analysis of variance (ANOVA) procedures except where there were unequal sample sizes and imbalance in design; then the GLM procedure was used. Post hoc analysis was performed against controls using the Dunnett’s test, and we used the Tukey test for between-treatment comparisons (male addition experiments). Data for egg numbers and viability to 14 hpf, survival and mortality of embryos to 100 hpf, and rate of embryo development were nested within the tank replicates to avoid pseudoreplication, and ANOVA was performed on 5-day means. When multiple measurements, such as weights and gonadosomatic index, were made from a single tank, these were also nested. VTG data did not conform to normality, so we adopted nonparametric analysis (Kruskal-Wallis). Significant deviations from expected sex ratios or levels of abnormal adult and gonadal morphology were tested using the chi-square test.
Results and Discussion
Natural variation in fecundity.
The average fecundity of this wild type strain of zebrafish was around 13 eggs/female, which is about 50% lower than that in some other inbred lines that have been selected for growth and reproductive output (Eaton and Farley 1974; Ensenbach and Nagel 1997). We found considerable variation in the numbers of eggs spawned daily in the zebrafish populations (Figure 1A,B), highlighting the need for extensive replication in studies of this nature. Our purpose, however, was to provide an experimental system that includes this natural variation found in wild populations. Cumulative and nested egg production was subsequently assessed over 5-day intervals to normalize measurements across the tanks; because females have a spawning periodicity of around 1.9 days (Eaton and Farley 1974), each female spawns at least once during a 5-day period. No significant differences in egg production occurred during the four consecutive 5-day periods in the F0 controls (mean, 0.2 eggs/female/day; F = 1.44, p = 0.27, n = 12, on 5-day nested means).
Exposure concentrations of estrogens.
Measured mean concentrations of EE2 and E2 were between 90 and 100% of nominals: EE2 (mean ± SEM) concentrations were 0.5 ± 0.0 ng/L (0.5 ng/L EE2), 4.5 ± 0.3 ng/L (5 ng/L EE2), and E2 4.8 ± 0.1 ng/L (5 ng/L EE 2 ). EE 2 and E 2 were undetectable (< 0.1 ng/L) in the control group tanks and E2 was undetectable (< 0.1 ng/L) in the EE2 treatments. Mean ± SEM E1 concentrations in the control and treated tanks ranged between 0.5 ± 0.1 and 1.1 ± 0.1 ng/L and probably originated as an excreted product from the fish. There are no data on the effects of E1 in zebrafish, but in the rainbow trout, reproductive effects occur only at doses 3 orders of magnitude higher than the E1 concentrations found in the exposure aquaria (Thorpe et al. 2003). We used nominal steroid concentrations to describe the exposures in this study.
Impacts of estrogen exposure on reproductive success during multigenerational exposure.
F0 generation.
For the 5-day period prior to the start of the estrogen exposures, we found no significant differences in egg numbers (F = 0.96, p = 0.43, n = 12), numbers of non-viable eggs at 14 hpf (F = 1.16, p = 0.34, n = 12), or level of mortality at 100 hpf (F = 0.91, p = 0.47, n = 12) between all five experimental groups (n = 12). There were also no differences in the reproductive output between the control groups in the F0 generation compared with the F1 generation, either in egg numbers (F = 0.52, p = 0.47, n = 12), nonviable eggs at 14 hpf (F = 2.8, p = 0.11, n = 12), or embryo mortality at 100 hpf (F = 0.45, p = 0.51, n = 12) for pooled 15-and 10-day means in each generation. A mean of 91.5% of the eggs were fertilized and survived to 100 hpf (posthatch) in all treatments before exposure and in control treatments throughout the experiment. This level of fertilization and survival is high when compared to similar studies on zebrafish (Hill and Janz 2003), sheepshead minnows (Cyprinodon variegatus; Zillioux et al. 2001), and medaka (Oryzias latipes; Balch et al. 2004), where lower survival (70, 65, and 62%, respectively) in controls probably relates to suboptimal breeding conditions or stresses associated with embryo culture.
The short term exposure to 50 ng/L EE2 in the F0 generation caused a time-related reduction in egg production and egg viability to 14 hpf (Figure 2; two-way ANOVA for all cases: n = 12, p < 0.01) and no survival of their F1 offspring to 100 hpf. After 10 days exposure there was complete reproductive failure (no egg production) in the 50 ng/L EE2 exposure group. These data support previous findings for high dosage, short-term effects of EE2 (Lange et al. 2001; Scholz and Gutzeit 2000; Seki et al. 2002; Van den Belt et al. 2002; Zillioux et al. 2001), and this treatment was subsequently terminated. There were no effects, however, of any other estrogen treatment on numbers and viability of eggs from the F0 generation at 14 hpf (Figure 2), embryo mortality in the F1 generation (F = 0.36, p = 0.78, n = 12), or impacts on larval integrity at 100 hpf; the proportion of developmental abnormality, hatch rate, and level of spine curvature were all not significantly different from controls; p > 0.05 for all cases. Similarly, we found no effects after an additional 26-day exposure (40 days continuous exposure) to 0.5 ng or 5 ng/L EE2 or 5 ng/L E2 on egg production (F = 1.31, p = 0.28, n = 12), egg nonviability (F = 1.30, p = 0.28, n = 12), or F1 mortality to 100 hpf (F = 1.71, p = 0.18, n = 12) and larval integrity (p > 0.05 for all cases) at 100 hpf.
Mean cumulative survival at 52 dpf was between 66% and 79%, with no differences (F = 1.1, p = 0.35, n = 12) between the treatments. This rate of survival is high for cultured zebrafish embryos (Ensenbach and Nagel 1997) and was higher than a comparable study (50%; Hill and Janz 2003). Most (98%) of this mortality occurred during the first stages of exogenous feeding and was not related to treatment. There were no effects of the estrogen treatments on growth at 52 dpf (mean = 65–80 mg, F = 1.45 p > 0.24, n = 12). The mortality rate between 52 dpf and 7 months of age was < 0.2% throughout, and we found no differences (F = 0.65, p > 0.63, n = 12) in fish weight between treatments for either sex at the end of the experiment when fish were slaughtered (9 months; mean = 232–349 mg).
F1 generation.
In complete contrast, life-long exposure (210 dpf) to 5 ng/L EE2 resulted in complete reproductive failure in the F1 generation, with no viability in the eggs at 14 hpf (Figure 3); we found no viable eggs in almost 12,000 spawned (F = 7.6, p < 0.001). Egg production was also reduced in fish in the 5–ng/L EE2 exposure group, approximately 42–45% of that of the control for the two successive 5-day assessment periods (Figure 3; F = 207, p < 0.001). We found no effects of either 0.5 ng/L EE2 or 5 ng/L E2 on egg numbers, but proportions of nonviable eggs/total eggs spawned at 14 hpf in both of these treatments were more than twice that in the controls (F = 207, p < 0.001; post hoc comparisons with p < 0.05). A large variation in egg numbers, however, meant that these effects on viability at 14 hpf did not affect total reproductive success at 14 hpf (i.e., total number surviving 14 hpf) in the 0.5 ng/L EE2 or 5 ng/L E2 treatments (Figure 2). The rate of embryo mortality to 100 hpf in the surviving F2 embryos was low (< 1%) and not significantly increased by these low exposures (F = 0.63, p < 0.48, n = 12). Larval integrity (proportion of developmental abnormality, hatch rate, and level of spine curvature) of the F2 embryos at 100 hpf in these surviving groups was also not affected.
Two recent studies have also examined the impact of full life-long exposure to EE2 on reproductive success in other fishes. Lange et al. (2001) found that life-long exposure to 0.2 and 1 ng/L EE2 in the fathead minnow (Pimephales promelas) caused 20 and 35% reductions, respectively, in the offspring’s hatching success and no impact on fecundity, which was comparable with the impact of our 0.5 ng/L EE2 exposure. In the Lange et al. study, however, the impact on reproductive success of a higher dose (4 ng/L EE2), one similar to that which would have caused complete reproductive failure in our study (5 ng/L EE2), was not tested because it was not possible to sex these fish for the pair-wise breeding setup used. In a study on medaka, Balch et al. (2004) found no significant effects of life-long exposure at lower doses (0.2 and 1 ng/L EE2), but at 10 ng/L EE2 (there was no intermediate dose) they found complete reproductive failure, which was related to suppressed reproductive activity.
Thus, life-long exposures to very low and environmentally relevant concentrations of EE2 have severe and deleterious effects on reproductive success for breeding populations of zebrafish, and there is evidence that these strong effects will occur in other species at similar concentrations (Balch et al. 2004; Lange et al. 2001). Furthermore, these effects occur at concentrations that are at least an order of magnitude lower than for short-term exposures of mature fish proximate to spawning time; Seki et al. (2002), Van den Belt et al. (2002), and Zillioux et al. (2001) provide other examples of lower sensitivity to adult-only exposure.
Analysis of endocrine disruption.
Reproductive failure in F0 generation.
We found that 50 ng/L EE2 was acutely toxic and resulted in 35% mortality; in the surviving fish there were negative effects on a wide range of health measures, including reduced hematocrit, increased spinal deformities, and reduced gonad growth. Reproductive failure ensued because of complete cessation of spawning in this treatment group (Denslow et al. 1999; Seki et al. 2002; Van den Belt et al. 2002). There was no reduction in reproductive success or health effects in any of the other estrogen treatment groups.
Reproductive failure in F1 generation.
We investigated the mechanism(s) of disruption leading to reproductive failure in the F1 generation by assessing sperm quality, fertilization success in their offspring (F2 generation), gonad development and maturation, and male reproductive behavior in the breeding populations. In the 5 ng/L EE2 treatment group, we found no phenotypic males, as discerned by the absence of any secondary sex characteristics, such as slightly yellow/bronze coloration and bright anal fin markings. This gave the initial impression that sex reversal had been induced, as occurs in some fish species after exposure to steroidal estrogens (Iwamatsu 1999; Lange et al. 2001; Scholz and Gutzeit 2000). Further studies on these F1 fish found that no fish contained expressible sperm. The hypothesis that reduced egg viability at 14 hpf was due to nonfertilization rather than early embryo mortality was confirmed through hourly time lapse image analyses of egg/embryo development for this treatment. Gonadal histology on the F1 fish after life-long exposure to 5 ng/L EE2 established that none of the males had normal testes. Of these fish, 43% had gonads that had not fully differentiated into testes; these undetermined gonads resembled primary stage ovary-type tissue, which is the natural condition of immature fish during early stages of normal male gonadal differentiation (Maack and Segner 2003). Figure 4A shows an example. Gonadal evidence that these fish were indeed feminized males was further supported by the concentrations of blood VTG in these animals. Via histology, we found that all of these life-long exposed fish that were not clearly mature/maturing females had compromised gonads and also had very low concentrations of blood VTG (mean ± SEM = 1.8 ± 1.1 μg/mL), whereas fish that were definitively females contained extremely high concentrations of blood VTG (1,092 ± 106 μg/mL). We found no fish with an intermediate response. This highly dichotomous response to the estrogenic treatment after long-term exposure, which was strongly correlated to the histology and behavior—these dysfunctional males showed natural spawning behavior—gives good evidence these differential responses were determined by the underlying genetic sex. The interpretation that long-term exposure to estrogens suppresses male pattern sexual differentiation and arrests testes development rather than producing functional females is confirmed by earlier work on zebrafish (Hill and Janz 2003; Segner et al. 2003a; Van den Belt et al. 2003; Weber et al. 2003). In some of these earlier studies on zebrafish (Hill and Janz 2003; Weber et al. 2003), males with undifferentiated testes have been categorized as females and have been reported as a skewed sex ratio. This is a slightly misleading interpretation in an undifferentiated gonochorist species such as the zebrafish, because males that have arrested sexual differentiation, while superficially resembling early ovary type tissue (as do both sexes at this stage), do not develop into functional females and their gonads will differentiate into testes when removed from exposure (Hill and Janz 2003). It would be more accurate to describe these fish as simply showing undetermined gonadal sex rather than assigning female status.
We found a low incidence of intersex gonads (four fish; Figure 4B,C) in the 5 ng/L exposure group. Although similarly low occurrences of intersex have been found in various species when exposed to estrogens during development (Van den Belt et al. 2003), the high level of intersex found in some natural species (Jobling et al. 1998) has not been replicated in the laboratory. This may relate to between-species differences in their susceptibility to this intersex condition or it could indicate the involvement of other, as yet, unknown chemical or environmental factors. It is doubtful if the fish with intersex gonads in our study were sexually functional because they also had extensive malformations of the ovarian and sperm ducts, as shown in other species [e.g., carp (Gimeno and Komen 1996) and fathead minnow (van Aerle et al. 2002)]; there was no fertilization in these groups. Further data on the effects on the histopathology and enhanced images are available online in the “Toxicological Pathology Atlas of Small Laboratory Fish” (RIVM 2004).
Behavioral analysis and male replacement experiments.
Close observation of the F1 adults in the 5 ng/L EE2 treatment group indicated that even though there was no fertilization, natural spawning behavior still occurred and resulted in egg-laying activity, even though these fish were all superficially female. Removing all the males from control tanks in the F1 generation caused complete cessation of spawning, showing that the presence of males, or at least male pattern behavior, was needed to stimulate spawning in females (Figure 5).
When two healthy nonexposed males were taken from the control group and substituted for two males from populations previously exposed to 5 ng/L EE2 (six tanks), there was an increase in embryo viability, showing that the females in the 5 ng/L EE2 group were fertile. Even with healthy males, the rate of survival to 14 hpf was, however, significantly less than in the control group. This reduction in survival to 14 hpf was due to reduced fertilization success (tested using time-lapse videography) and indicates that the effects were not due to reduced egg quality in the EE2-exposed females. Experiments conducted in our laboratory have shown that even when the population sex ratio is strongly biased toward females in normal healthy populations (14 females:2 males), fertilization rates are > 90%. Thus, the high level of unfertilized eggs in the 5 ng/L EE2 exposures with replacement males is unlikely to be a function of the presence of only two fertile males. Close observations of the spawning activity in these tanks revealed that sexually compromised males actively participated in the spawning act, chasing females and competing with the healthy males for proximity to the females as they spawned. Thus, it was clear that the reduced fertilization was, at least in part, due to infertile males interfering with the fertilization capability of healthy males. Egg production in the EE2-treated group with healthy males was higher when compared with controls (Figure 5). The presence of vigorous, healthy males may have induced the greater egg production in these females after a prolonged period with EE2-exposed males. Moreover, egg production in this treatment group was similar to previous controls; egg production in the associated controls was relatively low.
The data from this experiment show that normal gonadal differentiation and development is relatively more sensitive to disruption than is male reproductive behavior. We suggest that there is a higher threshold on sensitivity to behavioral disruption relative to exposure concentrations that cause inhibition of functional testes development. Although few studies examine the impact of endocrine disruption on reproductive behavior in relation to reproduction success, Balch et al. (2004) confirmed that medaka behavior was unaffected at doses of EE2 < 10 ng/L, even though there were significant gonadal abnormalities at exposures of 2 ng/L.
Retention of a normal pattern of behavior in the infertile males that affects the fitness of other males may have an even greater impact on the reproductive success than if these males did not participate in spawning. The findings illustrate that information on the effects of EDCs and the interactions between fish within a spawning group (i.e., their mating systems) is necessary to develop our understanding of population-level implications of endocrine disruption. In the wild, group-spawning fish come together on a spawning ground; they may have migrated from different areas, and therefore different chemical exposure regimes, and thus they may have different degrees of disruption to their reproductive systems. To date, none of these factors has been taken into consideration when evaluating the potential impacts of EDCs such as EE2 on breeding success in wild fish populations.
Transgenerational effects, life stage sensitivity, and recovery from EE2 exposure.
It is well documented that maternal transfer of the synthetic estrogen diethylstilbestrol into the developing fetus in humans resulted in cases of sexual dysfunction, which became manifest at puberty (Bern 1992). Maternal transfer of EDCs may also occur in fish, when pollutants are co-transported with VTG into the developing oocyte (Gray et al. 1999). In the present study we found no transgenerational effects of F0 exposure to < 5 ng/L EE2 on the level of embryo viability at 14 hpf or F1 embryo mortality and larval integrity (proportion of developmental abnormality, hatch rate, and level of spine curvature) at 100 hpf, when the offspring were reared in clean water and compared with the corresponding treatment in continuous F0 and F1 exposure or control treatment (n = 6, p > 0.05 in all cases). This is not surprising because we also found no effects up to 100 hpf when both the parents (F0) and offspring (F1) were exposed at these same concentrations during the main multigenerational experiment. Moreover, reproductive success in the F1 subgroups (n = 5) reared to adulthood in clean water but with parental F0 exposure (0.5 and 5 ng/mL EE2 and 5 ng/mL E2) was not affected, either in the number of eggs spawned by the F1 (F = 1.07, p = 0.39 n = 6) or the 14 hr viability of the resulting eggs (F = 0.84, p = 0.29; six tanks per treatment) when compared to the control eggs collected at the same time. This contrasts with continuous multigenerational exposures (F0 and F1) causing significant or complete reproductive failure at similar doses. F0-only exposure also had no consequences for the integrity of the F2 offspring, either in the level of embryo mortality or larval integrity at 100 hpf (p > 0.05 in all cases), again consistent with what would be expected if there were no transgenerational impact. These results, therefore, give little evidence of any transgenerational (maternal) effects of exposure to EE2 or E2, at least when measuring population level consequences for reproductive success and survival. There are no other studies that have reported transgenerational effects of steroid hormones on reproductive success, although a study by Foran et al. (2002) showed transgenerational impacts on VTG and estrogen receptor responsiveness in medaka, but only at extremely high doses (> 500 ng/L). Reported transgenerational impacts of other endocrine disruptors, such as DDT on F1 gonadal development (Metcalfe et al. 2000) and nonylphenol on F1 steroid levels (Schwaiger et al. 2002), may be related to different biochemical properties of these pollutants.
In populations (three tanks) of fish exposed to 0.5 and 5 ng/L EE2 and 5 ng/L E2 to 75 dpf and then reared in clean freshwater to adulthood (a depuration of 5 months), we found no differences in fecundity at 210–220 dpf when compared with the control for these subgroups (F = 0.46 p = 0.72, 10-day means). This is in contrast with the strong impact of continuous full life-long exposure (Figure 6) to 5 ng/L EE2 in the F1 generation that caused a considerable reduction in egg numbers, thus illustrating a capacity for recovery in their reproductive output (numbers of eggs spawned).
Interestingly, however, even after a 5 month period of depuration, there was still a highly significant (F = 12.81 p = 0.003) impact of exposure on fertilization success; the proportion of nonviable eggs at 14 hpf increased to 16.2% in 0.5 ng/L EE2 and 24% in 5 ng/L EE2 compared with a rate of 7.8% in the controls. Even though males were still able to produce sperm (shown by stripping) and fertilize the eggs spawned by females, there was also persistent disruption to testes development, which could explain the reduced fertilization success. Histology showed extensive malformations of the sperm ducts, the presence of an ovarian cavity in the testis, variation in proportion of testicular cell types, and ciliation of sperm ducts (Figure 4D), a feature normally found in ovarian ducts that has been reported in wild intersex roach (Nolan et al. 2001). Persistent effects on testes of developmental exposure to similar levels of EE2 in zebrafish were not reported by Weber et al. (2003), but duct morphology was not examined. Partial recovery from EE2 exposure during early sexual differentiation can therefore occur with a sufficient period of depuration, but certain morphologic effects are long lived. The persistent nature of EDC-induced gonadal abnormalities has been confirmed in several fishes (Gimeno and Komen 1996; McAllister and Kime 2003; Scholz and Gutzeit 2000; van Aerle et al. 2002), and differences in the level of recovery after depuration probably relate to diverse modes of sexual differentiation found between species.
Vitellogenin and steroid hormone response.
In the F0 generation after 40 days exposure to the lower, sublethal concentrations of EE2, we found a highly significant (F = 41.64, p < 0.001) and dose-related induction of VTG in both sexes (Figure 6A). In males, a dose of only 0.5 ng/L EE2 induced a 5,000-fold increase in blood VTG, which concurs with previous studies in fish, including zebrafish (Fenske et al. 2001; Thorpe et al. 2003). There was also a significant (F = 17.59, p < 0.001, n = 8) and dose-related suppression of the major male fish sex hormone 11-KT in F0 males; in the blood of fish treated with 0.5, 5, or 50 ng/L EE2 or 5 ng/L E2, 11-KT concentrations were 30, 5, 6, and 8% of controls, respectively (mean ± SEM = 94 ± 46 ng/mL). The sensitivity of both VTG and 11-KT to exogenous steroidal estrogens reinforces their value as biomarkers for exposure to estrogen after short-term exposure (Brion et al. 2002; Denslow et al. 1999). Very considerable (3 orders of magnitude) changes in blood VTG and up to 95% reduction in 11-KT, however, did not impact the short-term reproductive success of the zebrafish populations, emphasizing their utility as biomarkers of estrogen exposure, rather than necessarily measures of reproductive impact. There were no significant impacts of the estrogen treatments on endogenous blood E2, although there was a high level of variability between fish. The measurements of 11-KT and E2 are the first data on reproductive steroid hormones in zebrafish, and the method (Nash et al. 2000) could be adapted to other small species (≤300 mg). To further investigate natural levels of a range of steroids in zebrafish and their response to endocrine disruption, ongoing research in our laboratories is examining a larger number of replicates that were collected in this study and in new experiments.
In contrast with the short-term adult exposure (Figure 6A), we observed no induction of VTG in males after life-long exposure to < 5 ng/L EE2 (Figure 6B), suggesting an acclimation to the EE2 exposure. Similarly there were no effects of a multigenerational life-long exposure to estrogen on VTG in females, but the VTG concentration in F1 controls was higher than in both the F0 controls and 5 ng/L EE2 fish (Figure 6B). It seems likely that there is strong down-regulation of vitellogenic response after long-term exposure to exogenous estrogens, which has not been reported before. Studies in fish have shown that there are seasonal variations in the number of estrogen receptors and in the ligand affinity of these receptors (Smith and Thomas 1991), and thus responsiveness to estrogen, but we do not know the mechanism for acclimation to estrogen observed here in males. A reduced vitellogenic response (or indeed lack of a response) in males after long-term exposure to low levels of estrogen further complicates the use of VTG as a biomarker for estrogen exposure in wild populations; fish that have been subjected to long-term exposure to estrogen and with no measurable blood VTG could still be reproductively compromised.
The temporal disassociation between the impact of estrogen exposure on reproductive success and the vitellogenic response also clearly shows that the perturbations to reproductive physiology that ultimately cause reproductive failure are probably not directly linked or at least not a direct consequence of the stimulation of vitellogenin.
Conclusions
Overall, our findings on the effective concentration of EE2 on reproductive success raise serious concerns for possible population-level effects on fisheries. Concern about population-level consequences associated with exposure to EE2 in the aquatic environment is further exacerbated by the fact that detection capabilities for routine assessments of EE2 in effluents and environmental samples are generally above concentrations that are biologically significant (Kolpin et al. 2002a). Extremely high potency and persistence in the aquatic environment (Johnson and Williams 2004) is also likely to be mirrored by other persistent pharmaceuticals which are, as yet, not measured in routine assessments of effluents (Metcalfe et al. 2003).
The data presented in this article give evidence that different reproductive components have differential sensitivities to endocrine disruption and that these sensitivities are dependent on the length of exposure and timing of exposure relative to development and maturity. Full life-long exposures had a strong impact on reproductive success at a concentration that was at least one order of magnitude less than when fish were given short-term exposures proximate to spawning. Conversely, after full life-long exposure there was no apparent stimulation of VTG in the F1 adults, whereas short-term exposures strongly stimulated VTG in the parental F0 generation at similar doses. These data have important implications for bodies devising effective methodologies for the diagnosis of the ecologic risk from endocrine disruptors and for those devising laboratory testing strategies for hazard assessment. Because it is the impacts at the population level that are ultimately of most concern, special care must be taken when interpreting the results from either short-term testing procedures or from biomarkers such as VTG. Although integrative long-term multigenerational studies are expensive and time consuming, the mechanistic information they produce is invaluable if we want to understand both the potential population consequences of endocrine disruption and the mode of action that leads to reproductive failure. Although these long-term studies cannot be repeated for every potential EDC, the mechanistic knowledge gained should be integrated into the design of shorter testing methodologies and new mechanistic approaches such as toxicogenomics, to allow for more accurate predictions of the population level consequences.
The value of an integrative approach can be clearly seen from the data obtained in our male replacement studies. A differential in relative sensitivity to disruption between gonadal and behavioral sexual differentiation had the consequence that male-pattern behavior was more robust to the effects of EE2 exposure than was gonadal development, where exposure caused complete male infertility. If behavior is considered in isolation, then a lower impact on behavior may seem to have fewer population consequences; when behavior is considered in combination with infertility, it may actually increase the risk of reproductive failure in natural populations. We suggest that reproductive behavior plays a pivotal role in how chemically induced reproductive dysfunction(s) act to affect reproductive success and/or genetic integrity of populations. Moreover, there exists the possibility of other important interactions between endocrine disruption and mating systems that could strongly influence the population-level impact of reduced fertility. Sexual selection and mate choice strategies are complex, and endocrine disruption may interact or interfere with these in both negative and positive ways. Factors that determine the choice of a male by the female could, for example, be exaggerated in males with reduced fertility, giving these fish an even greater potential for interfering with the natural mating process and further increasing the impact of endocrine disruption on reproductive success. We suggest that further studies should examine this previously overlooked area.
Figure 1 Between-tank and between-day variations in number of eggs over a 20-day period. (A) Total number of eggs in five random control tanks. (B) Mean (± SEM) number of eggs for the same tanks.
Figure 2 Reproductive success in the F0 generation of zebrafish exposed to 0.5, 5, and 50 ng/L EE2, 5 ng/L E2, and unexposed controls for three consecutive 5-day periods: (A) 1–5 days, (B) 6–10 days, and (C) 11–15 days. Total bar length indicates the total number of eggs per tank (mean ± SEM; top error bar). The lighter bar indicates total survival of viable eggs at 14 hpf (mean ± SEM; bottom error bar). The black section indicates the number of nonviable eggs at 14 hpf.
*Significant decrease in egg number and 14 hpf viability when compared with the control group for each period, and increase in rate of nonviable eggs when compared with the same group in (A); ANOVA, all cases n = 12, p < 0.01, post hoc analysis against control treatments by Dunnet’s test with p > 0.05.
Figure 3 Reproductive success of the F1 generation of zebrafish after 7 months (210 dpf) exposure to 0.5 and 5 ng/L EE2, 5 ng/L E2, and unexposed controls for two successive 5-day periods: (A) 1–5 days, and (B) 6–10 days. Total bar length indicates the total number of eggs per tank (mean ± SEM; top error bar). The lighter bar indicates the total number of viable eggs at 14 hpf (mean ± SEM; bottom error bar). The black section indicates the proportion of eggs nonviable at 14 hpf.
*Long-term exposure to 5 ng/L EE2 resulted in a reduced fecundity (n = 12, p < 0.01) and no survival past 14 hpf. **The proportion of nonviable eggs was significantly higher for all treatments when compared with the control rates (n = 12, p < 0.05).
Figure 4 Effects of life-long exposure to 5 ng/L EE2 on gonad development in adult zebrafish (314 dpf). (A) Persisting juvenile undifferentiated (ovary-type) gonad in presumptive males. (B) Intersex fish with one ovary and one testis. (C) Intersex fish with two testes and smaller juvenile (ovary-type) tissue. (D) Ciliated sperm duct in testis of mature male (found only in adults when exposure to EE2 was stopped at 75 dpf).
Figure 5 Reproductive success (5-day means) in the F1 generation of zebrafish at 240 dpf after lifelong exposure to 5 ng/L EE2, with subsequent manipulation of males in the populations (all experiments done under no direct exposure). In the controls, males were either retained (control; six tanks) or removed (control – males; six tanks). In the EE2 treatment, EE2-exposed males were either retained (5 ng/L EE2, six tanks) or two males were substituted with two healthy control males (EE2 + males; six tanks). Total bar length indicates the total number of eggs per tank (mean ± SEM) for the six replicate tanks in each group. The lighter bar indicates the total number of viable eggs (mean ± SEM) to 14 hpf. The black section indicates the percentage of nonviable eggs at 14 hpf.
*Significantly different (p < 0.05) from control in the proportion of viable eggs at 14 hpf. **Significantly different (p < 0.05) from control in total egg numbers. #Significantly different (p < 0.05) number of eggs laid with the addition of healthy males compared with controls (F = 16.5, p < 0.001, n = 6); the proportion of nonviable eggs was still significantly higher (F = 177, p < 0.001, n = 6) than in the control group.
Figure 6 Whole blood VTG concentrations (mean ± SEM) in male and female zebrafish in the F0 generation after 40 days exposure to 0.5, 0.5, 5, or 50 ng/L EE2 (A) and in the F1 generation after life-long (310 dpf) exposure to 0, 0.5, or 5 ng/L EE2.
*Dose-dependent induction of VTG (p < 0.05 compared with controls of the same sex).
==== Refs
References
Aherne GW Briggs R 1989 The relevance of the presence of certain synthetic steroids in the aquatic environment J Pharm Pharmacol 41 735 736 2575159
Andersen L Holbech H Gessbo A Norrgren L Petersen GI 2003 Effects of exposure to 17α-ethinylestradiol during early development on sexual differentiation and induction of vitellogenin in zebrafish (Danio rerio ) Comp Biochem Physiol C Toxicol Pharmacol 134 365 374 12643983
Balch GC Mackenzie CA Metcalfe CD 2004 Alterations to gonadal development and reproductive success in Japanese medaka (Oryzias latipes ) exposed to 17α-ethinylestradiol Environ Toxicol Chem 23 782 791 15285373
Bern HA 1992. The fragile fetus. In: Chemically-Induced Alterations in Sexual and Functional Development: The Wildlife Human Connection (Colborn T, Clement C, eds). Princeton, NJ:Princeton Scientific Publishing, 9–15.
Bortone SA Davis WP 1994 Fish intersexuality as indicator of environmental stress Bioscience 44 165 172
Brion F Nilsen BM Eidem JK Goksoyr A Porcher JM 2002 Development and validation of an enzyme-linked immunosorbent assay to measure vitellogenin in the zebrafish (Danio rerio ) Environ Toxicol Chem 21 1699 1708 12152772
Colborn T Clement C 1992. Chemically-Induced Alterations in Sexual and Functional Development: The Wildlife Human Connection. Princeton, NJ:Princeton Scientific Publishing.
Dawson A 1998 Comparative reproductive physiology of non-mammalian species Pure Appl Chem 70 1657 1669
Denslow ND Chow MC Kroll KJ Green L 1999 Vitellogenin as a biomarker of exposure for estrogen or estrogen mimics Ecotoxicology 8 385 398
Desbrow C Routledge EJ Brighty G Sumpter JP Waldock MJ 1998 Indentification of estrogenic chemicals in STW effluent. 1. Chemical fractionation and in vitro biological screening Environ Sci Technol 32 1559 1565
Eaton RC Farley RD 1974 Spawning cycle and egg production of zebrafish, Brachydanio rerio , in the laboratory Copeia 1974 195 204
Elliott M Hemmingway KL Krueger D Theil R Hylland K Arukwe A 2003. From the individual to the population and community responses to pollution. In: Effects of Pollution on Fish (Lawrence AJ, Hemmingway KL, eds). Oxford, UK:Blackwell, 221–255.
Ensenbach U Nagel R 1997 Toxicity of binary chemical mixtures: effects on reproduction of zebrafish (Brachydanio rerio ) Arch Environ Contam Toxicol 32 204 210 9069198
Fenske M Van Aerle R Brack S Tyler CR Segner H 2001 Development of a homologous zebrafish (Danio rerio Hamilton-Buhanan) vitellogenin enzyme-linked immunosorbent assay (ELISA) and its application for studies on estrogenic chemicals Comp Biochem Physiol C 129 217 232
Foran CM Peterson BN Benson WH 2002 Transgenerational and developmental exposure of Japanese medaka (Oryzias latipes ) to ethinylestradiol results in endocrine and reproductive differences in the response to ethinylestradiol as adults Toxicol Sci 68 389 402 12151635
Gibbs PE Bryan GW Pascoe PL 1991 TBT-induced imposex in the dogwhelk, Nucella-Lapillus - geographical uniformity of the response and effects Mar Environ Res 32 79 87
Gimeno S Komen H 1996 Feminization of male carp Nature 384 221 222 8918871
Gray MA Teather KL Metcalfe CD 1999 Reproductive success and behavior of Japanese medaka (Oryzias latipes ) exposed to 4-tert -octylphenol Environ Toxicol Chem 18 2587 2594
Guillette LJ Gunderson MP 2001 Alterations in development of reproductive and endocrine systems of wildlife populations exposed to endocrine-disrupting contaminants Reproduction 122 857 864 11732981
Haubruge E Petit F Gage MJG 2000 Reduced sperm counts in guppies (Poecilia reticulata ) following exposure to low levels of tributyltin and bisphenol A Proc Roy Soc London Ser B 267 2333 2337
Hill RL Janz DM 2003 Developmental estrogenic exposure in zebrafish (Danio rerio ). I. Effects on sex ratio and breeding success Aquatic Toxicol 63 417 429
Iwamatsu T 1999 Convenient method for sex reversal in a freshwater teleost, the medaka J Exp Zool 283 210 214
Jobling S Beresford N Nolan M Rodgers-Gray T Brighty GC Sumpter JP 2002a Altered sexual maturation and gamete production in wild roach (Rutilus rutilus ) living in rivers that receive treated sewage effluents Biol Reprod 66 272 281 11804939
Jobling S Coey S Whitmore JG Kime DE Van Look KJW McAllister BG 2002b Wild intersex roach (Rutilus rutilus ) have reduced fertility Biol Reprod 67 515 524 12135890
Jobling S Nolan M Tyler CR Brighty G Sumpter JP 1998 Widespread sexual disruption in wild fish Environ Sci Technol 32 2498 2506
Johnson AC Williams RJ 2004 A model to estimate influent and effluent concentrations of estradiol, estrone, and ethinylestradiol at sewage treatment works Environ Sci Technol 38 3649 3658 15296317
Kelly C 2000 Analysis of steroids in environmental water samples using solid-phase extraction and ion-trap gas chromatography-mass spectrometry and gas chromatography-tandem mass spectrometry J Chromatogr A 872 309 314 10749507
Kime DE 1998. Endocrine Disruption in Fish. Boston:Kluwer.
Kime DE Ebrahimi M Nysten K Roelants I Rurangwa E Moore HDM 1996 Use of computer assisted sperm analysis (CASA) for monitoring the effects of pollution on sperm quality of fish; application to the effects of heavy metals Aquat Toxicol 36 223 237
Kimmel CB Ballard WW Kimmel SR Ullmann B Schilling TF 1995 Stages of embryonic development of the zebrafish Dev Dyn 203 253 310 8589427
Kolpin DW Furlong ET Meyer MT Thurman EM Zaugg SD Barber LB 2002a Pharmaceuticals, hormones, and other organic wastewater contaminants in U.S. streams, 1999–2000: a national reconnaissance Environ Sci Technol 36 1202 1211 11944670
Kolpin DW Furlong ET Meyer MT Thurman EM Zaugg SD Barber LB 2002b Response to comment on, ”Pharmaceuticals, hormones, and other organic waste-water contaminants in U.S. streams, 1999–2000: a national reconnaissance” Environ Sci Technol 36 4007 4008
Lange R Hutchinson TH Croudace CP Siegmund F 2001 Effects of the synthetic estrogen 17α-ethinylestradiol on the life-cycle of the fathead minnow (Pimephales promelas ) Environ Toxicol Chem 20 1216 1227 11392131
Larsson DGJ Adolfsson-Erici M Parkkonen J Pettersson M Berg AH Olsson PE 1999 Ethinyloestradiol—an undesired fish contraceptive? Aquat Toxicol 45 91 97
Larsson DGJ Hällman H Förlin L 2000 Environmental toxicology —more male fish near a pulp mill Environ Toxicol Chem 19 2911 2917
Maack G Segner H 2003 Morphological development of the gonads in zebrafish J Fish Biol 62 895 906
Matthiessen P Gibbs PE 1998 Critical appraisal of the evidence for tributyltin-mediated endocrine disruption in mollusks Environ Toxicol Chem 17 37 43
McAllister BG Kime DE 2003 Early life exposure to environmental levels of the aromatase inhibitor tributyltin causes masculinisation and irreversible sperm damage in zebrafish (Danio rerio ) Aquat Toxicol 65 309 316 13678849
Metcalfe CD Koenig BG Bennie DT Servos M Ternes TA Hirsch R 2003 Occurrence of neutral and acidic drugs in the effluents of Canadian sewage treatment plants Environ Toxicol Chem 22 2872 2880 14713026
Metcalfe CD Metcalfe TL Kiparissis Y Koenig BG Khan C Hughes RJ 2001 Estrogenic potency of chemicals detected in sewage treatment plant effluents as determined by in vivo assays with Japanese medaka (Oryzias latipes ) Environ Toxicol Chem 20 297 308 11351429
Metcalfe TL Metcalfe CD Kiparissis Y Niimi AJ Foran CM Benson WH 2000 Gonadal development and endocrine responses in Japanese medaka (Oryzias latipes ) exposed to o,p ‘-DDT in water or through maternal transfer Environ Toxicol Chem 19 1893 1900
Nagahama Y 1994 Endocrine regulation of gametogenesis in fish Int J Dev Biol 38 217 229 7981031
Nash JP Cuisset B Bhattacharyya S Suter HC Le Menn F Kime DE 2000 An enzyme linked immunosorbant assay (ELISA) for testosterone, estradiol, and 17,20β-dihydroxy-4-pregnen-3-one using acetylcholinesterase as tracer: application to measurement of diel patterns in rainbow trout (Oncorhynchus mykiss ) Fish Physiol Biochem 22 355 363
Nolan M Jobling S Brighty G Sumpter JP Tyler CR 2001 A histological description of intersexuality in the roach J Fish Biol 58 160 176
Ohtake F Takeyama K Matsumoto T Kitagawa H Yamamoto Y Nohara K 2003 Modulation of oestrogen receptor signalling by association with the activated dioxin receptor Nature 423 545 550 12774124
Purdom CE Hardiman PA Bye VJ Eno NC Tyler CR Sumpter JP 1994 Oestrogenic effects of effluent from sewage treatment works Chem Ecol 8 275 285
RIVM 2004. Toxicological Pathology Atlas of Small Laboratory Fish. Available: http://www.rivm.nl/fishtoxpat/ [accessed 26 October 2004].
Scholz S Gutzeit HO 2000 17α-Ethinylestradiol affects reproduction, sexual differentiation and aromatase gene expression of the medaka (Oryzias latipes ) Aquat Toxicol 50 363 373 10967398
Schwaiger J Mallow U Ferling H Knoerr S Braunbeck T Kalbfus W 2002 How estrogenic is nonylphenol? A transgenerational study using rainbow trout (Oncorhynchus mykiss ) as a test organism Aquat Toxicol 59 177 189 12127735
Segner H Caroll K Fenske M Janssen CR Maack G Pascoe D 2003a Identification of endocrine-disrupting effects in aquatic vertebrates and invertebrates: report from the European IDEA project Ecotoxicol Environ Saf 54 302 314 12651186
Segner H Navas JM Schafers C Wenzel A 2003b Potencies of estrogenic compounds in in vitro screening assays and in life cycle tests with zebrafish in vivo Ecotoxicol Environ Saf 54 315 322 12651187
Seki M Yokota H Matsubara H Tsuruda Y Maeda N Tadokoro H 2002 Effect of ethinylestradiol on the reproduction and induction of vitellogenin and testis-ova in medaka (Oryzias latipes ) Environ Toxicol Chem 21 1692 1698 12152771
Smith JS Thomas P 1991 Changes in hepatic estrogen-receptor concentrations during the annual reproductive and ovarian cycles of a marine teleost, the spotted seatrout, Cynoscion nebulosus Gen Comp Endocrinol 81 234 245 2019398
Strussmann CA Nakamura M 2002 Morphology, endocrinology, and environmental modulation of gonadal sex differentiation in teleost fishes Fish Physiol Biochem 26 13 29
Ternes TA Stumpf M Mueller J Haberer K Wilken RD Servos M 1999 Behavior and occurrence of estrogens in municipal sewage treatment plants—I. Investigations in Germany, Canada and Brazil Sci Total Environ 225 81 90 10028705
Thorpe KL Cummings RI Hutchinson TH Scholze M Brighty G Sumpter JP 2003 Relative potencies and combination effects of steroidal estrogens in fish Environ Sci Technol 37 1142 1149 12680667
Tyler CR Jobling S Sumpter JP 1998 Endocrine disruption in wildlife: a critical review of the evidence Crit Rev Toxicol 28 319 361 9711432
Tyler CR Routledge EJ 1998 Oestrogenic effects in fish in English rivers with evidence of their causation Pure Appl Chem 70 1795 1804
U.S. EPA 1986. Fish Life-Cycle Toxicity Tests. EPA 540/9-86–137. Washington, DC:U.S. Environmental Protection Agency.
Van Aerle R Pounds N Hutchinson TH Maddix S Tyler CR 2002 Window of sensitivity for the estrogenic effects of ethinylestradiol in early life-stages of fathead minnow, Pimephales promelas Ecotoxicology 11 423 434 12521139
Van den Belt K Verheyen R Witters H 2003 Effects of 17alpha-ethynylestradiol in a partial life-cycle test with zebrafish (Danio rerio ): effects on growth, gonads and female reproductive success Sci Total Environ 309 127 137 12798098
Van den Belt K Wester PW Van der Ven LTM Verheyen R Witters H 2002 Effects of ethynylestradiol on the reproductive physiology in zebrafish (Danio rerio ): time dependency and reversibility Environ Toxicol Chem 21 767 775 11951950
Van Der Kraak G 1998 Observations of endocrine effects in wildlife with evidence of their causation Pure Appl Chem 70 1785 1794
Weber LP Hill RL Janz DM 2003 Developmental estrogenic exposure in zebrafish (Danio rerio ): II. Histological evaluation of gametogenesis and organ toxicity Aquat Toxicol 63 431 446 12758007
Zillioux EJ Johnson IC Kiparissis Y Metcalfe CD Wheat JV Ward SG 2001 The sheepshead minnow as an in vivo model for endocrine disruption in marine teleosts: a partial life-cycle test with 17α-ethynylestradiol Environ Toxicol Chem 20 1968 1978 11521823
|
15579420
|
PMC1253666
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec 4; 112(17):1725-1733
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7209
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science 10.1289/ehp.7212ehp0112-00173415579421ResearchArticlesTemporal Variability of Urinary Phthalate Metabolite Levels in Men of Reproductive Age Hauser Russ 12Meeker John D. 1Park Sohee 3Silva Manori J. 4Calafat Antonia M. 41Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA2Vincent Memorial Obstetrics and Gynecology Service, Andrology Laboratory and In Vitro Fertilization Unit, Massachusetts General Hospital, Boston, Massachusetts, USA3Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA4National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, Georgia, USAAddress correspondence to R. Hauser, Harvard School of Public Health, Department of Environmental Health, Occupational Health Program, Building 1, Room 1405, 665 Huntington Ave., Boston, MA 02115 USA. Telephone: (617) 432-3326. Fax: (617) 432-0219. E-mail:
[email protected] thank J. Reidy, A. Herbert, E. Samandar, and J. Preau from the Centers for Disease Control and Prevention and S. Duty, J. Frelich, L. Godfrey-Bailey, A. Trisini, and R. Dadd from the Harvard School of Public Health.
This work was supported by grants ES09718 and ES00002 from the National Institute of Environmental Health Sciences (NIEHS). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of NIEHS.
The authors declare they have no competing financial interests.
12 2004 16 8 2004 112 17 1734 1740 27 4 2004 16 8 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Phthalates are a family of multifunctional chemicals widely used in personal care and other consumer products. The ubiquitous use of phthalates results in human exposure through multiple sources and routes, including dietary ingestion, dermal absorption, inhalation, and parenteral exposure from medical devices containing phthalates. We explored the temporal variability over 3 months in urinary phthalate metabolite levels among 11 men who collected up to nine urine samples each during this time period. Eight phthalate metabolites were measured by solid-phase extraction–high-performance liquid chromatography–tandem mass spectrometry. Statistical analyses were performed to determine the between- and within-subject variance apportionment, and the sensitivity and specificity of a single urine sample to classify a subject’s 3-month average exposure. Five of the eight phthalates were frequently detected. Monoethyl phthalate (MEP) was detected in 100% of samples; monobutyl phthalate, monobenzyl phthalate, mono-2-ethylhexyl phthalate (MEHP), and monomethyl phthalate were detected in > 90% of samples. Although we found both substantial day-to-day and month-to-month variability in each individual’s urinary phthalate metabolite levels, a single urine sample was moderately predictive of each subject’s exposure over 3 months. The sensitivities ranged from 0.56 to 0.74. Both the degree of between- and within-subject variance and the predictive ability of a single urine sample differed among phthalate metabolites. In particular, a single urine sample was most predictive for MEP and least predictive for MEHP. These results suggest that the most efficient exposure assessment strategy for a particular study may depend on the phthalates of interest.
biomarkershumanphthalatesreliabilityurine
==== Body
Phthalates, diesters of phthalic acid, are a family of multifunctional chemicals that are widely used in personal and consumer products. Phthalates are used to hold color and scent in consumer and personal care products (Koo et al. 2002); as solvents in paints, glue, insect repellents, lubricants, and adhesives [Agency for Toxic Substances and Disease Registry (ATSDR 2001]; and to soften a wide range of plastics (Bradbury 1996), including polyvinyl chloride (PVC) used in the manufacture of medical products such as blood, intravenous, and dialysate bags and tubing (Nassberger et al. 1987). Diethyl phthalate (DEP), di-n-butyl phthalate (DBP), and butyl benzyl phthalate (BBzP) are principally used in personal care products, such as body lotions, gels, shampoos, and deodorants (ATSDR 1995, 2001). They also have U.S. Food and Drug Administration approval for uses in food packaging and processing materials that are in contact with food, and as a result they have been found in food (Castle et al. 1990; Page and Lacroix 1995). DBP, BBzP, and di-(2-ethylhexyl) phthalate are also used in residential building materials such as floorings, paints, carpet backings, adhesives, and wallpaper, and in PVC products such as auto parts and interiors (ATSDR 2001, 2002). Although the volatility of phthalates is relatively low, studies have shown that phthalates are present in residential indoor air (Jaakkoala et al. 1999; Rudel et al. 2003).
The ubiquitous use of phthalates results in human exposure via dietary ingestion of foods (such as milk, butter, and meats), dermal absorption of low-molecular-weight phthalates (e.g., DEP, DBP, BBzP), inhalation of the more volatile phthalates, and parenteral exposure from medical devices containing phthalates (ATSDR 1995, 2001, 2002). Recently, researchers at the Centers for Disease Control and Prevention (CDC) developed analytical methods for the quantitative detection of phthalate metabolites in urine (Blount et al. 2000). Phthalate monoester metabolites were measured because of potential sample contamination from the parent diesters and because the metabolites are considered the biologically active toxicant (Li et al. 1998; Peck and Albro 1982: Sjoberg et al. 1986). The use of phthalate metabolites in urine as biomarkers of exposure now allows researchers to accurately measure human exposure to phthalates. These biomarkers represent an integrative measure of phthalate exposure from multiple sources and pathways. Recently, four phthalate metabolites—monoethyl phthalate (MEP), mono-(2-ethylhexyl) phthalate (MEHP), monobutyl phthalate (MBP), and monobenzyl phthalate (MBzP)—were found in the urine samples of > 75% of approximately 2,550 participants of the National Health Nutrition and Examination Survey (NHANES) 1999–2000 (CDC 2003; Silva et al. 2004).
Because humans and other mammals rapidly metabolize phthalate diesters to their respective monoesters, which in turn may be further metabolized, phthalates do not bio-accumulate (ATSDR 1995, 2001, 2002; Peck and Albro 1982). Because biologic half-lives of phthalates are on the order of hours, urinary metabolite levels reflect exposures that most likely occurred ≤1 day preceding the collection of the urine specimen. However, because most health end points of interest are likely associated with exposures over time intervals longer than a few days, information on the temporal variability of urinary levels of phthalate metabolites is needed to optimize the design of exposure assessment in epidemiologic studies. Currently there are limited published data on the temporal variability of urinary phthalate monoester metabolite concentrations. A recent study documented good reproducibility of urinary phthalate monoester levels in two first-morning urine specimens collected for 2 consecutive days; day-to-day intraclass correlation coefficients (ICCs) ranged from 0.5 to 0.8 (Hoppin et al. 2002). Time intervals beyond a couple of days were not explored.
Variability in an individual’s exposure to phthalates can result from changes in the use of personal care products, diet, or daily activity patterns, such as time spent in specific micro-environments (i.e., residential, workplace, or other) with ambient phthalate levels. Therefore, characterizing an individual’s phthalate exposure is complex, and exposure may vary considerably over short time periods, such as days. Although phthalate bio-markers in urine are available to accurately measure a person’s exposure at a single point in time, determining exposure over time intervals of weeks or months will require multiple measurements of phthalate metabolites. Therefore, the present study was designed to explore the temporal variability in urinary phthalate metabolite levels. Our design allowed us to determine between- and within-subject variability in urinary phthalate metabolite levels, as well as apportion the within-person variability into monthly and daily variances. We also explored the sensitivity of a single urine measurement to predict an individual’s 3-month average exposure. This information can be used for designing exposure assessment strategies for epidemiologic studies and to adjust for measurement error in phthalate exposure.
Materials and Methods
Eleven men from our ongoing study of the relationship between environmental agents and male reproductive health agreed to participate in the phthalate variability study. Participant recruitment into the environmental agents and male reproductive health study has been previously described (Hauser et al. 2003). Briefly, men who were the partner in couples seeking fertility evaluation for inability to conceive were recruited to participate. The study site was the Massachusetts General Hospital (MGH) Andrology Laboratory, so most men resided in the New England area. At the clinic visit, each man was asked to produce a single semen sample and to collect a single spot urine sample.
For each of the 11 men in the phthalate temporal variability study, up to nine additional spot urine samples were collected during three cycles over a 92-day period. Ten of these 11 men each contributed a total of 10 urine samples (nine for the variability study and one for the male reproductive study), whereas one of the men provided a total of seven samples (including six for the variability study). Nested within each of the three cycles were three urine samples, collected on the first 3 consecutive days of each cycle. The first cycle began upon enrollment into the phthalate temporal variability study, and urine samples were collected on days 0, 1, and 2. Cycles 2 and 3 began 30 days and 90 days after cycle 1, respectively. Therefore, the nine urine samples were collected on days 0, 1, and 2 (cycle 1); days 30, 31, and 32 (cycle 2); and days 90, 91, and 92 (cycle 3).
All the urine samples were collected in a sterile specimen cup. The urine sample on day 0 was collected at the MGH Andrology laboratory. All other samples were collected at the subject’s home and frozen before overnight shipment to the Harvard School of Public Health (HSPH) on blue ice. All urine samples were then shipped frozen on dry ice from HSPH to CDC. Eight phthalate monoesters—MBzP, MBP, MEP, MEHP, monomethyl phthalate (MMP), mono-n-octyl phthalate (MOP), mono-3-methyl-5-dimethylhexyl phthalate (MINP), and monocyclohexyl phthalate (MCHP)—were measured in each spot urine sample using an analytical approach developed at the CDC (Silva et al. 2003). Briefly, the determination of phthalate metabolites in urine involved enzymatic deconjugation of the glucuronidated metabolites, solid-phase extraction, separation with high-performance liquid chromatography, and detection by tandem mass spectrometry. Detection limits were in the low micrograms per liter range. Reagent blanks and 13C4-labeled internal standards were used along with conjugated internal standards to increase the precision of the measurements. One method blank, two quality control samples (human urine spiked with phthalates), and two sets of standards were analyzed along with every 21 unknown urine samples. Analysts at the CDC were blind to all information concerning subjects.
Several methods adjust for urine volume (Boeniger et al. 1993; Teass et al. 1998). Although creatinine is a frequently used form of adjustment, if a compound is excreted primarily by tubular secretion it is not appropriate to adjust for creatinine level (Teass et al. 1998). Although the methods of excretion of the phthalate monoesters measured in this study are unknown, terephthalic acid was found to be actively secreted by renal tubules and actively reabsorbed by the kidney (Tremaine and Quebbemann 1985). Furthermore, because organic compounds that are glucuronidated in the liver, like the phthalates, are eliminated by active tubular secretion (Boeniger et al. 1993), creatinine adjustment may not be appropriate for phthalates. Additionally, creatinine levels may be confounded by muscularity, physical activity, urine flow, time of day, diet, and disease states (Boeniger et al. 1993; Teass et al. 1998). For these reasons, specific gravity, rather than creatinine, was used to normalize phthalate levels.
Urinary phthalate levels were normalized for dilution by specific gravity adjustment using the formula Pc = P × [(1.024 – 1)/(SG – 1)], where Pc is the specific-gravity–corrected phthalate concentration (micrograms per liter), P is the observed phthalate concentration (micrograms per liter), and SG is the specific gravity of the urine sample (Boeniger et al. 1993; Teass et al. 1998). Specific gravity was measured using a handheld refractometer (National Instrument Company, Inc., Baltimore, MD), which was calibrated with deionized water before each measurement.
Statistical analyses.
We performed the statistical analyses using the Statistical Analysis Software (SAS), version 8.1 (SAS Institute, Cary, NC). Both unadjusted and specific-gravity–adjusted values were used. For values below the limit of detection (LOD), corresponding to 1.2 (MEP), 0.94 (MBP), 0.47 (MBzP), 0.86 (MEHP), 0.70 (MMP), 0.77 (MOP), 0.79 (MINP), and 0.93 μg/L (MCHP), we used an imputed value equal to one-half the LOD.
We constructed graphs to compare metabolite levels within and between subjects, and calculated Spearman correlation coefficients to investigate correlations between samples collected at different time points.
To assess between- and within-person variability of metabolite levels, we calculated ICCs for each metabolite based on output from a random effects model fit using PROC MIXED (Rosner 1999). ICC, defined as the ratio of between-person variance to total variance, is a measure of reliability of repeated measures over time. ICC ranges from 0 to 1, with values near 1 indicating high reliability and values near 0 indicating poor reliability. ICC can also be used in an internal validity study to account for measurement error in epidemiology effect estimates (Carroll et al. 1995; Rosner et al. 1992).
To apportion variances among nested components, we fit a hierarchical model (using PROC MIXED). For a more robust estimate of between-subject variability, we used the results of the single urine samples collected from all 369 men enrolled so far in the ongoing environmental agents and male reproductive health study in the variance apportionment analysis. Because the 11 men in this variability study were also enrolled in the male reproductive health study, their single urine sample collected for the reproductive study contributed additional information on variability. Within-subject variance was further apportioned into cycle-to-cycle variance and day-to-day variance (Box et al. 1978). Day-to-day variance was defined as the variance in phthalate metabolite levels between samples 1 or 2 days apart, regardless of whether they were collected in cycle 1, 2, or 3. Cycle-to-cycle variance was defined as the variance between the three cycles minus the day-to-day variances within the cycles. Because day is nested within cycle, the cycle-to-cycle variance uses information from the three nested daily samples in cycles 1, 2, and 3.
Although ICC is an indicator of reliability for continuous measures, it does not measure the extent of exposure misclassification that may occur if exposure is categorized into tertiles of low, medium, and high exposure. To explore categorical exposure misclassification, we performed sensitivity and specificity analyses and surrogate category analyses. In both analyses, tertiles were created using the mean of the nine repeat urine samples for each of the 10 subjects in the variability study. The subject with only six repeat urine samples was not included in these analyses because he did not have complete data. Tertiles based on the 369 single urine samples from subjects in the male reproductive health study produced an unbalanced and unstable design because some of these tertiles contained zero subjects from the variability study. This led to nonidentifiable results for that tertile. Therefore, analyses using tertiles based on the 369 single urine samples are not presented.
In the surrogate category analysis, we calculated actual values for surrogate categories to show the quantitative differences in phthalate metabolite levels that correspond to the relative categories defined by a single urine sample from the 10 variability subjects (Willett 1998). We grouped variability subjects first into tertiles by treating each of the nine repeat urine samples as a single spot urine sample (i.e., the surrogate method). For instance, for each of the nine repeat urine samples, the 10 subjects were categorized into high, medium, or low tertiles. The “true value” for these same subjects based on their 3-month average phthalate metabolite levels (using all the nine replicate samples) was then assigned to the tertiles defined by the single (surrogate) sample. Each of the nine samples was used as the surrogate sample in separate calculations to check for consistency. Each subject’s 10th sample from the male reproductive health study was not used in this analysis because this sample could have been collected up to 12 months earlier.
We also evaluated sensitivity and specificity of a single urine sample as a predictor of high and low tertiles of 3-month average phthalate metabolite levels by comparing the distribution of predicted and observed levels for agreement. For observed or “true” exposure, we calculated 3-month average metabolite levels (using all the nine replicate samples) for each subject and divided the 10 subjects into tertiles. The distribution of 96 individual samples (10 subjects providing nine replicate samples, one subject providing six) was then also divided into tertiles, with each sample representing a predicted value based on a single spot urine sample. For each sample time (days 0–92), agreement between predicted and observed “true” tertile categorization was scored across all subjects, resulting in nine separate contingency tables. All nine tables were then combined into a single table, where overall sensitivity and specificity were calculated (Peck et al. 2003). The same method was used to assess the sensitivity and specificity if two samples, and then additionally if three samples were taken for each subject at least one cycle apart within a 92-day time period. When evaluating the sensitivity of two and three samples, all possible combinations of sample pairings from the nine repeated samples, excluding samples from the same cycle, were used in the analysis. The goal was to simulate and compare the ability of exposure assessments that involve one, two, or three urine samples to predict a subject’s “true” 3-month average exposure tertile classification.
Results
We measured eight phthalate metabolites in urine. However, because > 75% of the samples had nondetectable levels of MCHP, MOP, and MINP, the results for these three metabolites were not informative and were not included in the analyses. MEP was detected in 100% of samples, whereas MBP, MBzP, MEHP, and MMP were detected in > 90% of samples.
Unadjusted and specific-gravity–adjusted median concentrations of MEP, MBP, MBzP, MEHP, and MMP from the 369 men who provided a single urine sample for the environmental agents and male reproductive health study are presented in Table 1. Of these 369 men, 11 also participated in the variability study. Ten of the 11 men provided nine urine samples collected over 92 days, whereas 1 man collected six urine samples over 32 days only. In Figures 1–5, the unadjusted (Figures 1A–5A) and specific-gravity–adjusted (Figures 1B–5B) urinary phthalate metabolite concentrations are plotted by day for each subject (the one subject with only six urine samples was not plotted). Even after dilution adjustment, there was still substantial variability in phthalate metabolite concentrations over time. MEHP concentrations showed large within-subject variability, whereas MEP showed less within-subject variability.
Of the total subject variance among the 369 subjects, the day-to-day variance component ranged from 27.2% (MBP) to 58.1% (MMP), whereas the cycle-to-cycle variances ranged from 1.5% (MBP) to 16.3% (MEP). Cycle-to-cycle variance is the within-subject variance remaining after day-to-day variance is calculated using the replicate samples nested within each of the three cycles. These results suggest that, after accounting for day-to-day variance, there is little additional cycle-to-cycle variance. Therefore, if we were to collect only two urine samples a day apart, we would account for 83.7–98.5%, depending on the phthalate monoester, of the total subject variance, which is composed of between- and within-subject variance. Likewise, if we collected two urine samples 1 month apart we would account for both cycle-to-cycle and day-today variability, or 100% of the within-subject variance.
To determine the predictive ability of a single urine sample to correctly categorize a subject’s exposure into high, medium, or low tertiles, we calculated actual values (mean and geometric mean values) for surrogate categories. The results are presented in Table 3 (only the 10 subjects who provided nine urine samples each were used in this analysis). Overall, the results suggest that a single spot urine sample was predictive of the 3-month average exposure because there were monotonic increasing geometric means across tertiles. For instance, for MBP, when a single sample on day 0 was used to group subjects into low-, medium-, and high-exposure groups, the “true” geometric mean MBP levels increased from 12.7 μg/L in the group designated as low exposure, to 22.8 μg/L in the medium-exposure group, to 28.3 μg/L in the high-exposure group. Although single spot urine samples were generally predictive, there were differences in the predictive ability of a single urine sample for different phthalate mono-esters. A single urine sample was least predictive for MEHP, where only five of the nine spot urine samples produced a monotonic increasing geometric mean. In contrast, eight of the nine spot urine samples produced monotonic increasing geometric means for MBzP, MBP, MEP, and MMP. As expected, MEP, with the widest range in exposure levels, showed the largest difference in geometric means between low-, medium-, and high-exposure categories.
For a more quantitative assessment of how well a single urine sample predicts a subject’s exposure category based on 3-month average metabolite levels, we conducted sensitivity and specificity analyses, using only the results from the 10 subjects who provided nine urine samples each (Table 4). The proportion of men who truly had the highest 3-month average exposure (top 33%) that would be identified as such using single urine samples anytime throughout that 3-month period (i.e., sensitivity) ranged from 0.56 for MEHP to 0.74 for MMP. The proportion of men with truly comparatively low exposure (tertiles 2 and 3) that were classified correctly (i.e., specificity) ranged from 0.83 for MEHP to 0.90 for MMP. Sensitivity analyses for one, two, or three urine samples are presented in Table 4. When two samples were collected 1–3 months apart, there were small increases in sensitivity and specificity, especially evident for MEHP. When three urine samples were collected, each 1–3 months apart, sensitivity moderately increased for MEHP and MMP, with slight increases for the other monoesters. In contrast, when three urine samples were collected on 3 consecutive days, sensitivity for MEHP, MBzP, MBP, and MMP did not increase. However, sensitivity did increase for MEP.
We also performed all analyses described above using unadjusted phthalate levels (data not shown). Overall, variance apportionment and sensitivity analyses were very similar to the specific-gravity–adjusted results shown above. The surrogate exposure category method differed slightly with less consistent dose–response categories found for the unadjusted phthalate metabolite levels.
Discussion
Although the present study found substantial within-subject variability in urinary phthalate metabolite levels, the sensitivity of a single spot urine sample to predict 3-month average phthalate exposure was moderate to high. As expected, because phthalates are rapidly metabolized and do not bioaccumulate, the collection of additional urine samples 1–3 months apart improves the prediction of a subject’s 3-month average exposure. The levels of urinary metabolite levels found in the present study were similar to reference ranges measured in U.S. males for NHANES 1999–2000 (CDC 2003; Silva et al. 2004).
The predictive ability of a single urine sample to determine a subject’s 3-month average exposure varied across phthalates. For MEHP, a single urine sample was least predictive of the tertile categorization and had the lowest sensitivity (Table 4). This implies that in statistical analyses in which only a single urine sample is available to categorize a subject’s 3-month exposure to MEHP, there is likely exposure measure misclassification resulting in bias toward the null hypothesis for exposure–response relationships. MEHP has been associated with developmental reproductive toxicity in laboratory studies (Oishi 1986; Park et al. 2002; Sjoberg et al. 1986). However, in our previously published study, we did not find an association between MEHP and semen parameters among adult men (Duty et al. 2003). In contrast, we did find associations of MBP and MBzP with semen parameters. Although our study differed from the animal studies because we measured adult and not gestational exposure, our findings suggesting that a single urine sample, used to categorize a subject’s exposure, did not adequately measure 3-month average exposure to MEHP. This may partially explain our inability to detect associations between semen parameters with MEHP. To improve upon our exposure classification of MEHP, we are currently collecting two urine samples 1 month apart from all subjects. This will allow us to use measurement error correction methods to adjust for exposure misclassification of phthalate exposure (Carroll et al. 1995).
It is possible the calculated sensitivities and specificities may be slightly overestimated to a small degree because we included predicted values in the calculation of the observed values. Therefore, the errors of predicted and observed values are not totally independent, which can lead to an overestimation of sensitivity and specificity (Willett 1998). Similarly, a portion of the increased sensitivity and specificity observed when taking two or three samples per subject instead of a single sample may be caused partly by the increased dependence between the errors of the predicted and observed values.
Apportioning the sources of variability in urinary phthalate metabolite levels can be used to design more valid and efficient exposure assessments. As expected, the urinary phthalate metabolite concentrations in samples collected close together in time, separated by 1–2 days, were more correlated than those in samples collected farther apart in time, separated by 1–3 months. Two samples collected a month or more apart include variability in urinary phthalate metabolite levels contributed to both by day-to-day changes in exposure and by monthly trends in phthalate exposure, such as seasonal changes in diet, personal product use, or activity patterns, as well as other environmental or biologic factors.
For each health end point of interest in an epidemiologic study, the relevant time window over which exposure is measured needs to be defined. For acute responses after acute exposures, a single urine sample may be adequate to define phthalate exposure. However, we are generally interested in health end points that have exposure windows of months, if not years. To this end, accurate exposure assessment depends on a strategy whereby we accurately measure exposure over these time windows. The simplest approach is to collect multiple urine samples from all subjects over the time interval of interest. However, it is not always feasible to collect multiple urine samples because of both cost constraints and limitations imposed by the subject’s commitments to multiple collections. Based on the results of this phthalate variability study, for male reproductive health end points, we recommend collecting at least two urine samples 1–3 months apart. This will provide an estimate of the within-person variability taking into account both month-to-month and day-to-day variance. Nevertheless, if the study design only permitted collecting two samples 1–2 days apart, this, too, would provide a reasonable estimate of within-subject variance contributed to by day-to-day variance. After collection of the replicate urine samples in either sampling scheme, measurement error models could then be used to adjust for measurement error in exposure (Carroll et al. 1995). A discussion of this is beyond the scope of this report.
In conclusion, although a single urine sample was moderately predictive of 3-month exposure to phthalates, the predictive ability varied across phthalate monoesters. A single urine sample was more predictive for MEP and less predictive for MEHP. The single sample performed well in classifying a subject’s exposure into tertiles, and the amount of nondifferential random exposure misclassification is likely to be moderate or small for most phthalate metabolites of interest. The variance apportionment analysis suggests that two urine samples, the second collected 1–3 months after the first sample, is the minimum number of samples necessary to account for the within subject day-to-day and cycle-to-cycle variability in urinary phthalate metabolite levels. Because the degree of between- and within-subject variance and thus the predictive ability of a single urine sample differ among phthalate metabolites, the most efficient exposure assessment strategy for a particular study depends on the phthalates of interest. The results from the present study will be used in our ongoing environmental agents and male reproductive health study to correct for measurement error in the effect estimates of exposure–response relationships between phthalates and sperm function. The findings from this variability study may also be pertinent to other end points with relevant exposure periods of several months. However, if the study population is not adult men of reproductive age, such as studies involving children or pregnant women, we recommend that a variability study be conducted to determine population-specific exposure assessment strategies.
Correction
The values in Tables 1 and 3 have been rounded from those in the manuscript published online to reflect laboratory sensitivities. In Table 2, for all subjects the SE for ln(MBzP) day is 0.10, and that for percent of total variance ln(MEP) day is 40.9. The errors have been corrected here.
Figure 1 Nine repeated urine samples collected from 10 men over a 3-month period: MEHP. (A) Unadjusted. (B) Specific-gravity adjusted.
Figure 2 Nine repeated urine samples collected from 10 men over a 3-month period: MBzP. (A) Unadjusted. (B) Specific-gravity adjusted.
Figure 3 Nine repeated urine samples collected from 10 men over a 3-month period: MEP. (A) Unadjusted. (B) Specific-gravity adjusted.
Figure 4 Nine repeated urine samples collected from 10 men over a 3-month period: MBP. (A) Unadjusted. (B) Specific-gravity adjusted.
Figure 5 Nine repeated urine samples collected from 10 men over a 3-month period: MMP. (A) Unadjusted. (B) Specific-gravity adjusted.
Table 1 Distribution of phthalate metabolite levels (μg/L) measured in a single spot urine sample from 369 men.
Selected percentiles
Phthalate metabolite Geometric mean 10th 25th 50th 75th 90th 95th
Unadjusted
MEHP 5.7 0.5 1.9 5.2 17.2 63.6 110
MBzP 5.6 1.1 2.4 6.0 13.7 25.3 34.7
MEP 149 22.7 46.1 128 444 1,144 1,879
MBP 13.3 2.9 7.0 13.6 29.3 50.4 73.1
MMP 3.8 0.4 1.7 4.4 9.6 21.5 29.9
Specific-gravity adjusted
MEHP 6.8 0.8 2.4 6.5 19.5 64.5 120
MBzP 6.6 1.8 3.8 7.2 14.0 22.8 36.2
MEP 175 30.7 58.7 153 495 1,145 1,897
MBP 15.8 4.8 9.8 16 29.2 45.9 66.7
MMP 4.5 0.6 2.2 4.9 11.7 22.4 30.4
Table 2 Variance apportionment for specific-gravity–adjusted phthalate levels in urine.
Variability subjects only (N = 11, n = 96)
All subjectsa (N = 369, n = 465)
Variance estimate ± SE Percent of total variance Variance estimate ± SE Percent of total variance
ln(MEHP)
Subjectb 0.49 ± 0.32 27.9 1.57 ± 0.31 54.3
Cyclec 0.30 ± 0.20 17.3 0.33 ± 0.21 11.4
Dayd 0.97 ± 0.17 54.7 0.99 ± 0.18 34.3
ln(MBzP)
Subject 0.47 ± 0.25 42.5 0.80 ± 0.14 55.1
Cycle 0.075 ± 0.086 6.9 0.083 ± 0.09 5.7
Day 0.54 ± 0.096 50.5 0.57 ± 0.10 39.2
ln(MEP)
Subject 1.08 ± 0.59 46.2 0.87 ± 0.19 42.9
Cycle 0.33 ± 0.20 14.5 0.33 ± 0.16 16.3
Day 0.89 ± 0.16 39.3 0.83 ± 0.13 40.9
ln(MBP)
Subject 0.14 ± 0.085 29.0 0.84 ± 0.10 71.3
Cycle 0.025 ± 0.046 5.0 0.018 ± 0.041 1.5
Day 0.33 ± 0.058 66.0 0.32 ± 0.059 27.2
ln(MMP)
Subject 1.11 ± 0.55 51.7 0.51 ± 0.21 27.4
Cycle 0.011 ± 0.12 0.5 0.27 ± 0.25 14.5
Day 1.03 ± 0.18 47.8 1.08 ± 0.19 58.1
Abbreviations: N, number of subjects; n, number of samples.
a Includes 10 variability subjects who provided 10 samples each, 1 subject who provided 7 samples, plus 358 subjects who provided a single sample.
b Between-subject variance.
c Variance between three cycles after accounting for nested day-today variance.
d Variance between 3 consecutive days within a cycle.
Table 3 Values for surrogate exposure categories comparing a single urine sample with 3-month average levels based on nine replicates from 10 men.
Mean (μg/L)
Geometric mean (μg/L)
Surrogate Low Medium High Low Medium High
MEHP
Day 0 19.9 28.9 44.7 9.3 11.5 18.3
Day 1 9.5 55.7 19.4 5.1 26.3 11.0
Day 2 18.8 26.2 49.3 7.1 11.1 25.2
Day 30 5.6 44.9 37.6 4.4 24.3 14.2
Day 31 5.6 43.8 39.0 4.4 20.1 18.4
Day 32 23.6 23.2 48.6 11.2 9.2 20.5
Day 90 10.0 29.7 53.5 5.0 12.7 29.9
Day 91 9.5 30.1 53.5 5.1 14.3 24.8
Day 92 10.2 31.1 51.5 6.1 11.7 27.5
MBzP
Day 0 4.9 11.2 14.3 3.1 7.5 13.2
Day 1 6.6 9.3 15.2 2.9 7.8 13.3
Day 2 7.8 9.2 14.0 4.3 6.0 12.8
Day 30 6.3 11.2 12.8 3.9 8.5 8.9
Day 31 6.6 10.1 14.0 2.9 8.0 12.8
Day 32 7.2 10.1 13.4 3.5 7.5 11.9
Day 90 8.3 11.1 11.0 4.2 7.8 9.2
Day 91 8.0 9.9 12.9 3.7 7.8 10.6
Day 92 7.2 9.9 13.7 3.5 7.8 11.3
MEP
Day 0 73.2 158.4 172 28.9 46.8 94.4
Day 1 26.6 199.6 163 15.8 98.3 64.1
Day 2 30.2 113 276 6.2 70.2 97.8
Day 30 146 92.8 186 24.4 39.7 139
Day 31 26.6 104 291 15.8 53.1 146
Day 32 26.6 182 186 15.8 55.0 139
Day 90 30.2 158 216 16.2 50.2 153
Day 91 33.4 155 216 16.0 50.7 153
Day 92 63.9 132 216 20.3 42.4 153
MBP
Day 0 16.3 30 30.5 12.7 22.8 28.3
Day 1 16.7 24.9 37.3 13.1 21.6 29.3
Day 2 16.7 26.3 35.5 13.1 20.5 31.4
Day 30 18.0 23.4 38.1 13.5 18.6 34.7
Day 31 16.3 27.7 34.0 12.7 22.7 28.5
Day 32 16.7 27.7 33.6 13.1 22.7 27.6
Day 90 26.4 24.4 28.4 19.8 21.6 19.4
Day 91 21.7 22.0 36.3 14.4 18.7 32.3
Day 92 21.3 26.6 30.5 13.9 21.3 28.3
MMP
Day 0 4.2 7.9 30.2 2.0 5.6 23.2
Day 1 4.0 9.4 28.3 2.4 5.2 21.3
Day 2 5.0 7.3 30.2 4.1 3.3 23.2
Day 30 3.9 8.1 30.2 2.1 5.3 23.2
Day 31 4.3 9.2 28.3 2.5 5.0 21.3
Day 32 4.9 11.5 24.8 3.3 5.7 13.7
Day 90 4.2 12.4 24.3 2.0 6.2 19.9
Day 91 4.3 12.3 24.3 2.5 5.3 19.9
Day 92 4.0 12.5 24.3 2.2 5.8 19.9
Only samples from the 10 subjects who provided nine urine samples each were used in this analysis.
Table 4 Sensitivity and specificity for predicting men with the highest 3-month average phthalate levels (top 33%) with one, two, or three urine samples (n = 10 men, 90 samples).
MEHP
MBzP
MEP
MBP
MMP
No. of samples Sensitivity Specificity Sensitivity Specificity Sensitivity Specificity Sensitivity Specificity Sensitivity Specificity
One sample 0.56 0.83 0.63 0.84 0.63 (0.67)a 0.87 (0.86) 0.67 0.87 0.74 0.90
Two samples (at least 1 month apart) 0.63 0.84 0.65 0.85 0.69 (0.78) 0.88 (0.90) 0.65 0.85 0.81 0.92
Three samples (at least 1 month apart) 0.73 0.88 0.69 0.87 0.68 (0.70) 0.88 (0.87) 0.68 0.86 0.90 0.96
Three samples (3 consecutive days) 0.56 0.81 0.67 0.86 0.78 (0.67) 0.90 (0.90) 0.67 0.86 0.78 0.90
Only samples from the 10 subjects who provided nine urine samples each were used in this analysis.
a Values in parentheses are sensitivity and specificity using geometric mean ranks instead of arithmetic mean ranks for observed tertile classification; for the other four phthalates these values were identical.
==== Refs
References
ATSDR 1995. Toxicological Profile for Diethyl Phthalate (DEP). Atlanta, GA:Agency for Toxic Substances and Disease Registry. Available: http://www.atsdr.cdc.gov/toxprofiles/tp73.html [accessed 28 January 2004].
ATSDR 2001. Toxicological Profile for Di-n-butyl Phthalate (DBP). Atlanta, GA:Agency for Toxic Substances and Disease Registry. Available: http://www.atsdr.cdc.gov/toxprofiles/tp135.html [accessed 28 January 2004].
ATSDR 2002. Toxicological Profile for Di(2-ethylhexyl)phthalate (DEHP). Atlanta, GA:Agency for Toxic Substances and Disease Registry. Available: http://www.atsdr.cdc.gov/toxprofiles/tp9.html [accessed 28 January 2004].
Blount BC Milgram KE Silva MJ Malek NA Reidy JA Needham LL 2000 Quantitative detection of eight phthalate metabolites in human urine using HPLC-APCI-MS/MS Anal Chem 72 4127 4134 10994974
Boeniger MF Lowry LK Rosenberg J 1993 Interpretation of urine results used to assess chemical exposure with emphasis on creatinine adjustments: a review Am Ind Hyg Assoc J 54 615 627 8237794
Box GE Hunter WG Hunter JS 1978. Statistics for Experimenters. New York:John Wiley & Sons.
Bradbury J 1996 UK panics over phthalates in babymilk formulae Lancet 347 1541 8684110
Carroll RJ Ruppert D Stefanski LA 1995. Measurement Error in Nonlinear Models. New York:CRC Press.
Castle L Jickells SM Gilbert J Harrison N 1990 Migration testing of plastics and microwave-active materials for high-temperature food-use applications Food Addit Contam 7 779 796 2150378
CDC 2003. Second National Report on Human Exposure to Environmental Chemicals. Atlanta, GA:Centers for Disease Control and Prevention. Available: http://www.cdc.gov/exposurereport/2nd/report_results.htm [accessed 15 March 2003].
Duty SM Silva MJ Barr DB Brock JW Ryan L Chen Z 2003 The relationship between environmental exposure to phthalates and human semen parameters Epidemiology 14 269 277 12859026
Hauser R Chen Z Pothier L Ryan L Altshul L 2003 The relationship between human semen parameters and environmental exposure to polychlorinated biphenyls and p,p ′-DDE Environ Health Perspect 111 1505 1511 12948891
Hoppin JA Brock JW Davis BJ Baird DD 2002 Reproducibility of urinary phthalate metabolites in first morning urine samples Environ Health Perspect 110 515 518 12003755
Jaakkoala JJ Oie L Nafstad P Botten G Samuelsen SO Magnus P 1999 Interior surface materials in the home and the development of bronchial obstruction in young children in Oslo, Norway Am J Public Health 2 188 191
Koo J-W Parham F Kohn MC Masten SA Brock JW Needham LL 2002 The association between biomarker-based exposure estimates for phthalates and demographic factors in a human reference population Environ Health Perspect 110 405 410 11940459
Li L-H Jester WF Orth JM 1998 Effects of relatively low levels of mono-(2-ethylhexyl) phthalate on cocultured Sertoli cells and gonocytes from neonatal rats Toxicol Appl Pharmacol 153 258 265 9878596
Nassberger L Arbin A Ostelius J 1987 Exposure of patients to phthalates from polyvinyl chloride tubes and bags during dialysis Nephron 45 286 290 3587468
Oishi S 1986 Testicular atrophy induced by di(2-ethylhexyl)phthalate: changes in histology, cell specific enzymes and zinc concentrations in rat testis Arch Toxicol 59 4 290 295 2881530
Page BD Lacroix GM 1995 The occurrence of phthalate esters and di-2-ethylhexyl adipate plasticizers in a Canadian packaging and food samples in 1985–1989: a survey Food Addit Contam 12 129 151 7758627
Park JD Habeebu SSM Klaassen CD 2002 Testicular toxicity of di-(2-ethylhexyl)phthalate in young Sprague-Dawley rats Toxicology 171 105 115 11836017
Peck CC Albro PW 1982 Toxic potential for the plasticizer di(2-ethylhexyl) phthalate in the context of its disposition and metabolism in primates and man Environ Health Perspect 45 11 17 7140682
Peck JD Hulka BS Savitz DA Baird D Poole C Richardson BE 2003 Accuracy of fetal growth indicators as surrogate measures of steroid hormone levels during pregnancy Am J Epidemiol 157 258 266 12543626
Rosner B 1999. Fundamentals of Biostatistics. Pacific Grove, CA:Duxbury Press.
Rosner BD Spiegelman D Willett WC 1992 Correction of logistic regression relative risk estimates and confidence intervals for random within-person measurement error Am J Epidemiol 136 11 1400 1413 1488967
Rudel RA Camann DE Spengler JD Korn LR Brody JG 2003 Phthalates, alkylphenols, pesticides, polybrominated diphenyl ethers, and other endocrine-disrupting compounds in indoor air and dust Environ Sci Technol 37 20 4543 4553 14594359
Silva MJ Barr DB Reidy JA Malek NA Hodge CC Caudill SP 2004 Urinary levels of seven phthalate metabolites in the U.S. population from the National Health and Nutrition Examination Survey (NHANES) 1999–2000 Environ Health Perspect 112 331 338 14998749
Silva MJ Malek NA Hodge CC Reidy JA Kato K Barr DB 2003 Improved quantitative detection of 11 urinary phthalate metabolites in humans using liquid chromatography-atmospheric pressure chemical ionization tandem mass spectrometry J Chromatog B 789 393 404
Sjoberg P Lindquist NG Ploen L 1986 Age-dependent response of the rat testis to di-2-(ethylhexyl) phthalate Environ Health Perspect 65 237 242 3709447
Teass AW Biagini RE DeBord G Hull RD 1998. Application of biological monitoring methods. In: NIOSH Manual of Analytical Method (Eller PM, ed). Cincinnati, OH:National Institute for Occupational Safety and Health, Division of Physical Sciences and Engineering, 52–62.
Tremaine LM Quebbemann AJ 1985 The renal handling of terephthalic acid Toxicol Appl Pharmacol 77 165 174 3966238
Willett W 1998. Nutritional Epidemiology. New York:Oxford University Press.
|
15579421
|
PMC1253667
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec 16; 112(17):1734-1740
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7212
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science 10.1289/ehp.7306ehp0112-00174115579422Environmental MedicineReviewEpidemiology of Health Effects of Radiofrequency Exposure ICNIRP (International Commission for Non-Ionizing Radiation Protection) Standing Committee on Epidemiology: Ahlbom Anders 12Green Adele 3Kheifets Leeka 4Savitz David 5Swerdlow Anthony 61Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden2Stockholm Center for Public Health, Stockholm, Sweden3Epidemiology and Public Health Unit, Queensland Institute of Medical Research, Brisbane, Australia4Department of Epidemiology, School of Public Health, University of California at Los Angeles, Los Angeles, California, USA5Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA6Section of Epidemiology, Institute of Cancer Research, Sutton, Surrey, United KingdomAddress correspondence to A. Ahlbom, Institute of Environmental Medicine, Karolinska Institutet, Box 210, 171 77 Stockholm, Sweden. Telephone: 46-8-5248-74-70. Fax: 4-8-31-39-61. E-mail:
[email protected] thank R. Neale for help with an initial draft, M. Feychting for comments, and M. Bittar for secretarial assistance. We also thank P. Vecchia for invaluable advice and P. Buffler for participation in planning of the work.
This work was supported by the ICNIRP.
The authors declare they have no competing financial interests.
12 2004 23 9 2004 112 17 1741 1754 1 6 2004 23 9 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. We have undertaken a comprehensive review of epidemiologic studies about the effects of radiofrequency fields (RFs) on human health in order to summarize the current state of knowledge, explain the methodologic issues that are involved, and aid in the planning of future studies. There have been a large number of occupational studies over several decades, particularly on cancer, cardiovascular disease, adverse reproductive outcome, and cataract, in relation to RF exposure. More recently, there have been studies of residential exposure, mainly from radio and television transmitters, and especially focusing on leukemia. There have also been studies of mobile telephone users, particularly on brain tumors and less often on other cancers and on symptoms. Results of these studies to date give no consistent or convincing evidence of a causal relation between RF exposure and any adverse health effect. On the other hand, the studies have too many deficiencies to rule out an association. A key concern across all studies is the quality of assessment of RF exposure. Despite the ubiquity of new technologies using RFs, little is known about population exposure from RF sources and even less about the relative importance of different sources. Other cautions are that mobile phone studies to date have been able to address only relatively short lag periods, that almost no data are available on the consequences of childhood exposure, and that published data largely concentrate on a small number of outcomes, especially brain tumor and leukemia.
electromagnetic fieldsEMFepidemiologyhealth effectsradiofrequencyRF
==== Body
The advent of mobile telephones, now used by about 1.6 billion people worldwide, has been accompanied by an upsurge in public and media concern about the possible hazards of this new technology, and specifically of radiofrequency field (RF) exposure. Although some epidemiologic research was conducted several decades ago on RFs in occupational settings, in general the effects of RFs in humans are an emerging area of investigation, and most studies are recent or not yet published. Furthermore, although the results of studies of mobile phone risks have received widespread public attention, their interpretation is not straightforward because of methodologic difficulties. In particular, because RFs are invisible and imperceptible, individuals cannot directly report on their exposure, and therefore the quality of exposure assessment needs particularly careful consideration when interpreting epidemiologic studies. In order to summarize the current state of knowledge, to explain the methodologic issues that need to be considered when assessing studies, and to aid in planning future studies, we have undertaken a broad review of epidemiologic knowledge about the effects of RFs on human health. We have divided the literature, for this purpose, into studies of RF exposure from occupational sources, from transmitters, and from mobile phones.
In this review we cover the possible effects of long-term exposure to RFs—defined as 100 kHz to 300 GHz—on the risk of diseases, for instance, cancer, heart disease, and adverse outcomes of pregnancy. We have not reviewed the health consequences of communications technology that are indirect or unlikely to be due to radiation. In particular, RFs can interfere with implanted medical devices, such as cardiac pacemakers, but the effects on health are a consequence of this interference, rather than a direct effect on the body; phone conversations by drivers of moving vehicles appear to raise the risk of motor vehicle accidents, but this is probably related to distraction rather than to RF exposure. Although anxieties and psychosomatic illnesses might be caused by knowledge of the presence of phones or phone masts, again, this would not be an effect of RFs and is not discussed.
As well as epidemiologic studies of disease causation, some studies have been published that use an epidemiologic design to investigate whether mobile phones can affect acute symptoms, such as headaches. For completeness, we have included these in this review, although such investigations are usually better conducted by laboratory volunteer experiments rather than by observational epidemiology, given the high degree of susceptibility to biased reporting in response to concerns.
Because this is primarily an epidemiologic review, we have not detailed the physics and dosimetry of RFs from different sources, which are described elsewhere [Hitchcock and Patterson 1995; Independent Expert Group on Mobile Phones (IEGMP) 2000; Mantiply et al. 1997]. However, because understanding of mobile-phone–related epidemiology is critically dependent on understanding of mobile phone technology, we have included some information explaining this technology. We have also included, because of its importance to future research advance, some comments on the interface between physics and epidemiology, and the gaps to be bridged between these disciplines if more rigorous investigation of potential RF effects is to be achieved.
Exposure
Sources of Exposure
Communications sources have increased greatly in recent years, and there is continuing change in the frequencies used and variety of applications. The first mobile phone systems were analog and used 450 and 900 MHz. Digital systems, operating at somewhat higher frequencies (1,800–1,900 MHz) and using different modulation techniques, became prevalent in the early 1990s. Currently, the third-generation systems using the Universal Mobile Telecommunication System are being introduced, which will operate in the 1,900–2,200 MHz frequency range. Occupational RF exposures occur to workers engaged in a number of industrial processes, particularly when using dielectric heaters for wood lamination and the sealing of plastics and industrial induction heaters. Relatively high levels of exposure to RFs can occur to workers in the broadcasting, transport, and communications industries and in the military, when they work in close proximity to RF transmitting antennas and radar systems. Medical exposures can come from medical diathermy equipment to treat pain and inflammation, electrosurgical devices for cutting tissues, and diagnostic equipment such as magnetic resonance imaging.
Distribution of Exposure in the Population
Despite the rapid growth of new technologies using RFs, little is known about population exposure from these and other RF sources and even less about the relative importance of different sources. In a typical house, non-occupational exposure could come from external sources, such as radio, television (TV), and mobile-phone base stations, as well as internal sources, such as a faulty microwave oven, in-house bases for cordless phones, or use of mobile phones.
Radio and TV transmitters have a large coverage area and therefore operate at relatively high power levels up to about 1 MW (Dahme 1999). Although these transmitters could generate fairly high fields at ground level, most are not located in heavily populated areas and do not lead to high exposure of the population.
Mobile-phone base stations are low-powered radio transmitters that communicate with users’ handsets. In early 2000, there were about 20,000 base stations in the United Kingdom and about 82,000 in the United States. Base stations can transmit power levels of ≥ 100 W (Schüz and Mann 2000). It is expected that the number of base stations will roughly double to accommodate new technology and a larger percentage of sites will have to be shared between operators, complicating exposure assessment. The power density levels inside a building can be from 1 to 100 times lower than outside, depending on the type of building construction (Schüz and Mann 2000). In addition, exposure can vary substantially within the building. For example, exposure was found to be about twice as high (and more variable) in the upper compared with the lower floors of a building (Anglesio et al. 2001). Driven by a typical pattern of use, the exposure from base stations shows a distinct diurnal pattern, characterized by lowest values during the night and by two maxima during the day, the first from 1000 hr to 1300 hr and the second from 1800 hr to 2200 hr (Silvi et al. 2001). There have been few and limited efforts to characterize population exposures; all of them have been small (usually areas around 10–20 base stations) (Anglesio et al. 2001; COST281 2001; Schüz and Mann 2000). The total power density from the base stations was slightly higher than, but comparable with, the background power density from all other RF sources combined.
Mobile phones operate at a typical power of 0.25 W. Analog systems operated at higher power levels than the newer digital systems. Similarly, older cordless phones operated to the analog standard, whereas modern ones operate to the digital with a transmitted power of a base around 0.09 W in a home but higher in a business setting. The actual exposure of the user depends on a number of factors such as characteristics of the phone, particularly the type and location of the antenna; the way the phone is handled; and most important, the adaptive power control, which may reduce the emitted power by orders of magnitude (up to a factor of 1,000). Factors that influence adaptive power control include distance from the base station, the frequency of handovers, and RF traffic conditions. Thus, the emitted power is higher in rural than in urban areas and when the user is moving (e.g., in a car). In areas where there is a great deal of phone use, phones may operate more than half of the time at the highest power levels. To compensate for the shielding effect of materials, power levels of phones are, on average, higher when a phone is used indoors than outdoors. RF absorption is maximal on the side of the head to which the phone is held, greatest close to the antenna, and decreases to less than one-tenth on the opposite side of the head (Dimbylow and Mann 1999).
In an occupational setting, higher exposures occur, albeit infrequently; for example, radar exposed workers in the U.S. Navy had potential for exposures > 100 mW/cm2 (Groves et al. 2002).
Epidemiologic Considerations in Exposure Assessment
General.
In the absence of information on what biologic mechanism is relevant, it is unclear what aspect of exposure needs to be captured in epidemiologic studies. Because heating is the only known effect of RFs, most research has assumed that the metric of choice must be a function of the specific absorption rate (SAR). Metrics used in epidemiologic studies of other agents, such as cumulative exposure, average exposure over specific time intervals, and peak exposure, need to be considered. Given the uncertainty about the relevant interaction mechanism, the dose needs to be assessed not just as external field intensity but also as SAR for specific anatomical sites. Integrating exposure over time is further complicated by the fact that sources vary markedly over very brief time periods relative to the time periods of interest.
Epidemiologic studies thus far have relied on rather crude proxies for exposure, such as job title, proximity to a base station, or use of a mobile phone. Refinement of exposure assessment is critical to improved epidemiology. This requires a bridge between the rather disparate worlds of epidemiology and physics. Although it is of interest to know about sources of variation or uncertainty in general, the critical need in epidemiologic studies is to identify those variables that are most important in determining exposure levels and most amenable to capture within populations.
A key element in linking the complexity of the exposure sources and patterns with the needs of epidemiology is a meter that is capable of monitoring individual exposure. Such meters have now been developed [National Radiation Protection Board (NRPB) 2003].
Ideally, the dose, time pattern, and frequencies (wavelengths) of exposure from all key sources should be estimated for each individual in the study. Dose– and duration–response analyses are important to assessment of etiology but have often been absent in the existing literature (Swerdlow 1999). In addition, the possible lag period between exposure and disease manifestation needs to be considered. Handheld mobile phones were not used regularly until the 1990s. Thus, studies published to date have had little power to detect possible effects involving long induction periods or effects from long-term heavy exposure to mobile phones or base stations.
Methodologically, it would be desirable to conduct studies to clarify the relative contributions of different spheres of life. Such knowledge would allow epidemiologists to design studies that incorporate all important sources of RF exposure, or at least determine how much it matters that the occupational studies to date have taken no account of residential or mobile phone exposures and vice versa.
Occupational exposures.
Most occupational epidemiologic studies have based their exposure assessments simply on job titles and have included no measurements (Tables 1–4). It is possible that some jobs (e.g., radar operator) are adequate indicators of RF exposure. However, many job titles that have been previously considered to indicate exposure may provide a poor proxy for RF exposure.
In addition to improving exposure assessment in individual studies, there is the potential to develop job–exposure matrices, with the rows corresponding to relatively homogeneous groups with respect to RF exposure, defined by job title, perhaps specific work location, calendar time, and other recordable work history, and the columns corresponding to RF exposure metrics.
Transmitter exposures.
All published epidemiologic studies of transmitter exposures have based exposure assessment on distance from the transmitter. The relation between exposure and distance from the antenna is usually very complex, especially in urban areas. Close to the antenna, the field is very low because of the directional antenna characteristics. As one moves away, the field pattern can be complicated, with peaks and valleys in field intensity with increasing distance from the antenna.
Estimation of community exposure to RFs from transmitters may, however, be amenable to refinement. Geographic information systems allow for precise assignment of residence, topography, and some other likely determinants of exposure. Historical information on power output from the transmitters may well be available. This information combined with personal measurements may provide refined measures of exposure that can be applied retrospectively, with empirical validation.
Mobile phones exposures.
Studies on mobile phones have used the simple dichotomy of user versus nonuser, with some incorporating information on years of use, number of phone calls per day, and duration of calls. Some studies have separated analog and digital phone use. Few have included use of cordless phones, which also generate RFs but from which exposure pattern is different.
Ongoing studies are attempting to incorporate information on intensity of use, place of use, position of the telephone, type of telephone, and calendar period of use. Each of these extensions need to be evaluated, however, to determine a) whether they are truly an important determinant of exposure and b) whether they are amenable to accurate historical reconstruction through recall or some type of written record. There is little benefit in knowing that the intensity of exposure varies by a parameter that cannot be captured, or gathering relatively precise information about, say, model of mobile phone, if no useful exposure variable can be derived from it.
Mechanisms
Heating of cells and tissues from RF exposure might have benign or adverse biologic effects. These effects, which reflect an imbalance in the amount of heat built up in the body and the effectiveness of mechanisms to remove it, can be due to either elevated temperatures or increased physiologic strain from attempts to remove the heat. Of particular concern for whole-body heating are effects in the elderly, people taking certain kinds of drugs, and the fetus and infant. Cardiovascular mortality, birth defects, and impaired ability to perform complex tasks are among the outcomes that have been associated with whole-body heating. The sensitivity of different tissues and cells to thermal damage from both localized and whole-body heating varies. The central nervous system, testis, and lens of the eye seem to be particularly sensitive, the last due to a limited capacity to dissipate heat rather than a greater sensitivity of its cells to heat-induced damage.
Laboratory studies suggest that adverse biologic effects can be caused by temperature rises in tissue that exceed 1°C above their normal temperatures (Goldstein et al. 2003). In addition to the absolute increase in temperature, duration of heating and thermoregulatory capacity of the body are important determinants of the harmful levels of tissue heating. High rates of physical activity and warm and humid environments will reduce tolerance to the additional heat loads.
There has been concern about possible carcinogenic effects of RFs below levels that cause detectably harmful heating. RFs are not sufficiently energetic to destabilize electron configurations within DNA molecules. Thus, there is no direct link between RF exposure and genotoxic effects such as DNA mutations, DNA strand breaks, or other genetic lesions. Experimental evidence from animal and laboratory studies at the cellular level confirms the lack of genotoxic effect of RFs (Krewski et al. 2001; Moulder et al. 1999). Similarly, an investigation in rodents did not find support for the suggestion that growth of tumors induced by other agents may be promoted by RFs from mobile phone signals (Imaida et al. 2001; Mason et al. 2001).
Repacholi et al. (1997) evaluated the effects of RFs on tumorigenesis in a moderately lymphoma-prone Eμ-Pim1 oncogenetransgenic mouse line. Exposure was associated with a statistically significant 2.4-fold increase in the risk of developing lymphoma. Utteridge et al. (2002) recently repeated this study with a larger number of mice and with several refinements in the experimental design and did not demonstrate any difference in the incidence or type of lymphomas that developed between control and treated groups. Questions have been raised about the conduct and reporting of both studies and the inconsistency has not been resolved (Goldstein et al. 2003). Additionally, extrapolating the transgenic model to humans remains controversial.
Outcomes
A particular public concern appears to be that the use of handheld mobile phones may be linked to the occurrence of malignant disease, especially brain cancer and, to a lesser extent, leukemia. Other tumors such as acoustic neuroma that occur in the head and neck region have also been investigated. Each of these conditions is rare. The incidence of malignant tumors of the brain in the general population is around 10–15 per 100,000 each year (Behin et al. 2003); the annual incidence of benign extracerebral tumors such as meningiomas is about 3 per 100,000, and benign tumors of the cranial nerves, such as acoustic neuromas, are rarer still. Because tumor incidence is so low, investigators have so far relied on case–control studies or, in a few instances, retrospective cohort studies. In addition, different tumor subtypes are likely to have different causes, as evidenced among brain tumors by the different molecular pathways leading to malignant astrocytomas on the one hand and benign meningiomas and acoustic neuromas on the other (Inskip et al. 1995). Similarly, there are a variety of types of leukemia, each probably with differences in causation, making it even more difficult to ascertain sufficient numbers of homogeneous tumors for study. Epidemiologic assessments have been further complicated because the environmental risk factors for malignant and benign brain tumors (Inskip et al. 1995), and hence potential confounders, are largely unknown beyond high-dose ionizing radiation. For leukemia (Petridou and Trichopoulos 2002), knowledge of potential confounders is greater but still limited. Other risk factors, besides ionizing radiation, include exposure to chemotherapy, cigarette smoking, and benzene, as well as constitutional chromosomal abnormalities among children in particular.
Available evidence suggests that induction of brain tumors occurs over decades after tumorigenic exposures early in life. Latency of tumors varies from months to years depending on how aggressive tumor growth is and the location of the tumor. Epidemiologic studies should therefore in principle allow for a lead time between potentially causal exposure and disease, although in the absence of biologic or epidemiologic evidence it is unclear what length this should be for potential RF effects.
Other chronic diseases such as cardiovascular disease, as well as symptoms, both acute and chronic, have been studied in relation to RF exposure. Headaches and other cranial discomforts including sensations of local warmth or heating, dizziness, visual disturbances, fatigue, and sleeplessness are the main symptoms reported by users of mobile phones. All of these are common symptoms in humans.
Review of Studies on Occupational Exposure
Cancer
Information on cancer risks in relation to occupational RF exposure comes largely from three types of epidemiologic study: cohort studies, investigating a wide range of cancer (and non-cancer) outcomes in groups with potential RF exposure (Tables 1 and 2); case–control studies of specific cancer sites, investigating occupational RFs as well as other exposures (Table 3); and analyses of routinely collected data sets on cancer incidence or mortality, in which risks of cancer have been assessed in relation to job title (Table 4). The most extensive literature addresses brain tumors and leukemia.
Considering study size, design, and likely quality of RF assessment, the most informative studies (Groves et al. 2002; Milham 1988; Morgan et al. 2000) provide little evidence of an association with either brain tumors or leukemia. The one possible exception was an increased risk of nonlymphocytic leukemia in radar-exposed navy veterans (Groves et al. 2002) restricted to only one of three highly exposed occupations (aviation electronics technicians), but this finding was divergent from that of an earlier study of U.S. naval personnel (Garland et al. 1990). Two U.S. case–control studies of brain tumor etiology have shown elevated odds ratios (ORs) of around 1.5 in relation to jobs believed to have RF exposure. However, the study by Thomas et al. (1987) was based on interviews with relatives of dead cases and hence was unable to identify exposure with much certainty. The other study (Grayson 1996) assessed exposures by a job–exposure matrix based on historical reports of incidents of exposure above permissible limits (10 mW/cm2). No clear or consistent trend was found in risk of brain tumor in relation to exposure score. A widely cited study of U.S. embassy staff in Moscow and their dependents with possible RF exposure was only published as a précis by a third party (Goldsmith 1995); this leaves the study methods unclear, but few brain tumors or leukemia occurred, and half were in dependents who lived outside the embassy.
A key concern across all these studies is the quality of assessment of RF exposure, including the question of whether it was truly present at all and, if so, for what proportion of the cohort. Although the published studies do not give consistent evidence for an increased leukemia or brain cancer risk, they cannot be counted as substantial evidence against a possible association. Most of the studies suffer from severe imprecision, with the cancers of greatest interest rarely found in cohort studies of modest size and the exposure of interest rarely found in geographically based case–control studies. The cohort studies generally lack data on other relevant exposures, including non-radio frequencies of radiation, as well as on RF exposures outside the workplace (e.g., mobile phones). The studies based on routine data are vulnerable to publication bias given the many data sets worldwide that could be used to address this issue. Several of these studies did not follow workers after they left the job of interest (Garland et al. 1990; Grayson 1996; Szmigielski 1996), with the potential for bias if individuals left employment because of health problems that later turned out to be due to cancer; this might especially be a problem for some types of brain tumor, which can be present for long periods before diagnosis. In addition, several studies have had substantial methodologic inadequacies—for instance, one study that found apparently increased risks for many different cancers used more sources of exposure information for cancer cases than for noncancer subjects and was analyzed improperly (Szmigielski et al. 2001).
Breast cancer.
Several studies have investigated the risk of breast cancer in relation to RF exposure. A cohort study of radio and telegraph operators in Norwegian merchant ships by Tynes et al. (1996) found a relative risk (RR) of breast cancer of 1.5 [95% confidence interval (CI), 1.1–2.0), based on 50 cases in women working in this occupation, and stronger for women ≥ 50 years of age [2.6 (95% CI, 1.3–5.5)]. An elevated RR found also for endometrial cancer suggests that reproductive and hormonal factors (for which full adjustment could not be made), not RFs, may have been responsible for the increased breast cancer risk. A large case–control study based on job titles from death certificates in the United States found no trend in risk of breast cancer in relation to probability or to level of occupational RF exposure (Cantor et al. 1995). A case–control study in the United States of men with breast cancer found an OR of 2.9 (95% CI, 0.8–10) in radio and communication workers (Demers et al. 1991), based on seven cases in exposed men, and with a low response rate in controls. A study of U.S. embassy personnel with potential RF exposure found two breast cancers, with 0.5 expected (Goldsmith 1995). Other studies of male (Groves et al. 2002) and female (Lagorio et al. 1997; Morgan et al. 2000) breast cancers, with few cases, did not report increased risks. The available data are insufficient to reach any conclusion on whether RF exposure is related to breast cancer risk, but the results of Tynes et al. (1996) do support continued evaluation of the possibility.
Testicular cancer.
Testicular cancer was considered in a U.S. case–control study (Hayes et al. 1990). A significantly increased risk was found for self-reported occupational exposure to microwave and other radio waves (OR = 3.1) but not for self-reported radar exposure or for radar or other microwave exposure assessed by an occupational hygienist based on job history. A cluster of testicular cancer (observed/expected ratio = 6.9) was reported in six police officers in Washington State (USA), who routinely used handheld traffic radar guns (Davis and Mostofi 1993). In a large U.S. Navy cohort with radar exposure, testicular cancer mortality was lower than expected [standardized mortality ratio (SMR) = 0.6 (95% CI, 0.2–1.4) in the group with potential for high exposure (Groves et al. 2002).
Ocular melanoma.
Ocular melanoma was associated with self-reported exposure to microwaves (excluding domestic microwave ovens) or radar [OR = 2.1 (95% CI, 1.1–4.0)] in a case–control study (Holly et al. 1996). Stang et al. (2001) found an increased risk of ocular melanoma in subjects with self-reported occupational exposure for at least 6 months and several hours per day to RFs (14% of cases, 10% of controls) and for occupational exposure several hours per day to radio sets [OR = 3.3 (95% CI, 1.2–9.2)]. There was no relation of risk to duration of this exposure, however, and risk was not increased for radar exposure [OR = 0.4 (95% CI, 0.0–2.6)]. The study was small and combined subjects from two different study designs.
Lung cancer.
A nested case–control study of electrical utility workers in Quebec (Canada) and France thought to be exposed to pulsed electromagnetic fields found a significant excess of lung cancer (Armstrong et al. 1994) and a dose–response gradient with increasing cumulative exposure. Adjustment for crude indicators of smoking and other factors left the results little changed. In an attempt to address a similar exposure in a cohort of U.S. electric utility workers, limited because of the ill-defined agent addressed in the original study, no increased risk of lung cancer was found (Savitz et al. 1997). No other studies of RFs have reported associations with lung cancer (Groves et al. 2002; Lagorio et al. 1997; Milham 1985, 1988; Morgan et al. 2000; Muhm 1992; Szmigielski 1996; Szmigielski et al. 2001; Tynes et al. 1996).
In conclusion, there is no cancer site for which there is consistent evidence, or even an individual study providing strong evidence, that occupational exposure to RFs affects risk. The quality of information on exposure has generally been poor, however, and it is not clear that the heterogeneous exposures studied should be combined in etiologic studies. This, combined with imprecision and methodologic limitations, leave unresolved the possibility of an association between occupational RFs and cancer.
Other Outcomes
Adverse reproductive outcomes.
A wide range of potential reproductive consequences of RF exposure have been investigated (Table 5), with a focus on exposures of physiotherapists to therapeutic short wave diathermy (typically 27.12 MHz). Depending on the type of equipment used and the location of the operator in relation to the equipment, substantial peak exposures can occur (Larsen and Skotte 1991). Many of the studies analyzed levels of exposure, on the basis of duration of work and type of equipment used (shortwaves or microwaves).
There are isolated suggestions of an association between RF exposure and delayed conception (Larsen et al. 1991), spontaneous abortion (Ouellet-Hellstrom and Stewart 1993; Taskinen et al. 1990), stillbirth (Larsen et al. 1991), preterm birth after exposure of fathers (Larsen et al. 1991), birth defects in aggregate (Larsen 1991), and increased male-to-female sex ratio (Larsen et al. 1991). Almost always, however, either the finding was not corroborated in other studies of comparable quality, or there are no other studies available. The evidence is strongest for spontaneous abortion (based on two independent studies with some support). Potential confounding by other aspects of work activity (e.g., physical exertion) needs to be considered, however.
Semen parameters have been examined among men with varying forms of military exposure to microwaves and radar (Table 5). Three of these studies found reductions in sperm density (Hjollund et al. 1997; Lancranjan et al. 1975; Weyandt et al. 1996), with variable results for other semen parameters. Several of these reports were based purely on volunteers, with no attempt to sample from a defined population (Lancranjan et al. 1975; Schrader et al. 1998; Weyandt et al. 1996), and those that did provide information about response proportions (Grajewski et al. 2000; Hjollund et al. 1997) had substantial nonresponse. However, given the well-known susceptibility of spermatogenesis to even subtle heating, the possibility of reduced fertility in exposed men is reasonable to evaluate.
Overall, problems of exposure assessment temper any conclusions regarding reproductive outcomes, and no adverse effects of RFs have been substantiated.
Cardiovascular disease.
Several methodologically weak studies from the Soviet Union addressed microwave exposure and acute effects on cardiovascular physiology (e.g., hypotension, bradycardia, tachycardia) as part of a set of ill-defined conditions (Jauchem 1997). Additional studies of considered symptoms among a range of potentially exposed groups including radar workers, pilots, radio broadcasting workers, and electronics industry workers. The variability in research methods, exposure characteristics, and outcome measures makes it difficult to draw conclusions: there are sporadic reports of symptoms among some groups of workers, but no obvious pattern is present.
Major clinical outcomes have been examined less frequently. In a mail survey of U.S. physical therapists (Hamburger et al. 1983) men more highly exposed to microwave and shortwave radiation, based on indices including length of employment and frequency of treatments, tended to report a significantly greater prevalence of heart disease, with ORs of 2–3. Selective response to this survey must be considered among possible explanations for the associations that were observed. In U.S. Navy veterans potentially exposed to radar (Groves et al. 2002) and in a cohort of nearly 200,000 Motorola workers (Morgan et al. 2000), heart disease SMRs were well below 1.0, and analyses of mortality (Groves et al. 2002), hospital admissions, and disability compensation (Robinette et al. 1980) did not support greater risk with greater potential exposure. Other cohort studies reporting cardiovascular mortality have had small numbers (Lagorio et al. 1997; Muhm 1992).
Overall, the literature on RFs and cardiovascular symptoms and disease provides little suggestion of an association but is at too rudimentary a level to draw firm conclusions.
Cataracts.
Laboratory research indicates that the lens of the eye is highly sensitive to heat, and damage can occur from even a single acute exposure. Hence, there is a potential mechanism for RFs to lead to increased cataract incidence. Epidemiologic research has been limited, however, especially with regard to exposure assessment.
Based on hospital records of U.S. military veterans (Cleary et al. 1965), men with cataracts were no more likely than men with other medical conditions to have been radar workers (OR = 0.67, p > 0.10). Age was adjusted using broad groupings, with little change to the result.
In two studies in the U.S. military, ocular examinations were conducted on microwave-exposed and unexposed workers, without knowledge of exposure status by the examiner. In one (Cleary and Pasternack 1966) a tendency toward increased minor lens changes was found among exposed workers, characterized as the equivalent of 5 years of advanced aging in the exposed compared with unexposed workers around 60 years of age. In the other (Shacklett et al. 1975), prevalence of lens opacities was similar in exposed and unexposed individuals matched on age.
In an Australian study of workers who built and maintained radio and TV transmitters, compared with unexposed workers from the same geographic regions (Hollows and Douglas 1984), posterior subcapsular opacities were in excess in exposed workers (borderline significant), but nuclear sclerosis prevalence was similar in exposed and unexposed workers. It was not specified whether evaluators were aware of exposure history. Exposures were estimated to be from 0.08 to 3,956 mW/cm2, with brief, intense exposures thought to be quite common.
The study designs above are limited with respect to exposure assessment and selection of unexposed workers. Solar radiation exposure, a known risk factor for cataracts, was not considered and could have differed between RF-exposed and unexposed workers. Not all of the opacities were of direct clinical importance, but they would be pertinent to a pathway that could lead to cataract later in life. The plausibility of a causal relation supports more extensive investigation.
Review of Studies on Environmental Exposure from Transmitters
The primary concern with transmitters has been with cancer risk among populations who live in proximity to transmitters, including those that are used for transmitting radio, television, microwave, and cellular telephone communications. There is a long history of public concern and resistance to the siting of such antennas, for reasons involving aesthetics and property values, as well as health concerns. Much of the research has been conducted in response to such concerns, either based solely on the exposure source or based on a perceived cancer cluster among persons living in the vicinity.
The studies of which we are aware are listed in Table 6, together with some fundamental characteristics and major findings.
The first study (Selvin et al. 1992) in San Francisco, California (USA) was focused on statistical analysis of spatial data and the results are not reported according to standard epidemiologic practice and do not include RR estimates. The source of exposure was a large TV antenna, and the three statistical methods considered in the report all showed that the pattern of cancer incidence was essentially random with respect to the antenna. A case–control study based on an apparent cluster of childhood leukemia (Maskarinec et al. 1994) was prompted by an observation of an unusually large number of childhood leukemia cases in a region of Hawaii (USA). There were 12 leukemia cases, and the OR for having lived within 2.6 miles of the radio antennas before diagnosis was 2.0 (95% CI, 0.06–8.3). Hocking et al. (1996) compared cancer incidence in three municipalities immediately surrounding three TV transmitters in northern Sydney, Australia, with the cancer incidence in six adjacent municipalities, estimating power densities from information on commencement of service of each transmitter, power, and frequency band. For leukemia incidence in adults, they found an RR of 1.2 (95% CI, 1.1–1.4) for the inner three municipalities compared with the surrounding municipalities. Their highest RR, 1.7 (95% CI, 1.1–2.5), was for the subcategory “other leukemia.” For childhood leukemia, they observed an RR of 1.6 (95% CI, 1.1–2.3). Neither for adults nor for children were there any risk elevations for brain tumor.
Dolk et al. (1997b) reported on an apparent cluster of leukemia and lymphomas near a U.K. radio and TV transmitter at Sutton Coldfield. The study area was defined as a 10 km radius circle around the transmitter. Ten bands of increasing distance from the antenna were defined as the basis of testing for declining incidence with increasing distance. The RR of adult leukemia within 2 km was 1.8 (95% CI, 1.2–2.7), and there was a statistically significant decline in risk with increasing distance from the antenna. In children younger than 15 years of age, there were two cases compared with 1.1 expected within the 2 km radius circle. The authors concluded that there was an excess risk of adult leukemia in the vicinity of the transmitter.
A second investigation (Dolk et al. 1997a), with a design similar to that of the first one, was extended to include 20 high-power TV and FM radio transmitters. Inside the 2 km radius circle the observed:expected ratio for adult leukemia was 0.97 (95% CI, 0.78–1.2), and for childhood leukemia, 1.1 (95% CI, 0.61–2.1). Thus, these results gave no more than very weak support to the original results.
McKenzie et al. (1998) reexamined the Sydney results discussed above. They found that the excess risk reported by Hocking et al. (1996) was mainly limited to one local government area within the studied region.
The Sutton Coldfield results have also been followed up by another group (Cooper et al. 2001). They used more recent cancer data to reanalyze cancer incidence around the transmitter and found considerably weaker results than the original.
An Italian study occasioned by local concerns investigated leukemia incidence in children and leukemia mortality in adults within a 10 km circle around the Vatican radio station (Michelozzi et al. 2002). The station consists of numerous transmitters with different transmission powers ranging from 5 to 600 kW and with different frequency ranges. In adults of both sexes taken together, the SMR within 2 km of the station was 1.8 (95% CI, 0.3–5.5) based on two cases. Stone’s test for trend in rates over successive 2-km bands around the station gave a p-value of 0.14. The excess risk and the trend were essentially confined to males. In children, the standardized incidence ratio (SIR) for those living within the 2 km radius circle was 6.1 (95% CI, 0.40–28) based on one case. Elevated rates were observed for all cumulative bands up to 10 km, but all had wide confidence intervals and the total number of cases within the 10-km radius circle was eight. The Stone test for trend was reported as p = 0.004. No systematic RF measurements have been made in the area, and the epidemiologic analyses are based on the simplistic proxy, distance from the source. The numbers of cases were small, especially for children, which precludes firm conclusions. For adults the results were inconsistent with the risk elevations largely confined to males.
Discussion.
The research on community exposures to RFs and cancer gives a very weak test of the possibility of a relation. Diverse exposure sources, poorly estimated population exposures, small numbers of cases, and selective investigation in response to cluster concerns have resulted in a literature that is inconclusive. Despite apparent positive relations between proximity and leukemia incidence in some analyses (Hocking et al. 1996; Michelozzi et al. 2002), the results have not been consistent within or between studies and do not show relations to RF exposure levels. It seems to us that a prerequisite for a new generation of informative studies to emerge is the use of an RF meter.
Some of the concern about health risks from living near transmitters is directed toward symptoms such as fatigue, sleep disturbances, and frequent headaches. It may be tempting to address such issues in a cross-sectional study of people living near transmitters, in which subjects are asked to report their symptoms. Indeed, such studies have been done (Navarro et al. 2003; Santini et al. 2002, 2003). However, this is a design in which exposure is poorly characterized and reporting bias with respect to symptoms is of concern. Experimental designs easily overcome these biases and thus would be preferable, although they have their own limitations such as difficulty in practice in detecting effects present in a small percentage of a population or when the effect is not immediate. In these latter situations, an observational study would be the design of choice, but only if a design was found that avoided reporting bias.
Review of Studies on Mobile Phone Use
Most studies of association between cancer and mobile phone use have evaluated the risk of brain tumors and acoustic neuromas (Table 7), although in a few instances the risks of other tumors have been explored. Also studies of symptoms in relation to mobile phone use have been conducted (Table 8). The first case–control study of brain tumors was conducted in Sweden (Hardell et al. 1999, 2000, 2001) and included adult cases diagnosed in two regions in Sweden between 1994 and 1996 and still alive, with two controls per case matched for region of residence. Details of intensity and duration of mobile phone use, preferred side (ear) of use, and whether phones were analog or digital, and handheld or hands-free, were gathered by postal questionnaire followed by telephone interview (Hardell et al. 1999). A total of 209 cases [about one-third of the malignant cases occurring in the study geographical area in the period (Ahlbom and Feychting 1999)] took part along with 425 controls (a reported 91% response rate—extraordinarily high for a contemporary population-based study). Originally no association of phone use with brain tumors was found (Hardell et al. 1999), although later reanalysis of side of use in relation to tumor site suggested a possible relationship (Hardell et al. 2001). A second larger study a few years later by the same authors (Hardell et al. 2002, 2003) was similar in design to the first. It involved 1,303 living cases (half of all brain tumors diagnosed 1997–2000) and their controls. Cumulative phone use for > 85 hr, 10 years before case diagnosis, gave ORs for brain tumors of 1.9 (95% CI, 1.1–3.2) and 3.0 (95% CI, 0.6–14.9), respectively, for analog and cordless phones, but ORs were not increased for digital phones. There was no adjustment for confounding variables. Ipsilateral use of analog phones was related to temporal tumors [OR = 2.5 (95% CI, 1.3–4.9)], and analog phone use was associated with acoustic neuroma [OR = 3.5 (95% CI, 1.8–6.8)] (Hardell et al. 2002, 2003).
Muscat et al. conducted two hospital-based case–control studies in the United States, one of malignant brain tumors (Muscat et al. 2000), the other of acoustic neuroma (Muscat et al. 2002), both using the same ascertainment and data collection procedures (Table 7). The first study included 469 cases of brain cancer (70% response rate) and 422 matched controls with a variety of malignant and benign conditions from the same hospitals (90% response rate). Information about mobile phone use was obtained by standard interview (of proxies for 9% of cases and 1% of controls). No increased risks were seen relating to frequency or duration of use, or for site or histologic subtype of brain cancer. An excess of brain cancer was found on the same side of the head as reported phone use among 41 cases with assessable data (p = 0.06), compared with a deficit on the side of mobile phone use for tumors specifically located in the temporal lobe (p = 0.33). In the acoustic neuroma study, 90 cases were compared with 86 controls, and no associations were seen with level or laterality of phone use.
In another U.S. hospital-based case–control study (Inskip et al. 2001), interview data were obtained from 782 cases with brain tumors (92% response rate; via proxies for 16% and 3% of glioma and acoustic neuroma patients, respectively) and 799 matched hospital controls with nonmalignant conditions (88% response; 3% by proxy). Results adjusted for potential confounders showed no association between cumulative use of mobile phones (mainly analog) and brain tumor overall or by histologic subtype or anatomical location.
Subscription records of national network providers were used to characterize mobile phone users in a Finnish case–control study (Auvinen et al. 2002). All people (398) diagnosed with brain tumors in 1996, ascertained from the National Cancer Registry, were matched with five controls per case drawn from the national population register (Table 7). The OR for brain tumors with ever-subscribed to phones was 2.1 (95% CI, 1.3–3.4) for analog phones and 1.0 for digital, and the OR for glioma was 1.5 (95% CI, 1.0–2.4) for any phone subscription. The average duration of subscription was 2–3 years for analog phones and less for digital. Adjusting for potential confounders did not alter results. No information was available about the frequency or duration of calls or about corporate subscriptions.
Of two cohort studies, an early U.S. study (Dreyer et al. 1999; Rothman et al. 1996) analyzed 1-year of follow-up of mortality in a cohort of 285,561 noncorporate users of mobile phones with at least two billing cycles from two U.S. carriers. Mortality was ascertained from the National Death Index. No relation was found between mortality from brain cancer and the use of handheld versus hands-free phones, based on only six cases. The overall mortality of the cohort was less that in the general population. The second cohort study was in Denmark (Johansen et al. 2002b) and included 420,095 private cellular network subscribers (80% of all subscribers), with average follow-up for analog and digital subscribers of 3.5 and 1.9 years, respectively. SIRs comparing cancer rates in phone users with national rates allowing for sex, age, and period showed no relation to risk of brain and nervous system cancers [SIR 0.95 (95% CI, 0.81–1.2)] and reduced risk of smoking-related cancers. Risks did not vary by age at, or time since, first subscription, phone type, or tumor location. Again, no information was available about the frequency or duration of calls or about corporate subscriptions.
Regarding other head and neck cancers, no association with parotid gland tumors (34 cases) was seen in the Finnish case–control study (Auvinen et al. 2002) or in the Danish cohort study (Johansen et al. 2002b). A mixed population and hospital-based case–control study of uveal melanoma (Stang et al. 2001) included 118 cases and 475 controls. Occupational exposure to mobile phones for several hours a day for ≥ 6 months assessed by interview gave an increased OR [4.2 (95% CI, 1.2–15)], reflecting the result in the hospital-based participants (OR = 10). There was no increased risk of uveal melanoma, however, in the Danish mobile phone user cohort (Johansen et al. 2002a). Finally, leukemia was assessed in both cohort studies, but no relation with phone use was found.
The first report from the multicenter Interphone study, a very large, international case–control study, has recently been published. This report from the Danish component focused on acoustic neuroma and was negative; however, the number of long-term users was small (Christensen et al. 2004).
Subjective symptoms, including tinnitus, headache, dizziness, fatigue, sensations of warmth, dysesthesia of the scalp, visual symptoms (e.g., flashes), memory loss, and sleep disturbance have been investigated in relation to mobile phone use (Chia et al. 2000; Oftedal et al. 2000; Sandstrom et al. 2001; details provided in Table 8). As discussed above in relation to transmitter studies, such research is highly susceptible to recall bias, and for completeness we have added Table 9, which includes experimental studies on mobile phone use and symptoms.
Discussion.
Handheld mobile phones were not used regularly until the 1990s, so published studies at present can only assess relatively short lag periods before cancer manifestation. The relevant lag periods are unknown. Furthermore, even in the large Danish study (Johansen et al. 2002b), long-term (15 years) subscribers to analog phones comprised only a small proportion of users.
Another issue relates to choice of study population. No study populations to date have included children, yet children are increasingly heavy users of mobile phones and they are potentially highly susceptible to harmful effects (although some of these effects might not manifest until adulthood). So far, study populations have been ascertained from population registers in Nordic studies, hospital in-patients in U.S. case–control studies, and cellular network private subscribers in the two cohort studies and the Finnish study (Table 7). Although the population-based studies should have avoided the selection biases inherent in the hospital based studies, this was not so in population-based case–control studies of prevalent living cases with low participation rates (Hardell et al. 1999, 2002) because, inter alia, those with high-grade tumors tend to be excluded. Although rapid recruitment of incident brain tumor cases was facilitated in the hospital-based studies, loss due to death was still greater for malignant than benign tumors as reflected in differential proxy response rates by tumor type (Inskip et al. 2001), and there is a weakness in using hospital controls with a variety of conditions of unknown relationship to mobile phone use.
Differential recall of mobile phone use among those with and without a cerebral tumor in case–control studies is a major potential source of bias, exacerbated by differential timing of data collection from cases and controls in the hospital studies. Reporting bias is also likely because presence of a brain tumor may distort both memory and hearing and because the use of proxy respondents was more common for cases than controls. Relying on private cellular network subscription as a measure of mobile phone use would also have resulted in substantial misclassification because subscribers bear only a modest relation to users (Funch et al. 1996) and because corporate users were either excluded or included in the unexposed group. Until there is some objective measure of RF exposure, or at least validation of self-reported records, the validity of self-reported indices of phone use [e.g., average minutes of use per day (Hardell et al. 2002; Inskip et al. 2001) or minutes or hours per month as indicators of RF exposure] remains unknown.
Overall, although occasional significant associations between various types of brain tumors and analog mobile phone use have emerged (often seen after multiple testing), no single association has been consistently reported across population-based studies. The timing of epidemiologic studies and the lack of knowledge about actual RF exposure to the brain from mobile phone use to date (Ghandi et al. 1999) militate strongly against current ability to detect any true association. Thus current evidence is inconclusive regarding cancer risk after heavy RF exposure from mobile phones. Similarly, the studies of symptoms to date do not suggest that a single exposure to RFs from a mobile phone results in immediately identifiable symptoms, but there are no adequate data available about the symptomatic effects of mobile phone use, especially among people who claim hypersensitivity to RFs.
General Conclusions and Recommendations
Results of epidemiologic studies to date give no consistent or convincing evidence of a causal relation between RF exposure and any adverse health effect. On the other hand, these studies have too many deficiencies to rule out an association.
A key concern across all studies is the quality of assessment of RF exposure, including the question of whether such exposure was present at all. Communication sources have increased greatly in recent years, and there is continuing change in the frequencies used and the variety of applications. Despite the rapid growth of new technologies using RFs, little is known about population exposure from these and other RF sources and even less about the relative importance of different sources. Certain studies that are currently under way have made serious attempts to improve exposure assessment, based on attempts to learn more about determinants of RF exposure levels. A key element in improving future studies would be the use of a meter that monitors individual exposure. In the absence of information on what biologic mechanism is relevant, if any, it is unclear what aspect of exposure needs to be captured in epidemiologic studies. Ideally, the dose needs to be assessed not just as external field intensity but also as cumulative exposure, as well as SAR, for specific anatomical sites.
The need for better exposure assessment is particularly strong in relation to transmitter studies, because the relation between distance and exposure is very weak. There is no point in conducting such studies unless it has been established that exposure levels vary substantially within the study area, and measurements of these RF levels are available. In the future, methods need to be developed to infer exposure based on some combination of knowledge regarding the sources of exposure, the levels of exposure, and location of people in relation to those sources, ideally informed by selective measurements.
Although the likelihood is low that fields emanating from base stations would create a health hazard because of their weakness, this possibility is nevertheless a concern for many people. To date no acceptable study on any outcome has been published on this. On the one hand, results from valid studies would be of value in relation to a social concern; on the other hand, it would be difficult to design and conduct a valid study, and there is no scientific point in conducting an invalid one.
Another general concern in mobile phone studies is that the lag periods that have been examined to date are necessarily short. The implication is that if a longer lag period is required for a health effect to occur, the effect could not be detected in these studies. Only in the few countries where mobile phones were introduced very early has it been possible to look at use ≥ 10 years ago. Much longer lag periods have been examined for occupational RF exposures, however. The published studies include some large occupational cohorts of good design and quality, except that there have been poor assessments of the degree of RF exposure, which render the results difficult to interpret.
Most research has focused on brain tumors and to some extent on leukemia. However, because the RF research questions are not driven by a specific biophysical hypothesis but rather by a general concern that there are unknown or misunderstood effects of RFs, studies on other health effects may be equally justified. Examples are eye diseases, neurodegenerative diseases, and cognitive function. Given the increase in new mobile phone technologies, it is essential to follow various possible health effects from the very beginning and for long periods, because such effects may be detected only after a long duration, because of the prolonged latency period of many chronic diseases. Thus, research is needed to address long-term exposure, as well as diseases other than those included in the ongoing case–control studies.
Another gap in the research is children. No study population to date has included children, with the exception of studies of people living near radio and TV antennas. Children are increasingly heavy users of mobile phones. They may be particularly susceptible to harmful effects (although there is no evidence of this), and they are likely to accumulate many years of exposure during their lives.
Table 1 Cohort studies of risk of cancer in relation to occupational or hobby RF exposure: description of studies.
Reference Occupational group Sex No. of subjects Measure of exposure Outcome
Milham 1988 Amateur radio operators Male 67,829 Hobby title Mortality
Garland et al. 1990 Navy personnel: electronics technicians, aviation electronics technicians, fire control techniciansa Male Not stated Job title Incidence
Muhm 1992 Electromagnetic pulse test workers Male 304 Job title Mortality
Tynes et al. 1996 Radio and telegraph operators on merchant ships Female 2,619 Measures in radio rooms of three ships Incidence
Szmigielski 1996b Military career personnel Male 128,000 total,c 3,700 exposedc Military health records; representative exposure levels given, based on measurements (no. not stated) Incidence
Szmigielski et al. 2001 Military career personnel Male 124,500 total, 3,900 exposed
Lagorio et al. 1997 Dielectric RF heat sealer operators Female 481 Unclear—stated that > 10 W/m2 frequently exceeded Mortality
Morgan et al. 2000 Motorola employees 56% male, 44% female 195,775 total, 24,621 exposed Job title, with expert assessment (not measured) of usual exposures Mortality
Groves et al. 2002 Navy personnel with potential radar exposure Male 40,581 total, 20,021 high exposure Job title, plus expert assessment on potential for high exposure, and information on type and power of radar units Mortality
Lilienfeld cited by Goldsmith 1995 U.S. embassy personnel Males and females Not stated Moscow embassy service Mortality
a We have extracted from the published article data on those jobs stated by Groves et al. (2002) to have greatest RF exposure.
b Not strictly a cohort study—there does not appear to be any follow-up; design appears to be calculation of annual rates, based on annual incidence and counts of employed population, and then averaging of these rates.
c Mean count each year”; presumably many but not all of the personnel will have been the same individuals from year to year of the study.
Table 2 Cohort studies of risk of cancer in relation to occupational RF exposure: results for brain tumor and leukemia.
Brain tumor
Leukemia
Reference Type of analysis No. RR (95% CI) No. RR (95% CI) Comment
Milham 1988 SMR, cohort vs. general 29 1.4 (0.9–2.0) 36 1.2 (0.9–1.7) In a sample, 31% of subjects population worked in EMF-exposed occupations; analyses by license class, a proxy for duration of licensing, showed no consistent trend in risk.
Garland et al. 1990 SIR, cohort vs. general population
Electronics technician —a 5 1.1 (0.4–2.5)
Aviation technician —a < 3 0.3 (0.0–1.9)
Fire control technician —a < 3 0.5 (0.0–2.5)
Muhm 1992 SMR, cohort vs. general population,underlying cause 0 — 1 4.4 (0.1–24.3) One of the leukemia cases may have been allocated to this work because of his leukemia.
SMR, cohort vs. general population, mentioned cause 0 — 2 7.7 (0.9–28.0)
SIR, cohort vs. general population — — 2 5.4 (0.7–19.7)
Tynes et al. 1996 SIR, cohort vs. general population 5 1.0 (0.3–2.3) 2 1.1 (0.1–4.1)
Szmigielski 1996 Average crude incidence rate in exposed vs. average crude rate in unexposed —a 1.9 (1.1–3.5)b —a 7.7c (—a) Poorly conducted and reported study; apparently more exposure data sources for cases than controls
Szmigielski et al. 2001 7 2.7 (p < 0.01)b 19 6.5 (p < 0.01)c “Expected” rates in Szmigielski (1996) paper appear to be incorrect, according to the Royal Society of Canada (1999). Significant excesses were reported for several cancer sites not seen in other studies, and for cancer overall, suggesting possible bias. Analyses of risk in relation to exposure level were presented only for total cancer, not specific cancer sites.
Lagorio et al. 1997 SMR, cohort vs. general population 1 10 1 5 Potential confounding by chemical exposures; losses to follow-up treated as alive to end of study period
Morgan et al. 2000 SMR, exposed workers vs. general population 17 0.5 (0.2–1.1) 21 0.8 (0.4–1.4) No duration–response trend
Rate ratio exposed vs. unexposed in cohort, cumulative exposure
None 34 1.0 66 1.0
< Median 7 1.0 (0.4–2.2) 8 0.6 (0.3–1.3)
≥ Median 10 0.9 (0.4–1.9) 13 0.6 (0.3–1.0)
Groves et al. 2002 SMR, overall cohort vs. general population 88 0.9 (0.7–1.1) 113 1.0 (0.8–1.2) Significant increased risk for nonlymphocytic leukemia in high
SMR, high exposure cohort vs. general population 37 0.7 (0.5–1.0) 69 1.1 (0.9–1.4) exposure cohort, but only increased in one of three high-exposure
Relative risk, exposed vs. unexposed in cohort 37/51 0.6 (0.4–1.0) 69/44 1.5 (1.0–2.2) occupations
Lilienfeld cited by Goldsmith 1995d Observed and expected, respectively, but source of latter unclear Adults: 2/1.9 Children: 0/– 2/2.0 2/4.0 Data also presented for other U.S. embassies in Eastern Europe, but unclear whether they were exposed. Both children with brain tumors and one child with leukemia were dependents who lived outside the embassy.
Abbreviations: —, no data; CI, confidence interval; EMF, electromagnetic field; RR, relative risk.
a No data published; for Szmigielski (1996) it is implied that there were two to three brain tumors in the exposed group, in which case we imply that the 95% CI for brain tumor is incorrect.
b Nervous system.
c Calculated from data in the article.
d Study not published by Lilienfeld, and too little information given in précis in Goldsmith (1995) for understanding or evaluation of the methods. Small numbers of cancers, and several of the cancers occurred in persons who lived out of the embassy (i.e., presumably were in the embassy little of the time, especially children); breast cancer in employees: 2 observed, 0.5 expected; cancers of female genitalia: 4 observed, 0.8 expected; exposures estimated to range from 5 to 18 μW/cm2 (basis of estimate not stated).
Table 3 Case–control studies of risk of brain tumor and leukemia in relation to occupational RF exposure.
Reference Sources of cases and controlsa Measure of exposure Exposure data collection method Mortality or incidence No. of cases/controls Type of analysis Results [OR (95% CI)]
Brain tumor Leukemia
Thomas et al. 1987 Cases: death certificates Controls: death certificates for deaths from other causes, except epilepsy, stroke, suicide, homicide Job title and industry Interview with relatives Mortality 435/386 ORs vs. never occupationally exposed 1.6 (1.0–2.4) —
Armstrong et al. 1994 Electrical utility workers (nested case–control) Job exposure matrix based on 1 week meter measurements at 5–20 MHzc for > 1,000 workers, assessing exposure to pulsed electromagnetic fields Company records Incidence 84/325 ORs for ≥ median exposure 0.8 (0.5–1.5)b —
95/374 ORs for ≥ 90th percentile 1.9 (0.5–7.6)b —
OR for ≥ median exposure — 0.7 (0.4–1.2)
OR for ≥ 90th percentile — 0.8 (0.2–3.4)
Grayson 1996 USAF (nested case–control) Job title and reports of incidents of high exposure for each job title Military records Incidence 230/920 OR vs. never exposed 1.4 (1.0–1.9) —
Abbreviations: —, no data; CI, confidence interval; ORs, odds ratios; USAF, U.S. Air Force.
a All studies restricted to men.
b Malignant brain tumors.
c It was later found that the meters also responded to fields of 150 and 300 MHz and to radio transmissions.
Table 4 Analyses of routinely collected data on brain tumor and leukemia risk in relation to occupational RF exposure.
References Type of analysis Exposed groupa Comparison cohort/control group Mortality or incidence Brain tumor
Leukemia
No.b RR (95% CI) No.b RR (95% CI)
Wright et al. 1982 Proportional incidence Radio and TV repairmen All other cancers Incidence — 1 1.2 (—)
Telephone linesmen — 2 3.1 (—)
Calle and Savitz 1985 Proportional mortality Radio and telegraph operators All causes of death Mortality — 6 2.3 (—)
Radio and TV repairmen — 3 0.9 (—)
Lin et al. 1985 Case–control Electric and telephone linemen, servicemen Noncancer deaths Mortality 27 —
Milham 1985 Proportional mortality Radio and telegraph operators All causes of deaths Mortality 1 0.4 (—) 5 1.0 (—)
Radio and TV repairmen 2 0.6 (—) 7 1.8 (—)
Pearce et al. 1989 Case–control Radio and TV repairmen All other cancers Incidence — 2 7.9 (2.2–28.1)
Tynes et al. 1996 Cohort Radiofrequency-exposed occupations Economically active males Incidence 3 0.6 (0.1–1.8) 9 2.8 (1.3–5.4)
Abbreviations: —, no data published; CI, confidence interval; RR, relative risk.
a All studies are of males; exposure assessment for all is based solely on job title, with no measures of exposure.
b No. in exposed group.
Table 5 Summary of literature on RF exposure and reproductive health outcomes.
Outcome Semen parameters Reference Geographic setting Population source and no. Exposure and outcome
Semen parameters
Lancranjan et al. 1975 Romania Microwave exposure (31) vs. controls (30) Sperm count: 50 (exp), 60 (ctl) million/mL
Percent motile: 36 (exp), 54 (ctl)
Weyandt et al. 1996 United States Military intelligence (20) vs. controls (30) Sperm density: 13 (exp), 35 (ctl)
Percent normal: 69 (exp), 73 (ctl)
Percent motile: 32 (exp), 43 (ctl)
Hjollund and Bonde 1997 Denmark Military: missile operators (19), other (489) Sperm density: 40 (exp), 62 (ctl)
Percent immotile: 52 (exp), 33 (ctl)
Percent normal: 61 (exp), 68 (ctl)
Schrader et al. 1998 United States (Texas) Military: radar operators (33), controls (103) Sperm density: 29 (exp), 32 (ctl)
Percent normal: 46 (exp), 42 (ctl)
Percent motile: 46 (exp), 45 (ctl)
Grajewski et al. 2000 United States (Maryland) RF heater operators Sperm density: 47 (exp), 45 (ctl)
Sperm count: 73 (exp), 93 (ctl)
Percent motile: 67 (exp), 52 (ctl)
Normal morphology: 81 (exp), 79 (ctl)
Fertility
Larsen et al. 1991 Denmark Physiotherapists (49), time to pregnancy > 6 months TWA exposure and TTP > 6 months RR = 1.0, 0.8 (0.2–2.2), 1.7 (0.7–4.1)
Spontaneous abortion
Taskinen et al. 1990 Finland Physiotherapists (204), spontaneous abortions SAb ≤ 10
Deep heat: 1.0, 1.3, 0.7
Shortwaves: 1.0, 1.2, 0.7
Microwaves 1.0, 0.7
SAb > 10
Deep heat: 1.0, 1.3, 2.6
Shortwaves: 1.0, 2.5, 2.4
Microwaves: 1.0, 2.4
Larsen et al. 1991 Denmark Physiotherapists (146), spontaneous abortions TWA exposure and SAb: RR = 1.0, 1.0 (0.5–1.8), 1.4 (0.7–2.8)
Ouellet-Hellstrom and Stewart 1993 United States Female physical therapists (1,664), spontaneous abortions Microwave diathermy exposures/month:
RR = 1.0, 1.1 (0.8–1.4), 1.5 (1.0–2.2), 1.6 (1.0–2.6)
Shortwave diathermy exposures/month:
RR = 1.0, 1.2 (1.0–1.5), 1.1 (0.9–1.4), 0.9 (0.6–1.2)
Stillbirth
Larsen et al. 1991 Denmark Physiotherapists (17), perinatal deaths TWA exposure and perinatal death
RR = 1.0, 1.5 (0.3–5.3), 2.9 (0.6–10.7)
Preterm birth
Larsen et al. 1991 Denmark Physiotherapists (37 male, 45 female) TWA exposure and preterm birth:
Male: RR = 1.0, 1.4 (0.4–4.7), 3.2 (0.7–13.2)
Female: RR = 1.0, 0.9 (0.4–2.1), 0.9 (0.3–2.8)
Low birth weight
Larsen et al. 1991 Denmark Physiotherapists (15 male, 24 female) TWA exposure and low birthweight:
Male: RR = 1.0, 0.0, 5.9 (1.0–28.2)
Female: RR = 1.0, 1.2 (0.4–3.3), 0.7 (0–3.2)
Guberan et al. 1994 Switzerland Physiotherapists (11 male, 14 female) No association with shortwaves (RR not reported)
Birth defects
Logue et al. 1985 United States Physical therapists (male), 192 birth defects Observed: expected range “appears to be higher than expected”
Taskinen et al. (1990) Finland Physiotherapists Deep heat: 1.0, 2.4 (1.0–5.3), 0.9 (0.3–2.7)
51 birth defects Shortwaves: 1.0, 2.7 (1.2–6.1), 1.0 (0.3–3.1)
Microwaves: 1.0, 0.5 (0.1–3.9)
Abbreviations: ctl, controls; exp, exposed; SAb, spontaneous abortions; TTP, time to pregnancy; TWA, time-weighted average.
Table 6 Summary of studies on transmitters and cancer.
Reference Source of exposure Comparison End points No. of cases Results [OR (95% CI)] Setting Comments
Selvin et al. 1992 MW antenna Internal Childhood cancer 123 Random San Francisco Analysis of spatial data; no epidemiologic parameters
Childhood leukemia 52 pattern
Maskarinec et al. 1994 LF radio (23.4 kHz) < 2.6 miles Childhood leukemia 12 2.0 (0.06–8.3) Hawaii Case–control; SIR analysis on same cases: 2.09 (1.08–3.65)
Hocking et al. 1996 TV antenna Inner/outer All age leukemia 1.24 (1.09–1.40) Northern Sydney 8–0.2 μW/cm2
Childhood leukemia 1.58 (1.07–2.34)
Dolk et al. 1997b TV and FM radio < 2 km Adult leukemia 23 1.83 (1.22–2.74) Sutton Coldfield
Dolk et al. 1997a TV and FM radio < 2 km Leukemia 79 0.97 (0.78–1.21) All of Great Britain
McKenzie et al. 1998 TV antennas Continuous μW/cm2 model Childhood leukemia Sydney Reanalysis of Hockings et al. (1996) with LGA analysis
Cooper et al. 2001 TV and FM radio < 2 km All age leukemia 20 1.32 (0.81–2.05) Sutton Reanalysis, more timely cancer data
Childhood leukemia 1 1.13 (0.03–6.27) Coldfield
Michelozzi et al. 2002 Radio station < 6 km Childhood leukemia 8 2.2 (1.0–4.1) Vatican
Adult leukemia 23 1.2 (0.8–1.8)
Abbreviations: MW, microwave; LF, low frequency; LGA, local government area.
Table 7 Summary of studies of mobile phone use and risk of brain tumors.
Reference (study design) Study population Tumor type (nos. of cases/controls) Exposure assessment Mobile phone type;duration of use in controls Mobile phone ever used [RR (95% CI)]
Hardell et al. 1999 (case–control) Sweden All tumors (209/425) Recalled mobile phone use by questionnaire and interview Mainly analog 450 or 900 MHz; 16% > 5 years 1.0 (0.7–1.4)a
Cases: 20–80 years of age Acoustic neuroma 0.8 (0.1–4.2)
Controls: regional population registers, Uppsala-Orebro 1994–1996, Stockholm 1995–1996
Muscat et al. 2000 (case–control) United States: hospital inpatients, New York, Providence, Boston Malignant brain tumor (469/422) Recalled mobile phone use via interview Mainly analog 800–900 MHz; 5% > 4 years 0.9 (0.6–1.2)
Cases: 18–80 years,1994–1998
Controls: malignant and nonmalignant conditions
Inskip et al. 2001 (case–control) United States: hospital inpatients, All tumors (782/799) Recalled mobile phone use via interview Mainly analog 800–900 MHz; 8% > 3 years 0.9 (0.7–1.1)
Boston, Phoenix, Pittsburgh Glioma (489/799) 1.0 (0.7–1.4)
Cases: ≥ 18 years of age, 1994–1998 Meningioma (197/799) 0.8 (0.5–1.2)
Controls: nonmalignant conditions Acoustic neuroma (96/799) 0.8 (0.5–1.4)
Muscat et al. 2002 (case–control) United States: hospital inpatients, New York Acoustic neuroma (90/86) Recalled mobile phone use via questionnaire Mainly analog 800–900 MHz; 7% 3–6 years 0.9
Cases: ≥ 18 years of age,1997–1999
Controls: nonmalignant conditions
Auvinen et al. 2002 (case–control) Finland All tumors (398/1,986) Duration of private cellular network subscription Analog, average 2–3 years subscription; digital, average < 1 year subscription 1.3 (0.9–1.8)
Cases: 20–69 years of age,1996 Glioma (198/989) 1.5 (1.0–2.4)
Controls: national population register Benign (129/643) 1.1 (0.5–2.4)
Salivary gland (34/170) 1.3 (0.4–4.7)
Hardell et al. 2002 (case–control) Sweden All tumors (1,303/1,303) Recalled mobile phone use via questionnaire Analog 450 or 900 MHz, median 8 years 1.3 (1.0–1.6)a
Cases: 20–80 years of age, 1997–2000
Controls: four regional population registers Digital 1,900 MHz, median 3 years 1.0 (0.8–1.2)
Hardell et al. 2003 (case–control) Acoustic neuroma (159/422) Analog 3.5 (1.8–6.8)
Digital 1.2 (0.7–2.2)
Dreyer et al. 1999 (cohort) United States: subscribers of two large cellular networks, 1993 Malignant brain tumor (6) Duration of subscription Analog, 1 year follow-up —
Cases: ≥ 20 years of age, deaths 1994 —
Johansen et al. 2002 (cohort) Denmark: private cellular network subscribers, 1982–1995 All tumors (154) Duration of subscription Analog 450 or 900 MHz or digital; up to 15 year follow-up SIR 1.0 (0.8–1.1)
Glioma (66) 0.9 (0.7–1.2)
Cases: ≥ 18 years of age, 1982–1996 Menigioma (16) 0.9 (0.5–1.4)
Christensen et al. 2004 Denmark: population-based case–control Acoustic neuroma (106); population controls (212) — — 0.90 (0.51–1.6)
a Analyzed with a 1-year lag period discounted.
Table 8 Summary of studies of mobile phone use and symptoms.
Reference (study design) Study population Analyses Exposure assessment Outcome assessment Results
Oftedal et al. 2000 (cross-sectional) Swedish and Norwegian mobile phone users, selected from network operator registers; included only people who used phone for job (n = 10,631) 1. Number of respondents with any symptom attributed to mobile phones Self-completed questionnaire Self-reported frequency of symptoms; patient considered to have symptom if occurred at least once per week 1. 13% of participants in Sweden and 31% in Norway reported at least one symptom in connection with use of a mobile phone; most common: warmth around ear; 22% of Norwegians and 7% of Swedes experienced symptom other than warmth.
2. Number of respondents who had taken steps to reduce symptoms 2. 45% of people experiencing symptoms had taken steps to reduce them, such as reduced calling time, use of hands-free kit, changing side phone used.
Sandstrom et al. 2001 (cross-sectional) Swedish and Norwegian mobile phone users, selected from network operator registers (n = 16,992) 1. Comparison of digital vs. analog mobile phone users Self-completed questionnaire, variables; transmitter system, calling time per day and number of calls per day Self-reported frequency of range of symptoms; participant considered to have symptoms if occurred at least once per week 1. OR among digital vs. analog phones: no increased risk for any symptoms; digital users at lower risk of warmth behind ear (OR = 0.64; 95% CI, 0.51–0.80) or on ear (OR = 0.68; 95% CI,0.53–0.86). Digital users in Sweden at lower risk of headaches (OR = 0.73; 95% CI, 0.56–0.95) and fatigue (OR = 0.80; 95% CI, 0.65–0.99).
2. Trends with increasing time of phone usage 2. With increasing minutes of phone use there was an increased odds of reporting fatigue, headaches, warmth, burning, and tightness at least once per week.
Chia et al. 2000 (cross-sectional) Random sample of 635 households in housing estate in Singapore; 808 respondents (response rate < 60%) 1. Prevalence ratio of headache in mobile phone users vs. non-users Interviewer-administered questionnaire; purpose of study masked; classified as mobile phone user if used at least once per day Questionnaire concerning nature and severity of “CNS symptoms” (headache, dizziness, warmth, tingling, visual disturbances); the frequency of headaches required before a respondent was classified as a headache sufferer was not specified 1. 45% mobile phone users; 3% experienced CNS problems; adjusted prevalence ratio for headache among users vs. non-users, 1.31 (95% CI, 1.00–1.70); no significant differences for any other symptoms.
2. Association between minutes, phone use and headache 2. Significant positive trend for increasing time spent on the mobile phone and prevalence of headache (p = 0.04).
CNS, central nervous system.
Table 9 Summary of experimental studies of mobile phone use and symptoms.
Reference Participants Exposure Protocol source Symptoms reported Results
Hietanen et al. 2002 20 volunteer subjects, mean age, 51 years for women and 47 years for men, all of whom classified themselves as hypersensitive to RFs Analog phone, transmitting at 900 MHz; 900 and 1,800 MHz digital phones Phones mounted near but not touching subjects ear; 3 or 4 experimental sessions lasting 30 min each, one of which was a sham exposure (random order) Subjects asked to describe symptoms experienced during exposure; blood pressure, heart rate, and breathing frequency monitored; follow-up form used to measure symptoms over subsequent days 19/20 participants reported symptoms during the tests; compared with women during sham exposure, relative number of symptoms reported by female subjects during analog exposure was 0.82, digital 900 MHz, 0.79; digital 1,800 MHz, 0.72; among men, number of symptoms during any RF exposure situtation was 0.85 compared with sham exposure.
Koivisto et al. 2001 48 volunteers, students at University of Turku, Finland; mean age, 26 years Digital 900 MHz phone Two exposure sessions, one with mobile phone on and one with off; subjects blinded to whether phone was off or on; half of participants had phone on first and half off first Questionnaire assessing symptoms administered in the beginning, middle, and end of session; subjects asked to rate strength of sensations on 4-point scale; symptoms assessed were dizziness, headache, fatigue, tingling, redness, warmth There were no significant differences between mean values for subjective ratings between exposure on and exposure off situtations.
==== Refs
References
Ahlbom A Feychting M 1999 Re: Use of cellular phones and the risk of brain tumours: a case-control study [Letter] Int J Oncol 15 1045 1047 10617373
Anglesio L Benedetto A Bonino A Colla D Martire F Saudino Fusette S 2001 Population exposure to electromagnetic fields generated by radio base stations: evaluation of the urban background by using provisional model and instrumental measurements Radiat Prot Dosimetry 97 355 358 11878419
Armstrong B Theriault G Guenel P Deadman J Goldberg M Heroux P 1994 Association between exposure to pulsed electromagnetic fields and cancer in electric utility workers in Quebec, Canada, and France Am J Epidemiol 140 805 820 7977291
Auvinen A Hietanen M Luukkonen R Koskela RS 2002 Brain tumors and salivary gland cancers among cellular telephone users Epidemiology 13 356 359 11964939
Behin A Hoang-Xuan K Carpentier AF Delattre JY 2003 Primary brain tumours in adults Lancet 361 323 331 12559880
Calle EE Savitz DA 1985 Leukemia in occupational groups with presumed exposure to electrical and magnetic fields N Engl J Med 313 23 1476 1477 4058553
Cantor KP Stewart PA Brinton LA Dosemeci M 1995 Occupational exposures and female breast cancer mortality in the United States J Occup Environ Med 37 336 348 7796202
Chia SE Chia HP Tan JS 2000 Prevalence of headache among handheld cellular telephone users in Singapore: a community study Environ Health Perspect 108 1059 1062 11102297
Christensen HC Schuz J Kosteljanetz M Poulsen HS Thomsen J Johansen C 2004 Cellular telephone use and risk of acoustic neuroma Am J Epidemiol 159 277 283 14742288
Cleary SF Pasternack BS 1966 Lenticular changes in microwave workers. A statistical study Arch Environ Health 12 23 29 4951655
Cleary SF Pasternack BS Beebe GW 1965 Cataract incidence in radar workers Arch Environ Health 11 179 182 5832248
Cooper D Hemmings K Saunders P 2001 Re: “Cancer incidence near radio and television transmitters in Great Britain. I. Sutton Coldfield transmitter; II. All high power transmitters” [Letter] Am J Epidemiol 153 202 204 11159167
COST281 (European Cooperation in the Field of Scientific and Technical Research.) 2001. Mobile Telecommunication Base Stations—Exposure to Electromagnetic Fields. Report of a Short Term Mission within COST 244bis. Available: http://www.cost281.org/activities/Short_term_mission.pdf [accessed 27 October 2004].
Dahme M 1999 Residential RF exposures Radiat Prot Dosimetry 83 113 117
Davis RL Mostofi FK 1993 Cluster of testicular cancer in police officers exposed to hand-held radar Am J Ind Med 24 231 233 8213849
Demers PA Thomas DB Rosenblatt KA Jimenez LM McTiernan A Stalsberg H 1991 Occupational exposure to electromagnetic fields and breast cancer in men Am J Epidemiol 134 340 347 1877594
Dimbylow PJ Mann SM 1999 Characterization of energy deposition in the head from cellular phones Radiat Prot Dosimetry 83 113 117
Dolk H Elliott P Shaddick G Walls P Thakrar B 1997a Cancer incidence near radio and television transmitters in Great Britain. II. All high power transmitters Am J Epidemiol 145 10 17 8982017
Dolk H Shaddick G Walls P Grundy C Thakrar B Kleinschmidt I 1997b Cancer incidence near radio and television transmitters in Great Britain. I. Sutton Coldfield transmitter Am J Epidemiol 145 1 9 8982016
Dreyer NA Loughlin JE Rothman KJ 1999 Cause-specific mortality in cellular telephone users JAMA 282 1814 1816 10573269
Funch DP Rothman KJ Loughlin JE Dreyer NA 1996 Utility of telephone company records for epidemiologic studies of cellular telephones Epidemiology 7 299 302 8728445
Garland FC Shaw E Gorham ED Garland CF White MR Sinsheimer PJ 1990 Incidence of leukemia in occupations with potential electromagnetic field exposure in United States Navy personnel Am J Epidemiol 132 293 303 2372008
Ghandi OP Lazzi G Tinniswood A Yu QS 1999 Comparison of numerical and experimental methods for determination of SAR and radiation patterns of handheld wireless telephones Bioelectromagnetics 20 93 101
Goldsmith JR 1995 Epidemiologic evidence of radiofrequency radiation (microwave) effects on health in military, broadcasting, and occupational studies Int J Occup Environ Health 1 47 57 9990158
Goldstein LS Kheifets L van Deventer E Repacholi M 2003 Comments on “Long-term exposure of Emicro-Pim1 transgenic mice to 898.4 MHz microwaves does not increase lymphoma incidence” by Utteridge et al., Radiat. Res. 158, 357–364 (2002) Radiat Res 159 275 276 12537535
Grajewski B Cox C Schrader SM Murray WE Edwards RM Turner TW 2000 Semen quality and hormone levels among radiofrequency heater operators J Occup Environ Med 42 993 1005 11039163
Grayson JK 1996 Radiation exposure, socioeconomic status, and brain tumor risk in the US Air Force: a nested case-control study Am J Epidemiol 143 480 486 8610663
Groves FD Page WF Gridley G Lisimaque L Stewart PA Tarone RE 2002 Cancer in Korean war navy technicians: mortality survey after 40 years Am J Epidemiol 155 810 818 11978584
Hamburger S Logue JN Silverman PM 1983 Occupational exposure to non-ionizing radiation and an association with heart disease: an exploratory study J Chronic Dis 36 791 802 6643646
Hardell L Mild KH Carlberg M 2002 Case-control study on the use of cellular and cordless phones and the risk for malignant brain tumours Int J Radiat Biol 78 931 936 12465658
Hardell L Mild KH Carlberg M 2003 Further aspects on cellular and cordless telephones and brain tumours Int J Oncol 22 399 407 12527940
Hardell L Mild KH Pahlson A Hallquist A 2001 Ionizing radiation, cellular telephones and the risk for brain tumours Eur J Cancer Prev 10 523 529 11916351
Hardell L Nasman A Pahlson A Hallquist A 2000 Case-control study on radiology work, medical X-ray investigations, and use of cellular telephones as risk factors for brain tumors MedGenMed 2 E2 11104448
Hardell L Nasman A Pahlson A Hallquist A Hansson Mild K 1999 Use of cellular telephones and the risk for brain tumours: a case-control study Int J Oncol 15 113 116 10375602
Hayes RB Brown LM Pottern LM Gomez M Kardaun JW Hoover RN 1990 Occupation and risk for testicular cancer: a case-control study Int J Epidemiol 19 825 831 1964675
Hietanen M Hämäläinen AM Husman T 2002 Hypersensitivity symptoms associated with exposure to cellular telephones: no causal link Bioelectromagnetics 23 264 270 11948605
Hitchcock RT Patterson RM 1995. Radio-Frequency and ELF Electromagnetic Energies. A Handbook for Health Professionals. New York:Van Nostrand Reinhold.
Hjollund NH Bonde JP Skotte J 1997 Semen analysis of personnel operating military radar equipment [Letter] Reprod Toxicol 11 897 9407601
Hocking B Gordon IR Grain HL Hatfield GE 1996 Cancer incidence and mortality and proximity to TV towers Med J Aust 165 601 605 8985435
Hollows FC Douglas JB 1984 Microwave cataract in radio-linemen and controls Lancet 2 406 407 6147485
Holly EA Aston DA Ahn DK Smith AH 1996 Intraocular melanoma linked to occupations and chemical exposures Epidemiology 7 55 61 8664402
IEGMP 2000. Mobile Phones and Health. Chilton, Didcot, UK:Independent Expert Group on Mobile Phones. Available: http://www.iegmp.org.uk/report/text.htm [accessed 5 November 2004].
Imaida K Kuzutani K Wang J Fujiwara O Ogiso T Kato K 2001 Lack of promotion of 7,12-dimethylbenz[a ]anthracene-initiated mouse skin carcinogenesis by 1.5 GHz electromagnetic near fields Carcinogenesis 22 1837 1841 11698347
Inskip PD Linet MS Heineman EF 1995 Etiology of brain tumors in adults Epidemiol Rev 17 382 414 8654518
Inskip PD Tarone RE Hatch EE Wilcosky TC Shapiro WR Selker RG 2001 Cellular-telephone use and brain tumors N Engl J Med 344 79 86 11150357
Jauchem JR 1997 Exposure to extremely-low-frequency electromagnetic fields and radiofrequency radiation: cardiovascular effects in humans Int Arch Occup Environ Health 70 9 21 9258703
Johansen C Boice JD Jr McLaughlin JK Christensen HC Olsen JH 2002a Mobile phones and malignant melanoma of the eye Br J Cancer 86 348 349 11875697
Johansen C Boice JD Jr McLaughlin JK Olsen JH 2002b Cellular telephones and cancer—a nationwide cohort study in Denmark J Natl Cancer Inst 93 203 207 11158188
Koivisto M Haarala C Krause CM Revonsuo A Laine M Hämäläinen H 2001 GSM phone signal does not produce subjective symptoms Bioelectromagnetics 22 212 215 11255218
Krewski D Byus CV Glickman BW Lotz WG Mandeville R McBride ML 2001 Potential health risks of radio-frequency fields from wireless telecommunication devices J Toxicol Environ Health B Crit Rev 4 1 143 11202058
Lagorio S Rossi S Vecchia P De Santis M Bastianini L Fusilli M 1997 Mortality of plastic-ware workers exposed to radiofrequencies Bioelectromagnetics 18 418 421 9261538
Lancranjan I Maicanescu M Rafaila E Klepsch I Popescu HI 1975 Gonadic function in workmen with long-term exposure to microwaves Health Phys 29 381 383 1193858
Larsen AI 1991 Congenital malformations and exposure to high-frequency electromagnetic radiation among Danish physiotherapists Scand J Work Environ Health 17 318 323 1947917
Larsen AI Olsen J Svane O 1991 Gender-specific reproductive outcome and exposure to high-frequency electromagnetic radiation among physiotherapists Scand J Work Environ Health 17 324 329 1947918
Larsen AI Skotte J 1991 Can exposure to electromagnetic radiation in diathermy operators be estimated from interview data? A pilot study Am J Ind Med 19 51 57 1989437
Lin RS Dischinger PC Conde J Farrell KP Occupational exposure to electromagnetic fields and the occurrence of brain tumors. An analysis of possible associations J Occup Med 27 6 413 419 4020499
Logue JN Hamburger S Silverman PM Chiacchierini RP Congenital anomalies and paternal occupational exposure to shortwave, microwave, infrared, and acoustic radiation J Occup Med 27 6 451 452 4020505
Mantiply ED Pohl KR Poppell SW Murphy JA 1997 Summary of measured radiofrequency electric and magnetic fields (10 kHz to 30 GHz) in the general and work environment Bioelectromagnetics 18 563 577 9383245
Maskarinec G Cooper J Swygert L 1994 Investigation of increased incidence in childhood leukemia near radio towers in Hawaii: preliminary observations J Environ Pathol Toxicol Oncol 13 33 37 7823291
Mason PA Walters TJ DiGiovanni J Beason CW Jauchem JR Dick EJ Jr 2001 Lack of effect of 94 GHz radio frequency radiation exposure in an animal model of skin carcinogenesis Carcinogenesis 22 1701 1708 11577012
McKenzie DR Yin Y Morrell S 1998 Childhood incidence of acute lymphoblastic leukaemia and exposure to broadcast radiation in Sydney—a second look Aust NZ J Public Health 22 360 367
Michelozzi P Capon A Kirchmayer U Forastiere F Biggeri A Barca A 2002 Adult and childhood leukemia near a high-power radio station in Rome, Italy Am J Epidemiol 155 1096 1103 12048223
Milham S Jr 1985 Silent keys: leukaemia mortality in amateur radio operators [Letter] Lancet 1 812 2858681
Milham S Jr 1988 Increased mortality in amateur radio operators due to lymphatic and hematopoietic malignancies Am J Epidemiol 127 50 54 3422125
Morgan RW Kelsh MA Zhao K Exuzides KA Heringer S Negrete W 2000 Radiofrequency exposure and mortality from cancer of the brain and lymphatic/hematopoietic systems Epidemiology 11 118 127 11021607
Moulder JE Erdreich LS Malyapa RS Merritt J Pickard WF Vijayalaxmi 1999 Cell phones and cancer: what is the evidence for a connection? Radiat Res 151 513 531 10319725
Muhm JM 1992 Mortality investigation of workers in an electromagnetic pulse test program J Occup Med 34 287 292 1545281
Muscat JE Malkin MG Shore RE Thompson S Neugut AI Stellman SD 2002 Handheld cellular telephones and risk of acoustic neuroma Neurology 58 1304 1306 11971109
Muscat JE Malkin MG Thompson S Shore RE Stellman SD McRee D 2000 Handheld cellular telephone use and risk of brain cancer JAMA 284 3001 3007 11122586
Navarro EA Segura J Portolés M Gómez-Perretta de Mateo C 2003 The microwave syndrome: a preliminary study in Spain Electromagn Biol Med 22 161 169
NRPB 2003. Health Effects from Radiofrequency Electromagnetic Fields. Report of an Independent Advisory Group on Non-ionising Radiation. Chilton, Didcot, UK:National Radiation Protection Board. Available: http://www.nrpb.org/publications/documents_of_nrpb/pdfs/doc_14_2.pdf [accessed 28 October 2004].
Oftedal G Wilen J Sandstrom M Mild KH 2000 Symptoms experienced in connection with mobile phone use Occup Med (Lond) 50 237 245 10912374
Ouellet-Hellstrom R Stewart WF 1993 Miscarriages among female physical therapists who report using radio- and microwave-frequency electromagnetic radiation Am J Epidemiol 138 775 786 8237966
Pearce N Reif J Fraser J Case-control studies of cancer in New Zealand electrical workers Int J Epidemiol 18 1 55 59 2722384
Petridou E Trichopoulos D 2002. Leukemias. In: Textbook of Cancer Epidemiology (Adami A, Trichopoulos D, Hunter D, eds). Oxford, UK:Oxford University Press, 556–572.
Repacholi MH Basten A Gebski V Noonan D Finnie J Harris AW 1997 Lymphomas in E mu-Pim1 transgenic mice exposed to pulsed 900 MHz electromagnetic fields Radiat Res 147 631 640 9146709
Robinette CD Silverman C Jablon S 1980 Effects upon health of occupational exposure to microwave radiation (radar) Am J Epidemiol 112 39 53 7395854
Rothman KJ Loughlin JE Funch DP Dreyer NA 1996 Overall mortality of cellular telephone customers Epidemiology 7 303 305 8728446
Royal Society of Canada 1999. A Review of the Potential Health Risks of Radiofrequency Fields from Wireless Telecommunication Devices. Ottawa, Ontario:Royal Society of Canada. Available: http://www.rsc.ca/english/RFreport.pdf [accessed 4 November 2004].
Sandstrom M Wilen J Oftedal G Hansson Mild K 2001 Mobile phone use and subjective symptoms. Comparison of symptoms experienced by users of analogue and digital mobile phones Occup Med (Lond) 51 25 35 11235824
Santini R Santini P Danze JM Le Ruz P Seigne M 2002 Investigation on the health of people living near mobile telephone relay stations: I/Incidence according to distance and sex Pathol Biol (Paris) 50 369 373 12168254
Santini R Santini P Danze JM Le Ruz P Seigne M 2003 Symptoms experienced by people in vicinity of base stations: II/Incidences of age, duration of exposure, location of subjects in relation to the antennas and other electromagnetic factors Pathol Biol (Paris) 51 412 415 12948762
Savitz DA Dufort V Armstrong B Theriault G 1997 Lung cancer in relation to employment in the electrical utility industry and exposure to magnetic fields Occup Environ Med 54 396 402 9245945
Schrader SM Langford RE Turner TW Breitenstein MJ Clark JC Jenkins BL 1998 Reproductive function in relation to duty assignments among military personnel Reprod Toxicol 12 465 468 9717697
Schüz J Mann S 2000 A discussion of potential exposure metrics for use in epidemiological studies on human exposure to radiowaves from mobile phone base stations J Expo Anal Environ Epidemiol 10 600 605 11140443
Selvin S Schulman J Merrill DW 1992 Distance and risk measures for the analysis of spatial data: a study of childhood cancers Soc Sci Med 34 769 777 1604371
Shacklett DE Tredici TJ Epstein DL 1975 Evaluation of possible microwave-induced lens changes in the United States Air Force Aviat Space Environ Med 46 1403 1406 1212147
Silvi AM Zari A Licitra G 2001 Assessment of the temporal trend of the exposure of people to electromagnetic fields produced by base stations for mobile telephones Radiat Prot Dosimetry 97 387 390 11878425
Stang A Anastassiou G Ahrens W Bromen K Bornfeld N Jockel KH 2001 The possible role of radiofrequency radiation in the development of uveal melanoma Epidemiology 12 7 12 11138823
Swerdlow AJ 1999 Measurement of radiofrequency radiation exposure in epidemiological studies Radiat Prot Dosimetry 83 149 153
Szmigielski S 1996 Cancer morbidity in subjects occupationally exposed to high frequency (radiofrequency and microwave) electromagnetic radiation Sci Total Environ 180 9 17 8717316
Szmigielski S Sobiczewska E Kubacki R 2001 Carcinogenic potency of microwave radiation: overview of the problem and results of epidemiological studies on Polish military personnel Eur J Oncol 6 193 199
Taskinen H Kyyronen P Hemminki K 1990 Effects of ultrasound, shortwaves, and physical exertion on pregnancy outcome in physiotherapists J Epidemiol Community Health 44 196 201 2273355
Thomas TL Stolley PD Stemhagen A Fontham ET Bleecker ML Stewart PA 1987 Brain tumor mortality risk among men with electrical and electronics jobs: a case-control study J Natl Cancer Inst 79 233 238 3474455
Tynes T Hannevik M Andersen A Vistnes AI Haldorsen T 1996 Incidence of breast cancer in Norwegian female radio and telegraph operators Cancer Causes Control 7 197 204 8740732
Utteridge TD Gebski V Finnie JW Vernon-Roberts B Kuchel TR 2002 Long-term exposure of E-mu-Pim1 transgenic mice to 898.4 MHz microwaves does not increase lymphoma incidence Radiat Res 158 357 364 12175314
Weyandt TB Schrader SM Turner TW Simon SD 1996 Semen analysis of military personnel associated with military duty assignments Reprod Toxicol 10 521 528 8946566
Wright WE Peters JM Mack TM Leukaemia in workers exposed to electrical and magnetic fields Lancet 2 1160 1161 6128476
|
15579422
|
PMC1253668
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec 23; 112(17):1741-1754
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7306
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science 10.1289/ehp.7166ehp0112-00175515579423Children's HealthCommentaryIncorporating Environmental Health into Pediatric Medical and Nursing Education McCurdy Leyla Erk 1Roberts James 2Rogers Bonnie 3Love Rebecca 1Etzel Ruth 4Paulson Jerome 5Witherspoon Nsedu Obot 5Dearry Allen 61National Environmental Education and Training Foundation, Washington, DC, USA2Medical University of South Carolina, Charleston, South Carolina, USA3University of North Carolina School of Public Health, Chapel Hill, North Carolina, USA4George Washington University School of Public Health and Health Services, Washington, DC, USA5Children’s Environmental Health Network, Washington, DC, USA6National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USAAddress correspondence to L.E. McCurdy, National Environmental Education and Training Foundation, 1707 H St. NW, Suite 900, Washington, DC 20006 USA. Telephone: (202) 261-6488. Fax: (202) 261-6464. E-mail:
[email protected] report has been generated through a partnership between the National Environmental Education and Training Foundation and the Children’s Environmental Health Network. Support for this project is made possible through a grant from the National Institute of Environmental Health Sciences.
The authors declare they have no competing financial interests.
12 2004 23 9 2004 112 17 1755 1760 8 4 2004 23 9 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Pediatric medical and nursing education currently lacks the environmental health content necessary to appropriately prepare pediatric health care professionals to prevent, recognize, manage, and treat environmental-exposure–related disease. Leading health institutions have recognized the need for improvements in health professionals’ environmental health education. Parents are seeking answers about the impact of environmental toxicants on their children. Given the biologic, psychological, and social differences between children and adults, there is a need for environmental health education specific to children. The National Environmental Education and Training Foundation, in partnership with the Children’s Environmental Health Network, created two working groups, one with expertise in medical education and one with expertise in nursing education. The working groups reviewed the transition from undergraduate student to professional to assess where in those processes pediatric environmental health could be emphasized. The medical education working group recommended increasing education about children’s environmental health in the medical school curricula, in residency training, and in continuing medical education. The group also recommended the expansion of fellowship training in children’s environmental health. Similarly, the nursing working group recommended increasing children’s environmental health content at the undergraduate, graduate, and continuing nursing education levels. Working groups also identified the key medical and nursing organizations that would be important in leveraging these changes. A concerted effort to prioritize pediatric environmental health by governmental organizations and foundations is essential in providing the resources and expertise to set policy and provide the tools for teaching pediatric environmental health to health care providers.
educationenvironmental healthmedical studentnursingnursing studentpediatricsresident
==== Body
With the widespread presence of environmental health hazards in our communities, concern about health risks for children has increased among the general public and the media, as well as among public and private organizations. In a national survey of parents, 41% percent stated they “worry a lot” about their children’s exposure to environmental poisons (Stickler and Simmons 1995). In 1998, the U.S. Environmental Protection Agency (EPA) and the National Institute of Environmental Health Sciences established eight Centers for Children’s Environmental Health and Disease Prevention Research, with four more added in 2000. The U.S. EPA and the Agency for Toxic Substances and Disease Registry (ATSDR) fund 11 Pediatric Environmental Health Specialty Units (PEHSUs). The U.S. EPA and ATSDR funded the first three PEHSUs in 1999. Over the past 10–15 years, the number of children’s environmental health advocacy organizations and federal and state commissions and boards on children’s environmental health has increased. The U.S. EPA created an Office of Children’s Health Protection, and in 1997 President Bill Clinton created the President’s Task Force on Children’s Environmental Health and Safety. Furthermore, total costs of environmentally attributable pollutant-related diseases such as lead poisoning, asthma, and cancer in American children is estimated at $54.9 billion annually (Landrigan et al. 2002).
Despite this increased interest and the economic burden, pediatric medical and nursing education currently lacks the environmental health content necessary to appropriately prepare pediatric health care professionals to recognize, manage, and prevent environmental-exposure–related diseases. Although nurses are the largest group of health professionals and the first—and often only—contact with the health care system for many individuals, most nurses have received no formal training in occupational or environmental health, and registered nurses do not feel well prepared to address environmental health issues in their practice, which has not changed much over time (Pope et al. 1995; Rogers 1991, 1994; Van Dongen 2002). Not all medical schools have faculty equipped to provide this training, and in the 75% of schools that require environmental medicine content, there is only an average of 7 hr environmental medicine instruction (Schenk et al. 1996). More than half of surveyed practicing pediatricians have seen a patient with environmental-exposure–related health issues; however, less than one-fifth are trained in taking an environmental history (Kilpatrick et al. 2002). In a separate survey, only 12% stated they gave advice often on environmental poisons (Stickler and Simmons 1995). Fewer than half of U.S. pediatric residency programs routinely include pediatric environmental health issues in their curricula, other than lead poisoning and environmental exacerbation of asthma (Roberts and Gitterman 2003).
Leading health institutions have called for improvements in health professionals’ environmental health education. The Institute of Medicine (IOM) recommends the integration of environmental health concepts into all levels of medical and nursing education and has issued competencies that graduating medical and nursing students should demonstrate, including the ability to take an environmental exposure history, to understand the influence of environmental exposures on human health, and to communicate environmental risks and prevention strategies (IOM 1988, 1991; Pope and Rall 1995; Pope et al. 1995). Several medical and nursing organizations have expressed their support of environmental health education for health care professionals by endorsing the Health Professionals and Environmental Health Education Position Statement [National Environmental Education and Training Foundation (NEETF) 2004; Rogers 2004].
Training of health care providers on the special environmental health issues related to children is almost nonexistent, yet such education is necessary given the biologic, psychological, and social differences between children and adults. To address this need, two working groups of pediatric physicians and nurses conducted an assessment of and identified points of insertion in the current medical and nursing education structures where environmental health content could be incorporated.
Materials and Methods
Because there are so many differences between medical and nursing education, separate working groups with distinct expertise in the respective fields were created to assess each of those areas. Members of the medical and nursing working groups were selected because of their expertise and knowledge about a) environmental health education or medical or nursing education in general, b) accreditation programs and systems, or c) curriculum development.
These working groups met by phone and shared materials electronically. Their task was to describe the two educational processes from undergraduate education to continuing education and to identify potential leverage points that could be used to increase the amount of children’s environmental health information in the education of physicians and nurses. All working group members were involved in all the discussions about all the potential leverage points, irrespective of whether the particular point involved education, accreditation, or curriculum development.
Results and Discussion
In this section we first outline the medical and nursing educational processes, including coursework, clinical practice experiences, and formal examinations. Tables 1 and 2 show medical and nursing education accrediting and licensing organizations. Tables 3 and 4 present the medical and nursing educational processes and leverage points for insertion of pediatric environmental health. We use these outlines to demonstrate how pediatric environmental health content could be most strategically inserted into existing curricula. This is envisioned as a multipronged, ongoing process because no single change will bring about the desired outcome of increased content. The following recommendations should be used to introduce pediatric environmental health education to achieve the standards outlined in the IOM recommendations.
Medical education.
Medical school is the first phase in the education structure of physicians. The curriculum provides instruction in the underlying sciences of medical practice (basic sciences) and in information-gathering, decision-making, and patient-management skills. Students take, and in some schools must pass, step 1 and step 2 of the U.S. Medical Licensing Examination (USMLE), between the second and third years and before graduation from medical school, respectively. Upon successful completion of medical school, students receive their MD degree and undertake the next phase of medical education, residency.
Residency offers physicians an organized educational program with guidance and supervision of the resident to facilitate the resident’s professional and personal development while ensuring safe and appropriate care for patients. Residents take step 3 of the USMLE during or after their first year of residency. A physician interested in a career in pediatric environmental health could choose a residency in one of three specialties: family medicine, pediatrics, or preventive medicine. Residents are prepared to undertake independent medical practice upon satisfactory completion of a residency and can apply to take a certifying examination to certify competency in their specialty.
Fellowships provide an optional, usually 3-year-long period of training after the completion of residency, for subspecialization. Fellowships offer a path to a faculty position in a medical school and/or a residency training program. When a specialty board offers certification in the field, completion of a fellowship can be a step toward certification by a specialty board or subboard. There is no specialty board or specialty certification available in pediatric environmental health. Currently, the Ambulatory Pediatric Association (APA) offers a 3-year pediatric environmental health fellowship training program, and the Cincinnati Children’s Hospital offers the general pediatric research fellowship with a strong emphasis on pediatric environmental health.
In most states, physicians must obtain 150 continuing medical education (CME) credits every three years on any topic they choose to maintain a medical license. Credits can be obtained by attending seminars, lectures, or workshops; by pursuing web-based programs; or by doing research projects, writing manuscripts, or reading material and taking a test.
Recertification ensures that physician specialists remain up-to-date in their specialty by requiring them to pass an exam to remain certified. Physicians certified by the American Board of Pediatrics after 1987 must be recertified every seven years, and those certified by the American Board of Preventive Medicine after 1997 must be recertified every 10 years. Currently, there is no requirement to include children’s environmental health content in the recertifying examinations for pediatrics or preventive medicine.
Nursing education.
To become a nurse, individuals must accomplish one of three undergraduate programs of study: a 2-year associate degree (AA), a 3-year diploma, or a 4-year baccalaureate degree (BSN). The curricula for the AA and diploma programs provide students instruction in the underlying sciences of nursing practice as well as the application of information in clinical settings. Nurses from AA and diploma programs can continue undergraduate nursing education with completion of the BSN. The first 2 years of the baccalaureate curriculum focus on the underlying sciences for practice, and the last 2 years provide opportunities for developing information-gathering, decision-making, and patient-care skills in a broad array of clinical and public health settings, including hospitals, clinics, public health departments, government, and workplace settings.
At the completion of the basic nursing program (AA, diploma, or BSN), graduates must pass the National Council Licensure Examination (NCLEX) to obtain a Registered Nurse (RN) license.
Baccalaureate-educated nurses can go to graduate school to develop advanced knowledge in a particular nursing specialty. Depending on the specialty and outcome focus of the nursing program of study, graduate nursing education curriculum may include advanced basic sciences, evidence-based nursing practice, health policy, advanced nursing assessment, research coursework, clinical coursework, and program planning and evaluation, usually with supervised practicum experiences in the specialty—for example, pediatrics, adult health, and occupational and environmental health.
Upon completion of the master’s degree, nursing graduates of certain clinically focused specialties must become certified by their state board of nursing based on graduation from an approved program and/or completion of the national board exam. National board exams are available for all nurse practitioner specialties, certified nurse midwives, certified nurse anesthetists, and some clinical nurse specialists. There have been significant efforts by nursing leaders to make the board exam requirements consistent across specialties.
Nurses with a master’s degree may continue for doctoral education in a specialty of their choosing. These specialties may or may not be in nursing (e.g., nursing, public health, educational psychology, anthropology, physiology, or other fields may be selected). The doctoral degree generally provides the graduate with advanced knowledge for teaching or research in nursing. There are no further board examinations or certifications for doctoral program graduates.
Nurses may also become certified in their chosen specialty through national nursing specialty certification boards, which generally require examination, experience, and continuing/academic education. National specialty boards offer programs to maintain/renew certification every 5–7 years. Requirements generally include continuing education contact hours at approved courses, self-assessment exercises, practice requirements, and/or retaking the national board examinations. Continuing education course approval is given by specialty organizations and must meet nationally recognized quality standards.
Potential leverage points in medical education.
Table 3 presents medical education and the corresponding points of insertion, strategies, and influential groups for incorporating children’s environmental health.
Medical school.
The working group identified several organizations and strategies that could be used to insert children’s environmental health content into medical schools. These include medical students and medical-student organizations, the creation of designated faculty leaders within schools of medicine, the Association of American Medical Colleges (AAMC), the Liaison Committee on Medical Education (LCME), and the National Board of Medical Examiners (NBME).
Medical students and medical-student organizations have some influence over the curriculum of their own medical school (Atkins et al. 1998; Grayson et al. 1999; Rollins et al. 1999). Students can promote the addition of children’s environmental health curricular elements and case studies at their medical schools through course evaluations and representation on curricular committees (Steyer et al. 2003). Students may also introduce topics through noncredit courses and activities, such as with the modules and tool kits on various topics provided by the American Medical Student Association or the idea book of projects issued by the American Medical Association (AMA) student section. Educating medical students on environmental health will prepare them to promote this issue at their medical schools.
Medical school faculty members are key to implementing curricula and influencing career choices of students by setting examples and providing direct counseling (Goldman et al. 1999; Schwartz et al. 1995). There should be a concentrated effort to develop qualified faculty members at pediatric training programs. The role of a faculty leader in pediatric environmental health would be to coordinate all children’s environmental health activities at the school, teach appropriate curricular material, provide case material that could be used in courses taught by others, and coordinate with colleagues around the country. Primary-care residency faculty trained in environmental/occupational health can increase the environmental/occupational health education offered at their schools (Frazier et al. 1999). Faculty leaders that have an interest in teaching environmental health are essential to integrating environmental health content into the curriculum and provide the impetus for change throughout a program. In several studies about how to integrate prevention-related topics, a key determinant of success was shown to be faculty and institutional leadership (Lindberg 1998; Sachdeva 2000; Skochelak et al. 2001; Susman and Pascoe 2001).
The AAMC, LCME, and NBME have no direct input into medical school curricula. The AAMC, however, sponsors regional meetings where innovative curricular activities are presented to others for consideration. Similar presentations are also made at APA meetings. It is recommended that faculty members teaching children’s environmental health or using children’s environmental health case material submit abstracts to present their activities at these meetings.
Residency training.
At the residency training level, leverage points include directors of residency education, pediatric department chairs, chief residents, residency review committees, and pediatric primary care education guidelines. Chief residents have influence within each residency-training program over the scheduling of conferences and educational activities and could require all residents to complete education on children’s environmental health. The American Academy of Pediatrics (AAP), with funding from the U.S. EPA, has created a 1-day program to train pediatric chief residents about children’s environmental health.
Pediatric residency review committees (RRC) can play a role in increasing children’s environmental health by requiring pediatric residency education to include children’s environmental health content. For programs that do not have faculty members qualified to teach that content, a web-based self-instructional module could be developed for residents, similar to the ATSDR’s web-based continuing education case studies. The ATSDR and U.S. EPA, through their cooperative agreement with the Association of Occupational and Environmental Clinics (AOEC), could task a PEHSU with developing and disseminating such a module. Training programs regarding the content and use of the module could be developed for residency program directors and chief residents.
Another strategy is to include teaching about children’s environmental health in the guidelines for pediatric primary care education. In one academic setting, the incorporation of a pediatric environmental health course resulted in physicians’ increased consideration of environmental causes for illness (Bearer and Phillips 1993). The APA has developed a set of guidelines for pediatric primary care education at the residency level and could include children’s environmental health in future iterations, possibly drawing from the competencies that the APA developed for specialists in pediatric environmental health, described below.
Fellowships and specialty certification.
Another strategy to prepare more experts in the field, who could meet growing patient demand and train the next generation of pediatricians, is to increase the number of fellows in pediatric environmental health. The Centers for Children’s Environmental Health and Disease Prevention Research and the PEHSUs could provide the platforms upon which to build these fellowship programs. In 2003, the APA published a list of competencies for specialists in pediatric environmental health (Etzel et al. 2003). Twenty-seven competencies, each accompanied by a list of suggested performance indications, were developed under three separate perspectives: academic, individual patient care, and community advocacy. These competencies are intended to help structure the training experience, achieve consensus with respect to expectations of fellows and faculty, provide opportunities for fellows to assess their own needs or gaps in training, and identify the expertise of fellowship graduates to potential employers.
The creation of a specialty board offering certification in pediatric environmental health serves as a leverage point to formalize pediatric environmental health as a subspecialty and allow physicians to specialize and become leaders in the field. The American Board of Preventive Medicine (ABPM) offers specialty certification in occupational medicine or general preventive medicine, and the American Board of Emergency Medicine, the American Board of Pediatrics (ABP), and the ABPM have a subboard in medical toxicology. Some physicians choose one of these specialties as a route to a career in pediatric environmental health. The ABP and/or the ABPM could seek permission from the American Board of Medical Specialties (ABMS) to develop a sub-board in pediatric environmental health.
Continuing medical education.
CME is a means to provide environmental health education to physicians postresidency and at later stages in their careers. CME on environmental health issues, such as environmental asthma triggers, has been effective in improving the health of patients and decreasing associated medical costs (Clark et al. 2000). The PEHSUs currently provide some CME activities; however, this working group recommends increasing the opportunities for practicing physicians, nurse practitioners, and other child health care providers to learn about children’s environmental health. Professional organizations, such as the AAP, the APA, the American Public Health Association (APHA), and other nongovernmental organizations, could provide children’s environmental health CME programming.
Pediatric practice.
Medical insurance companies influence medical practice. If services are reimbursable, they are more likely to be offered to patients. Fellowships can be funded in part from service-related income. The organizations involved in children’s environmental health, such as the AAP and the AOEC, should request reimbursement from insurance companies for environmentally related health care services provided to children and should lobby state legislatures and state insurance boards for such coverage.
Potential leverage points in nursing education.
Table 4 shows the steps in nursing education and corresponding points of insertion, strategies, and influential groups for inserting children’s environmental health.
Undergraduate nursing education.
Many undergraduate nursing education organizations and groups could introduce children’s environmental health content into nursing curricula: nursing students and nursing-student organizations, the National League for Nursing Accrediting Commission (NLNAC), and the Commission on Collegiate Nursing Education (CCNE).
Nursing students have influence over the content of the curriculum in their schools. Nursing-student organizations, by linking students in various schools and providing information at meetings for students to take back to their schools, can influence the curricular content. Nursing professionals and environmental organizations interested in children’s environmental health should strive for input into local, regional, and national nursing student groups to teach them about the importance of this topic. One existing effort in this realm is the AOEC’s sponsorship of two focus sessions on occupational and environmental health nursing at the National Student Nurses Association annual meeting.
NLNAC and CCNE should work to include examples of children’s environmental health issues throughout the undergraduate nursing curriculum. For example, cases related to children’s environmental health could be used for curriculum content on epidemiology that all nursing students take. Case studies covering a number of issues are available through the AOEC, the Great Lakes Center for Occupational and Environmental Safety and Health, and the ATSDR.
When nursing students do their fieldwork, they should be encouraged to work with local and regional agencies that focus on children’s environmental health issues.
AA, diploma, and baccalaureate degree nurses must pass the NCLEX to be licensed to practice as an RN. Influencing the NCLEX’s content is difficult because content is determined by a survey of the work of practicing nurses, and most practicing nurses have limited environmentally related activities in their day-to-day nursing activities. However, as practice changes to embrace environmental health content, the inclusion of environmental-health–related questions will influence curricula.
As in medical education, nursing faculty with pediatric environmental health background can significantly influence curricular content and practice activities at the undergraduate, graduate, and continuing nursing education levels. Development of children’s environmental health nursing faculty leaders is essential.
Graduate nursing education and certification.
The National Organization of Nurse Practitioner Faculties (NONPF) and the Association of Faculties of Pediatric Nurse Practitioner Programs should use their influence on the curricula and standards for education and competencies to increase children’s environmental health content in the programs for advanced practice nurses. For example, a competency requirement on environmental health education has been accepted by NONPF, which could expand this activity and ensure its inclusion in the curriculum of all nurse practitioner programs.
Organizations such as the Pediatric Nursing Certification Board (PNCB); the American Nurses Credentialing Center; the National Certification Corporation for Obstetrical, Gynecological, and Neonatal Nurses; the American College of Nurse Midwives; and the American Board of Occupational Health Nurses, which develop the certifying examinations for their respective specialties, should include children’s environmental health material in their examinations. Environmental health was included in a recent PNCB self-assessment exercise for certification maintenance of pediatric nurse practitioners.
Continuing nursing education.
As with CME, continuing education for nurses is a key point at which to educate nurses about pediatric environmental health. One such example is the innovative children’s environmental health continuing education program conceived by the University of Maryland School of Nursing Environmental Health Education Center in conjunction with the American Nurses Association. It should be expanded to include other topics and repeated on a regular basis to provide education to newly trained nurses or nurses with a newly identified interest in children’s health and the environment. Organizations such as APHA, the National Association of Pediatric Nurse Practitioners, and the School Nurses Association, should sponsor pre- or postconference workshops on children’s health and the environment for nurses at their annual conferences. The train-the-trainer format would be a useful technique for spreading children’s environmental health expertise.
Conclusion
We have identified several strategic opportunities to incorporate much-needed pediatric environmental health into the existing medical and nursing education process. Medical, nursing, and public health organizations, as well as patients, have expressed the need for health care providers to be better equipped to recognize and treat environmentally caused illness. We provide this comprehensive list of insertion points to guide medical and nursing education accrediting bodies, licensing bodies, and other key personnel that determine and influence medical and nursing curricula. Future efforts in this area should include evaluation of the existing pediatric environmental health education programs to determine the most effective formats for incorporating this subject. In addition, because knowledge and research in many areas of children’s environmental health are still developing, future efforts should focus on ensuring curriculum development and updates as the field advances. A concerted effort to prioritize pediatric environmental health by governmental organizations and foundations will be essential in providing the resources and expertise to set policy and provide the tools for teaching pediatric environmental health to health care providers.
Appendix 1: Medical and Nursing Education Working Groups
The following individuals participated in the review of medical education opportunities: Rob Amler, MD, MS—(then) Chief Medical Officer, ATSDR; Lois Colburn—Assistant Vice President for Minority and Community Programs, AAMC (Curriculum Development); Susan Cummins, MD, MPH—(then) Director, Board of Children Youth and Families, National Academy of Sciences, IOM; Deborah Danoff, MD—Assistant Vice President for Medical Education, AAMC; Ruth Etzel, MD, PhD—George Washington University School of Public Health and Health Services; Leyla Erk McCurdy, MPhil—National Environmental and Education Training Foundation, Project Director; Jerome A. Paulson, MD—(then) Soros Fellow, Children’s Environmental Health Network, and Co-director, Mid-Atlantic Center for Children’s Health and the Environment, Region 3 PEHSU; James Roberts, MD, MPH—Assistant Professor, Department of Pediatrics, Medical University of South Carolina; Chris Rosheim, DDS, MPH—(then) Health Education Specialist, ATSDR; Bernhard L. Wiedermann, MD—Associate Professor and Vice Chair for Education, Department of Pediatrics, George Washington University School of Medicine, and Director, Medical Education and Pediatric Residency Training Program, Children’s National Medical Center, Washington, DC.
The following individuals participated in the review of nursing education opportunities: Robert Atkins, MSN, CRNP—Director of Pediatric Nurse Practitioner Program, Temple University, Department of Nursing; Cathie Burns, PhD, RN, CPNP—Professor Emeritus, School of Nursing, Oregon Health Sciences University; Hurdis Griffith, PhD, RN—Dean of Rutgers School of Nursing; Barbara Kelley, EdD, MPH, MS—Associate Professor and Director for Graduate Nursing Program Northeastern University; Rita Lourie, MSN, RN—Director of Academic and Community Outreach, Temple University, Department of Nursing; Leyla Erk McCurdy, MPhil—National Environmental and Education Training Foundation; Grace K. Paranzino, MS, RN, CHES, FAAOHN—Assistant Professor, Drexel University School of Medicine, Department of Family, Community and Preventive Medicine, and Adjunct Assistant Professor, Department of Environmental and Occupational Health, Drexel University School of Public Health; Dorothy Powell, EdD, RN, FAAN—Associate Dean, College of Pharmacy, Nursing, and Allied Health Sciences, Howard University/Director Mississippi Delta Project; Bonnie Rogers, DrPH, COHN-S, FAAN—Director of Occupational/Health Safety and Nursing Programs, University of North Carolina School of Public Health; Izzat Sbeih, MPH—Health Policy Analyst, American Public Health Association.
Table 1 Organizations involved with medical accreditation and licensing.
Organization Function Consisting of representatives from Subsidiary organizations
Liaison Committee on Medical Education (LCME) Review and approval of medical school curricula; accreditation of medical schools American Medical Association (AMA); Association of American Medical Colleges (AAMC)
National Board of Medical Examiners (NBME) Development of U.S. medical licensing examination
Accreditation Council for Graduate Medical Education (ACGME) Development of methods to evaluate and promote the quality of graduate medical education; accreditation of programs in graduate medical education according to established standards AAMC; AMA; American Board of Medical Specialties (ABMS); American Hospital Association (AHA); Council of Medical Specialty Societies (CMSS) Residency review committees
Residency review committees (RRC): each specialty has a corresponding RRC Accreditation review of residency training programs; review and revision of specialty requirements Corresponding specialty board (American Board of Pediatrics and American Academy of Pediatrics for the pediatric RRC); AMA Council on Medical Education
American Board of Medical Specialties (ABMS) Assist specialty boards to promote the quality and efficiency of the process of evaluating and certifying physician specialists; act as spokesperson for specialty boards Specialty boards
Specialty boards Provide comprehensive exams; certify those who have satisfied requirements
Accreditation Council for Continuing Medical Education (ACCME) Promote and develop principles, policies, and standards for CME and apply them to the accreditation of institutions and organizations offering CME ABMS; AHA; AMA; AAMC; CMSS; Association for Hospital Medical Education; Federation of State Medical Boards; nonvoting members: resident physician section of AMA; U.S. Department of Health and Human Services; chair of the residency committee council
Table 2 Organizations involved with academic or legislated programs to assure quality of nursing practice.
Organization Function Consisting of representatives from
National League for Nursing Accrediting Commission (NLNAC) Approve nursing programs of study Independent body derived from the National League of Nursing
Commission on Collegiate Nursing Education (CCNE) Approve baccalaureate and graduate nursing curriculum, faculty, administration, and programs Independent body derived from the American Association of Colleges of Nursing
National Council of State Boards of Nursing (NCSBN) Administration of National Council Licensure Examination–RN State boards of nursing
State boards of nursing Provide licensure for registered nurses and certification for nurse practitioners, certified nurse midwives, and other graduate specialties that must be legally certified to practice in the state
Specialty boards
Pediatric Nursing Certification Board (PNCB) Professional certification of pediatric nurse practitioners and nurse specialists American Academy of Pediatrics; Association of Faculties of Pediatric Nurse Practitioners; National Association of Pediatric Nurse Practitioners; Society of Pediatric Nurses
American Nurses Credentialing Center (ANCC) Professional certification of pediatrics, adult, family, and geriatrics nurse practitioners
American Academy of Nurse Practitioners (AANP) Professional certification of adult and family nurse practitioners
National Certification Corporation for Obstetrical, Gynecological, and Neonatal Nurses (NCC) Professional certification of women’s health care nurse practitioners
American College of Nurse-Midwives (ACNM) Professional certification of certified nurse midwives
Nurse practitioner faculty organizations
National Organization of Nurse Practitioner Faculties (NONPF) Influence on curricula and standards for education/competencies for nurse practitioner programs and their graduates Faculty from all nurse practitioner specialties
Association of Faculties of Pediatric Nurse Practitioners (AFPNP) Influence on curricula and standards for education/ competencies for pediatric nurse practitioner programs and their graduates Faculty from pediatric nurse practitioner programs
Table 3 Medical education structure and leverage points for insertion of pediatric environmental health.
Medical education Leverage points
Medical school (MD curriculum) Association of American Medical Colleges, faculty, National Board of Medical Examiners (NBME), Liaison Committee on Medical Education, students, student organizations
Residency Accreditation Council for Graduate Medical Education (ACGME), American Board of Medical Specialties (ABMS), chief residents, directors of residency education, NBME, pediatric department chairs, primary care pediatric education guidelines, residency review committees, specialty boards
Fellowship (optional) ABMS, fellowships, specialty boards
Continuing medical education (CME) Accreditation Council for Continuing Medical Education (ACCME) professional organizations that provide CME
Recertification Specialty boards
Table 4 Nursing education structure and leverage points for insertion of pediatric environmental health.
Nursing education Leverage points
Undergraduate nursing education National League for Nursing Accrediting Commission, Commission on Collegiate Nursing Education, students, student organizations, National Student Nurse Association, nursing professionals and faculty, fieldwork, specialty organizations
Associate degree, diploma, baccalaureate degree
Graduate nursing education Pediatric Nursing Certification Board; American Nurses Credentialing Center; National Certification Corporation for Obstetrical, Gynecological, and Neonatal Nurses; National Organization of Nurse Practitioner Faculties; Association of Faculties of Pediatric Nurse Practitioner Programs; specialty organizations
Master’s degree (nurse specialists, nurse practitioner, certified nurse midwife, certified nurse anesthetist)
Doctoral degree Specialty organizations
Continuing education Specialty organizations, workshops at conferences
==== Refs
References
Atkins KM Roberts AE Cochran N 1998 How medical students can bring about curricular change Acad Med 73 11 1173 1176 9834699
Bearer CF Phillips R 1993 Pediatric environmental health training. Impact on pediatric residents Am J Dis Child 147 6 682 684 8506840
Clark NM Gong M Schork MA Kaciroti N Evans D Roloff D 2000 Long-term effects of asthma education for physicians on patient satisfaction and use of health services Eur Respir J 16 1 15 21 10933079
Etzel RA Crain EF Gitterman BA Oberg C Scheidt P Landrigan PJ 2003 Pediatric environmental health competencies for specialists Ambul Pediatr 3 60 63 12540257
Frazier LM Berberich NJ Moser R Jr Cromer JW Jr Hitchcock MA Monteiro FM 1999 Developing occupational and environmental medicine curricula for primary care residents: project EPOCH-Envi. Educating Physicians in Occupational Health and the Environment J Occup Environ Med 41 8 706 711 10457515
Goldman RH Rosenwasser S Armstrong E 1999 Incorporating an environmental/occupational medicine theme into the medical school curriculum J Occup Environ Med 41 1 47 52 9924720
Grayson MS Newton DA Klein M Irons T 1999 Promoting institutional change to encourage primary care: experience at New York Medical College and East Carolina University of Medicine Acad Med 74 suppl 1 S9 S15 9934303
IOM (Institute of Medicine) 1988. Role of the Primary Care Physician in Occupational and Environmental Medicine. Washington, DC:National Academy Press.
IOM (Institute of Medicine) 1991. Addressing the Physician Shortage in Occupational and Environmental Medicine. Washington, DC:National Academy Press.
Kilpatrick N Frumkin H Trowbridge J Escoffery C Geller R Rubin I 2002 The environmental history in pediatric practice: a study of pediatricians’ attitudes, beliefs, and practices Environ Health Perspect 110 823 827 12153766
Landrigan PJ Schechter CB Lipton JM Fahs MC Schwartz J 2002 Environmental pollutants and disease in American children: estimates of morbidity, mortality, and costs for lead poisoning, asthma, cancer, and developmental disabilities Environ Health Perspect 110 721 728 12117650
Lindberg MA 1998 The process of change: stories of the journey Acad Med 73 S4 S10 9759112
NEETF 2004. Health Professionals and Environmental Health Education Position Statement. Washington, DC:National Environmental Education and Training Foundation. Available: http://www.neetf.org/Health/PositionStatement2.pdf [accessed 25 October 2004].
Pope AM Rall DP eds, for Committee on Curriculum Development in Environmental Medicine, Institute of Medicine. 1995. Environmental Medicine: Integrating a Missing Element into Medical Education. Washington, DC:National Academy Press.
Pope AM Snyder MA Mood LH eds, for Committee on Enhancing Environmental Health Content in Practice, Institute of Medicine. 1995. Nursing, Health, and the Environment: Strengthening the Relationship to Improve the Public’s Health. Washington, DC:National Academy Press.
Roberts JR Gitterman BA 2003 Pediatric environmental health education: a survey of US pediatric residency programs Ambul Pediatr 3 1 57 59 12540256
Rogers B 1991 Occupational health nursing education: content in baccalaureate programs AAOHN J 39 3 101 108 2001270
Rogers B 1994 Linkages in environmental and occupational health: assessing, detecting, and containing exposure sources AAOHN J 42 7 336 343 8060398
Rogers B 2004 Environmental health hazards and health care professional education AAOHN J 52 4 154 155 15119813
Rollins LK Lynch DC Owen JA Shipengrover JA 1999 Moving from policy to practice in curriculum change at the University of Virginia School of Medicine, East Carolina University School of Medicine, and SUNY-Buffalo School of Medicine Acad Med 74 suppl 1 S104 S111 9934319
Sachdeva AK 2000 Faculty development and support needed to integrate the learning of prevention in the curricular of medical schools Acad Med 75 suppl 7 S35 S42 10926039
Schenk M Popp SM Neale AV Demers RY 1996 Environmental medicine content in medical school curricula Acad Med 71 499 501 9114870
Schwartz BS Pransky G Lashley D 1995 Recruiting the occupational and environmental medicine physicians of the future: results of a survey of current residents J Occup Environ Med 37 6 739 743 7670921
Skochelak S Barley G Fogarty J 2001 What did we learn about leadership in medical education? Effecting institutional change through the Interdisciplinary Generalist Curriculum Project Acad Med 76 suppl 4 S86 S90 11299176
Steyer TE Ravenell RL Mainous AG III Blue AV 2003 The role of medical students in curriculum committees Teach Learn Med 15 4 238 241 14612255
Stickler GB Simmons PS 1995 Pediatricians’ preference for anticipatory guidance topics compared with parental anxieties Clin Pediatr 34 7 384 387
Susman J Pascoe J 2001 Recommendations to Institutions Acad Med 76 suppl 4 S137 S139 11299187
Van Dongen CJ 2002 Environmental health and nursing practice: a survey of registered nurses Appl Nurs Res 15 2 67 73 11994822
|
15579423
|
PMC1253669
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec 23; 112(17):1755-1760
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7166
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science 10.1289/ehp.7287ehp0112-00176115579424Children's HealthArticlesPrenatal DDT Exposure in Relation to Anthropometric and Pubertal Measures in Adolescent Males Gladen Beth C. 1Klebanoff Mark A. 2Hediger Mary L. 2Katz Solomon H. 3Barr Dana B. 4Davis Mark D. 4Longnecker Matthew P. 11National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA2National Institute of Child Health and Human Development, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA3Krogman Center for Research in Child Growth and Development, University of Pennsylvania, Philadelphia, Pennsylvania, USA4National Center for Environmental Health, Centers for Disease Control and Prevention, Department of Health and Human Services, Atlanta, Georgia, USAAddress correspondence to B.C. Gladen, Biostatistics Branch, Mail Drop A3-03, National Institute of Environmental Health Sciences, P.O. Box 12233, Research Triangle Park, NC 27709 USA. Telephone: (919) 541-3461. Fax: (919) 541-4311. E-mail:
[email protected] authors declare they have no competing financial interests.
12 2004 7 9 2004 112 17 1761 1767 25 5 2004 7 9 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. DDT (dichlorodiphenyltrichloroethane), a pesticide once used widely in agriculture and now limited to public health use, remains a controversial chemical because of a combination of benefits and risks. DDT or its breakdown products are ubiquitous in the environment and in humans. Compounds in the DDT family have endocrine actions and have been associated with reproductive toxicity. A previous study reported associations between prenatal exposure to p,p′-DDE [1,1-dichloro-2,2-bis(p-chlorophenyl)-ethylene] and increased height and weight in adolescent boys. We examined a group with higher exposures to see whether similar associations would occur. Our study group was 304 males born in Philadelphia in the early 1960s who had participated in a previous study. Anthropometric and pubertal measures from one to six visits during their adolescent years were available, as were stored maternal serum samples from pregnancy. We measured p,p′-DDE, p,p′-DDT [1,1,1-trichloro-2,2-bis(p-chlorophenyl)-ethane], and o,p′-DDT [1,1,1-trichloro-2-(o-chlorophenyl)-2-(p-chlorophenyl)-ethane] in the maternal serum. Outcomes examined in the boys were height, ratio of sitting height to height, body mass index, triceps skinfold thickness, ratio of subscapular to the sum of triceps and subscapular skinfold thicknesses, skeletal age, serum testosterone, and serum dehydroepiandrosterone sulfate. No associations between prenatal exposure to any of the DDT compounds and any outcome measure were seen.
child developmentDDEDDTgrowthprenatal exposure delayed effectspuberty
==== Body
The combination of public health benefits and environmental risks associated with DDT has made use of the pesticide controversial (Walker et al. 2003). DDT was once used extensively throughout the world, for both agricultural and public health purposes [Agency for Toxic Substances and Disease Registry (ATSDR) 2002]. Use today is generally limited to vector control, primarily of malaria, and is covered as of May 2004 by the Stockholm Convention on Persistent Organic Pollutants, a treaty signed by 151 countries and currently ratified by more than 75 countries (Stockholm Convention on Persistent Organic Pollutants 2004). Decisions in any specific instance about whether to use DDT even for vector control can be hotly debated (Wendo 2004).
Use of DDT in the United States began in the 1940s, peaked in the early 1960s, and essentially ended in 1972. Timelines in other countries differed but generally followed the same pattern of steep rise and fall in amounts used. Despite the decline in use, several components and breakdown products of the pesticide are still widely detectable in the environment and in humans (Jaga and Dharmani 2003; Smith 1999). The pesticide product consists primarily of the actual insecticide p,p′-DDT [1,1,1-trichloro-2,2-bis(p-chlorophenyl)-ethane], with o,p′-DDT [1,1,1-trichloro-2-(o-chlorophenyl)-2-(p-chlorophenyl)-ethane] and several other minor components making up the remainder (ATSDR 2002). The primary degradation product and human metabolite of p,p′-DDT is p,p′-DDE [1,1-dichloro-2,2-bis(p-chlorophenyl)-ethylene]; the latter is also the most persistent member of the DDT family and the one that bioaccumulates most extensively in humans.
The various components of the DDT family have a number of known biologic actions. The insecticidal effects of p,p′-DDT are attributable to neurotoxicity. A number of endocrine effects have been shown, including antiandrogenic properties of p,p′-DDE (Gray et al. 2001), estrogenic properties of o,p′-DDT (Kupfer 1975), and modulation of steroid hormone homeostasis through induction of hepatic enzymes (Wyde et al. 2003; You et al. 2001). Changes in immune markers have been seen (Vine et al. 2001). Carcinogenicity has been demonstrated in animals, although evidence in humans is mixed (Turusov et al. 2002). Associations with impaired lactation have been reported (Gladen and Rogan 1995; Rogan et al. 1987). Reproductive effects have been shown as well. A large human study has shown associations of maternal p,p′-DDE with preterm birth and decreased birth weight (Longnecker et al. 2001). Animal studies with p,p′-DDE show a number of reproductive abnormalities in male offspring (Gray et al. 2001); whether similar effects are seen in humans at usual exposure levels is uncertain (Flores-Luévano et al. 2003; Hosie et al. 2000; Longnecker et al. 2002). Paternal occupational DDT exposure has also been associated with birth defects (Salazar-García et al. 2004).
Prenatal exposure to DDT can also have delayed effects. There are reports of neurotoxic and immunotoxic effects in young children (Dewailly et al. 2000; Ribas-Fitó et al. 2003), although not all studies show such effects (Gladen et al. 1988; Rogan et al. 1987). At even later ages, prenatal and lactational exposure to p,p′-DDE in animals has been associated with delayed male puberty in some but not all studies (Loeffler and Peterson 1999; You et al. 1998).
A previous human study showed that adolescent males with higher prenatal exposure to p,p′-DDE had increases in both height and body mass index (BMI) compared with those with lower exposures; markers of puberty were unaffected (Gladen et al. 2000). In view of the continuing controversy about DDT and concerns about substantial increases in childhood obesity (Ogden et al. 2002), we examined another population with higher exposures to see whether similar effects in adolescent males would be seen there.
Materials and Methods
Subjects.
The Collaborative Perinatal Project (CPP) was a large multicenter prospective study of approximately 50,000 children born between 1959 and 1966 (Broman 1984; Hardy 2003). Data collected included background information on the mothers obtained from questionnaires during pregnancy. Serum samples taken from the mothers during pregnancy were stored, and many are still available.
The Philadelphia Blood Pressure Project (PBPP) followed some of the children enrolled at one of the CPP centers during adolescence and early adulthood (Katz et al. 1980). This was an urban population; the children had been born at Pennsylvania Hospital and followed at Children’s Hospital of Philadelphia. Several subgroups were chosen for study; one was a stratified random sample of those enrolled in the CPP who were born between 1961 and 1965. These subjects were seen annually up to three times in 1977–1980 and again annually up to another three times in 1982–1985. Data collected included anthropometric measurements and pubertal markers.
The subjects of the present study were chosen from among the 373 singleton males from the random sample studied in the PBPP. Of those, 314 had stored maternal samples from the third trimester available. Those samples were shipped to the Centers for Disease Control and Prevention and analyzed for several DDT compounds. Of the samples shipped, nine had insufficient quantity for analysis, one was lost during analysis, and 304 were successfully analyzed. The 304 boys whose maternal samples were analyzed are the subjects of this report.
Primary variables.
Anthropometric measurements up to 20 years of age from the PBPP were used; data from a total of 1,137 visits from the 304 boys were available. Measurement techniques and reliabilities have been discussed previously (Katz et al. 1980; Tanner et al. 1969). Quantities measured at all visits included height, sitting height, weight, triceps skinfold thickness, and subscapular skinfold thickness. Height and sitting height were measured using a Holtain stadiometer (Holtain Ltd., Crymych, Wales). Weight was measured on a Health-O-Meter beam balance scale (Health-O-Meter, Bridgeview, IL). Skinfolds were measured using a Holtain skinfold caliper. We examined several measures of overall size and body proportion: height, the ratio of sitting height to height (height ratio), BMI, triceps skinfold thickness, and the ratio of subscapular to the sum of sub-scapular and triceps skinfold thicknesses (a measure of central adiposity). Missing data were minimal: Height was unavailable four times, sitting height 14 times, weight seven times, triceps skinfold thickness four times, and sub-scapular skinfold thickness seven times.
Skeletal age was determined at the three PBPP visits in 1977–1980, using the Tanner-Whitehouse II method of rating hand–wrist radiographs on the maturity of 20 individual bones (Katz et al. 1980; Tanner et al. 1975). Skeletal age was unavailable for 4% of the visits where it was scheduled to be done.
Testosterone was measured at the first two PBPP visits in 1977–1979 by radio-immunoassay on samples of venous blood collected at the time of examination (Furuyama et al. 1970; Zemel and Katz 1986). Dehydroepiandrosterone sulfate (DHEAS) was measured only at the second visit in 1978–1979, again by radioimmunoassay (Buster and Abraham 1972). Not all boys volunteered for the blood draw; testosterone was unavailable for 23% of the visits where it was scheduled to be done, and DHEAS was unavailable in 22%.
Maternal serum samples were analyzed for p,p′-DDE, p,p′-DDT, and o,p′-DDT using a semiautomated solid-phase extraction and gel permeation chromatography cleanup followed by an isotope dilution gas chromatography–high resolution mass spectrometry analysis (Barr et al. 2003; Sandau et al. 2003). Recovery correction was done for each analyte in each individual sample. For 25 samples, p,p′-DDT could not be measured because of quality control limit failure. Cholesterol and triglycerides were also measured using standard clinical assays. Total serum lipids were calculated as 62.3 + 2.27 cholesterol + triglycerides (Phillips et al. 1989). Pesticide concentrations were reported as nanograms of pesticide per gram total serum lipids. The sum of the three DDT compounds was calculated, unless p,p′-DDT could not be measured. Samples with nondetectable amounts for o,p′-DDT or p,p′-DDT were considered to be zero; because detection limits were low, imputing any other value up to the detection limit changed the sum of DDT by < 1% and never changed the categories when exposure was categorized.
Statistical analysis.
We used models to examine outcome measurements in relation to pesticide concentration after adjustment for important predictors and potential confounders. The age of the boy at examination is a key predictor and was included as a cubic polynomial to allow for nonlinearity. Parental size is also a strong predictor of child size; maternal height and prepregnancy BMI were available and were included as linear terms, but paternal size was not available. We also adjusted for breast-feeding (yes, no), maternal smoking at the time of pregnancy (yes, no), number of older siblings (0, 1, ≥ 2), race (African American, white), maternal age at birth (13–19, 20–24, 25–29, ≥ 30 years), and maternal age at menarche (8–11, 12, 13, ≥14 years). We used the family socioeconomic index (SEI) score, based on education, occupation, and income, created by the CPP investigators for internal comparisons (Myrianthopoulos and French 1968). Median SEI for the entire CPP was 4.3, with a range from 0 to 9.5; scores here were categorized into three groups (0–2.5, 2.6–5.0, ≥5.1). A term for each boy was included as a random effect to account for the correlation among multiple measures of the same boy. For triceps skinfold thickness and testosterone, the analysis was done on a log scale. Tests of statistical significance reported are either tests of whether categories differ for discrete predictors or tests for zero slope for continuous predictors. Models were fit using SAS version 9 (SAS Institute Inc., Cary, NC).
Results
Most of the 304 boys in this study were African American (Table 1). Most of their mothers reported smoking during pregnancy, and few mothers breast-fed their sons. One-quarter of the boys were first-born. The distribution of family SEI was similar to that of all African Americans in the CPP. Other characteristics of the mother and family around the time of birth are shown in Table 1.
Concentrations of p,p′-DDE in maternal serum during pregnancy ranged from 1 to 25 μg/g lipid (Table 2), with a median of 5.7 μg/g lipid. The other two DDT compounds were present at lower concentrations; median p,p′-DDT was 1.9 μg/g lipid, and median o,p′-DDT was 0.14 μg/g lipid. The three compounds measured were correlated; the correlation of p,p′-DDE with p,p′-DDT was 0.65 and with o,p′-DDT was 0.58, whereas p,p′-DDT and o,p′-DDT had a correlation of 0.77.
The boys had from one to six adolescent visits with anthropometric measurements available; 20% had one or two, 34% had three, and 47% had four or more. Age at the first measurement ranged from 10.8 to 17.9 years, with a median of 12.8 years. Age at the last measurement ranged from 12.2 to 20.0 years, with a median of 17.6 years. Age at first measurement was a major determinant of number of measurements, because those who were older at the start of follow-up left the age range of interest more quickly. In addition, no whites had more than three visits.
Height ranged from 132 to 196 cm, with the expected strong relationship to age. Selected percentiles at each age are shown in Table 3. Height ratio ranged from 46 to 55%. BMI was skewed, ranging from 14 to 45 kg/m2. Triceps skinfold was more skewed, ranging from 3.5 to 43.4 mm. Central adiposity ranged from 31 to 78%.
The boys also had up to three measures of skeletal age; 66% had all three measurements, and two boys had none. Skeletal age ranged from 8.7 to 18 years. In addition, 260 boys had one or two testosterone measurements available, and 213 had a single measurement of DHEAS. Testosterone ranged from 1 to 1,258 ng/dL; DHEAS ranged from 56 to 5,600 ng/mL.
The crude relationships of these anthropometric and pubertal measures to maternal prenatal concentrations of p,p′-DDE are shown in Table 4 for several age ranges. Not all boys had measurements available in all age ranges; for skeletal ages and hormones, there were few measurements past 17 years of age. Little systematic relationship to p,p′-DDE was seen for any of the measures.
Models as described above were fit to these measures to allow age to be treated as a continuous predictor and to adjust for other predictors and potential confounders (Table 5). In no case was p,p′-DDE a statistically significant predictor of the outcome (all p > 0.10). Effects of other predictors were seen. All outcomes were significantly related to the age of the boy at measurement (data not shown). Height also increased with maternal height (p < 0.001) and maternal BMI (p = 0.053); first-born boys also had higher means (p = 0.043), as did those from families with higher SEI (p = 0.094). Height ratio decreased with maternal height (p < 0.001); whites also had larger means (p < 0.001), as did later-born children (p = 0.063) and those whose mothers had early menarche (p = 0.095). BMI increased with maternal BMI (p < 0.001). Triceps skinfold increased with maternal BMI (p < 0.001); first-born boys (p = 0.037) and whites (p = 0.056) had higher means. Mean central adiposity was higher in African Americans (p = 0.002). Testosterone was increased among those whose mothers had early menarche (p = 0.052) and those from families with higher SEI (p = 0.092). Skeletal age and DHEAS showed no significant effects of predictors other than age of the boy.
Use of p,p′-DDT, o,p′-DDT, or the sum of the three compounds rather than p,p′-DDE as the exposure also resulted in no significant effects on any of the outcomes analyzed (data not shown). When the analysis shown in Table 5 was done separately for each of the age groups used in Table 4, the results were again not significant with one exception. At the youngest ages, the five exposure groups had significantly different BMIs, but the pattern was not monotonic in dose; as with the crude results in Table 4, the highest BMIs were seen for the 3–6 μg/g dose group. If the analysis shown in Table 5 is restricted to African Americans, the results are essentially unchanged (data not shown).
Discussion
In this study, we found no association of pre-natal exposure to p,p′-DDE, p,p′-DDT, or o,p′-DDT with any of the anthropometric or pubertal measures we examined in adolescent males. In a previous study of 278 adolescent boys and 316 girls, prenatal p,p′-DDE exposure was also not related to pubertal markers (Gladen et al. 2000). However, increased exposure in that study was associated with greater height and BMI of the boys. The subjects of the present study, who were born during the peak of DDT use in the United States, had higher exposures than those in the previous study, who were born after agricultural DDT use had been banned. Median p,p′-DDE in maternal serum in the present study was 5.7 μg/g serum lipid; the median in the previous study was approximately equivalent to 1.6 μg/g serum lipid [12.6 ng/g serum (Rogan et al. 1986), converted assuming 8 g lipid/L serum (Longnecker et al. 2003)]. The failure to replicate the previous findings on height and BMI in the present study with higher exposures raises the possibility that the earlier results may have been due to chance. However, there were a number of differences in the populations studied; for example, the previous study subjects were mostly whites, were mostly breast-fed, and had mothers who were of higher socioeconomic status and less likely to smoke.
Childhood concentration of p,p′-DDE has also been studied in relation to childhood height and pubertal development (Denham et al. 2004; Karmaus et al. 2002), and adult concentration of p,p′-DDE has been studied in relation to testosterone and DHEAS (Ayotte et al. 2001; Hagmar et al. 2001; Martin et al. 2002; Persky et al. 2001). However, these studies have limited relevance to the question addressed here. Prenatal exposure is likely to act through different mechanisms than does postnatal exposure. Childhood concentrations of persistent organochlorines such as the DDT compounds are poor surrogates for prenatal exposures, because concentrations even into adolescence are most strongly determined by breast-feeding (Jacobson et al. 1989; Karmaus et al. 2001; Nawrot et al. 2002).
The adolescent period studied here is a time of rapid development, with changes in body size and proportions, development of secondary sexual characteristics, skeletal maturation, and changes in the hormonal milieu all occurring. Prenatal exposure to compounds with endocrine activity might influence either the timing or the ultimate result of any or all of these changes. All of the outcome measures we studied reflect some aspect of adolescent development, although we do lack some classic outcomes such as Tanner stages and time of peak height velocity. Height increases with age, although it levels off in the later teens; height ratio first declines and then increases with age as body proportions shift (Hamill et al. 1973; Malina et al. 1974). BMI increases with age, albeit with considerable variability. Triceps skinfold thickness declines with age, again with considerable variability; it also becomes smaller relative to subscapular skin-fold thickness, such that central adiposity increases. Skeletal age increases with chronological age, up to full maturity at skeletal age 18. Testosterone and DHEAS concentrations increase with age, with considerable variability. The substantial variability seen with some of these measures means that our failure to find associations of prenatal exposure to the DDT compounds with any of these outcomes could be due to inadequate power, although the patterns of the observed relationships do not suggest this explanation.
We did have adequate power to discern effects of other known predictors. As expected, height and BMI of boys were influenced by the height and BMI of their mothers, consistent with previous work (Celi et al. 2003; Wingerd and Schoen 1974). The racial differences we saw were consistent with those seen elsewhere. In a national survey, the relationship of height and weight to race was inconsistent across age, but height ratio showed a clear racial difference (Hamill et al. 1973). In the same survey, whites had greater triceps skinfolds than did African Americans but similar subscapular skinfolds, leading to lower central adiposity (Johnston et al. 1974); racial differences in skeletal age were inconsistent across ages (Roche et al. 1975, 1978). First-born children have been shown to be taller and heavier (Celi et al. 2003; Ong et al. 2002; Wingerd and Schoen 1974), consistent with our findings; increased skinfold thickness among first-borns has also been reported in another investigation based on the PBPP (Stettler et al. 2000). Prenatal exposure to smoking has been associated with decreased height (Fogelman 1980) and increased obesity (Power and Jefferis 2002); our results were in the expected direction, although they did not achieve statistical significance. Our sample included very few breast-fed children, consistent with the low overall breast-feeding rates at that time and with the lower rates in African Americans and in the Northeast (Hirschman and Hendershot 1979), so the failure to see any associations of our outcomes to breast-feeding was not surprising.
Although there are many early influences on later development, such as the association of prenatal exposure to certain antipsychotic drugs with later height (Platt et al. 1988), most would be expected to be unrelated to exposure to DDT and thus are not candidate confounders. We controlled for the most likely confounders, although observational studies are always subject to potential residual confounding. We had no information about maternal diet before pregnancy or about the diet of the child after birth; maternal diet is a predictor of the exposure, and childhood diet is a predictor of growth and development. Adjusting for paternal size might have made our estimates more precise, but this information was not available. Birth weight has been shown to be related to prenatal p,p′-DDE exposure in the CPP population (Longnecker et al. 2001); however, we did not consider it appropriate to adjust for birth weight because this is an intermediate variable in the relationships between exposure and adolescent outcomes.
We measured exposure using third-trimester serum samples. Specific aspects of prenatal development occur during critical windows, so timing of exposure can be important. However, for persistent compounds such as DDT, concentrations are generally stable over periods of months or longer, with little variation over the course of pregnancy (Longnecker et al. 1999). The analytical methods used were sensitive, selective, and reliable, with relative standard deviations, including both the error from the sample preparation and the instrumental methods, of 11% and detection limits in the low picograms per millilliter range (Barr et al. 2003).
The participants in the study were not a random sample of the general population. Those enrolled in the CPP from the Philadelphia study center were clinic patients who were planning to deliver at the study hospital (Broman 1984); they were mostly African American and relatively low income, representative of the population obtaining medical care at this clinic. The PBPP study group was a random sample of the CPP study group (Katz et al. 1980). We have no information about exposure among those who chose not to participate in either the base CPP study or the PBPP follow-up, but there is no reason to anticipate that prenatal DDT exposure would differ between participants and nonparticipants. Refusal rates were greatest for the hormone measurements, but there was little systematic relationship to exposure; for example, among African Americans, those with both testosterone measurements available had a median p,p′-DDE of 6.2, whereas those with none or one, due to either a missed visit or a refusal, had a median of 6.3.
In summary, we have seen no association between prenatal exposure to DDT-related compounds and several anthropometric and pubertal measures in males. However, high variability in some of the outcome measures means we cannot rule out subtle changes.
Table 1 Background characteristics of boys and their families.
Characteristic Percent
Race
White 15
African American 85
Maternal smoking at time of pregnancy
No 44
Yes 56
Breast-fed
Yes 6
No 94
No. of older siblings
0 25
1 25
≥ 2 50
Maternal height (cm)
144–155.9 29
156–165.9 54
166–181 17
Maternal prepregnancy BMI (kg/m2)
16–19.9 21
20–24.9 47
25–29.9 23
30–44 9
Maternal age at menarche (years)
8–11 21
12 29
13 25
≥ 14 26
Maternal age at enrollment in CPP (years)
13–19 23
20–24 36
25–29 23
30–42 18
Family SEI at time of pregnancy
0–2.5 17
2.6–5.0 59
≥ 5.1 24
Number of cases (of 304) with missing data: three for breast-fed, one for number of older siblings, four for maternal height, six for maternal prepregnancy BMI, two for maternal age at menarche, 10 for family SEI at time of pregnancy.
Table 2 Distribution of chemical concentrations in maternal serum.
Chemical Concentration (μg/g lipid) Percent
p,p′-DDE 1.0–2.9 14
3.0–5.9 38
6.0–8.9 24
9.0–11.9 13
12.0–25.1 11
p,p′-DDTa NDb–0.9 17
1.0–1.9 36
2.0–2.9 24
3.0–3.9 11
4.0–12.7 11
o,p′-DDT NDc–0.07 29
0.08–0.15 28
0.16–0.23 18
0.24–0.31 10
0.32–1.33 14
∑ DDTa 1.8–3.9 11
4.0–7.9 37
8.0–11.9 28
12.0–15.9 13
16.0–33.1 11
ND, not detected.
a Not available for 25 (of 304) boys because of quality control limit failure.
b One sample had nondetectable p,p′-DDT (detection limit, 0.01 μg/g lipid).
c Fifteen samples had non-detectable o,p′-DDT (detection limits, 0.007–0.054 μg/g lipid).
Table 3 Percentiles of anthropometric and pubertal measures by age range (years).
Measure 10–10.9 11–11.9 12–12.9 13–13.9 14–14.9 15–15.9 16–16.9 17–17.9 18–18.9 19–20.0
Height (cm)
No. 10 97 149 185 140 111 105 118 111 107
90th — 157 165 171 177 180 184 185 185 185
Median 140 145 151 158 166 171 173 173 175 176
10th — 138 143 147 154 158 166 167 168 167
Height ratio (%)
No. 10 97 148 185 140 110 103 117 108 105
90th — 52.9 52.5 52.3 52.2 53.0 52.6 52.7 52.4 52.3
Median 52.0 51.1 50.5 50.3 50.1 50.2 50.5 50.8 50.8 50.8
10th — 49.4 49.0 48.8 48.7 48.3 48.4 49.0 49.1 49.4
BMI (kg/m2)
No. 10 97 149 185 139 111 105 118 110 106
90th — 22.0 23.9 23.7 24.2 25.2 24.6 27.5 27.5 27.8
Median 17.2 17.4 18.0 18.6 19.3 20.4 20.4 21.4 22.2 21.8
10th — 15.2 15.4 15.9 16.1 17.6 17.9 19.0 19.2 19.1
Triceps skinfold thickness (mm)
No. 10 97 149 185 140 111 105 118 111 107
90th — 16.9 18.2 16.7 16.1 17.1 10.3 15.0 15.3 14.6
Median 7.8 8.1 7.8 7.4 7.1 7.0 6.6 6.8 7.3 6.9
10th — 5.6 5.2 4.9 5.0 5.2 4.6 5.0 4.9 4.5
Central adiposity (%)
No. 9 97 148 185 140 110 105 118 111 107
90th — 52 54 56 56 58 60 63 64 65
median 44 46 47 48 49 52 55 56 56 58
10th — 40 41 41 42 42 46 49 49 50
Skeletal age (years)
No. 9 95 146 177 135 106 78 37 4 0
90th — 13.5 15.0 15.3 16.1 18.0 18.0 18.0 — —
Median 11.0 11.5 12.6 13.8 15.0 15.6 16.6 18.0 18.0 —
10th — 9.7 11.2 12.0 12.8 14.5 15.3 15.5 — —
Testosterone (ng/dL)
No. 4 66 104 76 69 59 32 5 0 0
90th — 160 336 430 517 575 787 — — —
Median 36 36 86 148 259 400 481 569 — —
10th — 13 21 38 44 110 327 — — —
DHEAS (ng/mL)
No. 0 4 67 43 32 31 30 6 0 0
90th — — 2,320 3,160 3,200 3,560 5,000 — — —
Median — 464 1,160 1,480 1,650 1,840 1,940 2,270 — —
10th — — 420 720 560 1,040 900 — — —
Values are number of measurements and percentiles; only the median is shown if n ≤10.
Table 4 Mean ± SE anthropometric and pubertal measures by maternal p,p′-DDE in specific age ranges (years).
p,p′-DDE (μg/g lipid) < 14 14–16.9 17–20
Height (cm)
< 3 151 ± 1.8 (28) 168 ± 1.9 (26) 174 ± 1.5 (25)
3–5.9 154 ± 0.9 (76) 168 ± 0.9 (86) 176 ± 0.8 (67)
6–8.9 155 ± 1.2 (50) 170 ± 1.3 (50) 176 ± 1.0 (51)
9–11.9 157 ± 2.0 (27) 173 ± 1.7 (24) 177 ± 1.5 (24)
≥ 12 152 ± 1.9 (18) 168 ± 2.1 (21) 173 ± 1.4 (19)
Height ratio (%)
< 3 50.8 ± 0.3 (28) 51.1 ± 0.4 (26) 51.2 ± 0.3 (25)
3–5.9 50.8 ± 0.1 (76) 50.6 ± 0.2 (84) 51.0 ± 0.2 (66)
6–8.9 50.7 ± 0.2 (50) 50.3 ± 0.2 (50) 50.7 ± 0.2 (51)
9–11.9 50.2 ± 0.3 (27) 50.3 ± 0.3 (24) 50.3 ± 0.3 (24)
≥ 12 50.7 ± 0.3 (18) 50.2 ± 0.3 (21) 50.9 ± 0.4 (18)
BMI (kg/m2)
< 3 17.9 ± 0.5 (28) 21.6 ± 1.0 (26) 21.5 ± 0.6 (25)
3–5.9 20.0 ± 0.5 (76) 20.8 ± 0.5 (85) 22.9 ± 0.4 (67)
6–8.9 18.9 ± 0.4 (50) 20.4 ± 0.5 (50) 22.6 ± 0.4 (51)
9–11.9 18.3 ± 0.5 (27) 21.3 ± 1.0 (24) 22.3 ± 0.9 (24)
≥ 12 18.2 ± 0.5 (18) 19.7 ± 0.6 (21) 21.2 ± 0.6 (19)
Triceps skinfold thickness (mm)
< 3 8.5 ± 0.6 (28) 10.3 ± 1.5 (26) 7.5 ± 0.6 (25)
3–5.9 11.0 ± 0.8 (76) 8.4 ± 0.5 (86) 8.9 ± 0.6 (67)
6–8.9 9.4 ± 0.7 (50) 8.5 ± 0.7 (50) 8.7 ± 0.6 (51)
9–11.9 8.9 ± 0.9 (27) 9.1 ± 1.5 (24) 8.6 ± 1.4 (24)
≥ 12 8.1 ± 0.7 (18) 8.2 ± 0.8 (21) 7.2 ± 0.8 (19)
Central adiposity (%)
< 3 46.2 ± 0.8 (28) 49.1 ± 1.0 (26) 56.8 ± 0.9 (25)
3–5.9 47.6 ± 0.6 (75) 51.9 ± 0.6 (86) 56.1 ± 0.6 (67)
6–8.9 47.7 ± 0.7 (50) 51.2 ± 0.7 (50) 55.3 ± 0.8 (51)
9–11.9 48.0 ± 0.7 (27) 50.8 ± 1.0 (24) 58.1 ± 0.9 (24)
≥ 12 46.5 ± 1.1 (18) 50.7 ± 1.0 (21) 57.2 ± 1.3 (19)
Skeletal age (years)
< 3 12.4 ± 0.3 (28) 15.8 ± 0.3 (24)
3–5.9 13.1 ± 0.1 (72) 15.4 ± 0.1 (73)
6–8.9 13.0 ± 0.2 (50) 15.4 ± 0.2 (43)
9–11.9 13.1 ± 0.3 (27) 15.9 ± 0.2 (22)
≥ 12 13.0 ± 0.3 (18) 15.6 ± 0.3 (21)
Testosterone (ng/dL)
< 3 124 ± 26 (26) 376 ± 33 (18)
3–5.9 136 ± 17 (63) 321 ± 28 (43)
6–8.9 172 ± 25 (42) 346 ± 46 (25)
9–11.9 111 ± 19 (24) 491 ± 103 (11)
≥ 12 142 ± 41 (13) 333 ± 52 (15)
DHEAS (ng/mL)
< 3 1,355 ± 184 (20) 2,248 ± 274 (16)
3–5.9 1,431 ± 142 (40) 1,901 ± 168 (35)
6–8.9 1,428 ± 186 (28) 1,911 ± 218 (19)
9–11.9 1,236 ± 186 (18) 2,352 ± 476 (10)
≥ 12 1,240 ± 180 (8) 2,186 ± 492 (13)
For each boy, all available measurements in the specified age range are averaged. Values are mean ± SE of these averages (no. of boys). Skeletal age and hormone concentrations are not shown in the upper age range because they were available for few boys.
Table 5 Regression of anthropometric and pubertal measures on maternal p,p′-DDE and other predictors.
Predictor, category/units Height (cm) Height ratio (%) BMI (kg/m2) Triceps (log mm) Central adiposity (%) Skeletal age (years) Testosterone (log ng/dL) DHEAS (ng/mL)
Maternal p,p′-DDE (μg/g lipid)
< 3 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref)
3–5.9 1.1 ± 1.3 0.1 ± 0.2 0.9 ± 0.7 0.06 ± 0.08 1.1 ± 0.9 0.4 ± 0.2 0.0 ± 0.2 −158 ± 217
6–8.9 1.0 ± 1.5 0.1 ± 0.2 0.2 ± 0.8 0.00 ± 0.09 0.5 ± 1.0 0.3 ± 0.3 0.1 ± 0.2 −140 ± 252
9–11.9 2.2 ± 1.7 0.0 ± 0.3 0.6 ± 0.9 0.00 ± 0.10 1.7 ± 1.2 0.5 ± 0.3 0.0 ± 0.2 −109 ± 281
≥ 12 0.4 ± 1.8 0.0 ± 0.3 −0.4 ± 0.9 −0.01 ± 0.11 0.6 ± 1.2 0.2 ± 0.3 0.1 ± 0.2 −148 ± 307
Maternal height per 10 cm 4.4 ± 0.7** −0.5 ± 0.1** −0.2 ± 0.4 0.05 ± 0.04 0.0 ± 0.5 −0.1 ± 0.1 −0.1 ± 0.1 −32 ± 114
Maternal BMI per 10 kg/m2 2.0 ± 1.0* 0.0 ± 0.2 2.2 ± 0.5** 0.25 ± 0.06** −0.3 ± 0.7 0.2 ± 0.2 0.2 ± 0.1 280 ± 179
Race
White −0.9 ± 1.3 2.1 ± 0.2 0.4 ± 0.7 0.15 ± 0.08 −2.8 ± 0.9 0.0 ± 0.2 0.0 ± 0.2 −110 ± 227
African American 0 (ref) 0 (ref)** 0 (ref) 0 (ref)* 0 (ref)** 0 (ref) 0 (ref) 0 (ref)
No. of older siblings
0 0 (ref)** 0 (ref)* 0 (ref) 0 (ref)** 0 (ref) 0 (ref) 0 (ref) 0 (ref)
1 −1.1 ± 1.3 0.0 ± 0.2 −0.6 ± 0.7 −0.11 ± 0.08 1.4 ± 0.9 −0.3 ± 0.2 −0.2 ± 0.2 −320 ± 235
≥ 2 −3.2 ± 1.4 0.4 ± 0.2 −0.9 ± 0.7 −0.21 ± 0.08 1.7 ± 0.9 −0.5 ± 0.2 −0.2 ± 0.2 −522 ± 245
Maternal smoking in pregnancy
No 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref)
Yes −0.2 ± 0.8 −0.2 ± 0.1 0.3 ± 0.5 0.02 ± 0.05 0.7 ± 0.6 0.0 ± 0.1 0.0 ± 0.1 60 ± 152
Breast-fed
No 0.4 ± 1.7 −0.3 ± 0.3 0.5 ± 0.9 0.12 ± 0.10 −0.7 ± 1.2 −0.1 ± 0.3 0.1 ± 0.2 −247 ± 285
Yes 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref)
Family SEI
≥ 5.1 2.4 ± 1.4 0.4 ± 0.2 1.1 ± 0.7 0.12 ± 0.08 −0.3 ± 0.9 0.4 ± 0.2 0.4 ± 0.2 207 ± 238
2.6–5.0 2.5 ± 1.2 0.1 ± 0.2 0.7 ± 0.6 0.04 ± 0.07 0.0 ± 0.8 0.4 ± 0.2 0.2 ± 0.2 184 ± 204
0–2.5 0 (ref)* 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref)* 0 (ref)
Maternal age at enrollment (years)
13–19 −0.9 ± 1.8 −0.1 ± 0.3 −0.7 ± 1.0 −0.20 ± 0.11 1.7 ± 1.2 −0.4 ± 0.3 0.2 ± 0.2 −340 ± 318
20–24 −0.6 ± 1.3 −0.3 ± 0.2 −0.5 ± 0.7 −0.08 ± 0.08 0.4 ± 0.9 −0.2 ± 0.2 −0.1 ± 0.2 −122 ± 237
25–29 0.2 ± 1.4 −0.4 ± 0.2 0.2 ± 0.7 −0.05 ± 0.08 0.5 ± 1.0 0.0 ± 0.2 0.2 ± 0.2 −252 ± 243
≥ 30 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref)
Maternal age at menarche (years)
8–11 0 (ref) 0 (ref)* 0 (ref) 0 (ref) 0 (ref) 0 (ref) 0 (ref)* 0 (ref)
12 −0.6 ± 1.2 −0.5 ± 0.2 0.0 ± 0.6 0.03 ± 0.07 −1.2 ± 0.8 −0.3 ± 0.2 −0.5 ± 0.2 −77 ± 212
13 0.3 ± 1.3 −0.4 ± 0.2 −0.4 ± 0.7 0.00 ± 0.08 −0.9 ± 0.9 −0.2 ± 0.2 −0.3 ± 0.2 47 ± 228
≥ 14 1.0 ± 1.3 −0.4 ± 0.2 −0.3 ± 0.7 0.00 ± 0.08 −1.3 ± 0.9 −0.4 ± 0.2 −0.3 ± 0.2 −52 ± 223
ref, reference. Values are regression coefficients ± SE, adjusted for all others shown and also for age of boy at measurement and correlation among multiple measures of the same boy.
* p < 0.10,
** p < 0.05, for tests of whether discrete groups differ or continuous slope is nonzero.
==== Refs
References
ATSDR 2002. Toxicological Profile for DDT, DDE, and DDD. Atlanta, GA:Agency for Toxic Substances and Disease Registry.
Ayotte P Giroux S Dewailly É Hernández Avila M Farias P Danis R 2001 DDT spraying for malaria control and reproductive function in Mexican men Epidemiology 12 366 367 11338320
Barr JR Maggio VL Barr DB Turner WE Sjödin A Sandau CD 2003 New high-resolution mass spectrometric approach for the measurement of polychlorinated biphenyls and organochlorine pesticides in human serum J Chromatogr B Analyt Technol Biomed Life Sci 794 137 148 12888206
Broman S 1984. The Collaborative Perinatal Project: an overview. In: Handbook of Longitudinal Research (Medrick SA, Harway M, Finello KM, eds). New York:Praeger Publications, 185–215.
Buster JE Abraham GE 1972 Radioimmunoassay of plasma dehydroepiandrosterone sulfate Anal Lett 5 543 551
Celi F Bini V DeGiorgi G Molinari D Faraoni F DiStefano G 2003 Epidemiology of overweight and obesity among school children and adolescents in three provinces of central Italy, 1993–2001: study of potential influencing variables Eur J Clin Nutr 57 1045 1051 12947421
Denham M Deane G Gallo MV Ravenscroft J Decaprio A Schell L 2004 Age at menarche among Akwesasne Mohawk girls exposed to lead, mercury, mirex, dichloro-diphenyldichloroethane (DDE), hexachlorobenzene (HCB) and polychlorinated biphenyls (PCBs) [Abstract] Am J Hum Biol 16 201
Dewailly É Ayotte P Bruneau S Gingras S Belles-Isles M Roy R 2000 Susceptibility to infections and immune status in Inuit infants exposed to organochlorines Environ Health Perspect 108 205 211 10706525
Flores-Luévano S Farías P Hernández M Romano-Riquer P Weber JP Dewailly E 2003 Concentraciones de DDT/DDE y riesgo de hipospadias. Un estudio piloto de casos y controles [in Spanish] Salud Publica Mex 45 431 438 14974286
Fogelman K 1980 Smoking in pregnancy and subsequent development of the child Child Care Health Dev 6 233 249 7408115
Furuyama S Mayes DM Nugent CA 1970 A radioimmunoassay for plasma testosterone Steroids 16 415 428 5533947
Gladen BC Ragan NB Rogan WJ 2000 Pubertal growth and development and prenatal and lactational exposure to PCBs and DDE J Pediatr 136 490 496 10753247
Gladen BC Rogan WJ 1995 DDE and shortened duration of lactation in a northern Mexican town Am J Public Health 85 504 508 7702113
Gladen BC Rogan WJ Hardy P Thullen J Tingelstad J Tully M 1988 Development after exposure to polychlorinated biphenyls and dichlorodiphenyl dichloroethene transplacentally and through human milk J Pediatr 113 991 995 3142988
Gray LE Ostby J Furr J Wolf CJ Lambright C Parks L 2001 Effects of environmental antiandrogens on reproductive development in experimental animals Hum Reprod Update 7 248 264 11392371
Hagmar L Björk J Sjödin A Bergman Å Erfurth EM 2001 Plasma levels of persistent organohalogens and hormone levels in adult male humans Arch Environ Health 56 138 143 11339677
Hamill PVV Johnston FE Lemeshow S 1973 Body weight, stature, and sitting height: white and Negro youths 12–17 years: United States Vital Health Stat 11 126 1 40 4539878
Hardy JB 2003 The Collaborative Perinatal Project: lessons and legacy Ann Epidemiol 13 303 311 12821268
Hirschman C Hendershot GE 1979 Trends in breast feeding among American mothers Vital Health Stat 23 3 1 46 524755
Hosie S Loff S Witt K Niessen K Waag KL 2000 Is there a correlation between organochlorine compounds and undescended testes? Eur J Pediatr Surg 10 304 309 11194541
Jacobson JL Humphrey HEB Jacobson SW Schantz SL Mullin MD Welch R 1989 Determinants of polychlorinated biphenyls (PCBs), polybrominated biphenyls (PBBs), and dichlorodiphenyl trichloroethane (DDT) levels in the sera of young children Am J Public Health 79 1401 1404 2551196
Jaga K Dharmani C 2003 Global surveillance of DDT and DDE levels in human tissues Int J Occup Med Environ Health 16 7 20 12705713
Johnston EE Hamill PVV Lemeshow S 1974 Skinfold thickness of youths 12–17 years, United States Vital Health Stat 11 132 1 75
Karmaus W Asakevich S Indurkhya A Witten J Kruse H 2002 Childhood growth and exposure to dichlorodiphenyl dichloroethene and polychlorinated biphenyls J Pediatr 140 33 39 11815761
Karmaus W DeKoning EP Kruse H Witten J Osius N 2001 Early childhood determinants of organochlorine concentrations in school-aged children Pediatr Res 50 331 336 11518819
Katz SH Hediger ML Schall JI Bowers EJ Barker WF Aurand S 1980 Blood pressure, growth and maturation from childhood through adolescence: mixed longitudinal analyses of the Philadelphia Blood Pressure Project Hypertension 2 I55 I69
Kupfer D 1975 Effects of pesticides and related compounds on steroid metabolism and function Crit Rev Toxicol 4 83 124
Loeffler IK Peterson RE 1999 Interactive effects of TCDD and p,p ’-DDE on male reproductive tract development in in utero and lactationally exposed rats Toxicol Appl Pharmacol 154 28 39 9882589
Longnecker MP Klebanoff MA Brock JW Zhou H Gray KA Needham LL 2002 Maternal serum level of 1,1-dichloro-2,2-bis(p -chlorophenyl)ethylene and risk of cryptorchidism, hypospadias, and polythelia among male offspring Am J Epidemiol 155 313 322 11836195
Longnecker MP Klebanoff MA Gladen BC Berendes HW 1999 Serial levels of serum organochlorines during pregnancy and postpartum Arch Environ Health 54 110 114 10094288
Longnecker MP Klebanoff MA Zhou H Brock JW 2001 Association between maternal serum concentration of the DDT metabolite DDE and preterm and small-for-gestational-age babies at birth Lancet 358 110 114 11463412
Longnecker MP Wolff MS Gladen BC Brock JW Grandjean P Jacobson JL 2003 Comparison of polychlorinated biphenyl levels across studies of human neurodevelopment Environ Health Perspect 111 65 70 12515680
Malina RM Hamill PVV Lemeshow S 1974 Body dimensions and proportions, white and Negro children, 6–11 years, United States Vital Health Stat 11 143 1 71 4549147
Martin SA Jr Harlow SD Sowers MF Longnecker MP Garabrant D Shore DL 2002 DDT metabolite and androgens in African-American farmers Epidemiology 13 454 458 12094101
Myrianthopoulos NC French KS 1968 An application of the U.S. Bureau of the Census socioeconomic index to a large, diversified patient population Soc Sci Med 2 283 299 5760819
Nawrot TS Staessen JA Den Hond EM Koppen G Schoeters G Fagard R 2002 Host and environmental determinants of polychlorinated aromatic hydrocarbons in serum of adolescents Environ Health Perspect 110 583 589 12055049
Ogden CL Flegal KM Carroll MD Johnson CL 2002 Prevalence and trends in overweight among US children and adolescents, 1999–2000 JAMA 288 1728 1732 12365956
Ong KKL Preece MA Emmett PM Ahmed ML Dunger DB ALSPAC Study Team 2002 Size at birth and early childhood growth in relation to maternal smoking, parity and infant breast-feeding: longitudinal birth cohort study and analysis Pediatr Res 52 863 867 12438662
Persky V Turyk M Anderson HA Hanrahan LP Falk C Steenport DN 2001 The effects of PCB exposure and fish consumption on endogenous hormones Environ Health Perspect 109 1275 1283 11748036
Phillips DL Pirkle JL Burse VW Bernert JT Jr Henderson LO Needham LL 1989 Chlorinated hydrocarbon levels in human serum: effects of fasting and feeding Arch Environ Contam Toxicol 18 495 500 2505694
Platt JE Friedhoff AJ Broman SH Bond RN Laska E Lin SP 1988 Effects of prenatal exposure to neuroleptic drugs on children’s growth Neuropsychopharmacology 1 205 212 2908019
Power C Jefferis BJ 2002 Fetal environment and subsequent obesity: a study of maternal smoking Int J Epidemiol 31 413 419 11980805
Ribas-Fitó N Cardo E Sala M de Muga ME Mazón C Verdú A 2003 Breastfeeding, exposure to organochlorine compounds, and neurodevelopment in infants Pediatrics 111 e580 e585 12728113
Roche AF Roberts J Hamill PVV 1975 Skeletal maturity of children 6–11 years: racial, geographic area, and socioeconomic differentials: United States Vital Health Stat 11 149 1 88 174300
Roche AF Roberts J Hamill PVV 1978 Skeletal maturity of youths 12–17 years: racial, geographic area, and socioeconomic differentials: United States, 1966–1970 Vital Health Stat 11 167 1 107 214960
Rogan WJ Gladen BC McKinney JD Carreras N Hardy P Thullen J 1986 Polychlorinated biphenyls (PCBs) and dichlorodiphenyl dichloroethene (DDE) in human milk: effects of maternal factors and previous lactation Am J Public Health 76 172 177 3080910
Rogan WJ Gladen BC McKinney JD Carreras N Hardy P Thullen J 1987 Polychlorinated biphenyls (PCBs) and dichlorodiphenyl dichloroethene (DDE) in human milk: effects on growth, morbidity, and duration of lactation Am J Public Health 77 1294 1297 3115123
Salazar-García F Gallardo-Díaz E Cerón-Mireles P Loomis D Borja-Aburto VH 2004 Reproductive effects of occupational DDT exposure among male malaria control workers Environ Health Perspect 112 542 547 15064158
Sandau CD Sjödin A Davis MD Barr JR Maggio VL Waterman AL 2003 Comprehensive solid-phase extraction method for persistent organic pollutants. Validation and application to the analysis of persistent chlorinated pesticides Anal Chem 75 71 77 12530820
Smith D 1999 Worldwide trends in DDT levels in human breast milk Int J Epidemiol 28 179 188 10342677
Stettler N Tershakovec AM Zemel BS Leonard MB Boston RC Katz SH 2000 Early risk factors for increased adiposity: a cohort study of African American subjects followed from birth to young adulthood Am J Clin Nutr 72 378 383 10919930
Stockholm Convention on Persistent Organic Pollutants 2004. Stockholm Convention on Persistent Organic Pollutants (POPs). Geneva:Secretariat for the Stockholm Convention on Persistent Organic Pollutants. Available: http://www.pops.int [accessed 24 August 2004].
Tanner JM Hiernaux J Jarman S 1969. Growth and physique studies. In: Human Biology, A Guide to Field Methods (Weiner JS, Lourie JA, eds). IBP Handbook No. 9. Oxford:Blackwell, International Biological Programme, 2–71.
Tanner JM Whitehouse RH Marshall WA Healy MJR Goldstein H 1975. Assessment of Skeletal Maturity and Prediction of Adult Height (Tanner-Whitehouse II Method). London:Academic Press.
Turusov V Rakitsky V Tomatis L 2002 Dichlorodiphenyltrichloroethane (DDT): ubiquity, persistence, and risks Environ Health Perspect 110 125 128 11836138
Vine MF Stein L Weigle K Schroeder J Degnan D Tse CK 2001 Plasma 1,1-dichloro-2,2-bis(p -chlorophenyl)ethylene (DDE) levels and immune response Am J Epidemiol 153 53 63 11159147
Walker KR Ricciardone MD Jensen J 2003 Developing an international consensus on DDT: a balance of environmental protection and disease control Int J Hyg Environ Health 206 423 435 12971698
Wendo C 2004 Uganda considers DDT to protect homes from malaria. Health officials claim DDT will help save money, but critics warn of environmental costs Lancet 363 1376 15114996
Wingerd J Schoen EJ 1974 Factors influencing length at birth and height at five years Pediatrics 53 737 741 4826730
Wyde ME Bartolucci E Ueda A Zhang H Yan B Negishi M 2003 The environmental pollutant 1,1-dichloro-2,2-bis (p -chlorophenyl)ethylene induces rat hepatic cytochrome P450 2B and 3A expression through the constitutive androstane receptor and pregnane X receptor Mol Pharmacol 64 474 481 12869653
You L Casanova M Archibeque-Engle S Sar M Fan LQ Heck HD 1998 Impaired male sexual development in perinatal Sprague-Dawley and Long-Evans Hooded rats exposed in utero and lactationally to p,p ′-DDE Toxicol Sci 45 162 173 9848123
You L Sar M Bartolucci E Ploch S Whitt M 2001 Induction of hepatic aromatase by p,p ′-DDE in adult male rats Mol Cell Endocrinol 178 207 214 11403911
Zemel BS Katz SH 1986 The contribution of adrenal and gonadal androgens to the growth in height of adolescent males Am J Phys Anthropol 71 459 466 2949623
|
15579424
|
PMC1253670
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec 7; 112(17):1761-1767
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7287
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science 10.1289/ehp.7027ehp0112-00176815579425Children's HealthArticlesPulmonary Epithelial Integrity in Children: Relationship to Ambient Ozone Exposure and Swimming Pool Attendance Lagerkvist Birgitta Json 1Bernard Alfred 2Blomberg Anders 3Bergstrom Erik 4Forsberg Bertil 1Holmstrom Karin 5Karp Kjell 5Lundstrom Nils-Goran 1Segerstedt Bo 1Svensson Mona 1Nordberg Gunnar 11Environmental and Occupational Medicine, Department of Public Health and Clinical Medicine, Umea University, Umea, Sweden2Unit of Industrial Toxicology, Catholic University of Louvain, Brussels, Belgium3Respiratory Medicine and Allergy, Department of Public Health and Clinical Medicine4Paediatrics, Department of Clinical Sciences, and5Clinical Physiology, Department of Surgical and Peri-operative Sciences, Umea University, Umea, SwedenAddress correspondence to B.J. Lagerkvist, Environmental Medicine, Department of Public Health and Clinical Medicine, Umea University, S-901 87 Umea, Sweden. Telephone: 46-90-7851343. Fax: 46-90-779630. E-mail:
[email protected] nurse M. Backman, Paediatrics, has contributed with excellent work in the practical part of this study. A. Hagenbjork-Gustafsson, the National Institute for Working Life, Umea, performed the ozone measurements.
Financial support has been given by the European Commission (HELIOS project, QLK4-1308), the Swedish Environmental Protection Agency, and Forskningsradet for Miljo, Areella Naringar och Samhalle.
The authors declare they have no competing financial interests.
12 2004 13 9 2004 112 17 1768 1771 12 2 2004 13 9 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Airway irritants such as ozone are known to impair lung function and induce airway inflammation. Clara cell protein (CC16) is a small anti-inflammatory protein secreted by the nonciliated bronchiolar Clara cells. CC16 in serum has been proposed as a noninvasive and sensitive marker of lung epithelial injury. In this study, we used lung function and serum CC16 concentration to examine the pulmonary responses to ambient O3 exposure and swimming pool attendance. The measurements were made on 57 children 10–11 years of age before and after outdoor exercise for 2 hr. Individual O3 exposure was estimated as the total exposure dose between 0700 hr until the second blood sample was obtained (mean O3 concentration/m3 × hours). The maximal 1-hr value was 118 μg/m3 (59 ppb), and the individual exposure dose ranged between 352 and 914 μg/m3hr. These O3 levels did not cause any significant changes in mean serum CC16 concentrations before or after outdoor exercise, nor was any decrease in lung function detected. However, children who regularly visited chlorinated indoor swimming pools had significantly lower CC16 levels in serum than did nonswimming children both before and after exercise (respectively, 57 ± 2.4 and 53 ± 1.7 μg/L vs. 8.2 ± 2.8 and 8.0 ± 2.6 μg/L; p < 0.002). These results indicate that repeated exposure to chlorination by-products in the air of indoor swimming pools has adverse effects on the Clara cell function in children. A possible relation between such damage to Clara cells and pulmonary morbidity (e.g., asthma) should be further investigated.
airway irritantschildrenClara cell protein (CC16)nitrogen trichlorideozoneswimming pool
==== Body
Ozone is an important component of air pollution. Ground-level O3 in urban air is formed in a photochemical reaction between oxygen and nitrogen dioxide from fossil fuel emissions under the influence of sunlight and volatile hydrocarbons. Therefore, the O3 levels tend to be high in areas with high intensity of ultra-violet radiation and high emissions of NO2 from car traffic or industries using fossil fuels (American Thoracic Society 1996; de Marco et al. 2002).
Epidemiologic and controlled human studies as well as animal experiments on exposure to O3 have reported airway inflammation and/or a decrease in lung function at ambient concentrations [reviewed by Balmes (1993); Krishna et al. 1995]. Human experimental exposure to O3 has demonstrated a spectrum of acute airway responses. Among these are decrements in forced vital capacity (FVC) and forced expiratory volume in 1 sec (FEV1), increased airway resistance (Blomberg et al. 1999; Seal 1993), altered airway permeability, and antioxidant defenses (Blomberg et al. 1999; Mudway et al. 2001), as well as a neutrophilic airway inflammation (Schelegle et al. 1991; Stenfors et al. 2002). Most of these studies were short-term exposures on healthy adults. Acute lung function changes in children have been shown in field exposures. Associations between ambient O3 levels and reductions in FVC and FEV1 in children in summer camps and big cities have been shown in several studies (American Thoracic Society 1996; Kopp et al. 2000). Recently, short-term effects of O3 were observed in children as an increased frequency of emergency visits for asthma (Fauroux et al. 2000)
Repeated exposure to other environmental and occupational gases (e.g., sulfur dioxide and chlorine) also increase the risk of airway irritation and asthmalike symptoms (Olin et al. 2002). Several studies have shown that competitive swimmers have an increased prevalence of airway inflammation, bronchial hyperresponsiveness, and asthma (Helenius and Haahtela 2000; Potts 1996). This was attributed to inhalation of chlorine gas and its derivatives formed by chlorination of ammonia derived from organic matter in swimming pool water [e.g., nitrogen trichloride, trichloramine, or chlorine azide (NCl3)].
In recent years there has been a growing interest in noninvasive indicators as a means to detect early effects of air irritants (Bernard et al. 1992; Broeckaert et al. 1999). Several reports describe different lung-specific secretory proteins, which may be used to detect changes in the number of and/or integrity of epithelial secretory cells (Hermans and Bernard 1999). One of these, Clara cell protein (CC16), is a small, 16-kDa protein produced and secreted by the nonciliated bronchiolar Clara cells and detectable in serum. CC16 has antioxidant properties, and the levels in serum increase when lung epithelium permeability is adversely affected by air pollutants or other lung toxicants (Broeckaert et al. 1999; Hermans and Bernard 1996). On the other hand, reduced levels of CC16 in lung lavage fluid are described in several lung disorders (e.g., chronic bronchitis) and in smokers. This may be caused by a decrease in the production of CC16 depending on a decreased number of Clara cells (Hermans and Bernard 1999). In this study we validated CC16 and the lung surfactant proteins A, B, and D in blood as biomarkers of adverse pulmonary effects. The advantage of studying lung proteins in serum instead of in bronchoalveolar lavage, which has been commonly used to study inflammatory effects in the airways, is obvious. Blood samples are more easily obtained than is lung lavage. Besides, lung lavage is not a suitable method in studies on children.
The general aim of the present program, which was part of a European Union project (HELIOS), was to examine lung function and possible changes in the serum levels of CC16 in relation to ambient O3 exposure in Italy, France, Belgium, and Sweden (Bernard et al. 2003). The effects of exposure to other environmental factors (e.g., chlorine and its by-products) in swimming pools were also examined. The present study was conducted in Umea, a town in northern Sweden with low to moderate O3 levels, and was divided into four substudies. The first part was conducted on healthy adults in winter, when O3 levels were low, and the second part in the summer when O3 levels were known to be higher than in other seasons. Similar studies were then repeated in children. In the present report we describe the results from the summer study on children.
Materials and Methods
The winter study on children, also the basis for the summer study, was conducted in November 2001; 139 children, 63 girls and 76 boys, from four primary schools were recruited. Children with a history of asthma or kidney disease were not included. The recruitment of school children was done according to the same protocol as in the study by Bernard et al. (2003) in Brussels. Lung function measurements were performed, and peripheral blood samples were obtained for analysis of CC16 in serum. In the present, summer, study, 57 of the children from the winter study were included, 56 Caucasian and one Chinese. The study was conducted in May 2002. The local ethics committee at Umea University approved the study protocol. A written informed consent was obtained from the parents.
The selection of the 57 children (33 boys and 24 girls) from the larger study in November 2001 was based on the results from the lung function tests and a questionnaire answered by the parents. Subjects who reported pollen allergy or childhood asthma and/or who had an FVC or FEV1 < 80% of the predicted value were not included, nor were children whose blood samples had difficulties or whose questionnaires were missing. The age (mean ± SD) of the participating children was 10.8 ± 0.4 years. Lung function testing and blood sampling (in November 2001) were repeated twice, before and after light exercise outdoors for 2 hr (range, 1.5–3.0 hr). The parents completed a questionnaire on, for example, current food intake, passive smoking, and airway illness since the larger, winter study. The participating children answered questions on outdoor activities and swimming pool attendance. Nearly 40% of the children were regular indoor pool visitors (i.e., they had visited an indoor pool for at least 1 hr/month during 6 months or longer). Sodium hypochlorite (1% chlorine) was used to disinfect the pool water. Based on swimming pool attendance according to the questionnaire, the children were divided into two subgroups, 34 non-pool visitors and 23 pool visitors.
We determined lung function parameters (e.g., FVC and FEV1) using a portable spirometer connected to a computerized data program (KoKo Spirometer and KoKo DigiDoser; Pulmonary Data Service Instrumentation, Inc., Louisville, KY, USA). The instruments were calibrated in the morning and after every 10th measurement. Changeable filter mouthpieces were purchased from Intramedic AB (Balsta, Sweden). One trained lung physiologist tested the lung function in all children. The tests were carried out in the standing position. The best reproducible flow/volume curves were used in the analysis. The computer program calculated the predicted normal values as a function of sex, age, height, and weight according to Polgar and Promadhat (1971).
Blood samples were obtained from the antecubital vein after local anesthesia with a cream or plaster (EMLA, AstraZeneca Ltd., Sodertalje, Sweden) immediately before (S1; four missing samples) and after (S2; three missing samples) the outdoor session. Two CC16 values were available for 20 pool visitors and 31 non-pool visitors. Blood (7.5 mL) was drawn in Sarstedt Monovette tubes for serum (Serum Z/9 mL, Sarstedt, Landskrona, Sweden). Each sample was allowed to clot for 1–2 hr at room temperature. After centrifugation at 3,000 rpm (within 2 hr after sampling), the serum was transferred to cryotubes and frozen at −80°C. These samples were then sent to the Industrial Toxicology Unit at the Catholic University of Louvain in Brussels for analysis. CC16 was determined by a latex immunoassay using rabbit anti-CC16 antibody (Dakopatts, Glostrup, Denmark) and also CC16 purified according to the standard in the laboratory (Bernard et al. 1992; Carbonelle et al. 2002). The assay has been validated by comparison with a monoclonal-antibody–based enzyme-linked immunosorbent assay (ELISA) (Hermans et al. 1998). All samples were run in duplicate at two different dilutions. The between- and within-run coefficients of variation ranged from 5 to 10%.
Outdoor O3 was monitored continuously at the university campus where the children spent time outdoors, using a Dasibi ultra-violet photometry ozone analyzer (model 1108; Dasibi Environmental Corporation, Glendale, CA, USA). O3 exposure was estimated as the total exposure of O3 between 0700 hr and the time the second blood sample was taken, between 1300 and 1600 hr (mean O3 concentration/m3 × number of hours). Because the children spent part of that time indoors (mean, 4 hr) and because it is known from other studies that indoor concentrations of O3 are lower than those outdoors (American Thoracic Society 1996), each individual’s exposure dose was estimated by assuming an exposure level of 50% of the mean outdoor O3 concentration during time spent indoors. This assessment was confirmed by measurement with passive diffusion samplers in the examination room. The filters were purchased from and analyzed at IVL Swedish Environmental Research Institute, Ltd. (Gothenburg, Sweden). The mean indoor O3 level during the study period was 40 μg/m3 (20 ppb).
The statistical program SPSS 11 (SPSS Inc., Chicago, IL, USA) was used for statistical analyses. Differences in FEV1 and CC16 before and after exercise and differences between groups were assessed with Student’s t-test, paired and unpaired. Pearson correlation tests were used for the analyses of correlations. A p-value < 0.05 was considered statistically significant.
Results
The mean daytime outdoor O3 concentration in the days studied ranged from 77 to 116 μg/m3, and the maximal 1-hr value was 118 μg/m3. The estimated individual exposure dose varied from 352 to 914 μg/m3hr.
FEV1 was significantly higher after outdoor exercise than before in both children who had regularly attended chlorinated swimming pools and children not swimming (Table 1). These differences remained also if the percentages of the predicted FEV1 (FEV1% predicted) were compared. The mean measured FEV1 values varied between 91.2 and 93.0% of the predicted ones. There were no significant differences between pool visitors and non-pool visitors, when comparing FEV1% predicted either before (p = 0.43) or after exercise (p = 0.45, Student’s t-test), nor was there any significant difference in body mass index (BMI) between the two groups of children.
The mean ± SD serum concentrations of CC16 in non-pool visitors were 8.2 ± 2.8 μg/L before exercise and 8.0 ± 2.6 μg/L after exercise. The corresponding values in pool visitors were 5.7 ± 2.4 and 5.3 ± 1.7 μg/L (Table 2; range, 2.2–16.1 μg/L). The BMI was 18.5 ± 2.9 kg/m2. Only one pool visitor and three nonvisitors were exposed to passive smoke. There were no significant correlations between the serum CC16 levels and parental smoking or BMI. No significant differences were found between pre- and postexposure levels of serum CC16, nor did the time spent outdoors (mean, 6 hr) during the 2 days preceding the test day have any influence on the CC16 levels. However, the average CC16 levels in pool visitors both before (S1) and after (S2) exercise were lower than in non-pool visitors (p < 0.01) (Table 2). Twenty-two children regularly visited an indoor swimming pool for 1–35 hr/month (median, 4 hr/month). The children had been visiting indoor swimming pools regularly between 6 months to 10 years (median, 3 years). Only two children had been swimming since they were babies. No statistically significant relationship was found for attending a swimming pool during the last days before the test, probably because only seven children had attended indoor swimming pools the last 2 days before the test. In our study, we did not find any correlation between parental smoking and effects on the airways of the children or CC16 levels, possibly because only one pool visitor and three non-pool visitors were exposed to passive smoke.
The correlations between O3 exposure and CC16 levels before or after exercise outdoors were not statistically significant in the group as a whole. However, when CC16 after exercise (S2) was considered, there was a tendency toward a correlation in non-pool visitors after exercise (p < 0.06) (Table 3, Figure 1).
Discussion
In this study, moderate O3 levels between 77 and 116 μg/m3 did not have any adverse effect on the lung function parameter FEV1 after 2 hr of outdoor exercise. In fact, the FEV1 was slightly increased at the second measurement. This could be an effect of better test performance after exercise than before. The ambient O3 levels in our study are also lower than those reported to affect lung function parameters at ambient O3 concentrations (Kinney et al. 1996; Nickmilder et al. 2003).
The serum CC16 levels found in this study did not correlate with BMI, a result that has been shown in other studies as well (Hermans et al. 1998). They were of the same magnitude as those recently reported in children of the same age in Belgium (Bernard et al. 2003; Carbonelle et al. 2002). In those studies, the serum levels of CC16 in children did not change significantly during swimming exercise. In the present study, we have compared the serum CC16 levels in pool visitors and in a control group not exposed to chlorination by-products and found significantly lower levels of serum CC16 in pool visitors suggesting adverse effects on Clara cells.
There were no significant differences between the levels of CC16 before and after outdoor exercise. Neither were there any statistically significant relationships between CC16 levels in serum and ambient O3 exposure, although a marginally significant tendency was found among nonswimmers (Figure 1). The lack of statistical significance may be due to the limited number of subjects and/or the O3 levels’ not being high enough to cause a response. In the present study, the O3 concentration was approximately one-fourth of the O3 concentration that recently was found to increase the serum CC16 levels in adult subjects (n = 22) exposed for 2 hr in an exposure chamber to 400 μg/m3 O3 (Blomberg et al. 2003). Another possible explanation for the lack of a clear relationship between serum CC16 and the O3 dose in the present study is that the time period between the measurements was not long enough to cause a measurable change in CC16 levels. There may also be an interference with diurnal variation not corrected for in the present study. Such a diurnal variation was indicated in a recent study on adults (n = 19) (Helleday et al. 2003). The reason why Bernard et al. (1997) did not find any significant variations in serum CC16 between 0900–1000 hr and 1600–1750 hr in seven healthy adults may be the low number of subjects studied.
Lower CC16 levels among subjects regularly attending chlorinated swimming pools are in accordance with the findings by our Belgian partners in the HELIOS project (Bernard et al. 2003; Carbonelle et al. 2002). These authors found that the concentrations of CC16 in trained swimmers were negatively correlated with their cumulated pool attendance. Thus, swimmers seem to have a somewhat decreased pool of CC16 in the Clara cells in the lungs. The CC16 concentration in serum reflects both the epithelial permeability and the integrity of Clara cells (Hermans and Bernard 1999). Therefore, it is conceivable that a repeated exposure to disinfecting byproducts formed by hypochlorite and organic matter (e.g., urea and sweat) in pools may decrease the CC16 secretion because of Clara cell dysfunction or damage. Thus, a possible increase in the intravascular leakage of CC16 caused by, for example, O3 exposure could be masked by a decrease in the production of CC16 in swimmers (Bernard et al. 2003; Carbonelle et al. 2002). That this could be the case also in our study is indicated by the tendency toward a correlation between short-term O3 exposure and the serum CC16 levels in non-pool visitors, but not in pool visitors, after exercise.
The levels of chlorination by-products were not measured in this study, but evidently they were high enough to affect the lung epithelium in children regularly visiting indoor pools. Because sodium hypochlorite (1% chlorine) was used as a sanitizer of the pool water, increased levels of NCl3 were likely to be present in the pool air. A limited number of measurements of NCl3 in indoor air at the swimming pool most frequently used by the swimming children in our study had been performed in 1995. Levels were similar to those reported in the same year from France by Hery et al. (1995), who identified NCl3 as the main component of chlorination by-products present in the air of indoor swimming pool areas. Hery et al. (1995) also reported that symptoms of irritation in the eyes and throat were correlated with the air levels of NCl3. Bernard et al. (2003) reported that NCl3 in public pools typically are in the range of 0.1–1 mg/m3 in air sampled 1.5 m above the water surface, that is, values similar to those reported by Hery et al. (1995) and the few Swedish measurements (Eriksson and Jacobsson, unpublished data).
Conclusions
Our results indicate that repeated exposure to chlorination by-products in the air of indoor swimming pools has an adverse effect on the Clara cell function in children, such that the anti-inflammatory role of CC16 in the lung could be diminished. A possible role of such influence on Clara cell function in inducing pulmonary morbidity (e.g., asthma) should be further studied. The lung function parameter FEV1 was not adversely affected by outdoor exercise at a moderate O3 concentration in either pool visitors or in non-pool visitors. A possible effect of ambient O3 on serum CC16 levels (in nonswimming children) needs further investigation.
Figure 1 Correlation between the individual O3 exposure dose and serum CC16 concentration (μg/L) after 2 hr of outdoor exercise. The solid and dashed lines represent the correlation presented in Table 3: respectively, non-pool visitors and pool visitors.
Table 1 FEV1 (L/sec) and FEV1% predicted before (S1) and after (S2) outdoor exercise in children who do and do not regularly visit pools (mean ± SD).
Category S1 S2 Diff S2 – S1 p-Value (paired t-test)
All (n = 57)
FEV1 2.19 ± 0.31 2.22 ± 0.32 0.033 ± 0.061 < 0.001
FEV1% predicted 91.3 ± 7.2 92.7 ± 7.6 1.4 ± 2.5 < 0.001
Non-pool visitors (n = 34)
FEV1 2.25 ± 0.32 2.29 ± 0.33 0.035 ± 0.063 0.003
FEV1% predicted 91.2 ± 5.6 92.6 ± 6.3 1.4 ± 2.5 0.002
Pool visitors (n = 23)
FEV1 2.09 ± 0.27 2.13 ± 0.28 0.031 ± 0.060 0.021
FEV1% predicted 91.5 ± 9.1 92.9 ± 9.5 1.3 ± 2.5 0.018
Diff, difference.
Table 2 CC16 levels (μg/L) in plasma of children who do and do not regularly visit pools, before (S1) and after (S2) outdoor exercise (mean ± SD).
Category S1 S2 Paired t-test
All (n = 31) 7.2 ± 2.9 7.0 ± 2.7 p = 0.31
Non-pool visitors (n = 31) 8.2 ± 2.8 8.0 ± 2.6 p = 0.68
Pool visitors (n = 20) 5.7 ± 2.4 5.3 ± 1.7 p = 0.14
t-Test pool visitors versus nonvisitors p < 0.002 p < 0.001
Table 3 Correlation between individual O3 exposure doses and serum CC16 concentrations in children after exercise (S2).
Category Correlation (S2) p-Value
All (n = 54) 0.17 < 0.21
Non-pool visitors (n = 33) 0.34 < 0.06
Pool visitors (n = 21) −0.08 < 0.74
==== Refs
References
American Thoracic Society, Committee of the Environmental and Occupational Health Assembly 1996 State of the art. Health effects of outdoor air pollution. Section 2. Ozone Am J Crit Care Med 153 15 27
Balmes JR 1993 The role of ozone exposure in the epidemiology of asthma Environ Health Perspect 101 suppl 4 219 224 8206036
Bernard A Carbonelle S Michel O Higuet S de Burbure C Buchet J-P 2003 Lung hyper-permeability and asthma prevalence in schoolchildren: unexpected associations with the attendance at indoor chlorinated swimming pools Occup Environ Med 60 385 394 12771389
Bernard A Hermans C Van Houte G 1997 Transient increase of Clara cell protein (CC16) after exposure to smoke Occup Environ Med 54 63 65 9072037
Bernard A Marchandise FX Depelchin S Lauwerys R Sibille Y 1992 Clara cell protein in serum and bronchoalveolar lavage Eur Resp J 5 1231 1238
Blomberg A Mudway IS Nordenhäll C Hedenström H Kelly FJ Frew AJ 1999 Ozone-induced lung function decrements do not correlate with early airway inflammatory or antioxidant responses Eur Respir J 13 1418 1428 10445622
Blomberg A Mudway I Svensson M Hagenbjörk-Gustafsson A Thomasson L Helleday R 2003 Clara cell protein as a biomarker for ozone-induced lung injury in humans Eur Respir J 22 883 888 14680073
Broeckaert F Arsalane K Hermans C Bergamaschi E Brustolin A Mutti A 1999 Lung epithelial damage at low concentrations of ambient ozone Lancet 353 900 901 10093991
Carbonelle S Francaux M Dumont X de Burbure C Morel G Bernard A 2002 Changes in serum pneumoproteins caused by short-term exposure to nitrogen trichloride in indoor chlorinated swimming pools Biomarkers 7 464 478 12581482
de Marco R Poli A Ferrari M Accordini S Giammanaco G Bugiani M 2002 The impact of climate and traffic-related NO2 on prevalence of asthma and allergic rhinitis in Italy Clin Exp Allergy 32 1405 1412 12372117
Fauroux B Sampil M Quenel P Lemoullec Y 2000 Ozone a trigger for hospital pediatric asthma emergency room visits Pediatr Pulmonol 30 1 41 46 10862161
Helenius I Haahtela T 2000 Allergy and asthma in elite summer sports athletes J Allergy Clin Immunol 106 3 444 452 10984362
Helleday R Segerstedt B Forsberg B Nordberg G Svensson M Bernard A 2003 Diurnal variation in serum levels of Clara cell protein (CC16) in humans [Abstract] Eur Resp J 22 suppl 45 75s
Hermans C Bernard A 1996 Clara cell protein: characteristics and potential applications as marker of lung toxicity Biomarkers 1 3 8 23888888
Hermans C Bernard A 1999 State of the art. Lung epithelium-specific proteins. Characteristics and potential applications as markers Am J Respir Crit Care Med 159 646 678 9927386
Hermans C Osman A Nyberg B Peterson C Bernard A 1998 Determinants of Clara cell protein (CC16) concentration in serum: a reassessment with two different methods Clin Chim Acta 272 101 110 9641352
Hery M Hecht G Gerber JM Gendre JC Hubert G 1995 Exposure to chloramines in the atmosphere of indoor swimming pools Ann Occup Hyg 39 427 439
Kinney PL Thurston GD Raizenne M 1996 The effects of ambient ozone on lung function in children: a reanalysis of six summer camp studies Environ Health Perspect 104 170 174 8820584
Kopp MV Bohnet W Frischer T Ulmer C Studnicka M Ihorst G 2000 Effects of ambient ozone on lung function in children ovar a two-year summer period Eur Respir J 16 893 900 11153589
Krishna MT Mudway I Kelly FJ Frew AJ Holgate ST 1995 Ozone, airways and allergic airway disease Clin Exp Allegy 25 1150 1158
Mudway IS Stenfors N Blomberg A Helleday R Dunster C Marklund SL 2001 Differences in basal airway anti-oxidant concentrations are not predictive of individual responsiveness to ozone: a comparison of healthy and mild asthmatic subjects Free Radic Biol Med 31 8 962 974 11595381
Nickmilder M Carbonelle S de Burbure Bernard A 2003 Relationship between ambient ozone and exhaled nitric oxide in children [Letter] JAMA 290 2546 2547 14625330
Olin A-C Granung G Hagberg S Adriansson M Brisman J Dalander O 2002 Respiratory health among bleachery workers exposed to ozone and chlorine dioxide Scand J Work Environ Health 28 2 117 123 12019588
Polgar G Promadhat V 1971. Pulmonary Function Testing in Children: Techniques and Standards. Philadelphia:W.B. Saunders.
Potts J 1996 Factors associated with respiratory problems in swimmers Sports Med 21 4 256 261 8726344
Schelegle ES Siefkin AD McDonald RJ 1991 Time course of ozone-induced neutrophilia in normal humans Am Rev Respir Dis 143 6 1353 1358 2048824
Seal E Jr McDonnell WF House DE Salaam SA Dewitt PJ Butler SO 1993 The pulmonary response of white and black adults to six concentrations of ozone Am Rev Respir Dis 147 4 804 810 8466113
Stenfors N Pourazar J Blomberg A Krishna MT Mudway I Helleday R 2002 Effect of ozone on bronchial mucosal inflammation in asthmatic and healthy subjects Respir Med 96 5 352 358 12113386
|
15579425
|
PMC1253671
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2004 Dec 13; 112(17):1768-1771
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7027
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science 10.1289/ehp.7348ehp0112-00177215579426Children's HealthArticlesThe Effects of the World Trade Center Event on Birth Outcomes among Term Deliveries at Three Lower Manhattan Hospitals Lederman Sally Ann 1Rauh Virginia 1Weiss Lisa 1Stein Janet L. 2Hoepner Lori A. 1Becker Mark 3Perera Frederica P. 11Columbia Center for Children’s Environmental Health, Mailman School of Public Health, Columbia University, New York, New York, USA2Department of Obstetrics and Gynecology, Beth Israel Medical Center, New York, New York, USA3Center for International Earth Science Information Network, Columbia University, New York, New York, USAAddress correspondence to S.A. Lederman, Columbia Center for Children’s Environmental Health, Mailman School of Public Health, Columbia University, 100 Haven Ave., #25F, Tower 3, New York, NY 10032 USA. Telephone: (212) 304-7280. Fax: (212) 544-1943. E-mail:
[email protected] thank J.C. King, G. DelPriore, the staff of the Elizabeth Seton Childbearing Center; and the staff of the obstetrics and pediatric departments and the administrations of the three recruitment hospitals, who made this study possible on very short notice; K. Lester for her role in implementing and coordinating the fieldwork; R. Day, C. Fields, M. Horton, S.B. Joy, K. Wan, E. Wong, and A. Sanchez, who assisted her in enrolling participants; H. Andrews for statistical advice; G. Simpson for assistance with data management; and K. Sims for office assistance to the project. We express our gratitude to the women who were willing to consider our project while they were in labor and to participate at a difficult and busy time.
This work was supported by grants from the September 11th Fund of the New York Community Trust and United Way of New York City; by the New York Times 9/11 Neediest Fund; by a special supplemental grant, National Institute of Environmental Health Sciences (NIEHS) ES09089, awarded to the NIEHS Center for Environmental Health in northern Manhattan; and by NIEHS grants 5P01 ES09600 and 5RO1 ES08977, and U.S. Environmental Protection Agency R827027, awarded to the Columbia Center for Children’s Environmental Health. The funders listed had no role in the design and conduct of the study; in the collection, analysis, or interpretation of the data; or in reviewing or approving the manuscript.
The authors declare they have no competing financial interests.
12 2004 8 9 2004 112 17 1772 1778 28 6 2004 7 9 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. The effects of prenatal exposure to pollutants from the World Trade Center (WTC) disaster on fetal growth and subsequent health and development of exposed children remain a source of concern. We assessed the impact of gestational timing of the disaster and distance from the WTC in the 4 weeks after 11 September on the birth outcomes of 300 nonsmoking women who were pregnant at the time of the event. They were recruited at delivery between December 2001 and June 2002 from three hospitals close to the WTC site. Residential and work addresses of all participants for each of the 4 weeks after 11 September 2001 were geocoded for classification by place and timing of exposure. Average daily hours spent at each location were based on the women’s reports for each week. Biomedical pregnancy and delivery data extracted from the medical records of each mother and newborn included medical complications, type of delivery, length of gestation, birth weight, birth length, and head circumference. Term infants born to women who were pregnant on 11 September 2001 and who were living within a 2-mile radius of the WTC during the month after the event showed significant decrements in term birth weight (−149 g) and birth length (−0.82 cm), compared with infants born to the other pregnant women studied, after controlling for sociodemographic and biomedical risk factors. The decrements remained significant with adjustment for gestational duration (−122 g and −0.74 cm, respectively). Women in the first trimester of pregnancy at the time of the WTC event delivered infants with significantly shorter gestation (−3.6 days) and a smaller head circumference (−0.48 cm), compared with women at later stages of pregnancy, regardless of the distance of their residence or work sites from the WTC. The observed adverse effects suggest an impact of pollutants and/or stress related to the WTC disaster and have implications for the health and development of exposed children.
birth lengthbirth weightgeographic information systemsgestational durationhead circumferencenewbornsWorld Trade Center
==== Body
At the time of the World Trade Center (WTC) tragedy, scientists and community members raised concerns about the effects on pregnant women and their children of exposure to the dust, smoke, and fumes. Analysis of dust samples from lower Manhattan in the days after the WTC event yielded a wide range of toxicants and irritants from building debris and combustion products (Lioy et al. 2002; McGee et al. 2003; Offenburg et al. 2003). These included a variety of neurodevelopmental toxicants and carcinogens such as polycyclic aromatic hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), polychlorinated dibenzodioxins, polychlorinated dibenzofurans, pesticides, other hydrocarbons, and metals (Chen and Thurston 2002; Jeffrey et al. 2003; Lioy et al. 2002; McKinney et al. 2002; Offenburg et al. 2003). The WTC plume contained high levels of PAHs, levels that spiked 1.8 km (1.1 mile) northeast of the WTC site several times in September and October 2001, with a peak on 3 October, during an inversion that brought smoke back to ground level. Similarly, measurements of trace elements, including lead, taken five blocks from the WTC site spiked in September and October (Service 2003), indicating variability in ambient exposures throughout the month after the event.
The fetus is thought to be more sensitive than the adult to a range of ambient pollutants, including PAHs, with recent studies showing a higher rate of genetic damage from PAHs and slower clearance of other toxicants in the newborn compared with the mother (Perera et al. 2003). Fetal growth effects of PAHs and other pollutants have been demonstrated (Dejmek et al. 1999, 2000; Perera et al. 1998; Wilhelm and Ritz 2003); specifically, prenatal exposure to airborne PAHs was associated with reduced birth weight, birth length, and head circumference (Perera et al. 1998, 2003). Shortening of gestation has also been shown for cigarette smoke (Centers for Disease Control and Prevention 2002; Lewtas 1994), of which PAH is only one of many constituents. At the areal level, previous studies of PCBs and ambient carbon monoxide show that birth weight is associated with distance from the source of the pollutants or the site of their measurement (Baibergenova et al. 2003; Ritz and Yu 1999), suggesting that geographic location can be used to approximate level of exposure.
In addition to concerns about the potentially high levels of exposures from the WTC event, questions arise as to possible differential risk associated with the timing, during gestation, of pregnant women’s exposure to the event itself and to the air pollutants associated with the event. One study found a significant association between early gestational exposure to particulate matter (or an associated air pollutant) and intrauterine growth retardation (Dejmek et al 1999). Other studies have demonstrated that women exposed to active and/or passive smoking (environmental tobacco smoke exposure) throughout pregnancy show significantly larger birth weight decrements compared with women who reduced exposure early in the pregnancy (Dejmek et al. 2002).
The WTC disaster was a singular event and highly stressful for many individuals. Several previous studies have demonstrated effects of stressful conditions on birth outcomes such as preterm delivery and low birth weight (Arck et al. 2001; Axelrod and Reisine 1984; Da Costa et al. 2000; Dunkel-Schetter 1998; Glynn et al. 2001; Goepfert and Goldenberg 1996; Hobel et al. 1999; Wadhwa et al. 1998, 2001). There is also some emerging evidence suggesting that stressful exposures may exacerbate the impact of toxicants (Rauh et al. 2004; Singer et al. 2002).
We undertook the present study to assess the birth outcomes of women in the New York City area who lived or worked in the vicinity of the WTC at the time of the WTC event and during the weeks that followed. Future analyses will use biomarker data on individual air pollutants (including PAHs, PCBs, dioxins, furans, brominated fire-retardant breakdown products, lead, cadmium, and mercury) measured in maternal blood and urine and cord blood.
Materials and Methods
Recruitment sites.
Three large downtown hospitals with maternity units were selected based on their close proximity to the WTC site and the characteristics of their local catchment areas. These were Beth Israel and St. Vincent’s hospitals (and St. Vincent’s affiliated Elizabeth Seton Childbearing Center), all approximately 2 miles from the WTC site, and New York University (NYU) Downtown Hospital, which is within a half-mile of the site. These three hospitals deliver a total of nearly 9,000 infants each year. All three draw women from Manhattan, but each also serves a broader area that includes the outlying boroughs as well as parts of New Jersey and Westchester, New York. Because of the ready availability of bilingual staff (Chinese/English) at NYU Downtown, most of their deliveries are to Chinese women residing in Chinatown in lower Manhattan as well as the wider catchment area.
Sample selection.
Singleton pregnant women were approached for enrollment by project staff at the time of labor and delivery at each of the three participating hospitals. Eligible women were between 18 and 39 years of age, met geographic criteria (described below), had not smoked during pregnancy (< 1 cigarette/day at any time), and reported no diabetes, hypertension, HIV infection or AIDS, or use of illegal drugs in the last year. Enrollment occurred between 13 December 2001 and 26 June 2002 and was implemented at each of the participating hospitals as soon after 11 September as institutional review board approval was obtained. Women were briefly screened for eligibility, recruited, enrolled, and confirmed as consenting while they were in labor, and interviewed after delivery by bilingual interviewers in their preferred or native language (English, Spanish, or Chinese).
Of 738 women initially screened, 369 women were eligible and gave consent for participation, 240 women were not eligible for participation, and 129 women refused to participate. Of the 369 eligible women, 329 contributed at least one blood sample (cord or maternal blood), medical record information, and a complete postpartum interview, all of which were required for full enrollment in the study. The sample was further reduced to 300 by the subsequent exclusion of women who were not yet pregnant on 11 September 2001 and those who delivered preterm (described below).
Data collection.
Information about the pregnancy and delivery was collected from the medical records of the mother and newborn. A 30- to 45-min interview was administered to each mother, in most cases on the day after delivery. The interview included questions on demographics, reproductive history, background environmental exposures, where the woman was working or living (where she actually was, even if not her usual residence or place of work) during each of the 4 weeks after 11 September 2001 and the average hours per day spent at each site in each week. Biomedical information about the pregnancy, type of delivery, and birth outcomes (gestational duration, birth weight, birth length, head circumference) were abstracted from the medical record or obtained from the maternal interview if the medical record was incomplete. The week of gestation at which the WTC event occurred was determined for all women. Because the timing of the event might have had an effect on the type and extent of any fetal growth problems associated with the event, we included a variable indicating whether or not the participant was in the first trimester on 11 September 2001. Because hospital recruitment did not begin until 13 December 2001, because of the need to obtain institutional review board approvals from the participating hospitals, women who delivered between 11 September 2001 and 13 December 2001 were not included in the study. Most of these excluded women were in the later stages of pregnancy at the time of the disaster; hence, most of the participants were in their first or second trimester on 11 September.
Geographic data.
Residential and work (for employed women) addresses were geocoded at the Center for International Earth Science Information Network of Columbia University’s Earth Institute, using geographic information system (GIS) software from Environmental Systems Research Institute (Redlands, CA), including ArcGIS 8.3 and the Street Map 2003 extension. The Manhattan hydrology layer came from the NYC DEP-funded NYCMap Project (NYC Department of Information Technology and Telecommunications 1999). Using the geocoded data, the linear distance from the WTC site was computed for each residence and work site. The estimated level of horizontal accuracy of the geocoded location is ± 25 feet. The GIS data enabled us to locate women in each of the 4 weeks after the disaster.
Statistical analyses.
We generated descriptive statistics and bivariate associations for all variables and examined them for distributional normality. We used multiple linear regression and logistic regression to assess the effects of proximity to the WTC site and stage of pregnancy when the event occurred, on gestational duration, birth weight, birth length, head circumference, ponderal index, and sex-specific small size for gestational age (SGA) among term deliveries (Alexander et al. 1996). We excluded 10 women who were determined not to have been pregnant on 11 September 2001, based on the gestational age of the baby at birth and the date of delivery. In addition, only women who had completed 36 weeks and 6 days of gestation, or 258 days, and considered full term were included in the analyses, because preterm delivery may have other, complex etiologies. These criteria excluded a total of 29 women, for a final sample of 300 women.
We included race/ethnicity (Asian, African American vs. all others) and Medicaid status (marker for poverty) as covariates in all analyses because of their potentially confounding effects on the relationship between exposure and birth outcomes. Other relevant covariates included infant sex, maternal height, prepregnancy weight, parity (0, ≥1), maternal age in years, cesarean section, and maternal medical complications (including preeclampsia, placental abruption, hypertension, and diagnosis of diabetes during the pregnancy). Smoking was not included because enrollment criteria required that women be nonsmokers during their entire pregnancy. In this cohort, sexually transmitted disease and alcohol use (self-report by interview yielded very low use) were not significantly associated with exposure or birth outcomes (p > 0.05), and their inclusion did not alter effect sizes. Therefore, we excluded them to limit the number of independent variables. All analyses were done using SPSS version 11.5 (SPSS Inc., Chicago, IL).
Results
Description of the sample.
Table 1 shows the maternal and newborn characteristics of the sample (n = 300) included in the analysis. The study population was diverse, reflecting the mixed residential and commercial nature of lower Manhattan and the broader area served by the delivery hospitals—an area with a wide socioeconomic range of employment and housing conditions. Of the 300 participants, 44.7% were college graduates and 17.7% had not completed high school. More than 80% were married or cohabiting for more than 7 years, 58.0% were having their first child, and only two women had a parity > 3, both in the reference group. Forty-two percent self-identified as white, 33% Asian, 15.3% black/African American, and 9.7% “other” or unidentified race/ethnicity. Of the 283 participants who responded to the question on Hispanic identification, 61 (21.6%) identified as Hispanic, of which 23 also identified themselves as white, 14 black/African American, and 24 “other/unidentified” race.
Classification of women by time and place.
The wide distribution of geocoded locations of women’s residential and work sites during week 1 is illustrated in Figure 1. For the analyses, women who resided or worked within 2 miles of the WTC site, an area including sections of New Jersey and Brooklyn, New York, and indicated in Figure 1 by the circle, were selected to capture health effects of the smoke and emissions. Women were classified into three exposure groups. Women were first classified by residence location, grouping all women who were living within the 2-mile radius at some time in the 4 weeks after 11 September 2001, regardless of where they worked. Then the remaining women were classified by whether they worked but did not live within the 2-mile radius. Anyone not in either of these groups was in the reference group, women who neither worked nor lived within the 2-mile radius at any time during the 4-week period. Twenty women in the group that lived within 2 miles also worked within 2 miles of the WTC. They were classified as residents of the area. Depending on the week, between 17 and 21 women who resided within the 2-mile radius left home for some part of each day to travel to places of employment outside the 2-mile radius. These women were also classified with the resident group. In addition, we classified women as either being in the first trimester of pregnancy (≤91 days) on 11 September or being in a later trimester, based on their gestational age at delivery.
The sample of women who resided within the area remained very stable over the 4 weeks, with only three women moving in or out of the area during the time period. The number of women who worked but did not live within the 2-mile radius increased over the 4-week period as women gradually returned to work (24 in the first week, increasing to 51 women in the fourth week). In all but the first week, those who worked in the area were, on average, approximately 0.4 miles closer to the WTC site than were area residents.
The distributions of average daily hours at home or work site within the 2-mile radius for each week after 11 September are shown in Figures 2 and 3. Among women who resided in the area, daily hours of exposure were relatively stable over the 4 weeks, with a weekly average range of 16.2–17.1 hr/day. Among women who were employed in the area, the daily hours at work increased from an average of 5.9 hr in the first week to 8.0 hr in the fourth week, as normal work hours were gradually resumed. The overall distribution of hours was bimodal, resulting in a significant difference between the residential and employment groups in daily hours of exposure averaged over the 4-week period such that the residential group spent significantly more hours within the 2-mile radius (16.7 hr) compared with the employment group (7.7 hr).
Birth outcomes.
All birth outcome analyses were limited to term deliveries. Table 2 shows the average length of gestation, birth weight, birth length, head circumference, ponderal index, and percentage of SGA births < 10th percentile; < 20th percentile is also shown) for term infants in each of the three exposure groups. There were significant group differences in unadjusted mean birth weight, birth length, and length of gestation. There were no significant differences in head circumference, ponderal index, or percentage of SGA births (either < 10th or < 20th percentile).
We used multiple regression analyses to assess the predictive power of proximity to the WTC and timing of the event in pregnancy for all birth outcomes, after adjustment for potential confounders and relevant covariates. Table 3, model 1, shows that term infants of women residing within the 2-mile radius during the 4 weeks after 11 September weighed, on average, 149 g less than did term infants born to women residing outside of that area, after adjustment for infant sex, maternal age, parity, prepregnancy weight, height, Medicaid receipt, race, and medical complications. This decrease in birth weight effect was not seen among infants born to women who were employed within the 2-mile radius.
The adverse effect on birth weight of residence within the 2-mile area was reduced but did remain significant after controlling for gestational duration (model 2), showing that the effect was partially mediated by but not entirely accounted for by shortening of gestation. The timing of the event during the first trimester of pregnancy was marginally significant (p = 0.057), and this effect was reduced substantially by the addition of gestational age to the model.
Table 3, model 3, shows the significant effect of residence within the 2-mile radius on birth length. Infants born to residents were, on average, 0.82 cm shorter than were those born to women living outside the area. This effect was reduced to 0.74 cm, yet remained significant, after the addition of gestational duration to the model (model 4). Again, this adverse effect was seen among area residents and not among women who traveled into the area to work in the first month. In fact, when gestation duration was controlled, women employed within 2 miles of the WTC had significantly longer infants (+ 1.0 cm). There was no significant birth length effect of trimester of pregnancy at the time of the event.
Table 4 shows that head circumference was not significantly associated with residence or employment within the 2-mile radius, after adjusting for covariates. There were significant negative effects on head circumference of timing of the WTC event, such that those who were in the first trimester of pregnancy on 11 September delivered term infants with significantly smaller heads (−0.48 cm). However, this effect was no longer significant with adjustment for gestational duration, indicating that the effect was mediated by shortening of duration of pregnancy. There were no residential or employment location effects on ponderal index or percentage of SGA births (< 10th percentile; results not shown).
Table 5 shows no significant reduction of length of gestation among term infants of women who lived within 2 miles of the WTC, and a marginally significant effect on those who worked in the area (p = 0.055). However, women who were in the first trimester of pregnancy on 11 September delivered, on average, 3.6 days earlier than did women in later stages of pregnancy, regardless of whether the women lived or worked close to the WTC. There were no significant interaction effects between distance and timing of exposure on any of the birth outcomes.
Discussion
Our results indicate that term infants born to women who were living within 2 miles of the WTC site during any of the 4 weeks after 11 September 2001 had significantly lower birth weights and shorter birth lengths than did term infants born to women living outside of the area. These birth weight and length effects were only partially mediated by a shortening of gestation, suggesting some additional effect on fetal growth, independent of length of gestation. In addition, occurrence of the WTC event during the first trimester of pregnancy was associated with significantly shortened gestation and slightly smaller head circumference, regardless of place of work or residence in the month after 11 September. Head circumference effects were entirely explained by gestational duration.
Our findings of decreased birth weight and length among term infants of mothers who resided within 2 miles of the WTC site are potentially important for subsequent health and development. Lower birth weight, even within the normal range (> 2,500 g), is associated with increased fetal mortality (Seeds and Peng 2000), neonatal mortality (Arias et al. 2003; Rees at al. 1996; Seeds and Peng 2000), infant mortality (Arias et al. 2003), subsequent poorer health and delayed physical and cognitive development (Barker 1996; Dietz 1994; Matte et al. 2001; Rice and Barone 2000; Richards et al. 2002), and increased susceptibility to stress in adulthood (which decreases with increasing birth weight up to 4,200 g; Nilsson et al. 2001).
The lack of similar effects on birth weight or birth length of infants born to women who worked but did not reside within the 2-mile radius may be due to fewer hours of exposure in this group. As shown in Figures 2 and 3, women who worked in the 2-mile radius spent significantly fewer hours per day in the area than did residents. Furthermore, a number of the employed women did not return to work within the 2-mile radius during the first week and/or worked shorter hours in the first few weeks after 11 September 2001, possibly minimizing their exposure during the highest emission period. Those who traveled into the area to work for some hours each day returned home daily to residences located outside of the area.
The additional finding that exposure to the event during the first trimester of pregnancy was associated with significantly shorter length of gestation among term infants, regardless of location of work or residence, is clinically important. The last weeks and days of gestation are characterized by rapid fetal growth. First, it has been previously shown that birth weight increases by approximately 500 g between 37 and 41 weeks of gestation, and the increase in weight during this period of gestation is of similar magnitude for infants in all size for gestational age categories, such as the 10th, 50th, or 90th percentiles of size for gestational age (Alexander et al. 1996). As noted above, increased infant birth weight is associated with a range of improved newborn health and developmental outcomes (Matte et al. 2001). Second, a shortening of gestation from 41 to 37 weeks is associated with a 4-fold increase in fetal mortality (0.77 vs. 3.0 per 1,000 births) and a 4-fold increase in neonatal mortality (0.44 vs. 1.6 per 1,000 births) (Seeds JW, Peng TCC, unpublished data). Smaller changes in gestational duration would be expected to have proportionately smaller, but still potentially important, effects on these outcomes.
Several previous studies have shown significant adverse effects of exposure to air pollution during pregnancy on birth weight and other pregnancy outcomes. Among African Americans in New York City, prenatal exposure to PAHs, as measured by personal air sampling during pregnancy, was associated with reduced birth weight and head circumference (Perera et al. 2003). Similarly, a study of mothers and newborns in Poland found that cord blood PAH–DNA adducts were significantly inversely related to birth weight, length, and head circumference (Perera et al. 1998). Other air pollutants, including sulfur dioxide and particulate matter ≤10 μm in diameter have also been shown to be associated with birth weight decrements (Chen et al. 2002; Yang et al. 2003).
Other adverse birth outcomes associated with air pollution include preterm delivery (Ritz et al. 2000; Xu et al. 1995), low birth weight (Bobak 2000; Bobak and Leon 1999; Lin et al. 2001; Wang et al. 1997), intrauterine growth restriction (Dejmek et al. 1999), and birth defects (Ritz et al. 2002). In addition, studies have shown that prenatal exposure to air pollutants is associated with increased rates of neonatal and postneonatal mortality (Bobak and Leon 1999; Pereira et al. 1998; Woodruff et al. 1997) and infant mortality (Loomis et al. 1999).
The air pollution from the dust and gases emitted during the WTC event and subsequent cleanup operation resulted in a relatively brief exposure, yet it is likely that the exposure was substantial for those pregnant women who spent large portions of each day within 2 miles of the site during the month after the tragedy. Proximity to specific sources of pollution (or the site of their measurement) has been used previously to characterize exposure and has demonstrated adverse effects on birth weight (Baibergenova et al. 2003; Ritz and Yu 1999). Using a measure of traffic density weighted for distance from the home, Wilhelm and Ritz (2003) reported an increased risk of preterm delivery and low birth weight among women who resided in the nearest quintile of distance from heavily trafficked roads. Consistent with these reports, the effect on birth weight in our study was seen among women living close to the WTC site in the 4 weeks after 11 September.
Although residential proximity was associated with reductions in birth weight and length, there were no apparent distance effects on head circumference, ponderal index, or percent SGA. Head circumference and length of gestation, however, were significantly associated with the timing of the event in the first trimester of pregnancy, although the head circumference effect was accounted for by length of gestation. We found no effects of proximity to the WTC site in the 4 weeks after the event on the odds of SGA births (< 10th percentile). Using a different recruitment procedure, Berkowitz et al. (2003) have reported increased risk of SGA births (8.2%) in a sample of private patients who were near the WTC on 11 September or in the subsequent 3 weeks compared with a sample of private patients who delivered in northern Manhattan during the same period (3.8%).
In the present study, the findings that length of pregnancy was associated with timing of the event in pregnancy, regardless of proximity, and that the reduced gestational duration had measurable effects on birth weight and length, suggest that additional mechanisms operating early in pregnancy, possibly stress related, may have been operative. There were no interaction effects between proximity to the site and timing of exposure, although there is always the possibility that the fetus is most vulnerable to toxic biochemical exposures in the first few months.
With respect to stress-related hypotheses, a number of previous studies have linked maternal stressful exposures to preterm delivery (Dunkel-Schetter 1998; Goepfert and Goldenberg 1996; Hobel et al. 1999; Wadhwa et al. 1998) and reductions in birth weight (e.g., Da Costa et al. 2000). Recently, maternal stress has also been implicated in miscarriage, through effects on immune mediators (Arck et al. 2001). Other reports have addressed the role of the maternal stress response as a possible modulator of toxicant effects (e.g., Singer et al. 2002). Taken together, this literature provides a biologic basis for possible adverse effects of stressful exposures on length of gestation (e.g., Wadhwa et al. 2001). Glynn et al. (2001) have shown that exposure to an earthquake was perceived as most stressful by women in early pregnancy and less stressful by women in later stages. These researchers observed that exposure to the earthquake in the first trimester of women within 50 miles of the epicenter was associated with a shortening of gestation to 38.06 weeks, compared with 38.69 weeks in those exposed in the second trimester, a difference of 4.4 days. In our study, gestation was also shorter, by 3.6 days, among women who were in the first trimester on 11 September 2001 compared with all other women. Lobel et al. (1992) demonstrated reductions in birth weight as well as gestational duration associated with perceived stress/distress, but no association with SGA (< 10th percentile). As in the present study, shortening of gestation accounted for only part of the decrement in birth weight that was associated with stress, suggesting that chronic stress can affect birth weight directly as well as indirectly through effects on gestation length.
A major strength of the present study is enrollment of exposed and unexposed women from a common clinical population. All women delivered at one of three lower Manhattan hospitals during the same time period. In addition, enrollment occurred before delivery, before the outcome of the pregnancy was known, so women’s decision to participate was not based on their knowledge of their own birth outcome. The potential sample selection bias introduced by volunteerism of women who experienced worrisome birth outcomes was thus avoided. Recruitment procedures ensured a wide range of race/ethnicity, income, education, and other characteristics, improving the generalizability of our findings. In addition, the subjects were geographically well dispersed during pregnancy with respect to the WTC site, providing a basis for comparing subjects with differential exposure.
A limitation of the study is that, because of the time required to obtain institutional review board approval from the participating hospitals, recruitment did not begin until December. Thus, the sample did not include women who were exposed during the last trimester of pregnancy, and we were able to compare only first versus second trimester effects. We were also unable to assess preterm deliveries, stillbirths, or spontaneous abortions possibly resulting from toxic exposures. Despite the inability to study these women who may have been at excess risk, we did detect a significant reduction in gestational duration among term deliveries.
The results reported here show that pregnant women living close to the WTC after 11 September 2001 were at increased risk of delivering infants with reduced weight and length, and that newborns of women exposed to this event in the first trimester had shorter gestations regardless of distance from the WTC site. Planned evaluations of children in this cohort at 1 and 2 years of age will address additional questions about the longer-term health and development implications of maternal prenatal exposure to pollution and psychologic distress resulting from the WTC disaster.
Figure 1 Geocoded locations of women’s work and residence addresses in the first week after 11 September 2001. Black circle indicates 2-mile radius from WTC site.
Figure 2 Average hours at home per day for women residing within 2 miles of the WTC site.
Figure 3 Average hours at work per day for women working within 2 miles of the WTC site.
Table 1 Subject characteristics.
No. of subjects Mean ± SD Range
Maternal age (years) 298 30.2 ± 5.14 18.1–40.7
Years of school 300 14.0 ± 3.58 2–21
Prepregnancy weight (lb) 299 135.7 ± 30.20 90–318
Height (cm) 298 163.1 ± 7.16 144.8–185.4
Income/household membera 272 $23,535 ± 17,053 $1,000–85,000
No. of prior live birthsb 300 0.62 ± 0.877 0–5
Primiparous (%) 58.0
Birth weight (g) 300 3,454 ± 453.8 2,040–5,255
Birth length (cm) 291 50.9 ± 2.89 32.0–57.0
Head circumference (cm) 291 34.3 ± 1.49 29.0–38.0
Gestational age (days) 300 278.0 ± 8.43 259–297
Trimester on 11 September 2001
First (< 92 days) 205
Second (92–182) 92
Third (≥183 days) 3
1-Min Apgar 300 8.7 ± 0.82 2–10
5-Min Apgar 298 9.0 ± 0.32 6–10
a Income based on midpoint of each of 10 household income categories, ranging from < $10,000 to > $90,000. The midpoint of the first category was set at $5,000, and that of the last category was set to $95,000. Some women did not report income.
b Only two women had a parity > 3.
Table 2 Unadjusted birth outcomes by place of residence and employment (within 2 miles of the WTC).
Birth outcomes Group 1: resided Group 2: worked Group 3: neither resided nor worked p-Valuea
Length of gestation (days) 277.7 (n = 80) 275.5 (n = 51) 279.0 (n = 169) 0.026
Birth weight (g) 3339.6 (n = 80) 3442.7 (n = 51) 3511.8 (n = 169) 0.019
Birth length (cm) 50.06 (n = 78) 51.44 (n = 48) 51.15 (n = 165) 0.008
Head circumference (cm) 34.10 (n = 78) 34.18 (n = 49) 34.51 (n = 164) 0.097
Ponderal indexb 2.75 (n = 78) 2.54 (n = 48) 2.65 (n = 165) 0.286
Percent SGA (< 10th percentile) 8.75 (n = 80) 5.88 (n = 51) 5.33 (n = 169) 0.581
Percent SGA (< 20th percentile) 23.8 (n = 80) 15.7 (n = 51) 18.3 (n = 169) 0.465
a By analysis of variance.
b Values are (g/cm3) ×100.
Table 3 Multiple regression of birth weight and birth length on proximity to the WTC and timing of the event in pregnancy in a sample of lower Manhattan term deliveries, 13 December 2001 through 26 June 2002.
Birth weight (g; n = 295a)
Birth length (cm; n = 287a)
Model 1
Model 2
Model 3
Model 4
Predictor Coefficient p-Value Coefficient p-Value Coefficient p-Value Coefficient p-Value
Resided within 2 miles −149 0.012 −122 0.024 −0.819 0.026 −0.737 0.039
Employed within 2 miles 1.44 0.984 53.7 0.419 0.853 0.063 1.01 0.024
1st trimester on 11 September −104 0.057 −27.0 0.595 −0.204 0.545 0.075 0.823
Maternal age (years) 2.14 0.713 −2.24 0.675 0.021 0.569 0.006 0.859
Male infant 237 0.000 206 0.000 1.51 0.000 1.42 0.000
Parity (0, ≥1) 107 0.053 152 0.003 0.376 0.273 0.508 0.131
Prepregnancy weight (lb) 1.69 0.081 1.45 0.100 0.000 0.933 −0.002 0.795
Maternal height (cm) 10.5 0.011 13.6 0.000 0.085 0.001 0.095 0.000
Medicaid 110 0.090 55.4 0.352 0.981 0.015 0.790 0.045
Asian 45.0 0.482 23.4 0.690 −1.04 0.010 −1.12 0.004
Black −60.8 0.424 −46.6 0.502 −0.901 0.060 −0.829 0.075
Maternal medical complicationsb −136 0.146 −77.4 0.365 −2.18 0.000 −1.98 0.001
Length of gestation (days) 21.6 0.000 0.075 0.000
a Numbers vary slightly because of occasional missing data.
b Complications included were hypertension, diabetes, and preeclampsia. No women had placental abruption.
Table 4 Multiple regression of head circumference (cm; n = 286a) on proximity to the WTC and timing of the event in pregnancy in a sample of lower Manhattan term deliveries, 13 December 2001 through 26 June 2002.
Model 1
Model 2
Predictor Coefficient p-Value Coefficient p-Value
Resided within 2 miles −0.288 0.151 −0.231 0.231
Employed within 2 miles −0.156 0.527 −0.037 0.876
1st trimester on 11 September −0.477 0.010 −0.300 0.096
Maternal age (years) 0.008 0.674 −0.002 0.902
Male infant 0.658 0.000 0.590 0.000
Parity (0, ≥1) 0.382 0.040 0.481 0.008
Prepregnancy weight (lb) 0.004 0.219 0.003 0.270
Maternal height (cm) 0.016 0.250 0.024 0.079
Medicaid 0.035 0.870 −0.084 0.692
Asian −0.004 0.985 −0.048 0.819
Black −0.279 0.280 −0.237 0.340
Maternal medical complicationsb −0.286 0.377 −0.163 0.602
Cesarean-section 0.627 0.003 0.600 0.003
Length of gestation (days) 0.049 0.000
a Numbers vary slightly because of occasional missing data.
b Complications included were hypertension, diabetes, and preeclampsia. No women had placental abruption.
Table 5 Multiple regression of gestational duration (days; n = 298a) on proximity to the WTC and timing of the event in pregnancy in a sample of lower Manhattan term deliveries, 13 December 2001 through 26 June 2002.
Length of gestation
Predictor Coefficient p-Value
Resided within 2 miles −1.22 0.279
Employed within 2 miles −2.59 0.055
1st trimester on 11 September −3.55 0.001
Male infant 1.26 0.188
Parity (0, ≥1) −1.92 0.065
Medicaid 2.71 0.026
Maternal age (years) 0.19 0.089
Asian 1.42 0.216
Black −1.04 0.462
Maternal medical complicationsb −2.55 0.153
a Numbers vary slightly because of occasional missing data.
b Complications included were hypertension, diabetes, and preeclampsia. No women had placental abruption.
==== Refs
References
Alexander GR Himes JH Kaufman RB Mor J Kogan M 1996 A United States national reference for fetal growth Obstet Gynecol 87 163 168 8559516
Arck PC Rose M Hertwig K Hagen E Hildebrandt M Klapp BF 2001 Stress and immune mediators in miscarriage Hum Reprod 16 1505 1511 11425839
Arias E MacDorman MF Strobino DM Guyer B 2003 Annual summary of vital statistics—2002 Pediatrics 112 1215 1230 14654589
Axelrod J Reisine TD 1984 Stress hormones: their interaction and regulation Science 224 452 459 6143403
Baibergenova A Kudyakov R Zdeb M Carpenter DO 2003 Low birth weight and residential proximity to PCB-contaminated waste sites Environ Health Perspect 111 1352 1357 12896858
Barker DJP 1996 Growth in utero and coronary heart disease Nut Rev 54 S1 S7
Berkowitz GS Wolff MS Janevic TM Holzman IR Yehuda R Landrigan PJ 2003 The World Trade Center disaster and intrauterine growth restriction [Letter] JAMA 290 595 596 12902358
Bobak M 2000 Outdoor air pollution, low birth weight, and prematurity Environ Health Perspect 108 173 176 10656859
Bobak M Leon DA 1999 Pregnancy outcomes and outdoor air pollution: an ecological study in districts of the Czech Republic 1986–8 Occup Environ Med 56 539 543 10492651
Centers for Disease Control and Prevention 2002 Cigarette smoking among adults—United States, 2000 MMWR Morb Mortal Wkly Rep 51 642 645 12186222
Chen L Yang W Jennison BL Goodrich A Omaye ST 2002 Air pollution and birth weight in northern Nevada, 1991–1999 Inhal Toxicol 14 141 157 12122577
Chen LC Thurston G 2002 World Trade Center cough Lancet 360 S37 S38 12504497
Da Costa D Dritsa M Larouche J Brender W 2000 Psychosocial predictors of labor/delivery complications and infant birth-weight: a prospective multivariate study J Psychosom Obstet Gynaecol 21 137 148 11076335
Dejmek J Selevan SG Benes I Solansky I Sram RJ 1999 Fetal growth and maternal exposure to particulate matter during pregnancy Environ Health Perspect 107 475 480 10339448
Dejmek J Solansky I Benes I Lenicek J Sram RJ 2000 The impact of polycyclic aromatic hydrocarbons and fine particles on pregnancy outcome Environ Health Perspect 108 1159 1164 11133396
Dejmek J Solansky I Podrazilova K Sram RJ 2002 The exposure of nonsmoking and smoking mothers to environmental tobacco smoke during different gestational phases and fetal growth Environ Health Perspect 110 601 606 12055052
Dietz WH 1994 Critical periods in childhood for the development of obesity Am J Clin Nutr 59 955 959 8172099
Dunkel-Schetter C 1998 Maternal stress and preterm delivery Prenat Neonat Med 3 39 42
Glynn LM Wadhwa PD Dunkel-Schetter C Chicz-Demet A Sandman CA 2001 When stress happens matters: effects of earthquake timing on stress responsivity in pregnancy Am J Obstet Gynecol 184 637 642 11262465
Goepfert AR Goldenberg RL 1996 Prediction of prematurity Curr Opin Obstet Gynecol 8 417 427 8979013
Hobel CJ Dunkel-Schetter C Roesch SC Castro LC Arora CP 1999 Maternal plasma corticotropin-releasing hormone associated with stress at 20 weeks gestation in pregnancies ending in preterm delivery Am J Obstet Gynecol 180 257 263
Jeffrey NL D’Andrea C Leighton J Rodenbeck SE Wilder L DeVoney D 2003 Potential exposures to airborne and settled surface dust in residential areas of lower Manhattan following the collapse of the World Trade Center—New York City, November 4–December 11, 2001 JAMA 289 1498 1500 12672752
Lewtas J 1994 Human exposure to complex mixtures of air pollutants Toxicol Lett 72 163 169 8202929
Lin MC Yu HS Tsai SS Cheng BH Hsu TY Wu TN 2001 Adverse pregnancy outcome in a petrochemical polluted area in Taiwan J Toxicol Environ Health A 63 565 574 11549116
Lioy PJ Weisel CP Millette JR Eisenreich S Vallero D Offenberg J 2002 Characterization of the dust/smoke aerosol that settled east of the World Trade Center (WTC) in lower Manhattan after the collapse of the WTC 11 September 2001 Environ Health Perspect 110 703 714 12117648
Lobel M Dunkel-Schetter C Scrimshaw SC 1992 Prenatal maternal stress and prematurity: a prospective study of socioeconomically disadvantaged women Health Psychol 11 32 40 1559532
Loomis D Castillejos M Gold DR McDonnell W Borja-Aburto VH 1999 Air pollution and infant mortality in Mexico City Epidemiology 10 118 123 10069245
Matte TD Bresnahan M Begg MD Susser E 2001 Influence of variation in birth weight within normal range and within sibships on IQ at age 7 years: cohort study Br Med J 323 310 314 11498487
McGee JK Chen LC Cohen MD Chee GR Prophete CM Haykal-Coates N 2003 Chemical analysis of World Trade Center fine particulate matter for use in toxicologic assessment Environ Health Perspect 111 972 980 12782501
McKinney K Benson S Lempert A Singal M Wallingford K Snyder E 2002 Occupational exposures to air contaminants at the World Trade Center Disaster site—New York, September – October, 2002 MMWR Morb Mortal Wkly Rep 51 453 456 12054422
NYC Department of Information Technology and Telecommunications 1999. Manhattan Hydrology Layer. NYCMap Project, Sclae 1:1,200. New York:NYC Department of Information Technology and Telecommunications.
Nilsson PM Nyberg P Ostergren PO 2001 Increased susceptibility to stress at a psychological assessment of stress tolerance is associated with impaired fetal growth Int J Epidemiol 30 75 80 11171861
Offenburg JH Eisenreich SJ Chen LC Cohen MC Chee G Prophete C 2003 Persistent organic pollutants in the dusts that settled across lower Manhattan after September 11, 2001 Environ Sci Technol 37 502 508 12630465
Pereira LA Loomis D Conceicao GM Braga AL Arcas RM Kishi HS 1998 Association between air pollution and intrauterine mortality in Sao Paulo, Brazil Environ Health Perspect 106 325 329 9618348
Perera FP Rauh V Tsai WY Kinney P Camann D Barr D 2003 Effects of transplacental exposure to environmental pollutants on birth outcomes in a multiethnic population Environ Health Perspect 111 201 205 12573906
Perera FP Whyatt RM Jedrychowski W Rauh V Manchester D Santella RM 1998 Recent developments in molecular epidemiology: a study of the effects of environmental polycyclic aromatic hydrocarbons on birth outcomes in Poland Am J Epidemiol 147 309 314 9482506
Rauh VA Whyatt RM Garfinkel R Andrews H Hoepner L Reyes A 2004 Developmental effects of exposure to environmental tobacco smoke and material hardship among inner-city children Neurotoxicol Teratol 26 373 385 15113599
Rees JM Lederman SA Kiely JL 1996 Birth weight associated with lowest neonatal mortality: infants of adolescent and adult mothers Pediatrics 98 1161 1166 8951270
Rice D Barone S Jr 2000 Critical periods of vulnerability for the developing nervous system: evidence from humans and animal models Environ Health Perspect 108 suppl 3 511 533 10852851
Richards M Hardy R Kuh D Wadsworth ME 2002 Birthweight, postnatal growth and cognitive function in a national UK birth cohort Int J Epidemiol 31 342 348 11980795
Ritz B Yu F 1999 The effect of ambient carbon monoxide on low birth weight among children born in southern California between 1989 and 1993 Environ Health Perspect 107 17 25 9872713
Ritz B Yu F Chapa G Fruin S 2000 Effect of air pollution on preterm birth among children born in southern California between 1989 and 1993 Epidemiology 11 502 511 10955401
Ritz B Yu F Fruin S Chapa G Shaw GM Harris JA 2002 Ambient air pollution and risk of birth defects in Southern California Am J Epidemiol 155 17 25 11772780
Seeds JW Peng TCC 2000 Does augmented growth impose an increased risk of fetal death? Am J Obstet Gynecol 183 316 323 10942464
Service RF 2003 World Trade Center: Chemical studies of 9/11 disaster tell complex tale of “bad stuff Science 301 1649 14500950
Singer LT Salvator A Arendt R Minnes S Farkas K Kliegman R 2002 Effects of cocaine/polydrug exposure and maternal psychological distress on infant birth outcomes Neurotoxicol Teratol 24 127 135 11943500
Wadhwa PD Culhane JF Rauh V Barve SS 2001 Stress and preterm birth: neuroendocrine, immune/inflammatory, and vascular mechanisms Matern Child Health J 5 119 125 11573837
Wadhwa PD Porto M Garite TJ Chicz-DeMet A Sandman CA 1998 Maternal corticotropin-releasing hormone levels in the early third trimester predict length of gestation in human pregnancy Am J Obstet Gynecol 179 1079 1085 9790402
Wang X Ding H Ryan L Xu X 1997 Association between air pollution and low birth weight: a community-based study Environ Health Perspect 105 514 520 9222137
Wilhelm M Ritz B 2003 Residential proximity to traffic and adverse birth outcomes in Los Angeles county, California, 1994–1996 Environ Health Perspect 111 207 216 12573907
Woodruff TJ Grillo J Schoendorf KC 1997 The relationship between selected causes of postneonatal infant mortality and particulate air pollution in the United States Environ Health Perspect 105 608 612 9288495
Xu X Ding H Wang X 1995 Acute effects of total suspended particles and sulfur dioxides on preterm delivery: a community-based cohort study Arch Environ Health 50 407 415 8572718
Yang CY Tseng YT Chang CC 2003 Effects of air pollution on birth weight among children born between 1995 and 1997 in Kaohsiung, Taiwan J Toxicol Environ Health A 66 807 816 12746128
|
15579426
|
PMC1253672
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2004 Dec 8; 112(17):1772-1778
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7348
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0097615579398PerspectivesEditorialGuest Editorial: The Legacy of Conflicts Haavisto Pekka United Nations Environment Programme, Geneva, Switzerland, E-mail:
[email protected] Haavisto is a former Finnish Minister of the Environment and Development Co-operation. He has been a member of the Finnish Parliament and is currently a member in the Helsinki City Council and a spokesperson for the European Greens. Haavisto has chaired several postconflict assessments for UNEP including assessments in the Balkans, Afghanistan, Liberia, Iraq, and the Occupied Palestinian Territories.
12 2004 112 17 A976 A976 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
The pictures during wars and conflicts usually bring to our living rooms the misery of human suffering. When conflicts are over, the news usually concentrates on reconstruction issues. However, the legacy of conflicts might also include longer-term security threats, such as environmental degradation, damaged infrastructure, and conflict-related risks to human health. Because of poor environmental administration in postconflict countries, environmental and health risks may not be addressed properly.
For the past 5 years the United Nations Environment Programme (UNEP) has been working in countries where the natural and human environments have been damaged as a direct or indirect consequence of conflict. In 1999, as the ruins of targeted industrial facilities in Kosovo, Serbia, and Montenegro were still smoldering, UNEP teams conducted the first postconflict environmental assessment there.
UNEP postconflict environmental assessments seek to identify immediate risks to human health and livelihoods and provide recommendations on priorities for clean-up, sustainable use of natural resources, and for strengthening environmental governance.
In the Balkans UNEP concluded that there were several environmental hot spots—such as targeted industrial facilities and oil refineries in Pancevo, Novi Sad, Kragujevac, and Bor—where immediate cleanup was needed to avoid further threats to human health. The Danube was at risk because of leakage of more than 60 different chemicals, including mercury, from Pancevo. These findings led the international community for the first time to include environmental clean-up in their postconflict humanitarian aid.
Since then, UNEP has conducted postconflict activities in Afghanistan, Bosnia and Herzegovina, Iraq, Liberia, the Occupied Palestinian Territories, and Serbia and Montenegro.
UNEP’s report on Afghanistan’s postconflict environmental assessment identified the pressures on the natural resources, including waters, soils, forests, and wildlife, and linked poor environmental management in the waste and water sectors directly to human health risks (UNEP 2003a). UNEP found that most of the country is subject to an alarming degree of environmental degradation exacerbated by poverty and population growth. Moreover, many of Afghanistan’s environmental problems can be traced back to the collapse of local and national forms of governance and resource management, highlighting the urgent need to rebuild the Afghan environmental administration.
In early 2003 UNEP published a Desk Study on the Environment in Iraq (UNEP 2003b). The report provided a timely overview of key environmental issues in the context of the recent conflict in Iraq. It also took into consideration the chronic environmental stress already in place from the Iran–Iraq war of the 1980s, the 1991 Gulf War, the unintended effects of the UN sanctions and environmental mismanagement by the former Iraqi regime. For example, draining the Mesopotamian Marshes and building artificial waterways has ruined some of the most valuable areas of biodiversity in Iraq. The water pollution is affecting not only the Euphrates and Tigris Rivers but also the wider Persian Gulf region.
The Desk Study on the Environment in the Occupied Palestinian Territories (UNEP 2003c) identified acute environmental problems that have arisen as a result of the ongoing conflict, as well as problems stemming from long-term inadequate resource allocation and environmental management. The report concluded that, despite the current political difficulties, environmental problems should be addressed immediately in order to preserve natural resources and establish a safe environment for future generations.
Wherever there has been a conflict, there are also environmental consequences. On the African continent UNEP has been working in Liberia, where the misuse of natural resources has not only been a source of conflict but has also sustained it. Furthermore, one of the most severe consequences of the conflict has been the massive movement of refugees and internally displaced people. A key contribution toward increasing regional stability will be to provide the Liberian government and people with the capacity and proficiency to manage their natural resources in a just and sustainable manner. Now the international community has to ensure that environmental issues are fully integrated into the overall reconstruction efforts.
Based on UNEP experience, there are certain general recommendations that can be made, despite the uniqueness of every postconflict situation. First, the environment cannot wait. Environmental experts should enter the country as soon as possible after the conflict to facilitate a proper assessment and integration of environmental issues into humanitarian aid and reconstruction efforts.
Second, support and capacity building of the existing or newly established environmental administration is crucial for long-term sustainability. Third, many postconflict countries have been suffering from political isolation, and there is an urgent need to reintegrate them into regional and international environmental cooperation.
The rules of warfare have been widely debated since the global war on terrorism started. What are the humanitarian principles that should be followed? Or are we adopting new rules in a new situation? Also the environmental rules of warfare should be debated. The ENMOD convention (UN 1977) already forbids environmental modification as a part of warfare: man-made floods or earthquakes are not allowed as weapons in wars.
Because targeting industrial facilities or using different type of weapons can pose high risks for populations, we should open a debate about the environmental rules of modern warfare. If there are wars, there must be rules.
==== Refs
References
UN (United Nations) 1977. Convention of the Prohibition of Military or Any Other Hostile Use of Environmental Modification Techniques. Available: http://disarmament.un.org:8080/TreatyStatus.nsf/ [accessed 12 November 2004].
UNEP 2003a. Afghanistan Post-Conflict Environmental Assessment. Geneva:United Nations Environment Programme. Available: http://postconflict.unep.ch/afghanistan/report/afghanistanpcajanuary2003.pdf [accessed 12 November 2004].
UNEP 2003b. Desk Study on the Environment in Iraq. Geneva:United Nations Environment Programme. Available: http://www.unep.org/pdf/iraq_ds_lowres.pdf [accessed 12 November 2004].
UNEP 2003c. Desk Study on the Environment in the Occupied Palestinian Territories. Geneva:United Nations Environment Programme. Available: http://www.unep.org/GC/GC22/Document/INF-31-WebOPT.pdf [accessed 12 November 2004].
|
15579398
|
PMC1253673
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A976
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.112-a976
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0098415579404EnvironewsForumWarfare: NRDC Knocks Nukes Chepesiuk Ron 12 2004 112 17 A984 A984 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
More than a decade after the end of the Cold War, the United States is spending 12 times as much on nuclear weapons and production as it does on programs to find and dispose of nuclear weapons, according to a recent report by the Natural Resources Defense Council (NRDC), a Washington, D.C.–based environmental organization. The report warns that the continued push for a new generation of nuclear weapons could lead to a second arms race. And with another arms race, analysts fear, could come renewed nuclear weapons testing and potential serious fallout for the environment.
“There is no good reason why the U.S. should be spending on average more than it did during the Cold War,” says Chris Paine, an analyst with the NRDC’s Nuclear Program and the report’s author. “The U.S. government needs to rethink the role that nuclear weapons should play in the post–Cold War era.”
Titled Weaponeers of Waste, the report analyzes six nuclear weapons projects, primarily located at the Los Alamos, Sandia, and Lawrence Liver-more laboratories. According to the report, the government spent $6.5 billion in fiscal year 2004, compared to the average $4.2 billion dollars (in 2004 dollars) it spent yearly during the Cold War. In fiscal year 2005, the U.S. Department of Energy (DOE), the federal agency overseeing the nuclear weapons complex, is asking Congress for $6.8 billion to support its nuclear weapons projects.
The report describes several of the projects it reviewed as “boondoggles.” They include the huge National Ignition Facility at Lawrence Livermore National Laboratory, a high-energy fusion laser that in 1997 the DOE said would be ready in 2005 at a cost of $1.2 billion, but now, after factoring in additional expenses and recalculating construction management costs, will cost as much as $5–8 billion. The government expects to complete the facility sometime between 2010 and 2014.
“The government seems determined to put a lot of money into very expensive nuclear weapons projects at the expense of nonproliferation programs, which are hurting for funding,” says Victoria Samson, a research analyst with the Washington, D.C.–based Center for Defense Information, a think tank that monitors the U.S. defense industry. “At a time that we are in a war on terrorism, it doesn’t seem like a good idea to spend money on [nuclear weapons] programs.”
Others believe the report is the real boondoggle. “The NDRC budget assessment is wrong, and they are misleading people,” says Bryan Wilkes, director of public affairs for the National Nuclear Security Administration in Washington, D.C. “Our weapons program budget also includes money for such things as security, administrative costs, infrastructure repair, secure transportation [to move weapons secretly around the country], and emergency response teams—not just nuclear weapons.”
Wilkes says charges that the government is spending too much money on nuclear weapons are irresponsible. He points to the science-based Stockpile Stewardship Program, which conducts tests to ensure the current stockpile remains safe, secure, and reliable without underground testing.
Wilkes further says the government has increased spending on nonproliferation programs by more than 60%. “If that figure doesn’t reflect our priorities,” he says, “I don’t know what does.” And he adamantly maintains there are no plans to develop, produce, or test nuclear weapons.
Yet according to Martin Butcher, director of security programs for the Washington, D.C.–based Physicians for Social Responsibility, there is deep skepticism in some quarters about such assurances, and concern that the Bush administration’s research program on nuclear weapons and refusal to ratify the Comprehensive Nuclear Test Ban Treaty may lead to the development of new or modified weapons that require proof testing.
“The history of nuclear weapons in this country has been an environmental catastrophe,” Butcher says. “We don’t want to repeat the mistakes of the past.” He adds that the Bush administration has given no signs of planning to resume atmospheric testing, but underground testing in the Nevada test site would still lead to the venting of irradiated gases. In the 1989 report The Contamination of Underground Nuclear Explosions, the congressional Office of Technology reported that since 1970, a total of 126 underground tests have resulted in 54,000 curies of radiation being vented into the atmosphere. Just one accident during nuclear testing could release 150 million curies into the atmosphere—about equivalent to what resulted when the atomic bomb was dropped on Hiroshima during World War II.
In the report, the NDRC urges Congress to implement several recommendations. They include consolidating the nuclear weapons complex to reduce costs, eliminate redundancies, and lessen its environmental footprint. The group also urges putting more focus on international efforts to reduce stockpiles and funding for the preparation of nuclear testing.
“Congress needs to take a closer look at the role and mission of our nuclear weapons programs,” says Daryl Kimball, executive director of the Arms Control Association, an independent organization that supports effective arms control and disarmament policies. “It’s a bad idea to assign new [projects and programs] to our country’s nuclear weapons program.”
Taking aim at nukes. A new report by the Natural Resources Defense Council challenges the government’s spending on and handling of nuclear weapons.
|
15579404
|
PMC1253674
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A984
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.112-a984
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a00987EnvironewsForumEHPnet: POV’s Borders: Environment Dooley Erin E. 12 2004 112 17 A987 A987 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
The Public Broadcasting Service (PBS) has long been known for the quality of its programming, which runs the gamut from children’s shows to revealing documentaries. Now PBS is taking its talents to the Internet with an award-winning series, POV’s Borders. An outgrowth of PBS’s long-running television series POV, each yearly installment of the online series seeks to challenge visitors’ preconceptions about everyday aspects of our existence. The latest installment in the online series is POV’s Borders: Environment. Located at http://www.pbs.org/pov/borders/2004/index.html, the multimedia presentation uses a plethora of tools to explore how people relate to the three essential elements of our existence: air, water, and the soil that grows our food.
According to the Air section of the website, there are 31 million vehicles in California serving a population of 36 million people. This portion of the website looks at what drives Californians’ auto purchasing choices. There are video and print interviews with people who purchased electric and hybrid cars, an online chat room that allows visitors to voice their opinion about which type of vehicle is best for the environment, and a mini-documentary about the first service station in California to offer alternative fuels.
The Water section examines the debate in the United States over drinking bottled water versus tap water. Among the issues in this debate is the amount of plastic piling up as a result of bottled water consumption. In this section, one man tells how he reuses his water bottles. There is also a portion on America’s most polluted waterway, Newtown Creek, which runs between Brooklyn and Queens in New York City. A short film describes how children have worked to help clean up this desolate waterway and reclaim it as a natural space. The site includes tips to help visitors do their own waterway mapping and links to other sites that focus on water quality, such as the Environmental Protection Agency’s volunteer monitoring page.
The Earth section looks at the ground as a source of food. Two interactive features in this section teach visitors about heirloom varieties of plants and about saving seeds. There is also an interview with photographer and pasta maker Douglas Gayeton about the Slow Foods movement in Italy. This movement is trying to conserve traditional processes of raising animals and plants as well as producing food products.
Gayeton is also featured in Border Talk, one of three complementary sections of the site. The Border Talk section presents essays by artists, scientists, and others whose work is related to the environment. The For Educators section of the site provides six free lesson plans to accompany the Air, Water, and Earth pages. The PDF- and HTML-format lesson plans are suitable for middle school and high school classes. Finally, the Resources section provides a convenient index by category of all of the websites referenced throughout the site.
|
0
|
PMC1253675
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A987
|
utf-8
|
Environ Health Perspect
| 2,004 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a00988EnvironewsNIEHS NewsEthics in Environmental Health Adler Tina 12 2004 112 17 A988 A990 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
When it comes to the ethics of health research, “there’s been a presumption that ethicists and ethics committees will be in charge and solve ethical problems,” says Ann Cook, director of the National Rural Bioethics Project at the University of Montana in Missoula. More and more, however, environmental health researchers are realizing their need to be directly involved in the ethics questions facing them and their community partners.
Cook describes ethics as “something that everyone in the community has a stake in and needs to know about.” The NIEHS and the National Human Genome Research Institute agree. In 2002 the two institutes launched a grants program called Partnerships to Address Ethical Challenges in Environmental Health, which aims to tackle these issues by promoting community–researcher collaborations.
As part of the larger NIEHS Environmental Justice Program framework, the Partnerships program seeks to remedy the unequal burden borne by socioeconomically disadvantaged persons in terms of residential exposure to greater-than-acceptable levels of environmental pollution, occupational exposure to hazardous substances, and fewer civic benefits such as sewage and water treatment. Chief among ethical concerns for such populations is ensuring that research studies are designed and conducted with the involvement of those being studied rather than regarding them simply as study subjects.
Program grantees, including Cook’s team, receive up to $200,000 annually for five years to investigate environmental ills in a community, survey residents’ attitudes about both local environmental problems and health studies in general, and develop educational campaigns to meet local needs. Grantee teams must include an environmental health scientist, a social scientist or expert on issues such as racial, ethnic, or socioeconomic discrimination, and a representative from a local community organization that works on environmental issues.
A variety of groups, from environmental organizations to schools of public health, receive funding through the Partnerships program. Grantees are now halfway through their projects and ready to discuss some of their findings—and frustrations.
Defining “Community”
In an effort to develop a series of models for carrying out effective community review of environmental health research, Peggy Shephard, executive director of West Harlem Environmental Action (WE ACT) in New York City, and her colleagues have been listening in on NIH panel discussions between researchers and their community partners. Shephard’s team has also conducted a series of interviews and focus groups with environmental health researchers and their long-term community partners about the workings of such relationships.
One of WE ACT’s preliminary findings is that “we need to stop using the word ‘community,’” says Shephard. The word is repeated so often and in so many contexts that it’s becoming meaningless, she says. In part because “community” has no clear definition among researchers, “we’re coming to the viewpoint that there is never real ‘community consent’ for research,” she says. For example, she asks, is consent achieved when one community group okays a health study, or only when representatives of multiple community groups endorse it? WE ACT is addressing these and other questions—including how to appropriately define “community”—in an upcoming report.
Ensuring Savvy Study Participants
Researchers at Boston University have rounded up four potentially divergent groups—public health officials, community activists, community residents, and representatives of academe—with the goal of coming to some common understanding of what is involved when scientists embark on a community health study. The team is led by David Ozonoff, an environmental epidemiologist at the Boston University School of Public Health.
What motivated the project, explains project manager and Ozonoff graduate student Madeleine Scammell, is the many calls to university and state health departments across the country from residents concerned about a variety of potential health hazards in their towns. Callers often request a health study, yet when studies are done, communities are often unhappy with the results because of vastly differing expectations about what a health study provides, says Ozonoff. For example, researchers, perhaps preoccupied with the problem of statistical power for small populations, are often stricter than a lay person might expect as to what constitutes positive evidence of an environmental health problem.
At focus groups and during interviews that Ozonoff’s team conducted, residents often reported that it’s tangible evidence of pollution (such as soot on the cars) rather than media coverage that motivates them to take action, says Scammell. Community members are also more concerned than researchers may appreciate about research politics, such as why their town was selected as a study site.
Teasing Out Interactions
A 200-mile stretch of New York’s Hudson River has achieved the dubious distinction of being one of the country’s largest Superfund sites. Staff at the W. Haywood Burns Environmental Education Center in Albany, where the Hudson and other polluted waterways converge, are investigating what this distinction means for residents of Albany’s poorest neighborhoods.
Led by principal investigator Donna Perry, a registered nurse at the Burns Center, the team and their community partners interviewed residents in 80 primarily African American households to get baseline information on respondents’ health and environment. They found that half of the respondents were smokers. Many had been physically assaulted and reported frequently hearing gunshots near their homes. The smell of gasoline, sewage, and exhaust also was common near their homes. Almost 44% of respondents had breathing problems. Perry and her colleagues are now determining whether the exposure to environmental pollutants in combination with smoking, emotional stress, heredity, lifestyle, and even community zoning decisions may create significant health hazards.
The team is developing health and environmental education materials that are culturally sensitive to the Albany residents they serve. Recommendations for conducting environmental health surveys in urban communities and communities of color are forthcoming, says Perry.
Countering a Toxic Talisman
Downriver from Albany, Hal Strelnick, a physician at Montefiore Medical Center in the Bronx, leads the South Bronx Environmental Justice Partnership. He and his colleagues are focusing some of their ethics grant dollars on an unusual problem with mercury: members of various religious groups believe that spreading this toxicant around their homes will bring good luck and ward off evil, explains Strelnick.
The ethical challenge of establishing rapport and trust with these groups is complicated; when the New York City Department of Health banned the sale of elemental mercury at the folk pharmacies serving some of these groups, adherents became reluctant to discuss the practice with outsiders. “We wanted to determine if there was a more productive and respectful and ethical way [to educate about mercury],” Strelnick says.
South Bronx residents are not “aware of mercury as an environmental problem unto itself, though they are highly aware of lead, and they understand when you explain that mercury acts like lead in the body,” says Strelnick. The team is partnering with community religious leaders to develop a protocol for educating the public, without panicking them, about the dangers of the ritual use of toxic substances. They are also working on a more general public information campaign on how residents can assess and address community environmental issues.
Building Trust and Community Capacity for Research
If you ask representatives of community organizations in an area neighboring a prestigious medical school about environmental health and community–researcher relations, you’d better be prepared for a landslide of ideas on how to build effective partnerships. That’s what Mark Farfel, a public health researcher at the Johns Hopkins Bloomberg School of Public Health in Baltimore, Maryland, and colleagues discovered when their Environmental Justice Partnership sought feedback about how to improve the research process.
The partnership uses a participatory model and comprises staff and faculty at the Bloomberg School of Public Health, 11 different East Baltimore organizations, and faculty and students from the Maryland Institute College of Art.
Focus group participants spoke about the poor state of their community’s environment and described negative experiences during research studies, including lack of communication from researchers conducting studies and lack of community involvement. Participants were not entirely negative, however. They agreed that research can be beneficial if the community is involved up front, if the findings are shared with participants and the community at large, and if community–researcher partnerships work to sustain needed programs and policies.
The partnership has followed up by writing grants with board organizations, holding a community fair, and designing educational programs for residents about issues such as lead poisoning. The community board is also working with the Bloomberg School of Public Health to ensure that research in East Baltimore is mutually beneficial.
Putting Environmental Research on Stage
Communities in North Carolina face environmental contamination from multiple sources, from hog slaughterhouses to wood-laminating industries. Carolyn Crump, a public health scientist at the University of North Carolina at Chapel Hill, and her community colleagues are using theater, along with more traditional educational materials, to open discussion on how health research affects the people who live near pollution hot spots. The team is writing and piloting scripts in the style of Reader’s Theater, in which performers read from a script rather than act out memorized parts. They are also developing facilitator guides that will identify key points for discussion following the performances.
The theater pieces may be performed at community centers, schools, churches, government or other professional offices, conferences, and workshops. The performances are meant to encourage performers and audience members to talk about, among other topics, their understanding of the role of research in identifying environmental hazards, says Crump.
The performances will also document the stories of communities fighting for environmental justice and the experiences of attorneys and researchers who work on environmental health issues. “Cross-disciplinary exchange is one of the main [intended] outcomes of our project,” Crump says.
Mining the Community Goodwill
Cook’s team in Montana is working with residents in Libby, a mining town in the upper northwest corner of the state. A vermiculite mine that operated in Libby from 1921 to 1990 exposed workers, their families, and the local environment to dangerous levels of toxic amphibole asbestos. “When you are dealing with Superfund kind of issues, communities can get fractured, so we are using information and ethics to bring people together,” says Cook.
Earlier health studies have shown that scientists, health care providers, and Libby residents alike need more information on many issues related to asbestos, including the health risks and health care options. To meet that need, Cook’s team is offering a website (http://www.umt.edu/Libbyhealth/) where visitors can read facts that dispel myths about asbestos, download learning activities, and read summaries written in lay language of the legal and scientific issues involved in the Libby case.
The team is also field-testing material designed to help people with asbestos-related disease and other community members understand what a research project is. “In places such as Libby, where there is lots of research going on, you need to clarify what it means to participate in a research project,” says Cook.
To reach out to younger members of the community, the group is developing materials on asbestos and the history of the community for use in local schools. “Schools didn’t discuss [the asbestos problem] with students because it was perceived as a hard topic to talk about,” Cook says.
Training International Bioethicists
The need for better partnerships between communities and researchers is in no way unique to the United States. The NIEHS also cosponsors, along with several other NIH institutes, projects that address inequities in developing countries.
Developing countries present unique bioethical challenges, says bioethicist Ruth Macklin of the Albert Einstein College of Medicine in the Bronx. For one thing, in countries where many participants are illiterate, written informed consent documents are inappropriate. In addition, she says, the lack of well-trained institutional review boards makes independent ethical review almost impossible. There is also pointed debate about whether foreign investigators need to provide care that is better than or equivalent to what the study participants would normally receive in their country.
To address such issues, Macklin and her colleagues provide seven months of bioethics training every year in Buenos Aires to four Latin American professionals and scholars with experience in studies involving human subjects or research ethics. The training is funded by the John E. Fogarty International Center’s International Bioethics Education and Career Development Awards program, which gives foreign and domestic universities up to $250,000 annually to support international bioethics education for professionals from low- and middle-income countries.
Under the guidance of Macklin and her colleagues, participants take courses in bioethics, attend meetings of different research ethics committees, and prepare a detailed plan for implementing activities in research ethics at their home institutions. Macklin’s recent graduates “are almost without exception engaged in ongoing research or program development in bioethics,” she says.
A Group Effort
When academic and community groups work together, whether in the United States or abroad, collaborators and participants need to address their long-held assumptions about science, communities, and poverty, ethics grantees say. For example, says Farfel, some African Americans are wary of researchers and their studies in the wake of the infamous Tuskegee Syphilis Study conducted from 1932 to 1972, during which the Public Health Service denied treatment to almost 400 poor African American men who had the disease. Episodes like that lead many would-be study participants to view research as something done to them, not for them, Farfel says.
Nevertheless, residents are increasingly receptive to this approach of bringing ethics and community participation into all aspects of environmental health research. “Receptive, yes,” says Cook. “And cautious.”
|
0
|
PMC1253676
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A988-A990
|
utf-8
|
Environ Health Perspect
| 2,004 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a00991EnvironewsNIEHS NewsHeadliners: Respiratory Health: Air Pollution Impairs Lung Development in Children Phelps Jerry 12 2004 112 17 A991 A991 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Gauderman WJ, Avol E, Gilliland F, Vora H, Thomas D, Berhane K, McConnell R, Kuenzli N, Lurmann F, Rappaport E, Margolis H, Bates D, Peters J. 2004. The effect of air pollution on lung development from 10 to 18 years of age. N Engl J Med 351(11):1057–1067.
Mounting evidence suggests that exposure to air pollution has long-term effects on lung development in children; reductions in lung function have been observed in studies in Europe and the United States. To further investigate these effects, this NIEHS-supported research team performed a prospective epidemiologic study on 1,759 children from 12 communities in Southern California.
The communities had a wide range of exposures to air pollutants including particulate matter, acid aerosols, ozone, and nitrogen dioxide. The team recruited fourth-graders and performed lung function tests annually for eight years.
Over the eight-year period, decreases in a measurement of lung function known as forced expiratory volume (FEV1) were associated with exposure to nitrogen dioxide, acid aerosols, particulate matter, and elemental carbon. The decreases noted were statistically and clinically significant. For example, the risk of diminished FEV1 was almost five times higher at the highest level of particulate matter exposure than at the lowest level. The magnitude of the effects on development of lung function was comparable to that reported for exposure to maternal smoking.
The authors conclude that these results can be generalized to children living in other parts of the United States that have high air pollution levels. The results indicate that current ambient air pollution levels can have chronic and adverse effects on lung development in children, leading to clinically significant lung function deficits in adulthood. Given the severity of the effects and the importance of lung development as a determinant of morbidity and mortality during adulthood, it is important to continue identifying strategies for reducing air pollution.
|
0
|
PMC1253677
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A991
|
utf-8
|
Environ Health Perspect
| 2,004 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0099215593452EnvironewsNIEHS NewsBeyond the Bench: Help Instead of Hype Dooley Erin E. 12 2004 112 17 A992 A992 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Breast cancer strikes 1 in 7 American women, making it the most commonly diagnosed cancer among women in the United States. Although certain genetic factors can play a part in the etiology of the disease, scientists are studying other important factors including estrogen-related factors, lifestyle choices, and environmental risk. Understanding these factors can help women make informed decisions about their health and avoid being another breast cancer statistic.
Researchers at the NIEHS-funded Center for Environmental Health and Susceptibility, housed in the University of North Carolina at Chapel Hill School of Public Health, are leading the way in determining both the genetic and other causes of breast cancer. And the center’s Community Outreach and Education Program (COEP), headed by Frances M. Lynn, a professor of environmental sciences and engineering, has developed a workshop program to spread the word to North Carolina residents that they need not be helpless victims of this disease.
To assist in developing the workshop, the COEP partnered with the Breast Cancer Coalition of North Carolina, a nonprofit organization that advocates on behalf of those with breast cancer and their families. A scientific advisory board representing a variety of medical disciplines reviewed the workshop materials and continues to work with COEP staff to answer participants’ questions and keep the workshop as current as possible.
Visitors to the center’s website can download the workshop materials at http://www.sph.unc.edu/cehs/outreach/elsi.htm. Visitors can download the 15-slide PowerPoint presentation that is used in the workshop, as well as an agenda, facilitator instructions, case studies, fact sheets, and take-home activities.
The presentation introduces the workshop audience to the known possible risk factors for breast cancer, as well as some risk-reduction measures women can take. The presentation divides risk factors into four groups: personal or estrogen-related risk, lifestyle risk, environmental risk, and genetic or inherited risk.
The environmental risk portion of the presentation explains gene–environment interactions that occur as a result of exposure to toxicants and how that differs from risk associated with inheriting one of the so-called breast cancer genes (BRCA1 or BRCA2). Despite the frightening prospect of breast cancer running in families, only 5–10% of breast cancer cases are thought to be genetic in origin. Slides describe instances where this inherited risk may be implicated in breast cancer. Participants also learn about the ethical, legal, and social implications of genetic testing—how the testing is done, how they should decide if they need it, and what may happen if they test positive.
The interactive portion of the workshop includes fun learning activities, such as Reduce Breast Cancer Bingo, which has been a hit with the senior citizens that have taken part in the program to date. Participants win when they correctly identify four risk-reduction facts in a row, including the importance of exercising, eating vegetables, and limiting exposure to secondhand smoke. A related activity presents participants with fictional case studies for three women, one with a family history of breast cancer, one with lifestyle risk factors, and one with environmental risk factors. Participants are asked to identify both the risk factors and any protective factors each women has, and to recommend how each woman might reduce her risk.
The workshop, which has been conducted across North Carolina, has been developed so that women who have completed it know not only how to better care for themselves but also how to advise other women. In conducting the workshops, COEP staff hope to dispel some of the myths women have about breast cancer and instill optimism instead.
|
15593452
|
PMC1253678
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A992
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.112-a992
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0099415579406EnvironewsFocusBattleScars: Global Conflicts and Environmental Health Brown Valerie J. 12 2004 112 17 A994 A1003 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
War is as old as humanity, but the study of its environmental health effects is just beginning. Age-old problems still follow war—lack of food, shelter, water, and sanitation, risk of infectious diseases, and psychological trauma. But war today, in all its modern permutations, can also saddle populations with new threats from industrial and military chemicals, pesticides, and radiation.
Modern conflicts show a fundamental departure from the form of earlier wars. The Nobel Foundation report Wars in the 20th Century and Nobel Peace Prize Statistics states, “From 1900 to 1910, wars of all categories were represented rather evenly, whereas from 1990 to 2000 most were civil wars.” Between 1945 and 1975 many former European colonies waged wars of independence in Latin America, Africa, and Asia. “Today there are few interstate wars with clearly defined parties, but civil wars have become increasingly internationalised,” states the report. “Few internal wars today take place without the intervention of foreign states.”
The post–Cold War world is split by development inequities, competition for control of natural resources, and seemingly intractable ethnic and religious divisions. Today, more than ever, conflict is a tangled interplay of social, political, and economic factors. In a speech delivered to the United Nations on 5 October 2004 titled “Development and Conflict,” Paul Collier of the Center for the Study of African Economies at Oxford University noted that the more dependent a country is on the export of natural resources, the more vulnerable it is to civil war, and that doubling the per capita income halves the risk of conflict. [For more on the connection between conflict and natural resources, see “Global Resources: Abuse, Scarcity, and Insecurity,” EHP 112:A168–A175 (2004)].
Wars are costly, too. Civil war in a poor country lasts an average of 10 years and costs $50 billion. More than half this cost is borne by neighboring countries, which often see influxes of fleeing refugees and combatants, Collier said.
Perhaps the most important change in warfare, from the perspective of the environment, is the fact that wars are no longer limited to a designated field and clearly identifiable combatants. Instead, they may rage in urban streets and village squares, on cultivated land, or along highways, and the fighters may emerge from and blend into the civilian population. Because conflicts are no longer cordoned off in specified combat zones, but are now played out in everyday human environments, the environmental health consequences of war increase exponentially.
The Effects of Destabilization
The invasion of modern warfare into urban areas means millions of people can be rapidly displaced. Some of these people become refugees in other countries, but many others stay in-country as so-called internally displaced persons (IDPs). Globally, the movement of refugees and IDPs is a fluid, indeed tidal phenomenon. The country of origin for the largest number of refugees is Afghanistan, with about 2.1 million people having fled by the end of 2003, according to the UN High Commissioner for Refugees report 2003 Global Refugee Trends. Most Afghan refugees go to neighboring Pakistan (which hosts about 12% of all refugees under the protection of the UN High Commissioner for Refugees) and Iran.
Despite the seemingly constant number of conflicts around the world and the many populations of refugees and IDPs, the 2003 Global Refugee Trends report noted a drop of just over 3 million in such populations from 2002 to 2003. An “almost unprecedented level of voluntary repatriation” was observed in 2002 and 2003, with 3.5 million refugees going home. The number of IDPs has also decreased in some regions, including Bosnia and Herzegovina, Angola, The Former Yugoslav Republic of Macedonia, and the Democratic Republic of the Congo.
But the report also noted significant increases in refugees moving from Sudan to Chad and from Liberia to Cote d’Ivoire, Guinea, Sierra Leone, and Ghana. And a total of at least 1 million IDPs remain in Azerbaijan, Georgia, the Russian Federation, and Serbia and Montenegro. Colombia and Liberia each saw more than 250,000 more IDPs in 2003.
By far the greatest danger to the greatest number of people in conflict areas and those fleeing violence is the lack of life’s most basic necessities: potable water, food, shelter, and sanitation facilities. Crowded quarters make infectious disease outbreaks inevitable. Stressed by trauma and malnutrition, and without adequate medical care, refugees cannot fight off cholera, typhus, hepatitis, scabies, and numerous other contagious ailments.
Carol Smedberg, an emergency medical technician who volunteers with the Portland, Oregon–based Northwest Medical Teams, visited Liberian IDP camps in September 2004. “The main problem is the water,” Smedberg says. “Normally we tell people to drink more water, but there the water is the cause [of most of the health problems].” People have only charcoal briquettes for fuel, Smedberg says, and it is almost impossible to boil their drinking water, which is taken out of a stream that is also used as a toilet. Chicken pox breaks out about every two weeks as new people arrive in the camps, according to Smedberg.
Relatively developed countries are at just as much risk of war-related environmental health problems as the developing world. According to the GEO Year Book 2003 published by the UN Environment Programme (UNEP), unreliable electricity supplies in Iraq have caused sewage treatment equipment to stop working, sending raw sewage and industrial waste directly into the Tigris River, Baghdad’s only source of water, as well as other bodies of water. On 25 September 2004 The New York Times reported that water and sewerage failures had contributed to an outbreak of at least 200 hepatitis E cases and 5 deaths. Like other forms of the disease, hepatitis E causes fever, jaundice, fatigue, nausea, and vomiting; it is especially threatening to pregnant women and fetuses.
Iraq’s problems don’t end there. In a Lancet paper published online on 29 October 2004, Les Roberts of the Johns Hopkins Center for International Emergency Disaster and Refugee Studies reported that the risk of death had more than doubled after the 2003 U.S. invasion. The major post-invasion cause of death was violence, which was widespread and attributed mainly to coalition air strikes. Excess deaths were estimated to be at least 100,000, with most victims being women and children. And a national assessment conducted by the new Iraqi government’s health ministry reported 5,460 cases of typhoid in the first three months of 2004, according to a 13 October 2004 article published in Nature online. The Iraqi report also said mumps, measles, and other infectious diseases were ravaging the country’s children, one-third of whom are chronically malnourished. In fact, the report said, Iraq’s once relatively robust overall state of health is now comparable to that of Yemen and Afghanistan, where citizens face very high infant mortality and little access to clean water and sanitation services.
It can be difficult, sometimes impossible, to deliver aid to conflict-ridden regions. In an April 2004 country brief on Sudan, officials with the UN World Food Program (WFP) estimated that food assistance was necessary for 1.18 million Sudanese who were chronically malnourished due to drought, floods, and war. Aid was begun but suspended in mid-October after two Save the Children aid workers were killed by a landmine, and the WFP decided the security situation was too unstable to put its aid workers at further risk.
Many of these same problems exist in the Chechnya conflict. By 2003 about 260,000 Chechens had set up camps in the adjacent Republic of Ingushetia in farm fields and factory grounds, living in leaky tents with inadequate protection from the cold. Tuberculosis was common.
The New York City–based International Rescue Committee (IRC) has set up or repaired 66 potable water supply points, collected garbage, and serviced latrines in Ingushetia, but Ingush authorities have restricted the amount and type of aid humanitarian groups could provide to refugees in Ingushetia. For example, according to a June 2003 press release by the international medical aid agency Médecins Sans Frontières (MSF), Ingush authorities had just that month suddenly declared an MSF temporary shelter project illegal and barred Chechen refugees from moving in.
Despite this pressure, most Chechen refugees are loath to return to Chechnya, where conditions are very dangerous, housing is almost nonexistent, and services have broken down. To help ease the situation in Chechnya, the IRC has for the last three years been trucking water to 20,000 Chechens in Grozny. And as of 2003 the organization had built 35 water reservoirs to be hooked up to the city’s water mains. The IRC also builds and maintains latrines in Grozny, conducts pest control activities, and resurrects homes, including making repairs to electrical and gas lines.
Weapons of War I: Landmines
Landmines have been in widespread military use since World War II, and the UN estimates there are 60–80 million laid around the world, many in places where conflict has long since ceased. Such landmines can destroy lives and societies for generations. According to the Landmine Monitor Report 2003, a publication of the International Campaign to Ban Landmines (ICBL), there are an estimated 200–215 million landmines currently stockpiled by 78 countries. All but about 10 million of those landmines are in nations that are not parties to the Mine Ban Treaty, an international convention that requires signatories to destroy their stockpiles within 4 years and clear all laid landmines within 10 years. Among these nonsignatories are China (home to an estimated 110 million landmines), Russia (with 50 million), the United States (with 10.4 million), and Pakistan (with 6 million). The Landmine Monitor Report 2003 also states that mines cause 15,000–20,000 new deaths and injuries per year (most victims are male civilians). Landmine conditions are dire and worsening in several countries, such as Chechnya and Nepal.
In more than 80 countries landmines make land unusable and impede the post-conflict return to functioning economies and social life. Children who have lost limbs generally need a new prosthesis every year to keep up with their growth. Survivors can have great difficulty working, particularly in rural and agricultural communities. And strained medical systems are easily overwhelmed by victims’ need for continuing care.
In Thailand, an area of about 2,557 square miles is contaminated with landmines, affecting half a million people, according to a Kingdom of Thailand Landmine Impact Survey completed in 2001. The densest concentration of landmines lies along the border with Cambodia. Most are distributed in hilly forest areas, preventing traditional uses of the forest, such as food- and wood-gathering, and making decommissioning very difficult.
But ICBL coordinator Liz Bernstein says the general trend is toward a lessening of the scale of devastation, thanks to the Mine Ban Treaty and other ban movements. The treaty has been ratified by 143 countries. More than half the countries where landmines are deployed are at peace, enabling decommissioning to begin. Bernstein says, “When we began [working on the treaty] there were 54 countries producing landmines; today there are about a dozen. Now there’s virtually no trade in landmines. The only governments we found last year actively using them on a daily basis were Russia in Chechnya and Burma/Myanmar, where there is a civil war.”
Weapons of War II: Depleted Uranium
Probably the most inflammatory war-related environmental health issue is that of depleted uranium (DU), which is the remnant of uranium left after U-235 (the isotope used in nuclear power generation and bomb production) is largely removed. Because of its high density, DU is used both in armor-piercing shells and in tank armor itself. DU ignites upon impact, sending a fine black powder of mixed soluble and insoluble uranium oxides into the air. The North Atlantic Treaty Organisation (NATO) and the U.S. military fired DU weapons during the 1991 Gulf War and against the Serbs in the Balkan crises of 1994–1995 and 1999. The United States also used DU in the 2003 Iraq war, and the British used small amounts in the Iraq and Kuwait wars in 1991 and in 2003.
Uranium is everywhere in the environment, but generally at low concentrations. Most human exposure is through ingestion via food and water. DU is about 60% as radioactive as naturally occurring uranium, and is chemically toxic as well. If ingested, DU behaves very similarly to ambient natural uranium, which the body clears fairly rapidly through urine and feces. However, the insoluble oxides of DU can become lodged in the body by inhalation or as shrapnel fragments. The radioactivity and chemotoxicity of DU may cause serious health effects in these circumstances. Large doses by any route of exposure can cause kidney and gene damage.
It is not clear how many people were exposed in the Balkans or in Iraq, or how much DU they were exposed to. Dan Fahey, a Ph.D. candidate at the University of California, Berkeley, and a DU policy analyst, says, “We don’t have good data. The Pentagon once said thousands of people [in the Gulf War] might have been unnecessarily exposed, and then backtracked to about nine hundred people.” According to an Army spokeswoman who spoke on condition of anonymity, no estimate of DU exposures in the 2003 Iraq war is available, but DU was used only during the invasion phase when the Iraqis were using tanks. Therefore, the U.S. Army believes exposures to be few in number and low-level.
Since the 1999 Kosovo war, allegations have flown that DU causes cancers such as Hodgkin lymphoma as well as immune, neurological, and reproductive damage. There is not a large body of research on these links. But a number of published in vitro and rodent studies by Alexandra Miller and colleagues at the Armed Forces Radiobiology Research Institute in Bethesda, Maryland, (including one published in the August 1998 issue of EHP) suggest that DU can change human cells to a tumor-inducing phenotype and cause oxidative DNA damage. In rodents DU was shown to migrate from the implant site to bone, kidney, muscle, and liver tissue; to alter the hippocampus; to cross the placental barrier; and to enter fetal tissue. Although DU is a weak alpha emitter, the bystander effect—in which untargeted cells surrounding an irradiated cell show damage similar to that of the target cell—may also be part of DU’s effects.
Nevertheless, the Army maintains that veterans with embedded DU shrapnel are not at risk for adverse effects. The Army spokeswoman says the government is tracking 70 Gulf War veterans who still carry DU shrapnel. “They have no ill effects from the shrapnel that came from DU rounds,” she says. “Depleted uranium has been studied probably more than any other substance used in warfare and has not been demonstrated to have ill effects. There have been thirty-five children born to these veterans, and none has a birth defect.”
Because of the dearth of good epidemiological DU studies, Fahey says the government’s highest priority should be to track a large number of DU-exposed Gulf War veterans. “If the latency period for DU is ten to thirty years,” Fahey says, “now is the time to be monitoring these nine hundred people.”
Weapons of War III: Herbicides
Herbicides as a weapon first came on to the radar during the Vietnam War, when some 19 million gallons of chemicals were sprayed on Vietnam and Laos to strip away enemy cover and destroy crops. The different herbicide formulations, known collectively today as Agent Orange, were contaminated with 2,3,7,8-tetrachlorodibenzo-p-dioxin, a known human carcinogen. Decades after spraying ended, a quarter of this persistent toxicant remains in the Vietnamese environment, and the NIEHS and the Vietnamese government are working together to fully characterize the health effects of exposure to Agent Orange.
Today, herbicides play a major role in the Colombian drug war, another example of the changed nature of modern war. Several insurgent groups have been battling the Colombian government in a protracted and bloody civil war. The war has provided narcotics growers and processors uncontrolled zones in which they can flourish; insurgents and narcotics cartels have formed alliances. According to the U.S. embassy in Bogotá, most of the cocaine and heroin on the U.S. market comes from Colombia. To stop this flood, the U.S. and Colombian governments have jointly developed and implemented the Plan Colombia eradication program.
A major component of the plan is aerial spraying of herbicide on coca and poppy plants, which began in 2000. The main ingredient is glyphosate, widely used as a weed killer in several formulations of Monsanto’s Roundup and in other products, and the most commonly used commercial herbicide in the world. According to the National Pesticide Telecommunications Network, glyphosate causes mild eye and skin irritation and digestive and respiratory irritation when ingested, and has not been shown to cause reproductive damage or cancer in humans or wildlife.
However, many Colombian farmers in sprayed areas report significant skin problems, headaches, vomiting, miscarriages, and deaths of small children—effects that they attribute to the spraying. Residents of the sprayed areas are not told when spraying will occur for security reasons, so they cannot take any steps to protect themselves, their families, their crops, or their livestock.
The Colombian government and the U.S. embassy have a monitoring program in place to investigate all complaints related to spraying, from reports of planes spraying legitimate crops to glyphosate causing health problems. Half of the nearly 5,000 complaints received to date have been rejected as invalid, because it was determined that spraying did not take place in the areas in question on the dates claimed. Another 1,680 cases are under review by the government/embassy team. Compensation for lost crops has been paid in 12 cases and, according to press officer Paul Watzlavick of the U.S. embassy, there have been no cases where it was determined that spraying caused adverse health effects in humans or animals.
There is some controversy over research being done on effects of the spraying. In 2001 Colombian toxicologist Camilo Uribe led an embassy–funded study of the spray program’s health effects in the town of Aponte, which concluded that the observed health problems in the village—mainly skin problems and eye inflammation—were not related to the spray program. In a critique of the study, Rachel Massey, a fellow of the Institute for Science and Interdisciplinary Studies in Amherst, Massachusetts, noted that the study did not follow normal epidemiological protocols, such as indicating the total number of patient records from which the samples were drawn and how cases were selected. Moreover, the Uribe report itself noted that 7 of 10 nearby municipalities reported increases in patients seeking help for symptoms that their community doctors thought might be related to the spraying. One of these towns, San Pablo, had 50 cases of dermatitis, conjunctivitis, respiratory conditions, and digestive problems after nearby spraying.
The U.S. government says the narcotics cartels are responsible for more environmental degradation and toxic chemical exposures than the spraying program is. Says Watzlavick, “The coca growers use tons of pesticides and herbicides on their fields in addition to tons of other chemicals to produce cocaine. These are the chemicals that we see ending up in the water systems.” Chemicals used in drug processing include kerosene, sulfuric acid, ammonia, acetone, and others, along with the herbicides paraquat and 2,4-D. Chemicals and waste products are often dumped in water or left on the ground. Activists don’t deny the likely drug-related exposures, but believe Colombians are suffering additive effects from both kinds of exposures.
Industrial Pollution: During Conflict and After
In the first Gulf War in 1991, Iraqi soldiers set more than 600 Kuwaiti oil wells afire. Vast columns of black smoke billowed into the sky for weeks. In an apparent attempt to deter invading forces during this war, Iraq built a 47-inch pipeline into western Kuwait and criss-crossed the area with trenches into which oil was pumped and set afire, according to the Center for Research and Studies on Kuwait, a Kuwaiti nongovernmental organization. Sabotage of Iraq’s own oil production facilities and pipelines began with the onset of war in 2003. Potentially toxic components of oil fires include polycyclic aromatic hydrocarbons (PAHs), metals, sulfur dioxide, ozone, and lead. Health effects from inhaling these components include cancer (from PAHs), asthma and airway inflammation (from ozone), burning of respiratory tissues and airway obstruction (from sulfur dioxide), and high blood pressure and kidney damage (from lead).
A 2000 Department of Defense study of Gulf War soldiers’ exposure to oil fires concluded that “except for particulate matter, air contaminants were below levels established [by the U.S. Environmental Protection Agency] to protect the health of the general population” and that no long-term damage was done, although some veterans blamed the oil fires for worsening their existing asthma and bronchitis, as well as for skin rashes and shortness of breath. According to the report, the Iraq–Kuwait region normally has some of the world’s highest levels of suspended particulate matter in the air, partly from the sandstorms common there; 18% of Kuwaiti civilians have respiratory problems, about three times the rate in the United States. Some of the soldiers’ symptoms might therefore have resulted from the combination of chemical and particulate exposures.
Urban and industrial areas present other serious environmental health risks in wartime. During the 1999 Kosovo war, NATO and U.S. planes repeatedly bombed several sites in Serbia, including the industrial complex at Panc evo, a town of 80,000 located a few miles northeast of Belgrade. The Panc evo complex includes a fertilizer plant, a petrochemical factory, and an oil refinery; wastewater from all the facilities drains into the Danube River through a canal. The joint UNEP/UN Center for Human Settlements Balkan Task Force issued a postwar environmental assessment concluding that although the war had triggered major chemical releases, the industrial sites were already seriously polluted.
The assessment team estimated that about 2,314 tons of the solvent ethylene dichloride and more than 88 tons of metallic mercury leaked out of the petrochemical plant during the war. Ethylene dichloride is a known human carcinogen, according to the National Toxicology Program, while mercury causes neurological and developmental damage. U.S. bombs burned about 500 tons of vinyl chloride monomer—also listed as a carcinogen by the National Toxicology Program—releasing dioxins, carbon monoxide, and polycyclic aromatic hydrocarbons. Fearful of further explosions, the fertilizer plant managers released about 275 tons of liquid ammonia into the canal. Though not identified as a carcinogen, ammonia can cause severe tissue burns and even blindness when inhaled or ingested, according to the Agency for Toxic Substances and Disease Registry.
Little information is available on disease patterns near the complex, but locals called a common ailment of site workers “Panc evo cancer.” Task force analysts think the condition was actually angiosarcoma of the liver resulting from high vinyl chloride monomer exposure.
The Wages of War
As the character of modern war has changed—becoming less of a “formal” battle between clearly designated opponents in a specified area and turning more to intermittent yet long-term conflicts among insurgents, militias, and government forces—civilians get caught in the cross-fire more frequently. They turn into refugees and IDPs, vulnerable not only to physical violence, malnutrition, and disease, but to chemical and radioactive exposures as well. Their living environments may remain contaminated with industrial and military chemicals and munitions emitting radionuclides long after conflicts have ceased.
Few military groups track civilian casualties, and those who do generally underestimate them. For example, although the United States does not have an official estimate of civilian casualties, research suggests that the U.S. action in Iraq has led directly to the deaths of an estimated 100,000 Iraqis, mostly women and children. Humanitarian aid systems designed to help people after natural disasters are not able to function properly in combat environments. Thus, in severely war-torn regions, help is often only sporadic as conditions permit, or is simply not available.
There are some encouraging signs of progress to be found in the record of the world’s wars. One is the fact that landmines are falling into disuse. The Mine Ban Treaty came about largely because landmine activists, frustrated at the slow pace of UN negotiations, held their own summit in Canada, drafted a convention, and began collecting signatures. The UN has now adopted the convention, and more countries continue to ratify the treaty. Some 31 million stockpiled mines have been destroyed since the campaign began, and the number of countries producing landmines has dropped from 54 to 12. Perhaps the landmine campaign may serve as a model for mitigating other types of war damage and trauma.
A brutal reality. Children in the Nawabad refugee camp in Afghanistan sit on a piece of abandoned military hardware. All across Afghanistan the detritus of war has become a plaything for generations of children.
Not yet out of the woods. Ethnic Albanian families leave the woods below Gajre to head to a safer location. They hid in the woods for three days while Serbian forces shelled their villages.
True environmental exposure. A refugee family in Sar-e-Pol, Afghanistan, huddles together against the cold in a makeshift shelter. Médecins Sans Frontières estimates there are 3,500 families living in tents made of nothing but cloth and plastic, in dire need of water and sanitation.
Sea of refugees. During the 1999 war, ethnic Albanian inhabitants of Pris tina waited in a field near the Macedonian border at Blace after being forced from their city by Serbian forces.
Babes and arms. (top) At Kibeho camp in Ngara, Tanzania, soldiers keep watch over some of the 1,000 children orphaned in the 1994 massacre of 4,000 Hutus by the Tutsi army of Rwanda. (bottom) Refugee children at the same camp must fetch drinking water from a muddy pond contaminated with fuel.
Innocent victims. (top) A child landmine victim in Kurdistan waits to be fitted with prostheses at a center for disabled children. (bottom) Congenital birth defects among Iraqi children are believed to be connected to the use of depleted uranium munitions by Allied forces during the first Gulf War.
Breaking the machinery of life. Major industrial sites frequently become prime targets for enemy forces due to the widespread impact of their demolition. One such target was the power station in Obilic, Kosovo, which now routinely fails, cutting off power to much of the country.
The barest of necessities. Chechen refugees in the Republic of Ingushetia collect water from a damaged well in Sputnik camp. There, some 8,000 people are living in 800 tents and an abandoned train.
Crop casualties. Many Colombian farmers believe their crops, like these bananas, are being ruined by drift from herbicide spraying of illegal poppy and coca crops. Many of the ruined crops were planted at the urging of the government as alternatives to the illegal plants.
Sending the environment up in smoke? Oil fires set during the first Gulf War are alleged to have caused respiratory effects in both soldiers and civilians.
Selected Modern-Day Conflicts
Country Date Begun Description Refugees/IDPs by the End of 2003
Afghanistan 1978 Fighting among Communist government, mujahideen, Soviet Union, Taliban, and United States 2,136,000 refugees
Angola 1975 Marxist government versus ethnic rebels; intervention by Cuba 323,600 refugees
Burundi 1991 Tutsi-led government versus Hutus 531,600 refugees; 800,000 IDPs
Cambodia 1979 South Vietnamese versus Khmer Rouge 29,663 refugees
Colombia 1984 Government versus Marxist guerrillas, other insurgents, and narcotics cartels 32,793 refugees; 294,999 new IDPs in 2003
Democratic Republic of the Congo 1997 Government versus remnants of Hutu militias from Rwanda; involvement of Uganda, Namibia, Zimbabwe, and Angola 453,400 refugees
Eritrea/Ethiopia 1998 Conflict over border territory 162,196 refugees
Indonesia 1989 Government versus Aceh province separatists 7,491 refugees
Iraq 1991, 2003 U.S. invasions 368,400 refugees
Israel 1948 Religious/ethnic/territorial conflict 800,000 refugees
Kosovo 1998 Serbian government versus ethnic separatist Albanians 257,000 IDPs
Liberia 1990 Government versus rebel groups, then fighting among rebel groups 353,300 refugees; 227,000 new IDPs in 2003
Myanmar 1983 Government versus Karens and other ethnic minorities demanding autonomy 138,108 refugees
Russia 1994 Government versus Chechen separatists 800,000 refugees
Somalia 1982 Government versus rebel movement and clan guerrillas 402,200 refugees
Sri Lanka 1983 Government versus Tamil Tiger separatists 103,368 refugees
Sudan 1983 Government versus rebels; Muslims versus Christians; Janjaweed militias versus black Muslims 606,200 refugees; 4,500,000 IDPs
Uganda 1996 Government versus Lord’s Resistance Army 220,000 refugees
Note: Some conflicts have ceased, some are sporadic, and some are ongoing. Not all types of information are available for all conflicts. See sources for details. All numbers are approximate.
Sources: Conflict Map. Stockholm, Sweden: Nobelprize.org, The Official Web Site of the Nobel Foundation. Available: http://nobelprize.org/peace/educational/conflictmap/about.html [accessed 10 November 2004]. IRC. 2003. Mortality in the Democratic Republic of Congo: Results from a Nationwide Survey. New York, NY: International Rescue Committee. Marshall MG, Gurr TR. 2003. Peace and Conflict 2003: A Global Survey of Armed Conflicts, Self-Determination Movements, and Democracy. College Park, MD: University of Maryland, Integrated Network for Societal Conflict Research. UNHCR. 2004. 2003 Global Refugee Trends. Geneva, Switzerland: United Nations High Commissioner for Refugees.
|
15579406
|
PMC1253679
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A994-A1003
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.112-a994
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0112-a0100215579396EnvironewsSpheres of InfluenceIs Environmental Health a Basic Human Right? Taylor David A. 12 2004 112 17 A1006 A1009 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Since the Universal Declaration of Human Rights was ratified by United Nations (UN) member countries in 1948, the principle of basic human rights has gained global acceptance. In recent years, proponents of environmental justice have extended that principle into the sphere of the environment, driven by a recognition that increasing scarcity of and conflict over natural resources requires new approaches for securing a peaceful future [see “Global Resources: Abuse, Scarcity, and Insecurity,” EHP 112:A168–A175 (2004)]. At the heart of this issue are two key questions: Are the forests, water, air, and food that are essential to our survival common goods to be shared by all? Or are they scarce economic goods, like minerals and timber, that are optimized when they are subject to commercial pressures of supply and demand?
“A human rights argument about natural resources can easily become one extreme of a two-extreme argument,” says Carl Bauer, a research fellow at Resources for the Future (RFF), a nonprofit policy think tank in Washington, D.C. On the one hand, he explains, the term “human right” carries an absolute value that can be hard to trump—it’s like arguing against freedom. At the other extreme is the concept of a free market unhindered by government oversight, which can exert a similar compelling attraction for advocates of a market-driven world economy. Navigating past freighted terms, though, we can examine the factors that shape how we allocate and use natural resources. In a time when the World Bank estimates that more than 1 billion people lack access to safe water, this most essential of resources has become a flash-point in the discussion of human rights versus market forces.
A Brief History of Rights
In Western society, the concepts of human rights and capitalism both emerged from the European Enlightenment. The English philosopher John Locke (1632–1704) wrote of people’s “natural rights” in terms of a contract between a people and its government. In his 1776 treatise The Wealth of Nations, Scottish philosopher and economist Adam Smith described an “invisible hand” that guides markets with a logic of demand and supply.
The term “human right” did not gain broad currency until the last century, and no global consensus existed before the Universal Declaration of Human Rights stated that “all human beings are born free and equal in dignity and rights.” Among its 30 articles, the declaration asserts that everyone has the right to life, liberty, and security of person, and guarantees to all people the right to a standard of living adequate for health and well-being.
That last guarantee has been elaborated in subsequent international agreements, including the 1989 Convention on the Rights of the Child, which states that nations will “recognize the right of the child to the enjoyment of the highest attainable standard of health,” and specifically notes that governments will take measures that account for “the dangers and risks of environmental pollution.” In 2000, the UN Committee on Economic, Social, and Cultural Rights adopted a clarification that extended that right to health to encompass those factors that determine good health, including access to safe drinking water and sanitation. According to the 2003 WHO publication The Right to Water, the declaration of water as a human right helps to ensure that governments redress cases of inequitable access to crucial resources. It also means that UN mechanisms for monitoring progress will be used to hold governments accountable.
Whose Jurisdiction?
To be enforceable, rights must be embedded in fundamental legal documents. In the United States, rights to resources are determined by state and federal law. Carolyn Raffensperger, a lawyer and founding executive director of the nonprofit Science and Environmental Health Network, has reviewed state constitutions and their different mandates on environmental health. In her review, summarized in the December 2003 issue of Conservation Biology, she saw a trend exemplified by a few states toward protecting shared resources for current and future generations. Eventually, she says, this trend may inform U.S. constitutional law.
Hawaii’s constitution illustrates this proactive stance. Article XI of the constitution states, “For the benefit of present and future generations, the State and its political subdivisions shall conserve and protect Hawaii’s natural beauty and all natural resources, including land, water, air, minerals and energy sources, and shall promote the development and utilization of these resources in a manner consistent with their conservation and in furtherance of the self-sufficiency of the State. . . . All public natural resources are held in trust by the State for the benefit of the people.”
The state’s supreme court has cited that stewardship role and applied a principle of preemptive precaution against actions that could reasonably be expected to degrade the state’s natural resources. For example, in 2000, the court ruled against a long-standing diversion of an irrigation ditch by sugar plantations of central Oahu. For Raffensperger, it’s then a small step to add to those constitutional protections that all citizens “are impoverished when resource degradation causes a rise in disease.”
Raffensperger concedes that even if the federal government does eventually pursue a similar approach of using preemptive precaution to protect resources, this will not resolve all resource equity problems. Some involve public versus private conflicts, and within private management, there are different situations. “Managing a resource is one thing,” says Raffensperger. “Owning it is another.”
Ownership versus Management
In the western United States, water rights have long been a bone of contention, with private parties, municipalities, and states squabbling over a region’s rivers for agricultural, industrial, and municipal uses. Recognizing the growing pressures and sinking aquifer levels, the U.S. Department of the Interior recently began an effort called Water 2025 to head off major conflicts and shortages. Water 2025 aims to avert conflicts in part by clarifying rights and legal claims. In that process, the government, armed only with conflict resolution techniques, facilitates dialogue between opposing parties.
In some cases, government contracts with private companies to manage resources such as forests and drinking water have been disastrous. In 1999, for example, the World Bank successfully convinced the city of Cochabamba, Bolivia, to contract out its water supply service. Within months the price of water skyrocketed. Activists claimed the price hikes came because the monopoly emboldened the contractor; the contractor claimed they were caused by rising maintenance and distribution costs. After a violent public outcry, the government quickly reversed its decision.
Despite that ill-fated example, the World Bank continues to see the challenge of providing water to all people as a huge task that requires the combined ingenuity and efficiency of the private sector and government. Others, too, insist there’s no reason to believe that public and private organizations can’t work together to improve equitable access to critical resources. Privately owned water utilities have existed in the United States since the colonial period, says Peter Cook, executive director of the National Association of Water Companies (NAWC), a Washington, D.C.–based industry association. These utilities have a strong record of accountability, efficiency, and health safety, as they are regulated by both the U.S. Environmental Protection Agency and states for quality, and by state public utility commissions to ensure fair customer rates.
Private companies managing public utilities have become more common since the early 1990s. Municipalities have renewed those contracts at a very high rate, suggesting that such public–private partnerships have convincing benefits, says Cook, who adds that private companies can save municipalities 10–40% in operating costs thanks to increased efficiency and lower personnel expenses. As budgets tighten, governments need to consider all available options for providing public services, Cook says.
The NAWC recognizes that poor communities should not endure hardship to pay for safe water. “We think there need to be programs to deal with this,” says Cook. Water bill assistance programs funded by voluntary charitable donations from other customers as well as subsidies from government agencies (such as the NAWC’s proposed Low-Income Water Assistance Program) could help those who need help most, while allowing the utility to charge full cost-of-service rates to all customers. Cook says full cost of service must be charged or the utility will not be economically viable over the long term, with consequences for service, public health, and management of the water resource.
“Just like food, someone has to pay for both the treatment and distribution of finished water before it can be safely consumed,” says Cook. “In the end, it’s the people who actually own the resource. We’re mainly concerned with meeting essential human needs for water and sanitation by providing water treatment and distribution services, not resource ownership.”
The Chilean Experience
Many economists argue that an efficient allocation of resources comes mainly through accurate valuation of scarce resources. They maintain that more careful pricing of a resource—considering nonmarket factors such as social goals of conservation and fair access—will encourage its sustainable use. Economic incentives can open the door to technological innovation and spur better distribution methods.
The kind of subsidy that Cook describes has been used effectively in Chile. In 1981 Chile enacted a water law that promoted free market forces and incentives in water use and reduced government regulation. Chile distinguishes between water use broadly speaking (including industrial, agricultural, and sanitation uses) and the more restricted case of water for people’s survival and health, which includes basic household water.
This is an important distinction, says Bauer, because resources essential for survival should be handled with more concern for equitable access than nonessential resources, which people can choose to forego. The distinction can clarify the policy priority between essential and nonessential water. For basic household water use, Chile’s example shows that targeted subsidies can work. The strength of the Chilean model for household water service, Bauer says, is that it both preserves the larger system of price signals needed for valuing a scarce resource and addresses low-income users’ needs within that system.
“The same price and tariff structures apply to users with different income levels, they’re just dealt with through subsidies,” Bauer explains. “It not only provides transparency about the subsidies provided to poor people—the value is clear from the pricing system—but it also leaves intact the system of price signals that accurately reflect the scarcity of the resource.”
But there are risks in codifying any rigid approach to natural resource access. Says Bauer, “Calling something a human right is well and good, but if a country is too poor to make good on those guarantees, where does that leave you? If the right to low-cost clean water for everyone is politically or economically impossible to enforce, you may end up making the debate about practical issues more difficult instead of furthering it.”
South Africa’s reformed water laws include explicit recognition of equity needs. “This was an important achievement in principle,” Bauer says. “The question is, how can they deliver? It may be better not to lock yourself into a constitutional requirement that everyone knows can’t be met.” On the other hand, he adds, declaring access to be a human right can be an important counterweight to the notion that public interests should be left to the free market.
Seeking an International Mandate
Unimpressed by market-based efforts to date, environmental justice advocates have sought a human rights tool to leverage change. In April 2004, Earthjustice, a nonprofit public interest law firm based in Oakland, California, called on the UN High Commissioner for Human Rights to take broader action on environmental health problems. In the report titled Human Rights and the Environment that was submitted to the commission’s 2004 session in Geneva, Earthjustice developed a proposal based on international human rights agreements and the growing recognition of a link between civil instability and environmental degradation. “The relationship between environmental problems and human rights violations calls for a holistic treatment of these issues,” the report said.
A similar case is made in Environment and Human Rights, a 2003 report by Germany’s nonprofit Wuppertal Institute for Climate, Environment, and Energy. That report asserts that commercial resource use—in its extraction of raw materials, ecosystem changes, and pollution effects—has a disproportionately large impact on the poor, who seek only subsistence. The report maintains that sustainability, the pursuit of human rights, and respect for the biosphere—not economic competition—should define a world consensus on allocation of resources.
Perhaps even more urgent than world consensus, though, are choices over priorities among household, agricultural, and industrial uses. Whether or not governments adopt a human rights approach, the debate points up key variables involved in resource allocation and decisions that demand our attention.
|
15579396
|
PMC1253680
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A1006-A1009
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.112-a1006
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0100415593453EnvironewsFocusThe Price of Preparing for War Schmidt Charles W. 12 2004 112 17 A1004 A1005 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Located a few miles from Anchorage, Alaska’s Eagle River Flats is a coastal saltwater marsh teeming with fish, wildlife—and unexploded mortar and artillery shells. The marsh lies on the Department of Defense’s (DOD) 62,000-acre training facility at Fort Richardson, headquarters to the Army’s Alaskan command and control units. Since World War II, Eagle River Flats has been Fort Richardson’s primary “ordnance impact zone,” where soldiers stationed at the fort come to train with live munitions.
Environmental assessments undertaken at the Flats by the Army have revealed high levels of contaminants including heavy metals, explosive compounds, and white phosphorus, a toxic agent used to generate smoke cover on the battlefield. It was this contamination with white phosphorus, which can damage bones and major internal organs, that in 1994 landed Eagle River Flats on the Superfund National Priorities List, a U.S. Environmental Protection Agency (EPA) compilation of the nation’s most polluted properties. Since then, the Army has been conducting an EPA-approved effort to clean up the white phosphorus.
But in April 2002 the DOD was sued by a citizens’ coalition urging the Army to address remaining contamination problems at the Flats. Among the plaintiffs were the indigenous Chickaloon Indians, who claimed the Army’s use of live munitions was polluting traditional hunting and fishing grounds. The suit also charged that unexploded mortar rounds and artillery shells in the area were leaching toxic chemicals that were migrating to nearby Cook Inlet. The plaintiffs’ attorney, Scott Allen of the San Francisco, California–based law firm Cox and Moyer, says the suit requested that the Army remove some 10,000 unexploded mortar rounds and artillery shells from the area (the number estimated in the Army’s 1998 proposed Superfund cleanup plan), remediate toxic contamination, and abstain from using the range for bombing exercises until a Clean Water Act permit had been obtained for munitions discharges.
When confronted with the lawsuit, the DOD took its case to Congress. There, it argued that the laws on the books were not intended to be applied to operational military ranges in this way, citing long-standing past state and federal regulatory interpretation and practice. The DOD further argued that suits like those brought at Eagle River Flats, if successful, could set a legal precedent whereby environmental litigants could halt military training and thus undermine troop readiness on the battlefield.
Before the 2002 lawsuit even arose, the DOD had proposed new legislation called the Readiness and Range Preservation Initiative (RRPI) to prevent just such lawsuits attempting to use hazardous waste laws to limit training. The RRPI calls for exemptions from a number of environmental laws on more than 8,000 operational DOD training ranges, a land area equal to roughly 24 million acres. Under this proposed new legislation, munitions would not be subject to hazardous waste permitting or cleanup requirements as long as they remain on operational ranges.
Military Readiness and Pollution
Preparing for war is a heavily industrialized mission that generates fuel spills, hazardous waste, and air pollution. The DOD owns more than 10% of the 1,240 sites currently on the National Priorities List, and has estimated the cost of cleaning up these sites at approximately $9.7 billion. In addition to lead and a variety of solvents, training facilities release munitions constituents including perchlorate (a thyroid toxicant), RDX (an explosive compound and neurotoxicant), and TNT (an explosive compound linked to anemia and altered liver function).
Nearly 1 in 10 Americans live within 10 miles of a DOD Superfund site—a sometimes perilous proximity. The Massachusetts Military Reservation, for instance, a 34-square-mile multi-use training facility in Cape Cod, is slowly leaching solvents, jet fuel, RDX, and perchlorate into the area’s sole aquifer, a drinking water source for up to 500,000 people at the height of tourist season.
Military aircraft from DOD facilities also generate noise and air pollution. For instance, in 1996, the most recent year for which data are available, more than 50,000 military flights contributed to the heavy air traffic over Washington, D.C. According to the Democratic Committee on Energy and Commerce, these flights emitted 75 tons of nitrogen oxides and volatile organic compounds, which generate smog. In 1999, the Sierra Army Depot, located 55 miles northeast of Reno, was California’s leading air polluter, according to the EPA Toxics Release Inventory. The base released some 5.4 million pounds of toxic chemicals that year, including aluminum, copper, and zinc fumes.
As of this publication, Congress has approved legislation requested by the DOD amending the Migratory Bird Protection Act, portions of the Endangered Species Act, and the Marine Mammal Protection Act. Now, the DOD is seeking changes through the RRPI to certain hazardous waste laws—specifically, the Comprehensive Environmental Response, Compensation, and Liability Act (CER-CLA), the Resource Conservation and Recovery Act (RCRA), and the Clean Air Act (CAA). The DOD acknowledges that these laws have never been shown to have interfered with specific military training, but says it can’t afford to wait until training is shut down before it acts. As evidence of the need to act now, the DOD points to a number of lawsuits and “close calls,” including the case at Eagle River Flats and the Navy’s 2002 temporary closure of its Farallon de Medinilla live-fire training range in the Pacific. That closure followed a lawsuit filed by the Center for Biological Diversity alleging that bombing at the range was killing protected migratory birds.
The DOD argues that even the threat of interference by hazardous waste litigation justifies its aims. Joe Willging, an environmental lawyer with the DOD General Counsel’s office, says in reference to the Farallon de Medinilla closure, “We don’t feel it’s wise to wait for that kind of train wreck to see if we are going to lose in litigation. . . . Our job is to send soldiers, sailors, airmen, and Marines into combat environments in the absolute best-prepared way we can. You can’t do that if you introduce artificialities into training. We want to maintain the ability to use those ranges in the optimum way based on military readiness considerations, not on other considerations.”
Questions of Scope
Top environmental officials in nearly every state oppose the RRPI, as do 39 state attorneys general. Their opposition is based on the DOD’s historic environmental record and growing reputation among state officials for routinely shirking its environmental responsibility. “The DOD has a consistent track record in litigation going back decades for trying to get out of its environmental requirements,” says Daniel Miller, Colorado’s assistant attorney general for environment. (DOD officials claim, however, that the department’s current compliance with environmental requirements is comparable to that of private industry in almost all environmental programs.)
The main goal of the RRPI is to ensure that both munitions and their constituents are exempt from CERCLA and RCRA hazardous waste classifications as long as they remain on operational ranges. Once the range closes or if the munitions or their constituents migrate offsite or pose an “imminent and substantial danger” to human health or agriculture, then CER-CLA and RCRA authority would come into force. At that point, according to the DOD, the relevant environmental agencies would assume jurisdictional authority and impose monitoring requirements and cleanup orders to address the offsite migration at the contamination’s source.
Finally, the RRPI seeks a three-year extension in the DOD’s obligation to demonstrate compliance with state plans to meet CAA standards for ozone, carbon monoxide, and particulate matter. The DOD claims the extension would provide flexibility in its decisions about where to field and base new weapons and aircraft, noting that military emissions typically are less than 0.5% of state emission quotas.
However, state attorneys general disagree with the DOD’s reading, and have expressed concern that the RRPI would effectively mean states could not require the DOD to take any action to address munitions-related contamination on a range—even if that contamination were to migrate offsite and contaminate drinking water supplies—unless regulators could prove imminent and substantial endangerment from the contamination. Further, says Steve Taylor, a national organizer with the Military Toxics Project, an environmental group based in Lewiston, Maine, without their normal authority to order sampling when warranted either offsite or at the source of contamination, regulators cannot possibly demonstrate the imminent and substantial endangerment required to invoke their emergency powers.
Thus, critics argue, the DOD assumes exclusive control over its facilities, assuming an inappropriate level of oversight given the department’s history with environmental compliance. The problem with this approach, Taylor emphasizes, is that munitions contamination that spreads offsite is likely to be harder and more expensive to clean up.
DOD officials contend that because neither the EPA nor any states have ever attempted to use these laws to regulate military training on operational ranges, the exemptions merely codify what are already standard practices. (State and EPA officials disagree with this point, arguing that the amendments actually reverse existing policy under which military munitions may become solid waste after they have been used.) Meanwhile, the DOD adds that it is engaged in a broad voluntary effort to gauge the potential for munitions constituents to migrate from any of its facilities, and that it intends to share the results of this effort with regulators and the public. “The reason DOD is undertaking these assessments is because we realize that our ranges must be operated in a sustainable way,” Willging says. “If they are not, and [migrating contamination] endangers public health, the proposed RRPI provisions will not apply. Therefore, it’s in our best interests to know the condition of our ranges and to respond when contamination threatens to spread.”
Opponents argue that the DOD’s proposals would actually affect both active and closed ranges. “We’ve identified over a dozen DOD operational ranges on the National Priorities List,” says an EPA official speaking off the record. “One could argue that absent an ‘imminent and substantial danger’ finding, EPA would have no jurisdiction under CERCLA to force those cleanups.”
A broad range of critics—including the National Association of Attorneys General and all major environmental organizations—also oppose the proposed CAA extension, arguing that it would extend public exposure to harmful air quality. Moreover, according to a 2004 fact sheet on DOD CAA provisions prepared by staff of the House Committee on Energy and Commerce, there is no evidence to suggest the CAA has ever adversely affected military readiness.
Culture War?
In late October 2004, the DOD settled its Eagle River Flats lawsuit. As part of the settlement, the agency agreed to a number of key provisions, including—among others—that it obtain a Clean Water Act permit for munitions discharges at the Flats, monitor water quality in the area, promptly clean up munitions that fall outside the immediate impact area, and work with outside experts to study the environmental impacts of bombing.
But the DOD is still committed to its RRPI goals, which it maintains are necessary in order to sustain military readiness. Why is the agency seeking environmental exemptions in the face of such broadly focused opposition? There is no easy answer. Some stakeholders suggest a culture war is at play, pointing out that the DOD has never taken kindly to environmental oversight, believing its national security mission elevates it beyond such concerns. The EPA official says there are many in the DOD itself who don’t support the RRPI’s proposals: “They see it as being driven by operational guys, farther up the chain of command.”
The DOD is currently considering its legislative package for fiscal year 2006. Whether the RRPI will be a part of that package is still being considered in the Pentagon. The next opportunity for DOD officials to present the proposal is likely to emerge when the Congress turns to its next appropriations bill.
Catching flak? The Department of Defense has come under fire for trying to exempt a number of its facilities from environment-protective laws in the name of maintaining optimal military preparedness.
|
15593453
|
PMC1253681
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A1004-A1005
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.112-a1004
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a01019AnnouncementsNIEHS Extramural UpdateAnne Spuches Receives 2004 Karen Wetterhahn Memorial Award 12 2004 112 17 A1019 A1019 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
The Superfund Basic Research Program (SBRP) is pleased to announce that Anne Spuches of Dartmouth College is the recipient of the seventh annual Karen Wetterhahn Memorial Award. The award was presented to Spuches on 4 November 2004 at the SBRP Annual Meeting at the University of Washington in Seattle.
The SBRP presents this annual award to an outstanding scholar to pay tribute to the life and scientific accomplishments of Karen E. Wetterhahn, former director of the SBRP at Dartmouth College. Wetterhahn died in 1997 as the result of an accidental exposure to dimethylmercury. An acknowledged international expert on the effects of heavy metals on biological systems, Wetterhahn was a leader in conducting research on how metals initiate cancer and other metal-induced human diseases at the molecular level. She fostered links between biology, chemistry, environmental studies, engineering, and medical science, insisting that “the life sciences are interdisciplinary.”
Spuches, who earned her Ph.D. in chemistry at Yale University, is in her second year as a postdoctoral fellow at Dartmouth College. Advised by professor Dean E. Wilcox, she is participating in interdisciplinary studies addressing the environmental and human health effects of arsenic. The toxicity of arsenic at low chronic exposure, primarily through arsenite in drinking water, poses a significant health risk for people around the world. Specifically, Spuches is using isothermal titration calorimetry to quantify the interaction of arsenite and monomethylarsenite with various thiols. This information is fundamental to mapping the distribution and chemistry of arsenic in the cell, and may also help in the design of more effective chelating agents for the treatment of arsenic poisoning.
The NIEHS congratulates Spuches on her research accomplishments and wishes her continued success in her scientific career.
|
0
|
PMC1253682
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A1019
|
utf-8
|
Environ Health Perspect
| 2,004 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a01020AnnouncementsFellowships, Grants, & AwardsFellowships, Grants, & Awards 12 2004 112 17 A1020 A1021 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
NIGMS National Centers for Systems Biology
The National Institute of General Medical Sciences (NIGMS) currently supports the analysis of complex biological systems through investigator-initiated research project grants. The resources needed to conduct the multifaceted, multidisciplinary projects that may be required to achieve significant advances in these complex areas may be beyond the scope of the typical R01 or P01 grant. Therefore, this request for applications (RFA) presents an opportunity for applicants to assemble large teams of investigators from diverse disciplines that may not be possible with other funding mechanisms.
The biomedical sciences have undergone a fundamental shift in the conceptual and technical approaches that can be applied to certain problems of profound importance. These problems center on understanding the behavior of biological systems whose function is the product of spatial and temporal ordering of myriad interacting components. Modeling approaches are being used to understand the orderly development of biological pattern in organisms such as Drosophila and Caenorhabditis elegans, and at the clinical level, new approaches are being explored to understand the integrated activity of tissues and organs.
Part of the impetus for systems-scale approaches rests on advances in acquiring data of the necessary quality and quantity to permit computational modeling. Among the most striking examples are the availability of complete DNA sequences for hundreds of organisms, including humans, and the availability of high-throughput instrumentation for analyses of gene function such as gene expression microarrays and proteomics technologies. These advances have made it feasible to generate a truly comprehensive parts list for any organism and to track changes over time. Ultimately, it should be possible to enumerate all the informational units of the genomes (protein coding genes, non–protein coding genes, regulatory regions), their processed forms, and their dynamic presence in cells.
Rapid advances in large-scale data collection and analysis have given scientists a global yet detailed view of cellular processes, instead of focusing on individual molecules or a small number of interacting molecules. Unprecedented opportunities have emerged that may open the door to uncover hidden rules governing the ensemble of biomolecules working concertedly to perform certain functions in the cell. In the meantime, substantial challenges in information integration, interpretation, and representation have arisen. In order to move beyond the phase of cataloguing the parts list and truly transform data into knowledge, and knowledge into principles, iterative cycles of data collection and model generation and validation will be necessary.
A higher-order problem presents itself in understanding how the genome-encoded components and the other molecules (metabolites, ions, water, etc.) are constituted in networks of interacting molecules with particular distributions in time and space. Advances in imaging techniques and analytic methods are beginning to yield copious quantitative and spatial data on specific molecules in biological systems. Knowledge of the network and changes in its components over time, and the local rules by which the individual components distribute material and information, will substantially advance our knowledge.
At the organism level, phenotype must take into account the relationships and interactions of biological and environmental variables. Basic biological systems—including gene sequences, structures, and pathways that direct metabolism and development—vary within individuals, among individuals, among populations, and among species. Advances in complex systems-level understanding must ultimately include models that account for these variations.
Medical, biotechnological, and other uses of biological information increasingly depend on our ability to understand the principles and dynamics that explain the behavior of the system as a whole. Whether the goal is to understand the consequences of disease or injury, identify particular molecular targets for drug interventions, or modify the metabolism of microorganisms to produce medicines, the challenge is predictability. Predicting how the system of interest will respond to an intervention is a computational problem. For biological systems, this challenge is daunting.
Parallel to scientific challenges are organizational and educational challenges. At the institutional level, building cohesive multidisciplinary research teams by integrating expertise across traditional disciplinary boundaries is not a simple undertaking. Beyond institutions, excessive overlap and redundancy in project selection and tool development exists in the research communities that could be reduced by promoting communications, collaborations, and technology and data sharing. The emergence of new science demands an adequate workforce of new scientists. Training for the future leaders of systems biology research who are knowledgeable and skilled in both experimental and computational subjects is timely. Good mechanisms and plans to address these challenges are significant tasks of the centers.
High priority will be given to projects that integrate multi-investigator, multidisciplinary approaches with a high degree of interplay between computational and experimental approaches. Innovation is critical for both research project design and infrastructure design with a mission of serving communities beyond the participating investigators, institutions, and collaborators. A variety of organizational models are possible; it is not the intent of this RFA to prescribe any particular one.
The NIGMS awarded two centers under this program in 2002 (http://www.nigms.nih.gov/news/releases/complex_centers.html), two centers in 2003 (http://www.nigms.nih.gov/news/releases/complex_centers-2003.html), and one center in 2004 (http://www.nigms.nih.gov/news/releases/quantitative_bio_center.html). Potential applicants should become familiar with the research focuses of the existing centers. Research conducted by the future centers should complement and enhance projects already funded.
Some groups interested in the subject of this RFA might find the P01 mechanism more suited to the scale of their efforts; they should consult the prior announcement at http://grants.nih.gov/grants/guide/pa-files/PA-98-077.html.
The NIGMS intends to support systems biology research for the areas that are central to its mission of supporting basic biomedical research, and that focus on developing new computational approaches to biomedical complexity. Research areas that historically have been computationally based (e.g., molecular structure and modeling) are excluded as a focus of this center program. Research focusing on disease processes and their specific organ systems is not eligible. NIGMS mission areas include, but are not limited to, the following: 1) signaling networks and the regulatory dynamics of cellular processes such as cell cycle control, transient complex formation, organelle biogenesis, and intercellular communications; 2) supramolecular machines, such as the replisome, spliceosome, and molecular motor assemblies in cell division and motility; 3) pattern formation and developmental processes in model systems (e.g., Drosophila, C. elegans, etc.); 4) metabolic networks and the control of the flux of substrates, intermediates, and products in cell physiology; 5) organ system networks involved in multiorgan failure in shock, trauma, and burn injury; and 6) genetic architecture of biological complexity related to inherited variation and environmental fluctuations.
The NIGMS National Centers for Systems Biology will be expected to provide national leadership in systems biology research and training. To do so, they will be expected to support training and outreach activities that will ensure the flow of information and expertise both into and out of the centers. Centers should have plans to bring the most advanced technologies developed at other laboratories to the centers and to disseminate expertise and knowledge to a wider community through collaborations, visiting investigatorships, fellowships, center websites, workshops, symposia, summer courses/internships, and/or other means. To maximize the impact, centers should conduct training at multiple levels appropriate to their institutions. Incorporation of developmental research projects led by junior and new investigators into the center research and development plans is strongly encouraged. Over a period of time, centers should evolve into integrated research, training, and knowledge exchange headquarters of scientific communities that will be the engines for coordinated scientific discoveries. The centers should also have plans for outreach to undergraduate institutions, including minority-serving institutions. Information on relevant minority-serving institutions may be obtained by consultation with staff of the NIGMS Division of Minority Opportunities in Research (http://www.nigms.nih.gov/about_nigms/more.html).
In addition to research and training contributions, successful centers will provide their home institutions with the means to implement organizational and professional changes that will make systems biology research an attractive career option for both established and entry-level investigators.
This funding opportunity will use the NIH P50 Research Center Grant award mechanism. As an applicant, you will be solely responsible for planning, directing, and executing the proposed project. This RFA is a one-time solicitation and may be reannounced in the future. The earliest expected award date is in December 2005. Applications that were submitted in response to previous RFAs of this program but unfunded may be revised and resubmitted for this RFA.
The NIGMS intends to commit up to $7 million in fiscal year 2006 to fund one to three new P50 center grants in response to this RFA. An applicant may request a project period of up to five years and a budget for direct costs of up to $2 million per year, exclusive of subproject fiscal and administrative costs (see http://grants.nih.gov/grants/guide/notice-files/NOT-OD-04-040.html).
The PHS 398 application instructions are available at http://grants.nih.gov/grants/funding/phs398/phs398.html in an interactive format. For further assistance, contact GrantsInfo by calling 301-435-0714 or e-mailing [email protected].
Applications must be prepared using the PHS 398 application instructions and forms (rev. 5/2001). Applications must have a Dun & Bradstreet (D&B) Data Universal Numbering System number as the universal identifier when applying for federal grants or cooperative agreements. This number can be obtained by calling 1-866-705-5711 or online at http://www.dnb.com/us/. The D&B number should be entered on line 11 of the face page of the PHS 398 form.
Letters of intent must be received by 25 January 2005, with 25 February 2005 the deadline for applications. The complete version of this announcement is available online at http://grants.nih.gov/grants/guide/rfa-files/RFA-GM-05-010.html#PartI.
Contact: James J. Anderson, Center for Bioinformatics and Computational Biology, NIGMS, 45 Center Dr, Rm 2As.25A, MSC 6200, Bethesda, MD 20892-6200 USA, 301-594-0943, fax: 301-480-2228, e-mail: [email protected]; Jiayin (Jerry) Li, Center for Bioinformatics and Computational Biology, NIGMS, 45 Center Dr, Rm 2As.19F, MSC 6200, Bethesda, MD 20892-6200 USA, 301-594-0682, fax: 301-480-2004, e-mail: [email protected]. Reference: RFA No. RFA-GM-03-009
Environmental and Human Health Effects of Manufactured Nanomaterials
The purpose of this collaborative research program is to strengthen support by the Environmental Protection Agency (EPA), the National Science Foundation (NSF), and the National Institute for Occupational Safety and Health (NIOSH) of research on the potential implications of nanotechnology and manufactured nanomaterials on human health and the environment. Research areas of interest include the toxicology, fate, transport/transformation, and bioavailability of nanomaterials, as well as human exposures to these materials. Proposals should address one of these topics.
The EPA supports research to meet its mission of protecting the environment and human health. Information used in risk assessment, which comprises hazard identification and exposure assessment, is central to the EPA’s methods to meet its mission. As such, the EPA is interested in funding research on the possible risks and exposure routes of newly produced chemicals and materials at the nanoscale.
At the NSF, proposals should assist and enable the engineering and scientific communities to advance the frontiers of research, innovation, and education. The research should focus on emerging and potentially transformative research ideas, application of new expertise, or new approaches to established research topics.
NIOSH supports research to identify and investigate the relationships between hazardous working conditions and associated occupational diseases and injuries; to develop more sensitive means of evaluating hazards at work sites, as well as methods for measuring early markers of adverse health effects and injuries; to develop new protective equipment, engineering control technology, and work practices to reduce the risk of occupational hazards; and to evaluate the technical feasibility or application of a new or improved occupational safety and health procedure, method, technique, or system.
Nanotechnology has been defined by the interagency Subcommittee on Nanoscale Science, Engineering, and Technology of the federal Office of Science and Technology Policy as research and technology development at the atomic, molecular, or macromolecular levels, in the length scale of approximately 1- to 100-nanometer (nm) range, to provide a fundamental understanding of phenomena and materials at the nanoscale, and to create and use structures, devices, and systems that have novel properties and functions because of their small and/or intermediate size. The novel and differentiating properties and functions are developed at a critical length scale of matter typically under 100 nm. Nanotechnology research and development includes manipulation under control of the nanoscale structures and their integration into larger material components, systems, and architectures. Within these larger-scale assemblies, the control and construction of their structures and components remains at the nanometer scale. In some particular cases, the critical length scale for novel properties and phenomena may be under 1 nm (e.g., manipulation of atoms ~0.1 nm) or larger than 100 nm (e.g., nanoparticle-reinforced polymers have the unique feature at ~200–300 nm as a function of the local bridges or bonds between the nanoparticles and the polymer). See http://www.nano.gov/ for more information.
Many industries are currently involved in nanotechnology-related activities. Among these activities is the manufacture of nanoscale materials that are used in a wide range of products, such as sunscreens, composites, medical devices, and chemical catalysts. According to data collected by the National Nanotechnology Initiative, the quantity of manufactured nanoscale materials is expected to grow significantly in the next five years. Business Communications Company has projected a $10 billion global demand for nanoscale materials, tools, and devices in 2010. This large increase in demand and production could lead to environmental exposures of humans and other organisms to nanoscale materials.
There is a serious lack of information about the human health and environmental implications of manufactured nanomaterials, e.g., nanoparticles, nanotubes, nanowires, fullerene derivatives, and other nanoscale materials. Environmental and other safety concerns about nanotechnology have been raised. As part of the missions of the EPA and NIOSH to protect human health and the environment, this solicitation requests research proposals that address potential health and environmental concerns of nanomaterials using the best science available, in keeping with the missions of the NSF and the other agencies.
Potentially harmful effects of nanotechnology might arise as a result of the nature of the nanoparticles themselves, the characteristics of the products made from them, or aspects of the manufacturing process involved. The large surface area, crystalline structure, and reactivity of some nanoparticles may facilitate transport in the environment or lead to harm because of their interactions with cellular material. The size of nanomaterials could facilitate and exacerbate any harmful effects caused by the composition of the material.
Some research has been done on inhalational and dermal exposure to nanoparticles. However, the current research on ultrafine particles may not be applicable to manufactured nanoparticles because the ultrafine materials studied are neither a consistent size nor pure in chemical or structural composition. Exposure may occur via the dermal and ingestion routes, as well as the inhalational route. It is unknown whether nanomaterials bioaccumulate and thereby pose human health and environmental risks.
Little is known about the fate, transport, and transformation of nanomaterials after they enter the environment. As the production of manufactured nanomaterials increases and as products containing manufactured nanomaterials are disposed of, these materials could have harmful effects as they move through the environment.
The RFA sponsors are particularly interested in supporting research related to manufactured nanomaterials in the following areas:
Toxicology of manufactured nanomaterials. What is the toxicity/potential toxicity of manufactured nanomaterials? Can similar nanomaterials be grouped with respect to their bioactivity? What are the health effects associated with nanomaterial mixed exposures or multiple exposure routes? What are the dose–response characteristics of nanomaterials? What are appropriate testing procedures, models, and biomarkers to evaluate the potential toxicological effects of nanomaterials in humans and/or other species in natural ecosystems? What extrapolation models are needed to evaluate or predict toxicity? What is the mode of action and mechanism of toxicity? What effects may occur in exposed human and wildlife populations? Are some subpopulations more sensitive to nanomaterials? Do nanoparticles impact ecological (animal/plant) receptors?
Environmental and biological fate, transport, and transformation of manufactured nanomaterials. By what means do/can manufactured nanomaterials enter the environment? What are the modes of dispersion for nanomaterials in the environment? Do manufactured nanoparticles undergo transformation in the environment? Do manufactured nanoparticles bioaccumulate through the food chain?
Exposure and bioavailability of manufactured nanomaterials. How and to what degree are humans exposed to nanomaterials in the environment and workplace? What effects may occur in exposed human populations and occupations? Are some subpopulations more vulnerable to nanomaterial exposure? What are the exposure pathways for humans? What are the effects of nanomaterials and mixtures on engineering controls and personal protective equipment? What releases might occur from the manufacturing processes of nanomaterials? At what stage in the product life cycle might exposure occur? How will changes from current processes to nanotechnology processes affect material flows of hazardous substances? What are the life cycle impacts from the manufacturing processes for nanomaterials?
Because the manufacturing of nanomaterials is not widespread and nomenclature is not standard, researchers must indicate in their proposals which nanomaterials they will use and where they will obtain them, including any needed collaboration with a materials manufacturing corporation or research lab that is synthesizing a commercially viable material. Thus, in the proposal, information on the source, potential use, composition, and present or future availability of the material being studied must be included. Researchers are encouraged to explore the appropriateness and availability of special nanotechnology user facilities at the Department of Energy; see http://www.nano.gov/html/centers/DOEcenters.html. The National Institute of Standards and Technology also offers user facilities; see http://www.nano.gov/html/centers/NISTcenters.html for information.
It is anticipated that a total of approximately $7 million will be awarded, depending on the availability of funds. The EPA intends to commit up to $5 million in fiscal year 2005, NIOSH intends to commit up to $1 million, and the NSF intends to commit up to $1 million. Depending on the proposal types, 16–20 awards may be given.
For a standard (e.g., R01 type) grant, an applicant may request a project period of up to three years and a budget for total costs (direct and indirect) not to exceed $400,000 total for a three-year period. For an exploratory (e.g., R21, SGER type) grant mechanism, an applicant may request a project period of up to two years and a budget for total costs (direct and indirect) not to exceed $200,000 total for a two-year period. Although the financial plans of the EPA, NIOSH, and the NSF provide support for this program, awards pursuant to this RFA are contingent upon the availability of funds and the receipt of a sufficient number of meritorious applications. Proposals with budgets exceeding the total award limits will not be considered. This RFA will use EPA, NIOSH, and NSF award mechanisms.
Applications must be received by 5 January 2005. The complete version of this announcement is available online at http://es.epa.gov/ncer/rfa/2004/2004_manufactured_nano.html.
Contact: Barbara Karn, EPA, 202-343-9704, e-mail: [email protected]; Nora Savage, EPA, 202-343-9858, e-mail: [email protected]; Cynthia J. Ekstein, NSF, 703-292-7941, e-mail: [email protected]; Adele M. Childress, Office of Extramural Programs, NIOSH, CDC, 1600 Clifton Rd NE, Executive Park, Bldg 24, Rm 1427, MS E-74, Atlanta, GA 30333 USA, 404-498-2509, fax: 404-498-2571, e-mail: [email protected]. Reference: STAR-2005-B1
|
0
|
PMC1253683
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A1020-A1021
|
utf-8
|
Environ Health Perspect
| 2,004 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0978a15579400PerspectivesCorrespondenceMercury Levels in Mothers Shea Katherine M. Consultant, One Buttons Lane, Chapel Hill, North Carolina, E-mail:
[email protected] author declares she has no competing financial interests.
Editors note: In accordance with journal policy, Mahaffey et al. were asked whether they wanted to respond to this letter, but they chose not to do so.
12 2004 112 17 A978 A978 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
I read with great interest the excellent article by Mahaffey et al. (2004), which further describes the characteristics of the 1,709 women from the National Health and Nutrition Examination Survey (NHANES) 1999–2000 who were sampled for total and organic mercury levels in blood. It adds valuable detail to the initial report published last year (Schober et al. 2003). I would appreciate clarification on one important point: in the “Discussion,” the authors cited a new analysis which indicates that the cord blood:maternal blood ratio is not 1:1 as assumed by the National Research Council (NRC) in 2000 (Committee on the Toxicological Effects of Methylmercury 2000), but rather 1.7:1. Using the same benchmark dose lower limit and uncertainty factor used by the NRC, Mahaffey et al. (2004) calculated that blood total mercury levels > 3.5 μg/L in mothers could be associated with increased risk to the developing fetal nervous system. I am very interested in the details of this analysis and particularly in understanding why the uncertainty factor applied by the NRC to account in part for toxicokinetic variability does not compensate for uncertainty related to the cord blood:maternal blood mercury ratio. This is a critical concept because it has a dramatic impact on how many women may carry mercury levels in excess of what is believed to be safe for a fetus.
==== Refs
References
Committee on the Toxicological Effects of Methylmercury, Board on Environmental Studies and Toxicology, Commission on Life Sciences, National Research Council 2000. Toxicological Effects of Methylmercury. Washington, DC:National Academy Press. Available: http://www.nap.edu/books/0309071402/html/ [accessed 28 October 2004].
Mahaffey KR Clickner RP Bodurow CC 2004 Blood organic mercury and dietary mercury intake: National Health and Nutrition Examination Survey, 1999 and 2000 Environ Health Perspect 112 562 570 15064162
Schober SE Sinks TH Jones RL Bolger PM McDowell M Osterloh J 2003 Blood mercury levels in U.S. children and women of childbearing age, 1999–2000 JAMA 289 1667 1674 12672735
|
15579400
|
PMC1253684
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A978a
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.112-a978a
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0978b15579399PerspectivesCorrespondenceU.S. PBDE Levels: Effects in Mice Cleet Christopher American Chemistry Council, Arlington, Virginia, E-mail:
[email protected] author is the manager of the American Chemistry Council’s (ACC) Brominated Flame Retardants Industry Panel (BFRIP). ACC is a trade association representing the leading companies in the business of chemistry. BFRIP is composed of the manufacturers of brominated flame retardants. The members of BFRIP are Albemarle Corporation; Ameribrom, Inc.; Bromine Counpounds, Ltd.; and the Great Lakes Chemical Corporation.
12 2004 112 17 A978 A979 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
I am pleased to submit this letter as a representative of the American Chemistry Council Brominated Flame Retardants Industry Panel (BFRIP). The BFRIP is composed of producers of brominated flame retardants; member companies include Albemarle Corporation, Ameribrom Inc., and Great Lakes Chemical Corporation.
In a recent study, Sjödin et al. (2004) investigated polybrominated diphenyl ethers (PBDEs) in human sera collected in the United States between 1988 and 2002. The authors concluded that such levels were increasing over time and were higher than those reported in Europe. Several points regarding these conclusions require clarification and are addressed below.
Sjödin et al. (2004) used the term “PBDEs”; however, the PBDEs analyzed in sera were only the tetra to hepta congeners. These congeners are commonly found in the commercial pentaBDE product, which is used in flexible polyurethane foam in upholstery applications. The sole U.S. manufacturer of the pentaBDE product (Great Lakes Chemical Corporation, West Lafayette, IN) will voluntarily discontinue production by the end of 2004. However, approximately 80% of the global production of PBDEs is composed of the decabromodiphenyl ether/oxide (DBDPO) commercial product, which is used primarily in electrical and electronic components (typically television cabinet backs, connectors, and wire and cable insulation) and to a minor extent in upholstery textiles. DBDPO was not included in the set of congeners analyzed by Sjödin et al. (2004). Thus, the comments with respect to time trends, if valid, apply only to tetra- to heptaPBDE congeners and not the major PBDE product in production and use, DBDPO.
Second, the results indicate that the PBDEs, and BDE-47 in particular, for the last two time intervals (1995–1999 and 2000–2002) appeared to level off. Of the six isomers analyzed, only BDE-153 appeared to increase between 1995–1999 and 2000–2002. Thus, the most recent data suggest that, in general, U.S. PBDE serum levels for the lower congeners are not continually increasing but have reached a plateau.
Third, the authors state that BDE-47 concentrations collected in similar time frames and reported by other studies in milk (83 or 130 ng/g lipid) and sera (0.63 ng/g lipid, 1988) compare “favorably” with their present sera results of 46 (1995–1999), 34 (2000–2002), and 5.4 (1985–1988) ng/g lipid. These values appear dissimilar from one another and appear to point out highly variable, rather than similar, results.
Finally, we question the validity of a comparison of U.S. to European PBDE levels. As indicated by Sjödin et al. (2004), the analyzed sera were not collected in such a way as to be representative of the general U.S. population. The same is likely true with respect to the blood and milk samples collected in Sweden; these samples are unlikely to be representative of the general European population. Thus, based on this collection process, one cannot reach reliable conclusions regarding U.S. versus European levels.
I would also like to correct information reported regarding manufacture of polybrominated biphenyls (PBBs). Sjödin et al. (2004) stated that the hexaBB product continued to be produced in Europe after the Michigan incident in the 1970s in which it was accidentally included in cattle feed. After that incident, production of only the decabromobiphenyl (decaBB) product, not the hexaBB product, continued in Europe, and that production ceased several years ago. The decaBB product did not exhibit the same toxicologic properties as the hexaBB product.
Finally, Sjödin et al. (2004) stated that “PBDEs cause neurodevelopmental effects in mice …,” citing Eriksson et al. (2001, 2002) and Viberg et al. (2002). Taylor et al. (2002) were unable to reproduce these effects in rats, whereas Viberg et al. (2004) reported similar results in rats and mice. Perhaps these diverging results are related to the small sample size and statistical design used by Eriksson et al. (2001, 2002) and Viberg et al. (2004) that grossly inflates the type 1 (i.e., false positive) error rate. Eriksson et al. and Viberg et al. both used mouse pups as the experimental unit, whereas the litter is the more appropriate measure [U.S. Environmental Protection Agency (EPA) 2004; Organisation for Economic Co-operation and Development (OECD) 2003]. Litter effects are substantial, and using more than one pup from a few litters, as reported by Eriksson et al. (2001, 2002) and Viberg et al. (2004), will confound treatment effects with litter effects (Holson and Pearce 1992). Holson and Pearce also stated that “within-litter variance would likely become substantially lower with age than that between litters.” This would further increase the already sizeable effects of litter and may account for the conclusions of Eriksson et al. (2001, 2002) and Viberg et al. (2004) that neurodevelopmental effects increase with age.
==== Refs
References
Eriksson P Jakobsson E Fredriksson A 2001 Brominated flame retardants: a novel class of developmental neurotoxicants in our environment? Environ Health Perspect 109 903 908 11673118
Eriksson P Viberg H Jakobsson E Orn U Fredridsson A 2002 A brominated flame retardant, 2,2′,4,4′,5′-pentabromodiphenyl ether: uptake, retention, and induction of neurobehavioral alterations in mice during a critical phase of neonatal brain development Toxicol Sci 67 98 103 11961221
Holson RR Pearce B 1992 Principles and pitfalls in the analysis of prenatal treatment effects in multiparous species Neurotoxicol Teratol 14 221 228 1635542
OECD 2003. OECD Guideline for the Testing of Chemicals: Proposal for a New Guideline 426. Developmental Neurotoxicity Study (Draft Document). Paris:Organisation for Economic Co-operation and Development. Available: http://www.oecd.org/dataoecd/14/12/15487898.pdf [accessed 27 May 2004].
Sjödin A Jones R Focant JF Lapeza C Wang R McGahee E 2004 Retrospective time-trend study of polybrominated diphenyl ether and polybrominated and polychlorinated biphenyl levels in human serum from the United States Environ Health Perspect 112 654 658 15121506
Taylor M Hedge J DeVito M Crofton K 2002 Perinatal exposure to a polybrominated diphenyl ether mixture (DE-71) disrupts thyroid hormones but not neurobehavioral development [Abstract] Toxicologist 66 1-S Abstract 642
U.S. EPA 1998. Health Effects Test Guidelines OPPTS 870.6300 Developmental Neurotoxicity Study. Washington, DC:U.S. Environmental Protection Agency. Available: http://www.epa.gov/opptsfrs/OPPTS_Harmonized/870_Health_Effects_Test_Guidelines/Series/870-6300.pdf [accessed 27 May 2004].
Viberg H Fredriksson A Eriksson P 2002 Neonatal exposure to the brominated flame retardant 2,2′,4,4′,5-pentabromodiphenyl ether causes altered susceptibility in the cholinergic transmitter system in the adult mouse Toxicol Sci 67 104 107 11961222
Viberg H Fredriksson A Eriksson P 2004 Comparative developmental neurotoxicity of PBDE 99 in two different mouse strains and rat [Abstract] Toxicologist 78 1-S Abstract 1907
|
15579399
|
PMC1253685
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A978b-A979
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.112-a978b
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0979a15579401PerspectivesCorrespondencePBDEs: Sjödin’s Response Sjödin Andreas Center for Disease Control and Prevention, Atlanta, Georgia, E-mail:
[email protected] author declares he has no competing financial interests.
12 2004 112 17 A979 A979 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
I appreciate Cleet’s response to our paper concerning time trends of polybrominated diphenyl ethers (PBDEs) and related compounds in the U.S. population (Sjödin et al. 2004), and I appreciate the opportunity to address his comments.
Pentabromodiphenyl ether (pentaBDE), along with the lower brominated congeners, was the topic of our investigation (Sjödin et al. (2004). Cleet’s statement emphasizing that the current production of PBDEs is solely in the form of decabromodiphenyl ether belittles the fact that, in 2001, 95% of the 7,500 metric tons of pentaBDE was produced and consumed in the United States [Bromine Science and Environmental Forum (BSEF) 2003]. The industry’s withdrawal of pentaBDE and octabromodiphenyl ether (octaBDE) from the market by the end of 2004 will decrease environmental output. However, continued monitoring of environmental and human levels is needed to measure exposures originating from pentaBDE and octaBDE manufactured before 2005 and to study potential exposure to decaBDE, which will continue to be manufactured.
Cleet’s second remark proposes the possibility that current human PBDE levels have reached a plateau. Because of the variability in our data (Sjödin et al. (2004) and the regionalized sampling, we believe such a conclusion may be premature. As Cleet mentions later in his letter, these studies may not be representative of U.S. and European populations. We did not claim that the sampled pools are representative. To further confirm and track our preliminary observations of human exposure to PBDEs, broader representative studies have been proposed.
Cleet’s third issue concerns comparability of our data on BDE-47 with earlier studies. We referenced several publications regarding the similarity of our measured levels to earlier findings. In a 1988 Illinois study, human levels of BDE-47 were reported to be 0.63 ng/g lipid, with a range of < 0.4–24 ng/g lipid (Sjödin et al. 2001). These Illinois levels can be contrasted to the data from serum pools collected in the southeastern United States, where we found a range of < 1–6 ng/g lipid for the same year [see Figure 1 in our paper (Sjödin et al. 2004)]. We also compared our BDE-47 levels to those in other studies: for example, 33 ng/g lipid in breast adipose tissue (range 7–200 ng/g) collected in the late 1990s (She et al. 2002); 83 ng/g lipid in a milk pool (n = 19) collected in 1997 in New York (Betts 2002); 130 ng/g lipid in a milk pool collected in 2000 in Austin, Texas, and Denver, Colorado (Päpke et al. 2001); and 41 ng/g lipid in milk collected in 2001 in Texas (Schecter et al. 2003). These authors reported concentrations in the same range as our study [e.g., Figure 1 in our paper (Sjödin et al. 2004)].
I appreciate Cleet’s clarification concerning production stoppage of hexabromobiphenyl (hexaBB) in Europe. Also, Cleet’s speculation about the differences in outcomes in animal studies is potentially useful. Although we did not study toxic effects of PBDEs, we asserted the cited studies to be examples of potential concern. We selected the work of Eriksson and colleagues in this regard, demonstrating observed effects in four publications: Eriksson et al. (2001, 2002), Viberg et al. (2002), and Sand et al. (2004).
==== Refs
References
Betts K 2002 Rapidly rising PBDE levels in North America Environ Sci Technol 36 50A 52A
BSEF 2003. Major Brominated Flame Retardants Volume Estimates: Total Market Demand By Region in 2001. Brussels:Bromine Science and Environmental Forum. Available: http://www.bsef-site.com/docs/BFR_vols_2001.doc [accessed 20 October 2004].
Eriksson P Jakobsson E Fredriksson A 2001 Brominated flame retardants: a novel class of developmental neurotoxicants in our environment? Environ Health Perspect 109 903 908 11673118
Eriksson P Viberg H Jakobsson E Örn U Fredriksson A 2002 A brominated flame retardant, 2,2′,4,4′,5-pentabromodiphenyl ether: uptake, retention, and induction of neurobehavioral alterations in mice during a critical phase of neonatal brain development Toxicol Sci 67 98 103 11961221
Päpke O Bathe L Bergman Å Fürst P Meironyté Guvenius D Herrmann T 2001 Determination of PBDEs in human milk from the United States – comparison of results from three laboratories Organohalogen Compounds 52 197 200
Sand S von Rosen D Eriksson P Fredriksson A Viberg H Victorin K 2004 Dose-response modeling and benchmark calculations from spontaneous behavior data on mice neonatally exposed to 2,2′,4,4′,5-pentabromodiphenyl ether Toxicol Sci 81 491 501 15254340
Schecter A Pavuk M Päpke O Ryan JJ Birnbaum L Rosen R 2003 Polybrominated diphenyl ethers in U.S. mothers milk Environ Health Perspect 111 1723 1729 14594622
She J Petreas M Winkler J Visita P McKinney M Kopec D 2002 PBDEin the San Francisco Bay area: measurement in harbor seal blubber and human breast adipose tissue Chemosphere 46 697 707 11999793
Sjödin A Jones R Focant JF Lapeza C Wang R McGahee E 2004 Retrospective time-trend study of polybrominated diphenyl ether and polybrominated and polychlorinated biphenyl levels in human serum from the United States Environ Health Perspect 112 654 658 15121506
Sjödin A Patterson DG Jr Bergman Å 2001 Brominated flame retardants in serum from U.S. blood donors Environ Sci Technol 35 3830 3833 11642440
Viberg H Fredriksson A Eriksson P 2002 Neonatal exposure to the brominated flame retardant 2,2′,4,4′,5-pentabromodiphenyl ether causes altered susceptibility in the cholinergic transmitter system in the adult mouse Toxicol Sci 67 104 107 11961222
|
0
|
PMC1253686
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A979a
|
utf-8
|
Environ Health Perspect
| 2,004 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0979b15579401PerspectivesCorrespondenceThe Human Population: Accepting Earth’s Limitations Salmony Steven Earl Disability Determination Services, Raleigh, North Carolina, E-mail:
[email protected] author declares he has no competing financial interests.
12 2004 112 17 A979 A980 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
I thank Fowler and Hobbs for their letter (2004) and their research (2003). The view that a complexity of factors impacts human population growth certainly makes sense, and they have correctly pointed out that scientifically organized efforts to deal with human problems must take account of manifold interconnected events. Although it is necessary to recognize and acknowledge the complexities inherent in cultural life and the natural world, it is equally important that a dizzying array of variables not blind us to certain scientific facts of biophysical reality. Humankind is bound by such predominant facts because the workings of the world exist independently of human wishes and beliefs.
With this in mind, I thank Hopfenberg for his article (2003) in which he provided an elegant model that accounts for the salient factors governing the dynamics of global human population numbers. According to his findings, the size of the human population is determined primarily by food availability.
The realization that these two points of view differ—that there is complexity and simplicity in the world we inhabit—does not necessarily mean that one is correct and the other incorrect. To the contrary, it could be that each point of view is valid based on the scope of observation.
It may be somehow not quite right to agree with the entire idea of Hobbs and Fowler (2004) that “human population size is beyond human capacity to list, comprehend, and synthesize” without noticing that the same can be said regarding any observable phenomenon. Reality is likely just as complex as Hobbs and Fowler described; but it is also clear from the research of Hopfenberg (2003) and Hopfenberg and Pimentel (2001) that the dynamics of human population growth is no longer preternatural but knowable, and that the population dynamics of Homo sapiens is not essentially different from the population dynamics of other species in both the complexity and the simplicity of the governing elements.
A comprehensive and objective approach to human problems and human potentiality must acknowledge that humankind is a part of the biophysical world, not apart from it. Although Hobbs and Fowler (2004) are correct to note the control human culture exercises in “value systems, economics, politics and religion” in taking account of what is real, human and environmental health could be increasingly at risk because humanity denies scientific facts over which living beings may not have control.
In light of the different sets of data presented by Fowler and Hobbs (2003) and by Hopfenberg (2003), perhaps it is a misnomer for Hobbs and Fowler (2004) to uniformly describe the many, complicated ways humanity is changing the natural world as an “unprecedented success.” Are particulate and solid-waste pollution or the conversion of biomass into human mass with resulting bio-diversity loss examples of success? Perhaps the economic success of the prevailing culture is not sustainable and cannot be maintained much longer. Unbridled economic globalization, unrestricted increases in human consumption of resources, and growing absolute human population numbers are negatively affecting Earth by degrading its fitness as a habitat for humans and other species.
A point in human history may have been reached when the scale and rate of growth of economic expansion, the consumption of natural resources, and the increasing human population can be seen as patently unsustainable. Understanding the causes of and limits to humanity’s impact in the world is a necessary step toward changing human production, consumption, and population trends. Regardless of how long a culture prizes growth and chooses to leave it unchecked, surely it is not too late to accept limits to growth of the human economy, human consumption, and human numbers worldwide by altering human behavior accordingly.
==== Refs
References
Fowler CW Hobbs L 2003 Is humanity sustainable? Proc R Soc Lond B Biol Sci 270 1533 2579 2583
Hobbs L Fowler CW 2004 Complexity of factors involved in human population growth [Letter] Environ Health Perspect 112 A726 A727 15345357
Hopfenberg R 2003 Human carrying capacity is determined by food availability Popul Environ 25 2 109 117
Hopfenberg R Pimentel D 2001 Human population numbers as a function of food supply Environ Dev Sustain 3 1 15
|
15579401
|
PMC1253687
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A979b-A980
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.112-a979b
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0980a15579403PerspectivesCorrespondenceConflicts of Interests: Declarations for All Nebert Daniel W. Department of Environmental Health, University of Cincinnati Medical Center, Cincinnati, Ohio, E-mail:
[email protected] 2004 112 17 A980 A980 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Concerning your editorial, “Embracing Scrutiny,” in the October issue of EHP [Environ Health Perspect 112:A788 (2004)], the need for full disclosure of all potential conflicts of interest by all coauthors contributing to a publication in EHP is commendable and obviously needed. Might I take this one step further and suggest that all reviewers of EHP manuscripts be required to sign a form listing all of their potential conflicts of interest.
|
15579403
|
PMC1253688
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A980a
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.112-a980
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0980b15579403PerspectivesCorrectionCorrections 12 2004 112 17 A980 A980 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
In the letter by Storm and Mazor [Environ Health Perspect 112:A862–A864 (2004)], the title of Table 1 was incorrect; also, P1 and P2 were not exposed but were unexposed children tested in another study. The corrected table is presented below.
At the time the October 2004 Forum article “Farm Chore Checkup” [Environ Health Perspect 112:A804 (2004)] went to press, Anne Gadomski’s assessment of the North American Guidelines for Children’s Agricultural Tasks was scheduled for publication in the October 2004 issue of the American Journal of Public Health (AJPH). However, publication of the assessment in AJPH was delayed; a new publication date has not been set. EHP regrets the error.
Wasserman et al. detected errors in their article “Water Arsenic Exposure and Children’s Intellectual Function in Araihazar, Bangladesh” [Environ Health Perspect 112:1329–1333 (2004)]. In the first paragraph of “Results” (p. 1331), the values should be reversed to read “On average, mothers and fathers reported 2.9 and 3.7 years of education, respectively.” In the second paragraph of “Results” (“Exposure characteristics”), the mean water As concentration should be 117.8 μg/L, not 117.8 μg/dL.
Also, on page 1332 in “As metabolism,” the authors would like to clarify that Chowdury et al. (2003) reported that only the first reaction of the arsenic metabolic pathway—the formation of MMA—is less active in children than in adults.
Table 1 Child participants in VCS studies.
Exposed
Unexposed
ID Age DD or ADD ID Age DD or ADD
E9a 8 – C9a 9 –
E10a,b 6 X C10a 8 –
E14a,b 12 X C14a 12 –
E17a 6 – C17a 5,7 –
P1b 8 X
P2b 10 X
a Children shown in Figure 1A (NYSDOH, unpublished data; Schreiber et al. 2002).
b Children shown in Figure 1B: E10 and E14 were from Schreiber et al. (2002); P1 and P2 were unexposed children examined in an NYSDOH study (NYSDOH 2004).
|
0
|
PMC1253689
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A980b
|
utf-8
|
Environ Health Perspect
| 2,004 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0985b15593451EnvironewsForumTrade/Commerce: NAFTA Worries in Juárez Dahl Richard 12 2004 112 17 A985 A985 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
In June 2004, Mexico’s government enacted a law requiring industrial facilities to measure, record, and report emissions of 104 chemicals that formerly were subject only to voluntary reporting. Mexico now joins the United States and Canada in mandating public access to such information through databases and other means. Although earlier Mexican laws had established some voluntary reporting, implementation was weak. The new law marks a watershed step in Mexico’s environmental legislation.
Critics say the list of 104 chemicals is paltry compared to the 650 and 268 tracked by the United States and Canada, respectively. But Paul J. Miller, air quality program coordinator at the Montréal-based Commission for Environmental Cooperation (CEC), says what’s most important at this point is to establish a workable rule, then add more substances to the list. The CEC is an environmental research organization created by a side agreement to the North American Free Trade Agreement (NAFTA).
The question is, will those additions come in time? Miller says that health problems related to pollution from heavily traveled border crossings are acute in Mexico because most crossings are located in thickly populated areas. With NAFTA’s 1993 opening of cross-border trading, motorized traffic across the U.S.–Mexico border increased. Heightened security following the terrorist attacks of 11 September 2001 means it takes even longer to get through border checkpoints, resulting in long lines of idling trucks and other vehicles.
Research by Mexico’s National Institute of Public Health concluded that air pollution from high-traffic border crossings between the United States and Mexico poses serious health risks to the children who live near those thoroughfares. In the study, written up in a November 2003 CEC working paper, the researchers examined the effects of air pollutants and ozone on the respiratory health of children in the Mexican city of Ciudad Juárez, which lies just across the border from El Paso, Texas. They found that the traffic pollution–related risks to children were “significant,” and recommended the implementation of cost-effective interventions to reduce the problem.
The researchers studied children’s respiratory health between 1997 and 2001 by matching hospital admission data to each child’s place of residence. They found a connection between poor air quality along the Ciudad Juárez thoroughfare and emergency room visits by children suffering from respiratory illness. Among the poorest citizens, exposure to particulate matter (PM) was related to an increase in infant mortality. Among infants aged 1–12 months, an increase of 20 micrograms PM per cubic meter air on the previous day was associated with a 62% increase in respiratory mortality. If elevated PM was observed on the two previous days, the risk of death was increased by 82%.
Carlos A. Rincón, a scientist with the nonprofit Environmental Defense in El Paso, says the population of Ciudad Juárez has been growing at 4.3% annually for years, mostly due to workers moving there to take jobs created largely by NAFTA. “The border areas should benefit from some of the wealth created by the NAFTA trade,” he says, adding, “Common problems require common solutions.”
Miller points out that NAFTA has no obligations to reduce air pollution, whether it be in Mexico, the United States, or Canada. So the CEC can only issue a call for action, as it did in the Ciudud Juárez working paper.
Fernando Holguin, formerly of the Mexican National Institute of Public Health now working for the Centers for Disease Control and Prevention and Emory University, hopes to enlist the help of municipal authorities in Ciudad Juárez in finding solutions. “The goal would be to either divert traffic flows from some areas where we’ve shown that schools are sensitive to traffic-related emissions or change the time in which certain kinds of vehicles are allowed to travel in certain parts of the city,” he says.
On a broader level, Miller suggests Mexico should reduce the sulfur content in diesel fuel sold there, as the United States and Canada have, and require particle traps on diesel exhausts. Long-term measures would include more expensive responses, such as moving congested border crossings to locations outside of heavily populated areas. In the meantime, Mexican officials plan to start the first phase of mandatory industry reporting by the end of 2004.
Ciudad Juárez. Trading on the environment?
|
15593451
|
PMC1253690
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A985a
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.112-a985a
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0985a15593451EnvironewsForumThe Beat Dooley Erin E. 12 2004 112 17 A985 A987 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Dodging the Bullet
Studies in the late 1990s showed that lead bullets were contaminating soil and groundwater near shooting ranges. Alternative “green” bullets made of tungsten were developed and first distributed to select Army facilities in 1999. Now researchers at the Stevens Institute of Technology have found that tungsten and its alloys dissolve in water and soil at rates that exceed lead. And tungsten, once thought to be a benign substance, is being investigated by the CDC as possibly contributing to a cluster of leukemia cases in Fallon, Nevada, where the mineral occurs naturally. Military bases are examining possible ways to capture the not-so-green bullets or prevent their leaching. Meanwhile, tungsten has been nominated for toxicity study by the National Toxicology Program.
The Worm Turns in Cambodia
Cambodia has successfully treated 75% of its nearly 3 million school-aged children against intestinal worms six years ahead of a World Health Organization goal for global parasite control. Cambodia is the first country to reach this international goal. The inexpensive treatment (2¢ per pill) can be administered by teachers in classrooms, as is being done in Cambodia.
Worldwide, intestinal worms affect at least 2 billion people. Children affected with intestinal worms weigh less than healthy children and are more prone to anemia. Left untreated, infection with intestinal worms can cause irreversible organ damage and impaired intellectual development. Once treated, however, affected children’s short- and long-term memory, reasoning capacity, and reading comprehension all improve dramatically, and school absenteeism drops as much as 25%.
Wave of Fish Advisories
New figures released by the U.S. EPA show that 35% of lake acreage in the United States and 24% of river miles contain enough pollution to warrant consumption advisories for fish caught in those waters. The advisories cover some 40 different substances; 98% of them involve PCBs, chlordane, dioxins, DDT, or mercury. Though the number of advisories rose from 2,814 in 2002 to 3,094 in 2003, EPA administrator Mike Leavitt attributed that increase to more monitoring rather than an increase in pollution. Environmental advocates say these latest findings point up the need to more strictly regulate coal-fired power plants, one of the primary sources of mercury.
Malawi Bans Methyl Bromide
Although the Montréal Protocol stipulates that methyl bromide need not be banned in developing countries until 2015, protocol party Malawi is working to phase out use of the ozone-depleting pesticide by the end of 2004. Imports of the pesticide after 31 December 2004 are to be impounded.
Malawi is the second largest user of the pesticide in Africa, and tobacco is one of the country’s principal sources of foreign cash flow. The ban will make the country the first in its region to phase out nonessential uses of the pesticide. The Malawian Agricultural Research and Extension Trust is working to raise awareness among the country’s farmers about the hazards of using the chemical and about alternatives to using it, which include soil-less culture of tobacco plants and use of more benign chemicals such as dazomet.
Plutonium Accumulating in Japanese Bay
Fifty years ago, the United States performed tests of nuclear weapons in the Marshall Islands, an island group almost halfway between Hawaii and Tokyo. Now radioactive plutonium particles that match the fallout from those blasts have been found in Japan’s Sagami Bay by researchers at the Japanese National Institute of Radiological Science. This is the first time such particles have been found in Japanese waters.
The researchers believe they pose no environmental risk. They plan to study other shorelines in Japan to determine how the particles traveled—useful information in the event of a nuclear emergency. At present researchers believe the particles were carried by the ocean currents.
Protecting Peanuts from Aflatoxins
The U.S. Agricultural Research Service has received EPA approval for the first biological pesticide to protect peanut crops against toxic Aspergillus mold strains that produce aflatoxins. Consumption of grains and nuts contaminated with aflatoxins has been linked with liver cancer and hepatitis in humans. Afla-Guard, as the new treatment is known, is from a nontoxigenic strain of flavus. It is applied beneath the plant canopy, where it competes against its aflatoxin-producing cousins, which generally colonize plants that are stressed by drought conditions. Afla-Guard also works on peanuts that are stored in warehouses. In field trials, the treatment reduced aflatoxin contamination by 70–90% after the first application, and even more with subsequent applications.
|
0
|
PMC1253691
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A985b-A987
|
utf-8
|
Environ Health Perspect
| 2,004 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0986aEnvironewsForumChildren’s Health: Flu, Fetuses, and Schizophrenia Wakefield Julie 12 2004 112 17 A986 A986 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Pregnant women who contract the flu may increase the risk that their child will develop schizophrenia later in life, according to a recent addition to a growing body of research along these lines. The study, published in the August 2004 Archives of General Psychiatry, “is not definitive but is the strongest evidence thus far that a prenatal virus may be a risk factor [for schizophrenia],” says lead investigator Ezra Susser, head of epidemiology at Columbia University’s Mailman School of Public Health.
“Influenza infection during pregnancy appears to be a risk factor,” agrees Johns Hopkins University neurovirologist Robert Yolken, who adds it is probably one of many risk factors for developing schizophrenia. The severe mental illness, which usually involves delusions, hallucinations, and disordered thinking, affects about 1% of the U.S. population. The Mailman team’s work is part of a larger study designed to examine prenatal infection and such factors as father’s age and prenatal exposure to chemicals in influencing schizophrenia in adulthood.
The Mailman team looked for influenza antibody in archived blood samples from 64 women whose children developed schizophrenia as adults and a control group of 125 women whose children did not develop the disorder. The samples were collected as part of the Child Health and Development Study, which collected blood samples from more than 12,000 mothers of children born between 1959 and 1967 and followed the children’s development into adulthood.
The risk of schizophrenia was tripled when the mother had the flu during the first half of pregnancy and increased sevenfold if exposure occurred in the first trimester. The overall risk is small, however. The findings suggest that about 97% of children born to women who got the flu while pregnant will not develop schizophrenia.
Although researchers do not know the mechanism of action, the Mailman team speculates that antibodies released by the mother’s immune system may affect the developing brain. But direct effects from the flu virus are also possible.
Researchers believe schizophrenia may result from a combination of genetic and environmental factors, including complications during delivery and exposure to the herpes simplex virus type 2 and to rubella virus during pregnancy. “It may not be just one virus,” Yolken says. “And [the key environmental factor] may vary from population to population, as genetic factors likely play a role.” Moreover, different strains of herpes or flu viruses may play greater or lesser roles.
Until more study is completed, the Mailman team still advocates that pregnant women get the flu shot. Susser says, “The very safest thing would be to get vaccinated against the flu virus before becoming pregnant.”
A cold now, catastrophe later. Having the flu while pregnant may pave the way for future schizophrenia in children.
|
0
|
PMC1253692
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A986a
|
utf-8
|
Environ Health Perspect
| 2,004 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0986bEnvironewsForumNeurology: A Better Model for PD Heimer Hakon 12 2004 112 17 A986 A986 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
The ubiquitin–proteasome system mediates protein recycling by tagging abnormal or unwanted proteins within cells with the small protein ubiquitin. Enzymes called proteasomes then dismantle the tagged proteins. Malfunctioning of this system is emerging as an important component of neurodegenerative diseases, such as Parkinson disease (PD), that feature the buildup of defective proteins and the gradual death of brain cells. This new PD research focus was validated by a recent study in which researcher Kevin St. P. McNaught and colleagues at the Mount Sinai School of Medicine induced a disorder closely resembling PD by exposing rats to proteasome inhibitors.
Researchers have long been able to create PD models in laboratory animals by using toxicants that kill dopamine nerve cells in an area of the brain called the substantia nigra. The substantia nigra is an important node in the brain circuitry that controls movement, and neurons in this area are hardest hit by PD. But in neurotoxicant models, the animals do not develop the full range of clinical and pathological features of the human disease, especially those that result from nerve cell death in other brain regions.
In their quest for a more representative model of PD, McNaught and colleagues took note of recent evidence that malfunction of the ubiquitin–proteasome system is a central factor in both the rare hereditary and common sporadic forms of PD. Over a period of two weeks, they injected rats with both man-made and naturally occurring proteasome inhibitors. Within two weeks of exposure, the rats began to show parkinsonian symptoms, including slowness of movement, rigidity, and tremor. “These symptoms gradually worsened over a period of weeks to months, and could be reversed with drugs that are used to treat PD patients,” says McNaught.
PET imaging and autopsy studies of the animals’ brains showed changes very similar to those seen in PD, including the abnormal accumulation of protein in the substantia nigra. In response to the proteasome inhibitors, nerve cells all over the brain boosted their proteasomal activity, but the substantia nigra and other PD-affected areas were unable to sustain this compensatory response, and ultimately showed reduced proteasomal activity as occurs in PD.
In the report of their findings, which was published in the July 2004 issue of the Annals of Neurology, the authors also raise the possibility that proteasome inhibitors in the environment, whether from bacteria, fungi, plant-based foods, or man-made sources, might play a role in the development of some cases of PD. Importantly, recent studies have shown that the widely used fungicide maneb is a potent proteasome inhibitor and can kill dopamine cells in culture. We must therefore determine the extent to which proteasome inhibitors are present in the environment and how humans might be exposed to these agents, says McNaught.
Jean Harry, principal investigator of the NIEHS Neurotoxicology Group, believes such a link is tenuous at this stage. She says, “What the study really offers the field is an exciting new model to address questions about the disease process and the potential impact of environmental factors.”
|
0
|
PMC1253693
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A986b
|
utf-8
|
Environ Health Perspect
| 2,004 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0990a15579405EnvironewsNIEHS NewsSymposium Explores Children’s Environments Dimes Martha M. 12 2004 112 17 A990 A992 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
“When we try to pick out anything by itself, we find it hitched to everything else in the Universe.” Quoting naturalist John Muir, Michael Fischer, an environmental consultant formerly of the William and Flora Hewlett Foundation, introduced the 2004 Biennial Scientific Symposium on Children’s Health as Impacted by Environmental Contaminants by emphasizing that children are at the nexus of many of the connections found in nature.
The symposium was designed to explore the interconnectedness of all elements of the environments in which children live, learn, and play, as well as ways to prevent environmental health risks. Hosted by the Children’s Environmental Health Institute (CEHI), the symposium was held 24–25 September 2004 at the McKinney Roughs Nature Park in Austin, Texas. The symposium was sponsored by the NIEHS, Physicians for Social Responsibility, the Texas Medical Association, the Lower Colorado River Authority, and the Centers for Disease Control and Prevention. The interdisciplinary group of participants included researchers, pediatricians and other health professionals, social workers, nonprofit and advocacy group representatives, architects, and engineers.
Topics ranged from the cellular level to the global. Because environmental toxicants are ubiquitous in air, water, food, and medications, said pediatrician and speaker Martin Lorin, we have seen a global rise in environmentally related diseases. However, in terms of the extent of the effects of exposures, he contended, we are seeing only the tip of the iceberg.
Participants agreed that to reduce harmful immediate and long-term effects of contaminants on children, we must study the interactions of environment, genes, developmental stage, and behavior. Discussions on endocrine disruptors (by John McLachlan of Tulane and Xavier Universities), developmental defects (by Richard Finnell of Texas A&M University), and respiratory disease (by Sharon Petronella of The University of Texas Medical Branch, Galveston), for example, addressed not just specific immediate health problems in children but also future trends: What kinds of adult diseases might be projected from fetal and childhood exposures? And how healthy are future populations likely to be?
Potential remedies for environmentally related health problems may be as simple as taking folic acid to help prevent birth defects or having a physician take an environmental history to spot potential health risks. Technical (air quality samplers, hand-held immunosensors, microarrays) and demographic (geographic information systems, longitudinal studies) tools also can help identify and alleviate environmental health threats.
The built environment—both materials and design—can significantly reduce children’s exposures to toxicants while creating safe and stimulating places to grow and learn. How do we replace the persistent bioaccumulative and toxic chemicals used to produce building materials with less-toxic alternatives?
Gail Vittori, codirector of the Center for Maximum Potential Building Systems, suggested several methods, among them eliminating interior finish materials that offgas volatile organic compounds, using recycled fly ash as a substitute for concrete, labeling building products more thoroughly, and using paints certified by the independent Green Seal standards program.
Vittori also recommended that builders participate in the Leadership in Energy and Environmental Design program, a voluntary standard established by the U.S. Green Building Council for assessing and certifying high-performance sustainable buildings. In schools, inadequate ventilation, use of toxic pesticides and cleaners, offgassing from building materials and furnishings, and poor maintenance should be remediated to avoid increases in asthma, allergies, and other respiratory diseases.
With an eye toward the future, the NIEHS and the U.S. Environmental Protection Agency will continue to fund the Centers for Children’s Environmental Health and Disease Prevention Research, according to NIEHS director Kenneth Olden. These centers promote multidisciplinary research and the translation and application of research to public health and clinical practice. The Centers for Disease Control and Prevention aims to expand environmental public health tracking to a full nationwide network, collecting and analyzing data on hazards, exposures, and health effects. And Fernando Guerra, director of health with the San Antonio Metropolitan Health District, noted that the multi-agency National Children’s Study “will provide for the first time an opportunity for children and families to benefit from the cumulative evidence that will be assembled over twenty-five years, to better understand causal relationships from many different influences, including the environment.”
The participants concluded that prevention, remediation, and attention to the long term are essential to addressing the unique vulnerabilities of infants and children. The challenge presented here is to blend research and clinical work with advocacy. Said CEHI director Janie Fields: “Together we are building a structure that bridges the health information gap between the medical, research, and environmental communities.”
|
15579405
|
PMC1253694
|
CC0
|
2021-01-04 23:40:52
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A990a-A992
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.112-a990
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a0990b15579405EnvironewsNIEHS NewsSchwartz Named New NIEHS/NTP Director 12 2004 112 17 A990 A990 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
On 25 October 2004 NIH director Elias Zerhouni announced the appointment of David Schwartz as the new director of the NIEHS and the National Toxicology Program. Schwartz, who will assume his new duties on 4 April 2005, is currently director of the Pulmonary, Allergy, and Critical Care Division and vice chair of research in the Department of Medicine at Duke University. While at Duke, Schwartz has also played a leading role in developing interdisciplinary Centers in Environmental Health Sciences, Environmental Genomics, and Environmental Asthma. Schwartz’s research has focused on the genetic and biological determinants of environmental lung disease and host defense.
Schwartz is filling the position left open by Kenneth Olden, who stepped down from the post late in 2003, but who agreed to remain in the position until his successor was named. Olden will stay on at the NIEHS as a researcher in the intramural program.
At the announcement of the appointment, DHHS secretary Tommy Thompson called Schwartz “one of the nation’s outstanding researchers in environmental health.” Thompson and Zerhouni acknowledged the leadership role that Schwartz is taking on at the NIEHS as environmental factors are being implicated more often in the etiology of disease. Zerhouni touted Schwartz’s interdisciplinary approach as one that “will help lead us to well-conceived strategies for preventing, diagnosing, and treating disease.”
As director of the NIEHS, Schwartz will oversee a $711 million budget that funds multidisciplinary biomedical research programs, as well as prevention and intervention efforts that encompass training, education, technology transfer, and community outreach. The NIEHS currently supports more than 850 research grants.
“I am delighted and honored to join NIH,” said Schwartz. “My vision for NIEHS is to improve human health by supporting integrated research and career development in environmental sciences, environmental medicine, and environmental public health. Given recent advances in biomedical research and computational biology, NIEHS is well positioned to use its expertise in toxicology to understand human biology, disease pathogenesis, and the unique distribution of disease in different populations.”
|
0
|
PMC1253695
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A990b
|
utf-8
|
Environ Health Perspect
| 2,004 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a1032aAnnouncementsBook ReviewThe River Runs Black: The Environmental Challenge to China’s Future Dore Giovanna Giovanna Dore is an environmental specialist with the Environment and Social Development Unit of the East Asia and Pacific Region at the World Bank. Her sectoral expertise lies in institutional development and economics for environment and natural resources management for China, Indonesia, Mongolia, the Philippines, and Vietnam.12 2004 112 17 A1032 A1032 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
By Elizabeth C. Economy
Ithaca, NY:Cornell University Press, 2004. 337 pp. ISBN: 0-8014-4220-6. $29.95 cloth.
In The River Runs Black, Elizabeth C. Economy strikes a fine balance between acknowledging the merits of the country’s continued economic transformation (especially in terms of reduced social, economic, and human cost of poverty), presenting an overview of the environmental challenges and impacts of such sustained economic growth, and how the range and significance of these challenges have changed and increased, particularly over the last three decades. Drawing on various original and secondary sources, she analyzes how these challenges are affecting the environmental agenda, identifies environmental management strategies and priorities, proposes lessons from the international experience, and suggests a course for improving environmental quality in China over the short to medium term.
Among the highlights of the book are the first five chapters, which, thanks to a dynamic and lean structure, take the reader through several centuries of Chinese history and environmental tradition. In Chapter 2, “A Legacy of Exploitation,” a sharp overview of how the traditional concepts and institutions of Confucianism have played a formidable role in shaping China’s original nonenvironmental development policies is complemented by discussion of the reasons why the relatively more eco-friendly philosophies of Taoism and Buddhism had a limited impact in the consciousness of Chinese leaders and people. From the historical and philosophical excursus, the author concludes that the predominance of Confucianism produced a long tradition of exploiting the environment for human needs, with little or no concern for the long-term impacts of the practical application of this philosophy—deforestation and exploitation of mining resources, poor water resources management, and, more important, no formal administrative structure in place to manage and protect environment and natural resources, leaving such tasks to the country’s leaders. Chapter 5, “The New Politics of the Environment,” the most interesting of these five chapters (and possibly of the entire book), offers many insights on the workings of civil society and nongovernmantal organizations’ participation in environmental decision making, their ability to influence it given existing policy and political constraints, and their limited access to funding and reliable information about environment and natural resources management.
Unfortunately, the second part of the book does not live up to this quality. The information of the last three chapters is less original and especially lacks most of the intriguing introspection and analysis offered earlier in the book. Chapter 7, “Lessons from Abroad,” offers a brief, detailed account of how other countries have dealt with environmental challenges in circumstances similar to those of China and how the international community has helped. This chapter is the most interesting of the last three because of the uncharacteristic scope of several of the comparisons presented (such as those with former Soviet Union and Eastern European countries). Yet the author fails to identify what the experiences of these other countries really mean for China and, especially, how China can best use the lessons learned from those experiences on balancing sound environmental management with economic demand while maintaining social stability.
Despite some reading fatigue from the last three chapters, The River Runs Black can please many audiences: those who are knowledgeable about China and the political economy of its environmental problems, and those who are only superficially interested in China and/or in environmental affairs. The book could also be excellent background reading for a graduate program in environmental policy and management and/or on China.
|
0
|
PMC1253696
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A1032a
|
utf-8
|
Environ Health Perspect
| 2,004 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institute of Environmental Health Science ehp0112-a1032aAnnouncementsBook ReviewThe River Runs Black: The Environmental Challenge to China’s Future Dore Giovanna Giovanna Dore is an environmental specialist with the Environment and Social Development Unit of the East Asia and Pacific Region at the World Bank. Her sectoral expertise lies in institutional development and economics for environment and natural resources management for China, Indonesia, Mongolia, the Philippines, and Vietnam.12 2004 112 17 A1032 A1032 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
By Elizabeth C. Economy
Ithaca, NY:Cornell University Press, 2004. 337 pp. ISBN: 0-8014-4220-6. $29.95 cloth.
In The River Runs Black, Elizabeth C. Economy strikes a fine balance between acknowledging the merits of the country’s continued economic transformation (especially in terms of reduced social, economic, and human cost of poverty), presenting an overview of the environmental challenges and impacts of such sustained economic growth, and how the range and significance of these challenges have changed and increased, particularly over the last three decades. Drawing on various original and secondary sources, she analyzes how these challenges are affecting the environmental agenda, identifies environmental management strategies and priorities, proposes lessons from the international experience, and suggests a course for improving environmental quality in China over the short to medium term.
Among the highlights of the book are the first five chapters, which, thanks to a dynamic and lean structure, take the reader through several centuries of Chinese history and environmental tradition. In Chapter 2, “A Legacy of Exploitation,” a sharp overview of how the traditional concepts and institutions of Confucianism have played a formidable role in shaping China’s original nonenvironmental development policies is complemented by discussion of the reasons why the relatively more eco-friendly philosophies of Taoism and Buddhism had a limited impact in the consciousness of Chinese leaders and people. From the historical and philosophical excursus, the author concludes that the predominance of Confucianism produced a long tradition of exploiting the environment for human needs, with little or no concern for the long-term impacts of the practical application of this philosophy—deforestation and exploitation of mining resources, poor water resources management, and, more important, no formal administrative structure in place to manage and protect environment and natural resources, leaving such tasks to the country’s leaders. Chapter 5, “The New Politics of the Environment,” the most interesting of these five chapters (and possibly of the entire book), offers many insights on the workings of civil society and nongovernmantal organizations’ participation in environmental decision making, their ability to influence it given existing policy and political constraints, and their limited access to funding and reliable information about environment and natural resources management.
Unfortunately, the second part of the book does not live up to this quality. The information of the last three chapters is less original and especially lacks most of the intriguing introspection and analysis offered earlier in the book. Chapter 7, “Lessons from Abroad,” offers a brief, detailed account of how other countries have dealt with environmental challenges in circumstances similar to those of China and how the international community has helped. This chapter is the most interesting of the last three because of the uncharacteristic scope of several of the comparisons presented (such as those with former Soviet Union and Eastern European countries). Yet the author fails to identify what the experiences of these other countries really mean for China and, especially, how China can best use the lessons learned from those experiences on balancing sound environmental management with economic demand while maintaining social stability.
Despite some reading fatigue from the last three chapters, The River Runs Black can please many audiences: those who are knowledgeable about China and the political economy of its environmental problems, and those who are only superficially interested in China and/or in environmental affairs. The book could also be excellent background reading for a graduate program in environmental policy and management and/or on China.
|
0
|
PMC1253697
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2004 Dec; 112(17):A1032b
|
latin-1
|
Environ Health Perspect
| 2,004 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7433ehp0113-00000115626639ResearchReviewIonizing Radiation and Chronic Lymphocytic Leukemia Richardson David B. 1Wing Steve 1Schroeder Jane 1Schmitz-Feuerhake Inge 2Hoffmann Wolfgang 31Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA2Department of Physics (retired), University of Bremen, Germany3Institute for Community Medicine, Division of Health Care Epidemiology and Community Health, Ernst-Moritz-Arndt-University Greifswald, Greifswald, GermanyAddress correspondence to D. Richardson, Department of Epidemiology, School of Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC 27599-8050 USA. Telephone: (919) 966-2675. Fax: (919) 966-6650. E-mail:
[email protected] authors declare they have no competing financial interests.
1 2005 21 10 2004 113 1 1 5 20 7 2004 21 10 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. The U.S. government recently implemented rules for awarding compensation to individuals with cancer who were exposed to ionizing radiation while working in the nuclear weapons complex. Under these rules, chronic lymphocytic leukemia (CLL) is considered to be a nonradiogenic form of cancer. In other words, workers who develop CLL automatically have their compensation claim rejected because the compensation rules hold that the risk of radiation-induced CLL is zero. In this article we review molecular, clinical, and epidemiologic evidence regarding the radiogenicity of CLL. We note that current understanding of radiation-induced tumorigenesis and the etiology of lymphatic neoplasia provides a strong mechanistic basis for expecting that ionizing radiation exposure increases CLL risk. The clinical characteristics of CLL, including prolonged latency and morbidity periods and a low case fatality rate, make it relatively difficult to evaluate associations between ionizing radiation and CLL risk via epidemiologic methods. The epidemiologic evidence of association between external exposure to ionizing radiation and CLL is weak. However, epidemiologic findings are consistent with a hypothesis of elevated CLL mortality risk after a latency and morbidity period that spans several decades. Our findings in this review suggest that there is not a persuasive basis for the conclusion that CLL is a nonradiogenic form of cancer.
chronic lymphocytic leukemiacompensationionizing radiationradiogenicity
==== Body
Less than 5 years after the atomic bombings of Hiroshima and Nagasaki, it was established that there was an excess of leukemia among the atomic bomb survivors (Committee for the Compilation of Materials 1981). Japanese physicians noted the unusual number of leukemia cases among survivors, and researchers associated with the Atomic Bomb Casualty Commission (ABCC) subsequently confirmed the observation in a series of epidemiologic surveys (Folley et al. 1952; Valentine 1951). When examined by leukemia subtype, researchers with the ABCC reported substantial excesses of acute forms of leukemia and chronic myeloid leukemia among A-bomb survivors. In contrast, no excess of chronic lymphocytic leukemia (CLL) was observed (Finch et al. 1969; Ishimaru et al. 1969).
A few years later, Court-Brown and Doll (1957) reported the results of a study of mortality among adult British males who had received X-ray therapy for an arthritic condition (ankylosing spondylitis). When examining leukemia by subtype, it was noted that in the first 5 years postirradiation, deaths due to acute forms of leukemia and chronic myeloid leukemia were in substantial excess among these patients. The researchers found no excess of CLL (Court-Brown and Doll 1965; Darby et al. 1987). These findings, and their consistency with those of the A-bomb survivor studies, led investigators to postulate that there were differences in the radiogenicity of leukemia by subtype, with CLL being much less readily inducible by exposure to ionizing radiation than other types of leukemia (Darby et al. 1987).
Over time, this hypothesis has come to be expressed more strongly (Department of Health and Human Services 2002). Although most lymphatic and hematopoietic tissues are considered to be extremely sensitive to the carcinogenic effects of ionizing radiation, it is routinely presumed that CLL incidence is entirely insensitive to the carcinogenic effects of radiation. This assertion has become institutionalized in the U.S. Energy Employees Occupational Illness Compensation Program, under which all claims for CLL must be rejected because of the presumption that the risk of radiation-induced CLL is zero (Department of Health and Human Services 2002). In this article, we review the basis for the current presumption that CLL incidence is entirely unaffected by ionizing radiation exposure.
Methods
In this article we present a review of the molecular, clinical, and epidemiologic evidence regarding the radiogenicity of CLL. We begin with a review of the current understanding of the molecular basis of CLL. Next, we review the clinical attributes of CLL and discuss the implications for etiologic research. Finally, we consider the epidemiologic literature on associations between external exposure to ionizing radiation and CLL risk. We focus on studies that have played a prominent role in the literature on the induction of leukemia, and specifically CLL, by ionizing radiation [National Research Council, Committee on the Biological Effects of Ionizing Radiation (BEIR V) 1990; United Nations Scientific Committee on the Effects of Atomic Radiation 2000]. Studies of the effects of exposure to ionizing radiation in utero or in childhood (e.g., for thymic enlargement or tinea capitis) were not included in this review because the average age of study participants at the end of follow-up tended to be less than the age at which CLL typically occurs.
The Revised European American Lymphoma classification scheme (Harris et al. 1994), which is widely accepted and was adopted by the World Health Organization, considers B-cell CLL and small lymphocytic lymphoma [SLL, a subtype of non-Hodgkin’s lymphoma (NHL)] to be a single disease entity, in recognition of the biologic and clinical similarities between these B-lymphocyte malignancies (Harris et al. 1999). Epidemiologic evidence of associations between ionizing radiation and risk of SLL would therefore be of interest in the context of this evaluation. However, epidemiologic studies have only recently begun to evaluate risk factors for SLL, and studies available for this review did not report results specifically for SLL.
Many of the epidemiologic studies that we reviewed reported results of analyses of standardized mortality ratios (SMRs) or standardized incidence ratios (SIRs). We have included 95% confidence intervals (CIs) for these findings. If a 95% CI was not reported in the text, we have calculated approximate 95% CIs (Rothman and Boice 1979). In this article we generically refer to measures of association based on odds ratios and rate ratios as estimates of relative risk (RR). Many of the studies that we reviewed reported estimates of radiation dose to the bone marrow. We have included these values in the text in order to allow comparison of the magnitude of doses between study populations. We report radiation dose estimates in millisieverts. Some of the reviewed papers reported dose estimates in milligrays, a physical quantity describing energy deposited per unit mass. For X-rays and gamma-rays, we assume a quality factor of unity; hence, 1 mGy = 1 mSv.
Results
Molecular basis of CLL.
CLL is a monoclonal disease of lymphocytes. Like other lymphoid cancers, CLL pathogenesis appears to be driven both by functional aberrations in immune function (Stevenson et al. 1998) and by somatic mutations, some of which may be a consequence of environmental exposures (Magrath 1992). Using contemporary molecular cytogenetic methods, chromosomal abnormalities are detected in most (> 80%) CLL cases (Stilgenbauer et al. 2002). Two tumor suppressor genes that are inactivated as a result of common CLL mutations, p53 and ATM, are established causal contributors to malignant transformation. Therefore, these and other common somatic mutations are believed to play a causal role in the etiology of CLL.
The type of mutations observed in clonal cells obtained from CLL patients, primarily deletions of chromosomal material, require double-strand breaks of the chromosomal DNA in order to occur (Dewald et al. 2003; Stilgenbauer et al. 2000). Double-strand breaks (in one-half of the gene pair) are routinely generated during immunoglobulin gene rearrangement during normal lymphocyte maturation. However, in marked contrast with other lymphocytic malignancies, somatic mutations (specifically, translocations) involving immunoglobulin genes are rare in CLL (Stilgenbauer et al. 2002). This suggests that environmental exposures, rather than endogenous processes related to gene rearrangement during normal lymphocyte maturation, play an important role in producing the somatic mutations that contribute to the genesis of CLL.
It is well established that ionizing radiation has the ability to produce double-strand breaks in chromosomal DNA (United Nations Scientific Committee on the Effects of Atomic Radiation 2000). The primary mechanism by which biologic damage occurs is believed to be via the creation of ionized atoms and molecules that become chemically reactive. This can occur directly via ionization of a critical molecule, such as DNA, or indirectly via ionization of nearby molecules, such as water.
Like all cancers, CLL requires multiple mutations before neoplastic transformation occurs. Rather than arising due to a loss of cellular control and rapid proliferation of clonal lymphocytes, in the case of CLL the carcinogenic process is believed to typically involve an early event that causes a failure of apoptosis. The effectively immortalized lymphocyte may then persist in the body for years, increasing the likelihood that the cell will acquire additional mutations leading to full neoplastic transformation and the accumulation of clonal cells that may result in clinical symptoms of malignant disease (Voutsadakis 2000). This multistage process of neoplastic transformation is believed to account for many of the observed characteristics of the natural history of the disease and, specifically, the protracted induction and/or latency period associated with CLL.
Ionizing radiation exposure could play a role in one or more stages of this multistage process of neoplastic transformation. In addition, it is plausible that some early-stage mutational events may increase the likelihood of ionizing radiation exposure influencing later-stage transformations. For example, in a considerable proportion of CLL clones (~ 20%), the ATM gene is mutated; the ATM gene product is known to be involved in the repair of DNA double-strand breaks (Dunst et al. 1998; Humphreys et al. 1989; Jones et al. 1995; Parshad et al. 1985; Stilgenbauer et al. 2000), and mutations of this gene are associated with increased vulnerability to the carcinogenic effects of ionizing radiation. The inactivation of this tumor suppressor gene is not necessarily due to radiation exposure itself, but could occur as an early event that increases susceptibility to subsequent ionizing-radiation–induced mutations that result in progression of the carcinogenic process to CLL.
Clinical aspects of CLL.
Compared with acute forms of leukemia and chronic myeloid leukemia, CLL is neither fast progressing nor highly fatal. With an increasing number of lymphocytes in the circulating bloodstream, eventually a person with CLL may present with symptoms of clinical significance such as shortness of breath, weight loss, or fever. However, often a patient with CLL is diagnosed during a routine medical examination that is not conducted because of any overt symptoms of disease (Rozman and Montserrat 1995).
The clinical aspects of the disease are important considerations from an epidemiologic perspective because they render CLL more prone to misclassification than acute lymphocytic and myeloid forms of leukemia. Even when patients present with overt symptoms of disease, diagnostic classification of CLL has long been characterized by a lack of consistency. Until recently, the same patient might be diagnosed with CLL by one hematologist and diagnosed with NHL by another, depending upon the classification scheme used by the diagnosing physician (Harris et al. 2000a, 2000b). CLL is now considered analogous to SLL (a subtype of NHL), the difference between the two being a function of the extent to which the tumor involves the bone marrow (CLL) versus solid tissue (SLL), with the recognition that both solid and circulating phases are present in many lymphoid neoplasms (Harris et al. 1999).
Particularly problematic are studies that rely on the use of cause of death information obtained from the death certificate as a proxy for information on CLL incidence. Cause of death information provides a relatively good measure of disease incidence if the disease progresses rapidly and has a high probability of leading to death. These are not the characteristics of CLL. Patients diagnosed with CLL often live many years without developing evidence of significant symptoms, and as a consequence of the typically old age at onset of CLL, many patients die with the disease, but from causes other than CLL (Crespo et al. 2003). In the United States, for example, the 5-year survival rate after a diagnosis of CLL is > 70% (Ries et al. 2003). Therefore, CLL is not necessarily the underlying cause of death recorded on a death certificate and, in fact, may not be indicated on the death certificate at all. In addition, deaths attributed to CLL tend to occur at very old ages when the validity of death certificate information tends to be poorest (Ron et al. 1994b). Furthermore, the direct repercussions or complications of CLL are often nonspecific, including immunodeficiency, and may increase the likelihood of infectious or malignant disease, thereby increasing the opportunity for conditions other than CLL to be recorded as the underlying cause of death. Secondary cancers frequently follow CLL incidence, and there is the possibility that the malignant clone of CLL can increase in malignancy due to additional chromosome breaks (dedifferentiation) and develop into a highly malignant B-cell NHL. Again, with high probability, the secondary cancer would be documented as the cause of death. This observation is supported by evidence from a recent study of patients with CLL in which Kyasa et al. (2004) found that the second malignancy was the primary cause of death recorded for 34% of CLL patient deaths.
Epidemiologic findings regarding radiogenicity.
Table 1 lists a number of epidemiologic studies of populations exposed to ionizing radiation and describes the numbers of cases and study findings for associations with CLL by exposure type.
Atomic bomb.
The Lifespan Study (LSS) of the Japanese atomic bomb survivors has served as one of the primary studies for evaluation of the carcinogenic effects of ionizing radiation. However, for evaluation of CLL risk after exposure to ionizing radiation, the LSS provides minimal information because the incidence of CLL is extremely low in Asian populations (Finch and Linet 1992; Groves et al. 1995). Furthermore, much of the research published over the past 50 years on the effects of the atomic bomb on CLL incidence and mortality in the LSS suffered problems of case misclassification (Preston et al. 1994). After an extensive review of hematologic specimens for leukemia cases identified during the period from 1945 through 1980, it was determined that 7 of the 10 CLL cases registered during that period were, in fact, not CLL. These were determined to be cases of acute T-cell leukemia (ATL), a relatively common disease among Nagasaki residents regardless of their status as an A-bomb survivor. ATL is strongly related to infection by the human T-lymphotropic virus type 1, which is particularly prevalent in the Nagasaki region. Consequently, reports on radiation–CLL associations that are based on information collected before this reclassification of leukemia are of questionable reliability because of these problems of case misclassification. With the reclassification of leukemia cases, analyses of cancer incidence among 86,293 survivors (average bone marrow dose estimated as 300 mSv) over the period 1950–1987 include only four CLL cases. Given the small number of CLL cases, specific analyses of radiation–CLL associations have not been reported (Preston et al. 1994; Tomonaga et al. 1991).
Radiation therapy for nonmalignant disease.
Studies of patients treated by radiotherapy provide more informative results because they include larger numbers of CLL cases. Of particular importance, given the size of the study cohort, duration of follow-up, and average magnitude of radiation dose, are the results of a study of cancer mortality among approximately 14,000 British ankylosing spondylitis patients who were treated by X irradiation between 1935 and 1954 (average bone marrow dose estimated as 4,400 mSv). With vital status follow-up through 1991, it was found that these patients were more likely to have a death attributed to CLL than were members of the general population (observed = 7; SMR = 1.44; 95% CI, 0.6–2.8) (Weiss et al. 1995). Furthermore, consistent with expectations of long latency and morbidity periods for CLL mortality, excess CLL mortality was observed almost exclusively in the period ≥25 years after irradiation (in contrast to acute and myeloid leukemia, for which a peak in excess mortality was observed in the first 5 years posttreatment). Under a 25-year exposure lag assumption, a 2-fold excess of CLL mortality was observed (observed = 6; SMR = 1.97; 95% CI, 0.7–4.3) (Weiss et al. 1994).
Damber et al. (1995) examined the incidence of CLL in a cohort of 20,204 Swedish patients who were treated by radiotherapy between 1950 and 1964 for benign diseases of the locomotor system such as ankylosing spondylitis, arthrosis, and spondylosis (average bone marrow dose estimated as 400 mSv). Compared with the British ankylosing spondylitis patients, the radiation doses delivered to these patients were typically an order of magnitude lower, and only small parts of the body were irradiated (Damber et al. 1995). Patients were classified into three groups based on estimated radiation doses (< 0.20, 0.20–0.50, and > 0.50 Gy), and SIRs were calculated under a 0-year exposure lag assumption (there was no evaluation of variation in cancer risk with time since irradiation). There was a slight deficit of CLL among patients who received the lowest radiation doses (observed = 1; SIR = 0.94; 95% CI, 0.6–1.5) and a small excess of CLL among patients in the upper two dose groups (0.20–0.50 Gy: observed = 15; SIR = 1.17; 95% CI, 0.7–1.9; > 0.50 Gy: observed = 16; SIR = 1.18; 95% CI, 0.7–1.9).
Among 12,955 female patients who were treated by radiotherapy for benign gynecologic disorders (median dose to active bone marrow estimated as 1,200 mSv), CLL mortality rates (pooled together with lymphatic leukemia not otherwise specified) were elevated when compared with general population mortality rates (observed = 17; SMR = 1.8; 95% CI, 1.0–2.9) (Inskip et al. 1993). Consistent with expectations of a protracted latency and morbidity period, there was no excess of CLL mortality in the first 10 years of follow-up (observed = 1; SMR = 0.93; 95% CI, 0.0–5.2). In subsequent decades after irradiation, however, there was an excess of CLL mortality among irradiated patients. Under 20- and 30-year exposure lag assumptions, the ratios of observed to expected CLL deaths were 1.64 (observed = 10; 95% CI, 0.8–3.0) and 2.2 (observed = 7; 95% CI, 0.9–4.5), respectively. A comparison was also drawn using an internal referent population (a group of 3,185 patients with treatments other than radiotherapy). Comparisons between irradiated and nonirradiated patients by leukemia subtype produced highly unstable results because of the small number of leukemia cases in the nonirradiated group. The overall rate ratio for CLL comparing irradiated to nonirradiated patients was 1.1 (90% CI, 0.5–3.0); under 20- and 30-year exposure lag assumptions, the rate ratios for CLL comparing irradiated to nonirradiated patients were 1.3 and 2.3, respectively.
Investigations of CLL mortality among women treated by radiotherapy for excessive uterine bleeding (metropathia hemorrhagica) (Darby et al. 1994) and women treated by radiotherapy for infertility or amenorrhea (Ron et al. 1994a) have not reported on the risk of CLL after irradiation because of the small numbers of CLL cases (one and two CLL deaths, respectively) observed in these cohorts.
Radiotherapy for malignant disease.
Studies of cancer after radiotherapy treatment for a previous cancer offer the opportunity to study populations that have received relatively high doses of radiation. However, the radiation doses delivered for cancer therapy tend to be extremely high and localized; the intended effect is killing cells in the irradiated area that effectively prevents cancer induction. Although cell killing is also an issue in radiotherapy for benign diagnoses, in tumor irradiation it represents the original goal of the therapy, and attenuation of the dose–response relation for cancer induction may therefore be accentuated. In addition, the effects of radiation exposure on cancer incidence may differ for a healthy population than for a group of patients who are hospitalized for cancer treatment. Not only are these patients being treated for an existing cancer, but they also many receive chemotherapy in conjunction with radiotherapy, which may influence subsequent cancer incidence. Further, CLL tends to be a chronic disease with a prolonged latency period, and therefore survivorship is important for a diagnosis of CLL; if mortality rates for causes other than CLL differ with respect to radiotherapy, then bias may occur in estimates of radiation–CLL associations.
In a cohort study of second cancers after radiotherapy for invasive cancer of the uterine cervix among 182,040 women (average bone marrow dose was estimated as 7,100 mSv), Boice et al. (1985) examined the observed and expected (O/E) numbers of second cancers. In the first decade after irradiation, there were fewer than expected cases of CLL (observed = 9; O/E = 0.7; 95% CI, 0.3–1.3), whereas under a 20-year exposure lag assumption a small excess of CLL mortality was reported (observed = 3; O/E = 1.25; 95% CI, 0.3–3.7). A case–control study of secondary cancers after radiotherapy for invasive cancer of the uterine cervix was conducted building upon this cohort analysis (Boice et al. 1987). The study included leukemia cases that were diagnosed at least 1 year after diagnosis of cervical cancer, with four controls matched to each case. CLL incidence among patients treated by radiotherapy was compared with CLL incidence among patients treated by other means. No excess of CLL was observed when comparing patients treated by radiotherapy with other patients (RR = 1.03; 90% CI, 0.3–3.9). As indicated by the 90% CIs, the findings of the study are highly imprecise, largely because almost all cervical cancer cases were treated by radio-therapy, the treatment of choice during the study period. All results for analyses of CLL pertain to a 1-year exposure lag assumption with no evaluation of variation in risk with time since irradiation.
In case–control studies of leukemia after radiotherapy for invasive cancer of the uterine corpus (Curtis et al. 1994) and breast cancer (Curtis et al. 1989), leukemia cases were identified between 1935 and 1985 using cancer registry data, and controls were matched by cancer registry, age, year of diagnosis, and race. Among patients treated for cancer of the uterine corpus, the RR for CLL, comparing patients treated by radiotherapy with others, was 0.90 (95% CI, 0.4–1.9). Among patients treated by radiotherapy for breast cancer, the RR for CLL, comparing patients treated by radiotherapy with others, was 1.84 (95% CI, 0.5–6.7). Neither of these studies reported on evaluation of variation in the association between CLL and radiotherapy treatment with time since treatment.
Other studies of populations externally exposed to ionizing radiation.
The epidemiologic literature on cancer mortality among workers in the nuclear industry provides minimal basis for evaluating the effects of external exposure to ionizing radiation on CLL because of low statistical power. In analyses that combined mortality information on 95,673 nuclear industry workers in the United States, United Kingdom, and Canada (average cumulative dose was 40 mSv), a negative association between ionizing radiation exposure and CLL mortality was observed (excess RR per Sv = –0.95; 90% CI, –4.0 to 9.4). However, it stretches the practical limits of epidemiology to expect to directly estimate risk from occupational cohort data in which few cases are observed in the higher (e.g., ≥100 mSv ) dose range; of the 27 CLL cases observed in the international collaborative study of nuclear workers, only 1 case was observed among workers who had ≥100 mSv cumulative dose (Cardis et al. 1995). Furthermore, the reported results pertain to analyses under a 2-year exposure lag assumption. Under a reasonable exposure lag assumption for a slow-progressing disease like CLL (e.g., 20 years), the distribution of CLL cases with respect to cumulative radiation dose would tend to shift farther toward zero. Such considerations underline the limited power of nuclear worker cohort studies to derive radiation risk estimates for CLL mortality.
Studies of patients exposed to ionizing radiation via diagnostic X-ray procedures also provide minimal information about the association between ionizing radiation exposure and CLL incidence. For example, although cancer mortality has been examined among Massachusetts tuberculosis patients who were examined by X-ray fluoroscopy, no case of CLL was observed among these patients (Davis et al. 1989).
Discussion
As ionizing radiation is transmitted through the human body, energy is transferred to the surrounding tissue and can produce biologic damage, including double-strand breaks in chromosomal DNA (United Nations Scientific Committee on the Effects of Atomic Radiation 2000). CLL appears to be similar to other hematologic malignancies whose pathogenesis involves structural changes on the chromosomal level that cause mutational changes on the molecular level, altering important cellular functions, and, ultimately, leading to malignant transformation of a cell (Irons and Stillman 1996). Therefore, at the level of DNA damage, there is no basis for the assumption that the association between ionizing radiation exposure and CLL risk would be zero. Rather, there is strong evidence that the somatic mutations that contribute to the genesis of CLL (in a process that is likely to also involve aberrations in immune function) can be produced by ionizing radiation exposure.
Given the radiobiologic plausibility of radiation-induced CLL, one would expect that the conclusion that CLL is nonradiogenic would be supported by a strong, consistent body of epidemiologic evidence indicating that CLL is an exception to the general principles of radiation carcinogenesis. This is not the case. Rather, there is limited epidemiologic evidence with which to evaluate the relative radiogenicity of CLL. Most studies include small numbers of cases, and few have conducted analyses to adequately account for the prolonged latency and morbidity periods of CLL.
A simple and parsimonious alternative to the hypothesis that CLL is entirely insensitive to ionizing radiation effects is that radiation does influence CLL incidence, but this association is more difficult to identify via epidemiologic methods than the association between ionizing radiation and acute lymphocytic and myeloid forms of leukemia. Acute lymphocytic and myeloid forms of leukemia arise as a consequence of an increased rate of mitosis (due to loss of cellular control over proliferation of transformed cells). Consequently, the number of white blood cells in the bone marrow and/or circulating in the bloodstream of a patient with acute lymphocytic or myeloid leukemia may increase dramatically over a relatively short period of time. In contrast, the fundamental mechanism of accumulation of CLL-clonal cells is an extension of the life span of the transformed lymphocytes due to a failure of apoptosis (Voutsadakis 2000), which leads to a gradual accumulation of circulating CLL cells. Thus, although clinical symptoms such as shortness of breath, weight loss, or fever may slowly develop over time, CLL is often diagnosed during routine physical examination of asymptomatic elderly patients.
This long asymptomatic period (followed by a protracted period of morbidity) has important implications for epidemiologic investigations of radiation–CLL associations. It means that case ascertainment may be poor and partly obscured by competing causes of death. Analytically, in order for an investigation of radiation-induced CLL mortality to detect an effect, the study must encompass a period of follow-up that is long enough to allow for an extended induction, latency, and morbidity period after exposure occurs. Studies with short duration of follow-up (e.g., one or two decades) could observe no effect of ionizing radiation on CLL simply because the time from exposure to end of follow-up is less than the minimal induction, latency, and morbidity period for radiation-induced CLL mortality. Furthermore, the ability to detect an association, if one exists, requires relating CLL incidence or mortality to exposures in the distant past using appropriate methods of survival analysis. If the effect of radiation on CLL risk only becomes apparent many years (or a few decades) after irradiation, then analyses conducted under relatively short exposure lag assumptions may suffer serious exposure misclassification problems.
The Revised European American Lymphoma classification scheme (Harris et al. 1994) reflects a recent attempt to use immunophenotypic and genetic characteristics in order to classify lymphomas into subgroups that share common clinical and pathologic characteristics. To the extent that refinements in disease classification improve the ability to identify cancer cases that are similar in terms of etiology and natural history (e.g., durations of latency and morbidity periods), these efforts should strengthen epidemiologic investigations. However, constructing nosologic schemes primarily with reference to considerations about disease management and prognosis rather than etiology, and classifying diseases into increasingly refined categories, poses potential problems for epidemiologic research. Evidence of the hazardous effects of an exposure may be obscured by classification of exposure-induced cases into different groups based upon clinical characteristics that are not etiologically relevant. Further, as the classification of diseases becomes refined, it becomes increasingly difficult to conduct statistical analyses with adequate power to address questions about the effects of an exposure on disease incidence. Given the ability to construct ever more refined disease categorizations, it may be increasingly important to identify mechanistic and etiologic grounds for aggregation of subtypes of diseases for epidemiologic research purposes.
Conclusion
The assumption, under existing federal regulations, that the risk of CLL after exposure to ionizing radiation is zero is unlikely to be correct. In order to be correct, CLL must be an exception to general principles of radiation carcinogenesis. In this review we found no support for that conclusion. Current understanding of the pathogenesis of CLL describes a process in which there is an important role played by mutational events that can be produced by exposure to ionizing radiation. The epidemiologic evidence of radiation–CLL associations is weak; however, given the limitations of the reviewed studies, these findings do not offer a persuasive basis for concluding that CLL is an exception to general principles of radiation carcinogenesis. In addition, there is a problem of logical inconsistency if the government continues to assert that CLL is nonradiogenic whereas SLL is radiogenic. Contemporary classification schemes hold that B-cell CLL and SLL are analogous diseases and should be considered as a single disease entity. It is possible that the magnitude of the association between ionizing radiation and CLL is smaller than that for other lymphomas and leukemias; evaluation of the magnitude of this association is difficult given the limitations of existing epidemiologic data. Nonetheless, it is likely that CLL incidence, like other forms of cancer, will be increased by exposure to ionizing radiation.
Table 1 Epidemiologic studies of populations exposed to ionizing radiation and risk of CLL: numbers of cases and summary of study findings by type of exposure.
Type of exposure/study Reference CLL cases Radiation risk
Atomic bomb
Japanese survivors Preston et al. 1994 4 NR
Radiotherapy
Ankylosing spondylitis Weiss et al. 1994, 1995 7 +a
Benign disorders of the locomotor system Damber et al. 1995 17 +b
Benign gynecologic disorders Inskip et al. 1993 17 +a
Cervical cancer Boice et al. 1985, 1987 52 −
Uterine cancer Curtis et al. 1994 54 −
Breast cancer Curtis et al. 1989 10 +
Occupation
Nuclear industry Cardis et al. 1995 27 −
Abbreviations: –, no evidence of radiation risk; +, evidence for radiation risk; NR, results not reported.
a For the period ≥25 years after irradiation.
b Among those receiving ≥0.20 Gy.
==== Refs
References
Boice JD Jr Blettner M Kleinerman RA Stovall M Moloney WC Engholm G 1987 Radiation dose and leukemia risk in patients treated for cancer of the cervix J Natl Cancer Inst 79 1295 1311 3480381
Boice JD Jr Day NE Andersen A Brinton LA Brown R Choi NW 1985 Second cancers following radiation treatment for cervical cancer. An international collaboration among cancer registries J Natl Cancer Inst 74 955 975 3858584
Cardis E Gilbert E Carpenter L Howe G Kato I Fix J 1995. Combined Analyses of Cancer Mortality Among Nuclear Industry Workers in Canada, the United Kingdom and the United States of America. IARC Technical Report No. 25. Lyon, France:International Agency for Research on Cancer.
Committee for the Compilation of Materials on Damage Caused by the Atomic Bombs in Hiroshima and Nagasaki 1981. Hirosima and Nagasaki: The Physical, Medical, and Social Effects of the Atomic Bombings. Tokyo:Iwanami Shoten.
Court-Brown W Doll R 1957. Leukemia and Aplastic Anaemia in Patients Irradiated for Anklyosing Spondylitis. Report no. 295. London:Her Majesty’s Stationery Office.
Court-Brown W Doll R 1965 Mortality from cancer and other causes after radiotherapy for ankylosing spondylitis Br Med J 2 1327 1332 5848660
Crespo M Bosch F Villamor N Bellosillo B Colomer D Rozman M 2003 ZAP-70 expression as a surrogate for immunoglobulin-variable-region mutations in chronic lymphocytic leukemia N Engl J Med 348 1764 1775 12724482
Curtis RE Boice JD Jr Stovall M Bernstein L Holowaty E Karjalainen S 1994 Relationship of leukemia risk to radiation dose following cancer of the uterine corpus J Natl Cancer Inst 86 1315 1324 8064889
Curtis RE Boice JD Jr Stovall M Flannery JT Moloney WC 1989 Leukemia risk following radiotherapy for breast cancer J Clin Oncol 7 21 29 2909667
Damber L Larsson LG Johansson L Norin T 1995 A cohort study with regard to the risk of haematological malignancies in patients treated with X-rays for benign lesions in the locomotor system. I. Epidemiological analyses Acta Oncol 34 713 719 7576736
Darby SC Doll R Gill SK Smith PG 1987 Long term mortality after a single treatment course with X-rays in patients treated for ankylosing spondylitis Br J Cancer 55 179 190 3814487
Darby SC Reeves G Key T Doll R Stovall M 1994 Mortality in a cohort of women given X-ray therapy for metropathia haemorrhagica Int J Cancer 56 793 801 8119768
Davis FG Boice JD Jr Hrubec Z Monson RR 1989 Cancer mortality in a radiation-exposed cohort of Massachusetts tuberculosis patients Cancer Res 49 6130 6136 2790825
Department of Health and Human Services 2002 42 CFR Parts 81 and 82. Guidelines for Determining the Probability of Causation and Methods for Radiation Dose Reconstruction Under the Employees Occupational Illness Compensation Program Act of 2000; Final Rules Fed Reg 67 22295 22314
Dewald GW Brockman SR Paternoster SF Bone ND O’Fallon JR Allmer C 2003 Chromosome anomalies detected by interphase fluorescence in situ hybridization: correlation with significant biological features of B-cell chronic lymphocytic leukaemia Br J Haematol 121 287 295 12694251
Dunst J Neubauer S Becker A Gebhart E 1998 Chromosomal in-vitro radiosensitivity of lymphocytes in radiotherapy patients and AT-homozygotes Strahlenther Onkol 174 510 516 9810318
Finch SC Hoshino T Itoga T Ichimaru M Ingram RH Jr 1969 Chronic lymphocytic leukemia in Hiroshima and Nagasaki, Japan Blood 33 79 86 5818236
Finch SC Linet MS 1992 Chronic leukaemias Baillieres Clin Haematol 5 27 56 1350742
Folley J Borges W Yamawaki T 1952 Incidence of leukemia in survivors of the atomic bomb Am J Med 13 311 321 12985588
Groves FD Linet MS Devesa SS 1995 Patterns of occurrence of the leukaemias Eur J Cancer 31A 941 949 7646927
Harris NL Jaffe ES Diebold J Flandrin G Muller-Hermelink HK Vardiman J 1999 World Health Organization classification of neoplastic diseases of the hematopoietic and lymphoid tissues: report of the Clinical Advisory Committee meeting—Airlie House, Virginia, November 1997 J Clin Oncol 17 3835 3849 10577857
Harris NL Jaffe ES Diebold J Flandrin G Muller-Hermelink HK Vardiman J 2000a Lymphoma classification—from controversy to consensus: the R.E.A.L. and WHO Classification of lymphoid neoplasms Ann Oncol 11 suppl 1 3 10 10707771
Harris NL Jaffe ES Diebold J Flandrin G Muller-Hermelink HK Vardiman J 2000b The World Health Organization classification of hematological malignancies report of the Clinical Advisory Committee meeting, Airlie House, Virginia, November 1997 Mod Pathol 13 193 207 10697278
Harris NL Jaffe ES Stein H Banks PM Chan JKC Cleary ML 1994 A revised European-American classification of lymphoid neoplasms: a proposal from the International Lymphoma Study Group Blood 84 1361 8068936
Humphreys MW Nevin NC Wooldridge MA 1989 Cytogenetic investigations in a family with ataxia telangiectasia Hum Genet 83 79 82 2767681
Inskip PD Kleinerman RA Stovall M Cookfair DL Hadjimichael O Moloney WC 1993 Leukemia, lymphoma, and multiple myeloma after pelvic radiotherapy for benign disease Radiat Res 135 108 124 8327655
Irons RD Stillman WS 1996 The process of leukemogenesis Environ Health Perspect 104 suppl 6 1239 1246 9118899
Ishimaru T Hoshino T Ichimaru M Okada H Tomiyasu T Tsuchimoto T 1969. Leukemia in Atomic Bomb Survivors: Hiroshima and Nagasaki. TR-25-69. Hiroshima, Japan:Atomic Bomb Casualty Commission.
Jones LA Scott D Cowan R Roberts SA 1995 Abnormal radiosensitivity of lymphocytes from breast cancer patients with excessive normal tissue damage after radiotherapy: chromosome aberrations after low dose-rate irradiation Int J Radiat Biol 67 519 528 7775827
Kyasa MJ Hazlett L Parrish RS Schichman SA Zent CS 2004 Veterans with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) have a markedly increased rate of second malignancy, which is the most common cause of death Leuk Lymphoma 45 507 513 15160912
Magrath I 1992 Molecular basis of lymphomagenesis Cancer Res 52 5529s 5540s 1394168
National Research Council, Committee on the Biological Effects of Ionizing Radiation (BEIR V) 1990. Health Effects of Exposure to Low Levels of Ionizing Radiation (BEIR V). Washington, DC:National Academy Press.
Parshad R Sanford KK Jones GM Tarone RE 1985 G2 chromosomal radiosensitivity of ataxia-telangiectasia heterozygotes Cancer Genet Cytogenet 14 163 168 3965121
Preston DL Kusumi S Tomonaga M Izumi S Ron E Kuramoto A 1994 Cancer incidence in atomic bomb survivors. Part III. Leukemia, lymphoma and multiple myeloma, 1950–1987 Radiat Res 137 S68 S97 8127953
Ries LAG Eisner MP Kosary CL Hankey BF Miller BA Clegg L eds. 2003. SEER Cancer Statistics Review, 1975–2000. Bethesda, MD:National Cancer Institute. Available: http://seer.cancer.gov/csr/1975_2000/ [accessed 18 November 2004].
Ron E Boice JD Jr Hamburger S Stovall M 1994a Mortality following radiation treatment for infertility of hormonal origin or amenorrhoea Int J Epidemiol 23 1165 1173 7721518
Ron E Carter R Jablon S Mabuchi K 1994b Agreement between death certificate and autopsy diagnoses among atomic bomb survivors Epidemiology 5 48 56 8117782
Rothman K Boice JD 1979. Epidemiologic Analyses with a Programmable Calculator. NIH Publication No. 79-1649. Washington, DC:U.S. Government Printing Office.
Rozman C Montserrat E 1995 Chronic lymphocytic leukemia N Engl J Med 333 1052 1057 7675049
Stevenson F Sahota S Zhu D Ottensmeier C Chapman C Oscier D 1998 Insight into the origin and clonal history of B-cell tumors as revealed by analysis of immunoglobulin variable region genes Immunol Rev 162 247 259 9602369
Stilgenbauer S Bullinger L Lichter P Dohner H 2002 Genetics of chronic lymphocytic leukemia: genomic aberrations and V(H) gene mutation status in pathogenesis and clinical course Leukemia 16 993 1007 12040431
Stilgenbauer S Lichter P Dohner H 2000 Genetic features of B-cell chronic lymphocytic leukemia Rev Clin Exp Hematol 4 48 72 11486330
Tomonaga M Matsuo T Carter RL Bennett JM Kuriyama K Imanaka F 1991. Differential effects of atomic bomb irradiation in inducing major leukemia types: analyses of open-city cases including the life span study cohort based upon updated diagnostic systems and the dosimetry system 1986 (DS86). TR 9-91. Hiroshima, Japan:Radiation Effects Research Foundation.
United Nations Scientific Committee on the Effects of Atomic Radiation 2000. Sources and Effects of Ionizing Radiation. Vol. II: Effects. New York:United Nations.
Valentine W 1951. Present Status of the Study of the Incidence of Leukemia Among Individuals Surviving Exposure to the Atomic Bomb in Hiroshima and Nagasaki. Hiroshima, Japan: Atomic Bomb Casualty Commission.
Voutsadakis IA 2000 Apoptosis and the pathogenesis of lymphoma Acta Oncol 39 151 156 10859004
Weiss HA Darby SC Doll R 1994 Cancer mortality following X-ray treatment for ankylosing spondylitis Int J Cancer 59 327 338 7927937
Weiss HA Darby SC Fearn T Doll R 1995 Leukemia mortality after X-ray treatment for ankylosing spondylitis Radiat Res 142 1 11 7899552
|
15626639
|
PMC1253701
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2005 Jan 21; 113(1):1-5
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7433
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7259ehp0113-00000615626640ResearchArticlesHuman Colon Microbiota Transform Polycyclic Aromatic Hydrocarbons to Estrogenic Metabolites Van de Wiele Tom 1Vanhaecke Lynn 1Boeckaert Charlotte 1Peru Kerry 2Headley John 2Verstraete Willy 1Siciliano Steven 31Laboratory of Microbial Ecology and Technology (LabMET), Ghent University, Gent, Belgium2National Water Research Institute, Environment Canada, Saskatoon, Saskatchewan, Canada3Department of Soil Research, University of Saskatchewan, Saskatoon, Saskatchewan, CanadaAddress correspondence to W. Verstraete, Laboratory of Microbial Ecology and Technology, Ghent University, Coupure Links, 653, B-9000 Gent, Belgium. Telephone: 32-9-264-59-76. Fax: 32-9-264-62-48. E-mail:
[email protected] Material is available online (http://ehp.niehs.nih.gov/members/2004/7259/supplemental.pdf).
We thank S. Dobbelaere, N. Boon, S. Seurinck, K. Verthé, and K. Rabaey for critically reading the manuscript.
This research was supported by the Fund for Scientific Research.
The authors declare they have no competing financial interests.
1 2005 22 9 2004 113 1 6 10 17 5 2004 22 9 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Ingestion is an important exposure route for polycyclic aromatic hydrocarbons (PAHs) to enter the human body. Although the formation of hazardous PAH metabolites by human biotransformation enzymes is well documented, nothing is known about the PAH transformation potency of human intestinal microbiota. Using a gastrointestinal simulator, we show that human intestinal microbiota can also bioactivate PAHs, more in particular to estrogenic metabolites. PAH compounds are not estrogenic, and indeed, stomach and small intestine digestions of 62.5 nmol naphthalene, phenanthrene, pyrene, and benzo(a)pyrene showed no estrogenic effects in the human estrogen receptor bioassay. In contrast, colon digests of these PAH compounds displayed estrogenicity, equivalent to 0.31, 2.14, 2.70, and 1.48 nmol 17α-ethynylestradiol (EE2), respectively. Inactivating the colon microbiota eliminated these estrogenic effects. Liquid chromatography–mass spectrometry analysis confirmed the microbial PAH transformation by the detection of PAH metabolites 1-hydroxypyrene and 7-hydroxybenzo(a)pyrene in colon digests of pyrene and benzo(a)pyrene. Furthermore, we show that colon digests of a PAH-contaminated soil (simulated ingestion dose of 5 g/day) displayed estrogenic activity equivalent to 0.58 nmol EE2, whereas stomach or small intestine digests did not. Although the matrix in which PAHs are ingested may result in lower exposure concentrations in the gut, our results imply that the PAH bioactivation potency of colon microbiota is not eliminated by the presence of soil. Moreover, because PAH toxicity is also linked to estrogenicity of the compounds, the PAH bioactivation potency of colon microbiota suggests that current risk assessment may underestimate the risk from ingested PAHs.
aryl hydrocarbon receptorestrogen receptororal exposuresimulator of the human intestinal microbial ecosystem (SHIME)
==== Body
Polycyclic aromatic hydrocarbons (PAHs) are high-priority environmental contaminants because of their toxic, carcinogenic, and putative estrogenic or antiestrogenic properties in the human body. Human exposure to high-molecular-weight PAHs mainly occurs through oral uptake of charcoal-broiled, grilled, and smoked meats (van Maanen et al. 1994) and through ingestion of soil or poorly cleaned vegetables, resulting in exposed doses about an order of magnitude higher than exposure by inhalation (Heisterkamp and van Veen 1997). The hazardous effects of ingested PAHs come from the PAH fraction released from the nutrients, soil, or associated organic matter in the intestinal lumen and that, upon intestinal absorption, reaches the intestine enterocytes and liver hepatocytes. In these cells, PAHs may act as ligands to the human aryl hydrocarbon (Ah) receptor, which plays a central role in the toxic response of specific aromatic hydrocarbons by the regulation of typical human biotransformation enzymes (reviewed by Hankinson 1995).
The risk from orally ingested PAHs is currently thought to be reduced when co-ingested soil or fibers decrease the intestinal PAH absorption and hence bioavailability (De Kok and van Maanen 2000). Most ingested PAHs pass harmlessly through the gastrointestinal (GI) tract without being transformed by human enzymes to hazardous metabolites. However, this assumes that no microbial bio-transformation of PAHs occurs. The human GI tract harbors an incredibly diverse microbial community, which typically performs fermentative processes but which is also capable of transforming xenobiotic compounds (Aura et al. 2002; Ilett et al. 1990; Macdonald et al. 1983). Hence, if microbial PAH bio-transformation in the human colon is possible, the susceptibility of the colon epithelium to bioactive PAH metabolites may increase the health risks that are associated with non-absorbed PAHs that reach the colon. To date, no information is available on the PAH bio-activation potency from human colon microbiota. To evaluate this, in this study we investigated the estrogenicity of PAHs because several PAH metabolites structurally resemble steroidal hormones that bind the human estrogen receptor (ER) (Ariese et al. 2001), which could thus lead to estrogenic or anti-estrogenic activity in vivo.
We opted for an in vitro approach to specifically look for microbial biotransformations and thus avoid possible interference from colon epithelium enzymes that would be present in an in vivo approach. Pure PAH compounds and a PAH-contaminated urban soil were incubated in the stomach, small intestine, and colon suspensions from a simulator of the human GI tract. Given the aromaticity of PAHs, we used a modified Ah receptor yeast assay (Miller 1997) to investigate whether the PAHs in the different digests could activate the human Ah receptor and subsequently induce signal transduction. We also investigated the estrogenicity of the PAH incubated digests by monitoring activation of the human ER in a modified ER yeast assay (Routledge and Sumpter 1996). In addition, we applied a newly optimized liquid chromatography–mass spectrometry (LC-MS) protocol to detect whether PAH metabolites were formed during incubation.
Materials and Methods
Chemicals.
PAH parent compounds naphthalene, phenanthrene, pyrene, and benzo(a)pyrene (reagent grade) were obtained from Sigma-Aldrich (Bornem, Belgium). To avoid solubility problems in the incubation tests, PAHs were first dissolved in ethanol before digestion. All stock solutions were prepared in amber glass bottles and stored in the dark at 4°C. Hydroxy-PAH metabolites 1-OH naphthalene, 9-OH phenanthrene, 1-OH pyrene, and 7-OH benzo(a)pyrene were reagent grade and also obtained from Sigma-Aldrich.
Incubations.
PAHs and soils were incubated in batches by sampling GI suspensions from a simulator of the human intestinal microbial ecosystem (SHIME). This dynamic model of the GI tract consists of five compartments representing the stomach, small intestine, and colon ascendens, transversum, and descendens (Figure 1). The colon suspension contains in vitro cultured microbiota that were isolated from human feces and are representative of the in vivo colon microbial ecology after a growth stabilization period in the different colon compartments (Molly et al. 1993). A typical stomach digestion consists of an incubation of PAHs or PAH-contaminated soil samples for 3 hr at pH 1.5 at 37°C. A small intestine digestion consists of an incubation for 5 hr at pH 7 at 37°C in the presence of bile salts (0.2 mmol/L) and pancreatic enzymes supplemented as pancreatic powder of porcine origin (0.4 g/L). A colon digestion consists of an incubation with colon microbiota for 48 hr at 37°C, withdrawn from the colon vessels of the SHIME reactor. Some samples were incubated with inactive colon microbiota. For this, colon microbiota were autoclaved for 30 min (121°C, 1 bar overpressure). Incubation of PAH standard compounds in stomach, small intestine, and colon digests occurred at a concentration of 20 μmol/L. This concentration is normally not encountered in the GI tract but gave us more possibilities to study microbial PAH metabolism in depth. GI digestion experiments on soil samples were performed as previously described (Van de Wiele et al. 2004b) to simulate a hypothetical soil ingestion of 5 g/day by pica-afflicted children (stomach, 40 mL; small intestine, 60 mL; colon, 100 mL). To avoid photocatalytic effects, all digestions were performed in amber flasks. After the respective incubations, samples were centrifuged at 3,000g for 10 min to remove most of the particulates and biomass. The supernatants were then stored at −20°C before analysis.
Sample treatment.
PAH parent components and PAH metabolites were extracted from the digests by performing a liquid/liquid extraction in which the digest and ethyl acetate were mixed in a 1:1 ratio. The ethyl acetate fraction was then put in a rotary evaporator to remove most of the solvent. The remainder of the solvent was removed under a gentle stream of nitrogen gas and finally replaced by dimethyl sulfoxide, which is suitable for use in bioassay tests. For chemical analysis of the samples using LC-MS, sample aliquots were subjected to solid-phase extraction using PrepSep C18 (250 mg; Fisher Scientific, Edmonton, Alberta, Canada). Hydroxy-PAHs were eluted with methanol.
PAH conjugate analysis.
To check whether conjugated PAH metabolites were formed in the different digests, samples were also incubated in the presence of β-glucuronidase and aryl sulfatase, both obtained from Sigma-Aldrich. After the PAH parent compounds had been incubated in SHIME suspension, a 1 mL aliquot of these samples was diluted in 1 mL 0.1 M acetate buffer, and the pH was adjusted to 5 with sodium hydroxide. A volume of 400 μL β-glucuronidase (100 U/mL) and 250 μL aryl sulfatase (60 U/mL) was added, and the mixture was incubated for 6 hr at 37°C to hydrolyze the PAH conjugates.
Bioassays.
For the bioassays, we used a modified protocol from De Boever et al. (2001) that was based on the protocol developed by Routledge and Sumpter (1996) for the yeast estrogen bioassay and Miller (1997) for the yeast Ah bioassay. Briefly, these researchers transformed Saccharomyces cerevisiae with the human Ah receptor gene and the human ER-α gene, together with expression plasmids containing responsive elements and the lacZ reporter gene (encoding the enzyme β-galactosidase). The expression of β-galactosidase is triggered by test chemicals, which upon binding to the respective receptors induce the conformational change necessary for binding of the receptor/ligand dimer to the responsive elements. This β-galactosidase activity is quantified at 540 nm by the conversion of the chromogenic substance chlorophenol red–β-d-galactopyranoside into chlorophenol red. The bioassay response is expressed as the absorbance at 540 nm divided by the optical density at 630 nm [(A540/A630)net]. Positive signals in the Ah receptor assay were typically expressed as percentage equivalence to 200 nM benzo(a)pyrene, which arbitrarily corresponded to a bioassay response of 100%. Similarly, estrogenic activity of the samples was expressed as percentage equivalence to 6.96 nM 17α-ethynyl estradiol (EE2), which elicited a 100% response in the ER bioassay (De Boever et al. 2001). To make sure that background signals from GI suspensions of soil or food matrices did not interfere with the detection of estrogenic signals in the bioassays, corrections were made in a set of negative control experiments by subtracting the response of a PAH-containing digest from that from a blank digest without PAHs (see Supplemental Material available online at http://ehp.niehs.nih.gov/docs/2004/7259/supplemental.pdf). The bio-assays were performed in 96-well plates in which 10 μL of the test compounds was tested and incubated with 240 μL of the genetically modified yeast (optical density, 0.25 at 610 nm). Serial dilutions of the test compounds were made in dimethyl sulfoxide, which allowed generation of dose–response curves for doses (ordinate) versus activity (abscissa). The data were fitted by a four-parametric logistic model using the Marquardt-Levenberg algorithm (Sigmaplot 4.0; SPSS Inc., Chicago, IL, USA) (De Boever et al. 2001).
PAH analysis.
Sample treatment for and determination of PAHs were performed by the Environmental Research Centre (Erembodegem, Belgium). Briefly, PAHs from pellets were extracted by a 1:1 acetone:hexane mixture using an ASE 200 accelerated solvent extractor (Dionex, Sunnyvale, CA, USA). PAHs from supernatants were extracted with dichloromethane. Analysis of the PAH content in the extracts was performed according to a standardized method [U.S. Environmental Protection Agency (EPA) method 8270 (U.S. EPA 1996)] by gas chromatography coupled with mass spectrometry (GC-MS). We used a quadrupole mass spectrometer (Trace-MS; Fisons/Thermoquest, Antwerp, Belgium). The detection limit for the different PAH components was 0.2 μg/L, and the quantification limit was 0.4 μg/L. The extraction efficiency of the sample preparation step before PAH analysis was between 80 and 110%, as determined with reference soil CRM535 (Environmental Research Center, Erembodegem, Belgium).
LC-MS analysis.
We performed LC-MS analysis of the samples for hydroxy-PAHs as previously described (Van de Wiele et al. (2004a). The identity of hydroxy-PAH metabolites in the samples was confirmed by using synthetic standards of these metabolites and comparing the HPLC profiles from the colon digests with those from the standards. Briefly, all samples for LC-MS analysis were subjected to solid-phase extraction using PrepSep C18 columns (250 mg). Sample volumes of 5 mL were loaded on the columns and washed with 10 mL Milli-Q water; the target analytes were then eluted with 10 mL methanol. Aliquots (1 mL) were subsampled and stored in amber vials at 4°C before LC-MS analysis. HPLC analysis was performed using a Waters 2695 separation module (Waters, Milford, MA, USA). The selected column was a 2.1 mm × 100 mm, 3.5 μm particle size, Waters XTerra MS C18 column, which was kept at a constant temperature of 26°C. The binary eluent system consisted of methanol:water 90:10 (vol/vol; eluent A) and methanol:water 10:90 (vol/vol; eluent B). MS analysis was performed with a Quattro Ultima Mass spectrometer (Micromass Technologies, Manchester, UK) that was equipped with an electrospray interface operating in the negative ion mode. Instrumental control and data acquisition were performed with MassLynx software version 3.5 (MicroMass Ltd., Manchester, UK). The electrospray ionization source was operated at 90°C, a desolvation temperature of 200°C, a cone voltage of 61 V, and a capillary voltage of 2.74 kV. Nitrogen gas served as the cone gas (flow rate of 159 L/hr), desolvation gas (490 L/hr), and nebulizer gas (set to maximum). The detector multiplier voltage was set to 650 V. We used selected ion monitoring for quantitative analysis monitoring the (M – H)− of m/z for the hydroxy-PAHs.
Results and Discussion
Because of their moderate-to-high degree of aromaticity, we expected pure solutions of naphthalene, phenanthrene, pyrene, and benzo(a)pyrene to test positive in the Ah bioassay. Naphthalene (200 nM) displayed 0.4% benzo(a)pyrene equivalence, whereas 200 nM phenanthrene and 200 nM pyrene displayed 15.1 and 48.2% benzo(a)pyrene equivalence, respectively. PAH compounds are not estrogenic, and indeed, up to 16 μM of the four pure PAHs did not induce an estrogenic response in the estrogen bioassay. Similarly, separate stomach and small intestine digests of the four PAHs did not show a significant estrogen response (Figure 2). In contrast, PAHs from colon digests became estrogenic. Conversion of the percent EE2 equivalence values, shown in Figure 2, to equivalent EE2 concentrations is as follows: for colon digests of 62.5 nM pyrene, 2.70 nM EE2 equivalence; for phenanthrene, 2.14 nM EE2 equivalence; for benzo(a)pyrene, 1.48 nM EE2 equivalence; and for naphthalene, 0.31 nM EE2 equivalence. This PAH bio-activation was only evident in colon digestion. This shows the selectivity of colon digestion toward an increase in estrogenicity, whereas no increased Ah response was detected, compared with stomach or small intestine digests. To make sure that the observed effects were not coming from the matrix background of the colon interacting with PAHs, we incubated PAHs in a heat-inactivated colon suspension. The removal of microbial activity markedly reduced the increase in estrogenic activity (Figure 2). This finding indicates that the risk for PAH bioactivation along the GI tract is not exclusively associated with human bio-transformation enzymes from the enterocytes in the small intestine epithelium and colonocytes in the large intestine epithelium (Autrup et al. 1978; De Kok and van Maanen 2000; Doherty and Charman 2002), but that colon microbiota can also bioactivate PAHs.
We then evaluated the significance of this process using lower, more realistic concentrations obtained from soil from a former urban playground contaminated with 49 ± 1.5 mg PAHs per kilogram soil (dry weight) by years of atmospheric deposition. Pica-afflicted children form the largest risk group for soil ingestion because of their unusual hand–mouth behavior and low body weight. Hence, we simulated the GI tract of a pica child, hypothetically ingesting 5 g soil/day. GC-MS analysis previously showed that the released PAH fraction from the soil matrix was highest in the stomach digest (18 ± 5.3 μg/L), followed by the small intestine digest (3 ± 1.1 μg/L) and the colon digest (2 ± 0.3 μg/L) (Van de Wiele et al. 2004b). This corresponded to a maximal Ah bioassay response for the stomach digest of 41 ± 2.9% benzo(a)pyrene equivalence; the small intestine, 27 ± 1.4%; and the colon, 22 ± 2.6% (Figure 3). Based on the role of the human Ah receptor in the toxicity of specific aromatic hydrocarbons, these findings would normally indicate that the colon digest represents the lowest risk for PAH bioactivation. Surprisingly, the trend in estrogenic activity was the inverse of observed PAH release or Ah bioassay response. Similar to the estrogen bioassay results on pure PAHs, there was negligible induction of estrogenic activity in the stomach (0.6%) and small intestine (2.0%) digestion (Figure 4). However, an average value of 20.1 ± 0.84% EE2 equivalence was observed in a colon digestion of the contaminated soil (Figure 4). We infer that the PAH bioactivation potency from colon microbiota also occurs at lower and relevant concentrations for human exposure and that the presence of soil does not eliminate this potency.
Soil organic matter and nutritional fibers are known to lower the fraction of a contaminant that can be absorbed by the intestine (O’Neill et al. 1991; Oomen et al. 2000; van Schooten et al. 1990). This would theoretically lower the risk from ingested contaminants because bioactivation by human biotransformation enzymes will be reduced because of a lower bioavailability. To test this hypothesis, we compared the estrogenicity from colon-incubated PAHs in the presence and absence of soil by calculating the bioactivation potency of the digests as estrogenicity/aromaticity. We divided—at equimolar concentrations—the percent EE2 equivalence of the different digests by their respective percent benzo(a)pyrene equivalence. At equimolar concentrations of 8.03 nmol PAH/L, this ratio was 0.93 for naphthalene, 2.16 for phenanthrene, 0.98 for pyrene, and 0.12 for benzo(a)pyrene, whereas the colon digest of the PAH-contaminated soil gave a ratio of 0.88, the same order of magnitude as the ratios for pure PAH compounds and one order of magnitude higher than the ratios for the stomach soil digest (0.016) or small intestine soil digest (0.077). These findings provide further evidence that the presence of a soil matrix does not eliminate the PAH bioactivation by colon micro-biota and that the estrogenic potency of soil-derived PAHs does not significantly decrease if compared with pure PAHs.
PAH metabolites that typically have estrogenic properties are hydroxylated derivatives because of their structural similarity to natural estrogens (Fertuck et al. 2001; Hirose et al. 2001). Hence, in the next step of the research, we screened with LC-MS for the presence of hydroxy-PAHs by analyzing the respective colon digests of 20 μmol/L pure PAH compounds. The identity of PAH metabolites was confirmed by comparing the HPLC profiles and MS spectra of the colon digests with those from chromatographic synthetic standards of several hydroxy-PAHs. The developed protocol had reasonably low detection limits for 1-OH naphthalene, 9-OH phenanthrene, 1-OH pyrene, and 7-OH benzo(a)pyrene (Table 1) (Van de Wiele et al. 2004a). No hydroxy-PAHs were detected upon stomach or small intestine incubations. From all colon digests, only the pyrene digest tested positive for a hydroxy-PAH metabolite, with 1-OH pyrene at a concentration of 2.5 μg/L (Table 1). Glucuronidated or sulfated PAH conjugates are also typical bio-transformation products from eukaryotic organisms (Cajthaml et al. 2002). Because the concentration of fungi and yeasts in the colon suspension amounted to 4.3 ± 0.6 log colony forming units (CFU)/mL, we tested whether PAH conjugates were present in colon digests of pure PAH compounds. Glucuronidase and arylsulfatase typically cleave off glucuronic acid or sulfate groups from conjugated PAHs, regenerating the hydroxy-PAH metabolites (Cajthaml et al. 2002). After incubating the extracts of the colon digests in the presence of glucuronidase (100 U/mL) and arylsulfatase (60 U/mL) for 6 hr at 37°C, we found higher concentrations of 1-OH pyrene (4.4 μg/L) and a new metabolite, 7-OH benzo(a)pyrene (1.9 μg/L). No hydroxy-PAHs were retrieved from inactivated colon samples. Although other hydroxy-PAHs may have formed than those tested during LC-MS analysis, these analytical data show that PAH bioactivation by colon microbiota may result from hydroxy-PAH metabolites.
The formation of hydroxy-PAH metabolites and especially the increased estrogenicity by human colon microbiota bring up two questions: are the observed transformations plausible for the in vivo human GI tract, and to what extent can bioactive PAH metabolites contribute to the total risk from oral PAH exposure? To answer the first question, literature shows that resident gut microbiota may influence xenobiotic metabolism from the intestinal epithelium (Hooper et al. 2001). Additionally, microbial glucuronidase activity in the intestine sometimes cleaves off glucuronic acid groups from excreted human conjugated metabolites, thus regenerating the more bioactive hydroxylated intermediates (Aura et al. 2002). These reports describe indirect effects of intestinal microbiota toward xenobiotic metabolism. However, our findings indicate a direct metabolism effect of human colon microbiota toward PAH parent compounds, because the in vitro approach used in the present study eliminated possible interferences by intestinal epithelium enzymes. The observed biotransformation and bioactivation reactions originate from a microbial community that resembles that of the in vivo intestinal lumen both in composition and in metabolic activity. Rather than containing the less active microbiota from fecal matter, the microbial community from the used in vitro method is more representative of the different parts of the human colon (Molly et al. 1993).
As suggested by the LC-MS results, the colon microbiota formed hydroxy-PAH metabolites, which may seem unlikely because this oxidative step would occur in an anaerobic environment, as shown by redox potential values from the colon suspension, which varied between −180 mV and −230 mV. These values are well within the range of −145 mV to −250 mV reported for the colon in vivo (Bowler et al. 2001; Chourasia and Jain 2003). Yet, oxidative reactions by intestinal bacteria from humans, mice, and rats have been described for the conversion of 2-amino-3-methylimidazo[4,5-f ]quinoline to its reportedly mutagenic 7-keto derivative (Rumney et al. 1993). Additionally, Enterococcus faecalis even performs aromatic hydroxylation reactions in the intestine in vivo (Huycke and Moore 2002). It is therefore not unlikely that intestinal microbiota may hydroxylate PAHs, also given the fact that anaerobic PAH hydroxylation has been reported by microorganisms, albeit in sediments (Karthikeyan and Bhandari 2001). These studies on oxidative reactions by intestinal microbiota and anaerobic PAH biotransformations may thus support our findings, which need further study to identify which microorganisms bioactivate PAHs.
To answer the second question concerning the contribution of the observed effects to the total risk from PAH ingestion, further research is warranted. Yet, microbial PAH bioactivation to estrogenic metabolites may constitute an increased health risk when the human body is orally exposed to contaminated soils. Human colon epithelium is 20% more permeable to 17β-estradiol than is the human small intestine epithelium (van der Bijl and van Eyk 2003) and also has a higher permeability to hydrophobic compounds in general (Ungell et al. 1998). PAH metabolites with structures resembling steroidal hormones may thus exhibit weak estrogenic or antiestrogenic activity in vivo (Ariese et al. 2001). Because PAHs that reach the colon will be biotransformed by colon microbiota, we conclude that, in the in vivo situation, the colonic epithelium—which has ERs—may be subjected to hazardous effects from microbial PAH metabolites. The equivalent EE2 response of 20% for the colon-incubated environmental sample (Figure 4) indicates that the observed activation of the human ER is significant. Still, it must be kept in mind that a positive response in ER-reporter gene assays such as that from the present study does not necessarily predict endogenous transcription (Gozgit et al. 2004). Gozgit et al. (2004) noted that several PAHs induced activity in ER-reporter gene assays but that these PAHs did not up-regulate estrogen-responsive genes. The authors concluded that ER-reporter gene assays may detect concentrations of toxicants that are not physiologically active. In light of these recent findings, the estrogenic response from microbial PAH bioactivation in this study needs careful interpretation. However, the finding of 1-OH pyrene and 7-OH benzo(a)pyrene as metabolites from human colon microbiota is something that is not anticipated from current scientific knowledge or risk assessment studies. Comparison of our findings from active to those from inactivated colon microbiota shows that the microbial bioactivation potency is a factor of 12 higher than would be currently expected in risk calculations. Moreover, the time during which bioactive hydroxy-PAHs could react with colonocytes is also considerably longer (up to 72 hr) than the residence time in human enterocytes or hepatocytes (6 hr maximum). Additionally, if taken up by colonocytes, the hydroxy-PAHs are typical metabolites that are more easily metabolized by human biotransformation enzymes to, for example, potent carcinogens such as benzo(a)pyrene-r7,t8-dihydrodiol-t9,10-epoxide (Kim et al. 1998). Clearly, these literature reports on human PAH metabolism and our findings of PAH bioactivation by colon microbiota indicate the importance of conducting future work in which the relative importance of the human bioactivation processes versus the microbial bioactivation processes should be compared.
Conclusion
Our results reveal that human colon microbiota can directly bioactivate PAHs, a potency that has not been reported before. As indicated by the analysis of a PAH-contaminated environmental sample, we also show that the presence of soil does not eliminate this microbial bioactivation potency. We therefore conclude that risk calculations that are based solely on human biotransformation enzymes may underestimate the risk from ingested aromatic contaminants because it does not consider the bioactivation processes described here.
Figure 1 Schematic representation of SHIME. Vessels 1–5 simulate conditions from the stomach, small intestine, colon ascendens, colon transversum, and colon descendens, respectively.
Figure 2 Estrogen response (mean ± SD) of naphthalene, phenanthrene, pyrene, and benzo(a)pyrene (62.5 nmol/L) incubated in stomach, small intestine, and colon digests and in digests with inactivated colon microbiota. Values are means of four replicates.
* None of the stomach digestions gave a significant response in the estrogen bioassay.
Figure 3 Dose–response curve of stomach, small intestine, and colon digests of PAH-contaminated playground soil in the Ah receptor yeast bioassay, expressed as percent benzo(a)pyrene equivalence in function of released PAH concentrations in the respective digests. Values are means of four replicates; error bars represent SD.
Figure 4 Released concentrations of PAHs and estrogen response in stomach, small intestine, and large intestine digests incubated with PAH-contaminated soil samples. Values are means of four replicates; error bars represent SD.
Table 1 Limits of detection (LODs) of hydroxy-PAHs obtained with LC-MS analysis, concentrations of the hydroxy-PAHs in the colon digest, and concentrations of the hydroxy-PAHs in the deconjugated colon digest.
Hydroxy-PAH LOD (μg/L) Colon digest (μg/L) Colon digest deconjugated (μg/L)
1-OH naphthalene 7.33 ND ND
9-OH phenanthrene 0.47 ND ND
1-OH pyrene 0.24 2.5 4.4
7-OH benzo(a)pyrene 0.95 ND 1.9
ND, not detected.
==== Refs
References
Ariese F Ernst WHO Sijm DTHM 2001 Natural and synthetic organic compounds in the environment—a symposium report Environ Toxicol Pharmacol 10 65 80 21782560
Aura AM O’Leary KA Williamson G Ojala M Bailey M Puupponen-Pimia R 2002 Quercetin derivatives are deconjugated and converted to hydroxyphenylacetic acids but not methylated by human fecal flora in vitro J Agr Food Chem 50 1725 1730 11879065
Autrup H Harris CC Trump BF Jeffrey AM 1978 Metabolism of benzo(a )pyrene and identification of the major benzo(a )pyrene–DNA adducts in cultured human colon Cancer Res 38 3689 3696 698928
Bowler DG Duerden BI Armstrong DG 2001 Wound microbiology and associated approaches to wound management Clin Microbiol Rev 14 244 269 11292638
Cajthaml T Moder M Kacer P Sasek V Popp P 2002 Study of fungal degradation products of polycyclic aromatic hydrocarbons using gas chomatography with ion trap mass spectrometry detection J Chromatogr A 974 213 222 12458938
Chourasia MK Jain SK 2003 Pharmaceutical approaches to colon targeted drug delivery systems J Pharm Pharm Sci 6 33 66 12753729
De Boever P Demare W Vanderperren E Cooreman K Bossier P Verstraete W 2001 Optimization of a yeast estrogen screen and its applicability to study the release of estrogenic isoflavones from a soygerm powder Environ Health Perspect 109 691 697 11485867
De Kok TM van Maanen JM 2000 Evaluation of fecal mutagenicity and colorectal cancer risk Mutat Res 463 53 101 10838209
Doherty MM Charman WN 2002 The mucosa of the small intestine. How clinically relevant as an organ of drug metabolism Clin Pharmacokinet 41 2035 2053
Fertuck KC Kumar S Sikka HC Matthews JB Zacharewski TR 2001 Interaction of PAH-related compounds with the α and βisoforms of the estrogen receptor Toxicol Lett 121 167 177 11369471
Gozgit JM Nestor KM Fasco MJ Pentecost BT Arcaro KF 2004 Differential action of polycyclic aromatic hydrocarbons on endogenous estrogen-responsive genes and on a transfected estrogen-responsive reporter in MCF-7 cells Toxicol Appl Pharmacol 196 58 67 15050408
Hankinson O 1995 The aryl hydrocarbon receptor complex Annu Rev Pharmacol Toxicol 35 307 340 7598497
Heisterkamp SH van Veen MP 1997. Exposure to Xenobiotics in Nutrition. Model Compounds: Butyl Benzyl Phthalate (BBP), Benzo[a]pyrene and Fluoranthene. Technical Report No. 604502 002. Bilthoven, Netherlands:RIVM.
Hirose T Morito K Kizu R Toriba A Hayakawa K Ogawa S 2001 Estrogenic/antiestrogenic activities of benzo(a )pyrene monohydroxy derivatives J Health Sci 47 552 558
Hooper LV Wong MH Thelin A Hansson L Falk PC Gordon JI 2001 Molecular analysis of commensal host-microbial relations hips in the intestine Science 291 881 884 11157169
Huycke MM Moore DR 2002 In vivo production of hydroxyl radical by Enterococcus faecalis colonizing the intestinal tract using aromatic hydroxylation Free Radical Biol Med 33 818 826 12208369
Ilett KF Tee LB Reeves PT Minchin RF 1990 Metabolism of drugs and other xenobiotics in the gut lumen and wall Pharmacol Therapeut 46 67 93
Karthikeyan R Bhandari A 2001 Anaerobic biotransformation of aromatic and polycyclic aromatic hydrocarbons in soil microcosms: a review J Hazard Subst Res 3 1 19
Kim JH Stansbury KH Walker NJ Trush MA Strickland PT Sutter TR 1998 Metabolism of benzo(a )pyrene and benzo(a )pyrene-7,8-diol by human cytochrome P450 1B1 Carcinogenesis 19 1847 1853 9806168
Macdonald IA Mader JA Bussard RG 1983 The role of rutin and quercitin in stimulating flavonol glycosidase activity by cultured cell-free microbial preparations of human feces and saliva Mutat Res 122 95 102 6419088
Miller CA 1997 Expression of the human aryl hydrocarbon receptor in yeast J Biol Chem 272 32824 32829 9407059
Molly K Vandewoestijne M Verstraete W 1993 Development of a 5-step multichamber reactor as a simulation of the human intestinal microbial ecosystem Appl Microbiol Biot 39 254 258
O’Neill IK Goldber MT Ghissassi FE Rojas-Moreno M 1991 Dietary fiber, fat and beef modulation of colonic nuclear aberrations and microcapsule-trapped gastrointestinal metabolites of benzo(a )pyrene-treated C57rB6 mice consuming human diets Carcinogenesis 12 175 180 1847318
Oomen AG Sips AJAM Groten JP Sijm DTHM Tolls J 2000 Mobilization of PCBs and lindane from soil during in vitro digestion and their distribution among bile salt micelles and proteins of human digestive fluid and the soil Environ Sci Technol 34 297 303
Routledge EJ Sumpter JP 1996 Estrogenic activity of surfactants and some of their degradation products assessed using a recombinant yeast screen Environ Toxicol Chem 15 241 248
Rumney CJ Rowland IR O’Neill IK 1993 Conversion of IQ to 7-OHIQ by gut microflora Nutr Cancer 19 67 76 8383316
Ungell AL Nylander S Bergstrand S Sjoberg A Lennernas H 1998 Membrane transport of drugs in different regions of the intestinal tract of the rat J Pharm Sci 87 360 366 9523990
U.S. EPA 1996. Method 8270C: Semivolatile Organic Compounds by Gas Chromatography/Mass Spectroscopy. In: Test Methods for Evaluating Solid Waste: Physical/Chemical Methods, Vol 1B. 3rd ed, Revision 3. Washington, DC:U.S. Environmental Protection Agency, Office of Solid Wastes.
van der Bijl P van Eyk AD 2003 Comparative in vitro permeability of human vaginal, small intestinal and colonic mucosa Int J Pharm 261 147 152 12878403
Van de Wiele TR Peru K Verstraete W Siciliano SD Headley JV 2004a Liquid chromatography mass spectrometry analysis of PAH hydroxylates, formed in a simulator of the human gastrointestinal tract J Chromatogr B 806 245 253
Van de Wiele TR Verstraete W Siciliano S 2004b Polyaromatic hydrocarbon release from a soil matrix in the in vitro gastrointestinal tract J Environ Qual 33 1343 1353 15254116
van Maanen JMS Moonen EJC Maas LM Kleinjans JCS van Schooten FJ 1994 Formation of aromatic DNA adducts in white blood cells in relation to urinary excretion of 1-hydroxypyrene during consumption of grilled meat Carcinogenesis 15 2263 2268 7955064
van Schooten FJ van Leeuwen FE Hillebrand MJX de Rijke ME Hart AAM van Veen HG 1990 Determination of benzo[a ]pyrene diol epoxide-DNA adducts in white blood cell DNA from coke oven workers: the impact of smoking J Natl Cancer Inst 82 927 933 2111410
|
15626640
|
PMC1253702
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan 22; 113(1):6-10
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7259
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7274ehp0113-00001115626641ResearchArticlesUptake and Elimination of Brevetoxin in Blood of Striped Mullet (Mugil cephalus) after Aqueous Exposure to Karenia brevis Woofter Ricky T. Brendtro Kirsten Ramsdell John S. Marine Biotoxins Program, Center for Coastal Environmental Health and Biomolecular Research, National Oceanic and Atmospheric Administration–National Ocean Service, Charleston, South Carolina, USAAddress correspondence to J.S. Ramsdell, Coastal Research Branch, Center for Coastal Environmental Health and Biomolecular Research, NOAA-National Ocean Service, 219 Fort Johnson Rd., Charleston, SC 29412 USA. Telephone: (843) 762-8510. Fax: (843) 762-8700. E-mail:
[email protected] National Ocean Service (NOS) does not approve, recommend, or endorse any proprietary product or material mentioned in this publication. No reference shall be made to NOS, or to this publication furnished by NOS, in any advertising or sales promotion that would indicate or imply that NOS approves, recommends, or endorses any proprietary product or proprietary material mentioned herein or that has as its purpose any intent to cause directly or indirectly the advertised product to be used or purchased because of NOS publication.
The authors declare they have no competing financial interests.
1 2005 23 9 2004 113 1 11 16 21 5 2004 23 9 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. There is a critical need to simply and reliably monitor brevetoxins routinely in the blood of humans and aquatic animals. We used striped mullet as laboratory test animals to better define the uptake and elimination kinetics of brevetoxin during an aqueous exposure to the brevetoxin-producing dinoflagellate Karenia brevis. Striped mullet were first exposed to sublethal densities of K. brevis (~ 250,000 cells/L) for 1, 4, 8, 12, and 24 hr. No mortality was observed in the aquaria, and at each time point blood samples were taken and applied to blood collection cards for brevetoxin analysis using radioimmunoassay (RIA). The RIA indicated that blood levels of brevetoxin (PbTx-3) increased to values significantly different from that of the controls at all five time points during exposure (p < 0.05). Striped mullet were then exposed to a K. brevis culture with a known brevetoxin concentration of 0.5 ng/mL. Even after exposures at a low brevetoxin concentration, RIA was able to detect 2.25 ± 0.62 ng/mL PbTx-3 equivalents in the blood of the mullet at 8 hr of exposure. When exposed to higher brevetoxin concentrations (3.5 and 5.4 ng/mL), blood brevetoxin increased to peak levels at 12 hr and then reached equilibrium after 24 hr in the continued presence of K. brevis. During this time of equilibrium, the mullet maintained brevetoxins with a blood:water coefficient of 2.2. To define the elimination of brevetoxin, striped mullet were next exposed for 8–10 hr and then transferred to fresh seawater containing no K. brevis for up to 116 hr. Blood brevetoxin levels remained elevated and decreased only by 50% 116 hr after transfer. The rate of elimination fit best to a two-phase exponential decay with a biologic half-life of 12 and 266 hr. This study, using RIA in conjunction with blood collection cards, demonstrates an effective means to monitor blood brevetoxin levels in finfish and provides a foundation to characterize biologically relevant levels of brevetoxin in other species impacted by red tide events.
bloodbrevetoxinradioimmunoassay
==== Body
Red tides have been documented on the Gulf Coast of Florida as early as 1530 (Taylor 1917). They occur nearly annually and often persist for many months (Woodcock 1948). The causative organism for these events, Karenia brevis (formerly Gymnodinium breve and Ptychodiscus brevis), produces a family of neurotoxins, collectively called brevetoxins (Davis 1948; Lin et al. 1981; Martin and Chatterjee 1969; Poli et al. 1986). Exposure to high densities of K. brevis (100,000–250,000 cells/L seawater) can cause fish kills (Quick and Henderson 1974; Steidinger and Joyce 1973). Brevetoxins from red tides are linked to deaths in marine mammals, including dolphins and manatees, which are intoxicated through both ingestion of organisms harboring high brevetoxin concentrations and inhalation of aerosolized brevetoxins (Landsberg and Steidinger 1998). Brevetoxins produced by K. brevis blooms also pose a risk to human health. Aerosol forms of the toxin are produced by wind and wave action and move onshore, causing transient respiratory irritation in people that inhale the toxin (Pierce 1986; Pierce et al. 1990). Humans can also experience the more severe symptoms of neurotoxic shellfish poisoning (NSP) as a result of consumption of molluscan shellfish that have accumulated brevetoxins (McFarren et al. 1965).
Blooms of K. brevis are regularly monitored to control health hazards associated with shellfish consumption. Bans on shellfish harvesting are initiated when K. brevis densities surpass 5,000 cells/L seawater (Landsberg and Steidinger 1998). Added significance lies in the fact that sustainability of shellfish aquaculture is at stake because of ecologic problems in harvesting areas. A better monitoring strategy will be a major factor in improving aquaculture practices and help control the hazards of toxin exposure. Biomonitoring, using readily collected biological fluids of target or sentinel species, permits the determination of biologically relevant toxin levels in living animals. Blood collection cards have provided a format for the simple collection, storage, and extraction of whole blood for detection of brevetoxins in laboratory mice that is compatible with biological (receptor assay) and instrumental (liquid chromatography–mass spectrometry) detection methods (Fairey et al. 2001). Recently, Woofter et al. (2003) developed a brevetoxin radioimmunoassay (RIA) that has improved the sensitivity of brevetoxin detection to < 2 ng/mL in whole blood. Because of the RIA’s higher sensitivity, doses 10 times less than those that elicit symptoms could be detected, and at higher levels of exposure, brevetoxins could be detected for at least 2 days. This RIA also had an added advantage for studies involving exposure to the predominant, less stable brevetoxin congener PbTx-2 in that it appears to also detect longer-lived metabolic products of the parent brevetoxin molecules.
Previous toxicokinetic studies for brevetoxin have used exposure by intravenous, intraperitoneal, intratracheal, and oral administration to laboratory mice and rats (Benson et al. 1999; Cattet and Geraci, 1993; Poli et al. 1990; Woofter et al. 2003). It was necessary to further these studies with marine species and with an exposure paradigm that incorporates contact with the causative organism, K. brevis. Exposing striped mullet (Mugil cephalus) to K. brevis in laboratory aquaria permits respiratory and oral exposure as well as dermal contact with the toxin-producing organism. Exposure to the toxin-producing species is important because K. brevis produces at least nine brevetoxin analogs, predominantly PbTx-2, a congener highly susceptible to metabolism (Plakas et al. 2002). Striped mullet is a widespread and abundant teleost species that inhabits estuaries and salt marshes as well as the open ocean (Collins 1985), where contact with K. brevis blooms is likely.
For this study, we exposed striped mullet to simulated blooms of K. brevis in laboratory aquaria. Brevetoxin accumulation in blood of the mullet over various lengths of exposure to K. brevis was used to determine the kinetics of uptake. Low-level exposures were also conducted to determine the lowest quantifiable levels of measurement. Finally, we performed a depuration study to determine the rate of brevetoxin elimination. The results demonstrate that mullet quickly accumulate brevetoxins in their blood and retain detectable brevetoxin levels many days after exposure to toxin has ended. This information provides a laboratory-based indication of the uptake of brevetoxin in fish that encounter a red tide, the biologically relevant levels that bathe tissues via the circulation, and an estimate of how long they disperse toxicity to upper trophic levels of the food chain after they leave the red tide. It is anticipated that this work will provide the opportunity to predict the extent of brevetoxin toxicity beyond the temporal and spatial bounds of an actual red tide event.
Materials and Methods
Striped mullet collection and maintenance.
Striped mullet (Mugil cephalus) between 10 and 20 cm in length were collected using both seine netting and cast netting in control estuarine creeks not known to experience K. brevis blooms, near Charleston Harbor, South Carolina. The mullet were transported to the laboratory in aerated coolers and held for 10 days to ensure viability. They were held in a 950-L specimen tank with constant filtration and aeration using a 20-L Eheim filtration system (Eheim GmbH & Co KG, Deizisau, Germany). The salinity of the sea-water was maintained at 20 ppt. The fish were fed Seaweed Selects Green Marine Algae (Ocean Nutrition, Salt Lake City, UT) daily.
Algal cultures.
In exposure 1 we used K. brevis cells of the SP2 strain. The cells were grown in a batch culture using 10-L Bellco spinner flasks (Bellco Glass, Inc., Vineland, NJ) containing L-1–enriched sea-water (Guillard and Morton 2003). K. brevis cell densities in culture were counted with a Multisizer 3 Coulter Counter (Beckman Coulter, Miami, FL).
Exposures 2–5 were performed with the Wilson isolate of K. brevis. The cells were maintained in 1-L batch cultures enriched with f/2 medium (Guillard 1973) with the following modifications to the trace metals solution: ferric sequestrene was used in place of EDTA·Na2 and FeCl3·6H2O, and 0.01 μM selenous acid was added.
All cultures were maintained at 25 ± 1°C on a 16:8-hr light:dark cycle with autoclaved, 20-μm-filtered 36% seawater obtained from the seawater system at the Florida Institute of Technology field station (Vero Beach, FL). Cool white lights provided a photon flux density of 150–175 μE/m2/sec. The cultures were harvested for use in exposure experiments within the mid to late log phase of growth. RIA of the culture was performed to assess the total brevetoxin concentration in the culture and expressed in nanogram per milliliter PbTx-3 equivalents.
Mullet exposure design.
A primary range-finding method (exposure 1), and later a cell toxicity method (exposures 2–4), was used for the 24-hr mullet exposure to K. brevis. In exposure 1, two glass rectangular 60-L treatment tanks were set up in a fume hood with three to four fish per tank. Fish were allowed to acclimate to the 20-ppt treatment tanks for 24 hr before exposure. Control fish were removed after this 24-hr period, and the K. brevis culture was added to the treatment tanks to an approximate density of 250,000 cells/L water. The fish were removed from each treatment tank after the desired exposure time (1, 4, 8, 12, and 24 hr).
Exposures 2–4 were conducted in four round 60-L treatment tanks with five fish per tank. One fish from each tank was removed before administration of K. brevis cells and served as a control. The culture was then divided evenly among the exposure tanks to expose fish to desired concentration of brevetoxin (0.49–5.54 ng/mL). One fish per tank was removed and bled at each time point (4, 8, 12, 24, 36, and 48 hr), at which time a 50-mL water sample was taken from each tank to determine the total, intracellular, and extra-cellular brevetoxin concentration.
To determine the elimination of brevetoxin, tanks for exposure 5 were set up and dosed (5.54 ng/mL PbTx-3 equivalents) as per exposures 2–4 except after 10 hr of exposure to the toxic culture, the fish were then transferred to tanks containing no K. brevis. At each time point (16, 26, 38, 72, and 116 hr posttransfer), fish were removed from the tanks and their blood sampled for toxin analysis.
Blood collection.
At each time point, the mullet were anesthetized with 0.15 g/L MS-222 (3-aminobenzoic acid ethyl ester) until motionless. Blood was collected from the dorsal vein using a heparinized (lithium salt heparin, 70 mg/mL) 1-mL syringe with a 27-gauge needle.
Whole blood samples were applied to the grade 903 cellulose filter paper blood collection cards (Schleicher & Schuell, Keene, NH). Blood (100 μL) was applied to each circle on the blood-collection card (Adam et al. 2000). The cards were then allowed to dry overnight in a cool, dark environment. Once the cards were dry, they were separated by 6 in. × 6 in. weighing paper and transferred to airtight plastic bags (both from VWR Scientific Products, Suwanee, GA) containing desiccant packages and humidity cards (both from Multisorb Technologies Inc., Buffalo, NY). The blood collection cards were stored at −20°C until analyzed.
Brevetoxin extraction from blood collection cards.
The dried blood spots were prepared and processed as previously described (Fairey et al. 2001). Briefly, the entire 100 μL dried blood spot was cut from the cellulose blood collection card and extracted overnight in 2 mL methanol with an extraction efficiency of 84 ± 2.4% for the PbTx-3 congener. Extraction efficiency and stability for brevetoxin metabolites on blood collection cards is unknown. The spots were removed, and the methanol extracts were brought to dryness with nitrogen using a Turbovap LV evaporator (Zymark, Hopkinton, MA) and then stored at −20°C until use. The blood spot extracts were resuspended in RIA assay buffer containing 10% methanol.
Brevetoxin extraction from seawater.
Total brevetoxin was extracted from the K. brevis culture samples and seawater samples in a separation funnel with 1 × 10 mL then 2 × 2.5 mL methylene chloride. The methylene chloride fractions were combined and dried with vacuum centrifugation using an SC210A Speedvac plus (Thermo Savant, Woburn, MA), then reconstituted in 1 mL methanol.
Radioimmunoassay.
RIAs were performed using a sheep antisera prepared against a PbTx-2–fetuin conjugate (Garthwaite et al. 2001; Woofter et al. 2003). RIAs were run in 12 × 75 borosilicate glass tubes in phosphate-buffered saline (PBS) containing 137 mM NaCl, 8 mM Na2HPO4, 1.5 mM KH2PO4, 2.7 mM KCl, and 0.01% Emulphor-EL 620 (all from Sigma Chemical Company, St. Louis, MO, except for Emulphor, from GAF, New York, NY). The assay tubes consisted of PbTx-3 standard or blood spot extract (50 μL), anti-PbTx antiserum (1:4,000), [3H]PbTx-3 (0.4 nM), in PBS (final assay volume of 500 μL). The seven PbTx-3 standards ranged from 0.01 to 1,000 ng/mL. The PbTx-3 standards and blood spot extracts were allowed to pre-incubate in buffer at room temperature with the anti–PbTx-3 antibody for 1 hr before the [3H]PbTx-3 tracer was added. The tubes were placed on a Titramax 100 shaker (Heidolph Instruments, Cinaminson, NJ) and incubated 1 hr. Sac-Cel (Alpco Diagnostics, Windham, NH) was then added to the assay tubes to allow for the separation of bound and unbound brevetoxin. The bound antibody was filtered onto 25 mm glass fiber filters, and each assay tube was rinsed with PBS (3 × 2 mL) using a 48-sample Semi-Auto Harvester (Brandel, Gaithersburg, MD). The filters were placed in 5.0 mL Scinti-verse (Fisher, Suwanee, GA), and the radioactivity was counted on a Tri-Carb 3100TR Liquid Scintilation Counter (Packard-PerkinElmer, Wellesley, MA).
Data analysis.
All concentrations and half-maximal effective concentration (EC50) values were determined using Prism Graph Pad 4.0 (GraphPad Software, Inc. San Diego, CA). When appropriate, we used Prism to run an analysis of variance to determine significance.
Results
The toxicokinetics of brevetoxin in finfish was determined by RIA of methanolic extract of dried blood stored on blood collection cards, a field collection method developed by Fairey et al. (2001) and adapted to RIA by Woofter et al. (2003). Because the blood kinetics of brevetoxin in finfish are not well characterized, we ran a preliminary exposure (exposure 1) in order to monitor the behavior of the fish and to optimize exposure time. During exposure 1, all fish at each time point were removed from the same aquarium, so these data reflect pseudoreplication. The blood brevetoxin levels in mullet exposed to 250,000 cells/L reached a peak level of 10.4 ± 0.84 ng/mL at 8 hr, and then declined to 4.03 ± 0.94 ng/mL after 24 hr exposure. We observed no behavioral changes and blood brevetoxin levels were significantly different from controls in all experimental groups (p < 0.01 at 1, 8, 12, and 24 hr; p < 0.05 at 4 hr; Figure 1). This exposure allowed us to evaluate the equilibrium of brevetoxin in the blood of striped mullet during a 24-hr exposure to 250,000 K. brevis cells/L.
Exposures 2–5 were run to estimate the limit of quantitation of blood brevetoxin in striped mullet, examine the relationship between internal and external dose, determine a long-term trend in blood brevetoxin levels, and estimate the toxicokinetics of brevetoxin in blood.
To estimate the limit of quantitation of blood brevetoxin in striped mullet after exposure to K. brevis, exposure 2 was run at a lower density of K. brevis, and the amount of toxin in the water was quantified at 0.49 ± 0.02 ng/mL PbTx-3 equivalents. Under these experimental conditions, detectable levels of brevetoxin were found in blood samples after 8 and 12 hr exposure but not at earlier (4 hr) or later (24 hr) times (Figure 2). After 8 hr exposure, the limit of quantifiable blood brevetoxin was 2.25 ± 0.62 ng/mL PbTx-3 equivalents (p < 0.05).
Next, we examined the relationship between internal and external dose of brevetoxin (exposure 3). For this exposure, we treated animals with a higher dose (3.49 ± 0.20 ng/mL) of brevetoxin containing K. brevis cell culture and measured both blood brevetoxin (internal dose) and tank water brevetoxin (external dose). At this higher dose, we observed a similar time dependency for blood brevetoxin levels as observed in exposures 1 and 2 (Figure 3). Blood brevetoxin levels were 19.23 ± 1.72 ng/mL PbTx-3 equivalents after 12 hr and then declined to 9.63 ± 1.64 ng/mL PbTx-3 equivalents after 24 hr exposure, with all blood levels being significantly different from controls (p < 0.01). However, the concentration of brevetoxin in the tank water remained constant for the duration of exposure and all other exposures.
Exposure 4 examined the long-term trend in blood brevetoxin levels, conducting treatments for up to 48 hr. For this experiment, we exposed mullet to 1,102,000 ± 2,100 K. brevis cells/L at 5.54 ± 0.58 ng/mL PbTx-3 equivalents for 48 hr. During this study, three fish out of a total of nine died during the first 10 hr of exposure, consistent with findings of Pierce (1993). After continuing exposure for 48 hr, we found that blood brevetoxin levels remained constant, with no significant difference between 24, 36, and 48 hr (p > 0.05; Figure 4). Comparing these plateau levels of blood brevetoxin with the external dose, animals were found to maintain approximately twice (2.20 ± 0.31) the water level of toxin in their blood.
As a final study, exposure 5 determined the elimination rate of brevetoxin from the blood of striped mullet. For this study, which was conducted in conjunction with the previously described extended exposure, mullet were removed from the K. brevis-treated tanks at 10 hr and placed in tanks containing control seawater. We chose to remove the fish at 10 hr because of the characteristic peak in blood brevetoxin levels between 8 and 12 hr of exposure. One fish was removed from each of their respective tanks at 10 hr to determine the level of blood brevetoxin accumulation before being transferred to control tanks. After being transferred to control seawater, one fish was removed per tank to be analyzed for blood brevetoxin levels at 16, 26, 38, 72, and 116 hr posttransfer. Blood brevetoxin levels decreased from 12.51 ± 2.3 ng/mL at 10 hr of exposure to 6.75 ± 1.92 ng/mL after 116 hr in control seawater (Figure 5).
To determine whether the blood brevetoxin elimination over time in striped mullet follows an exponential decay model, we applied our blood brevetoxin values to both a one-phase and a two-phase exponential decay model (Table 1). Because brevetoxin remained in the blood after 116 hr, we set the constraints to plateau at zero in order to calculate an approximate biologic half-life (t1/2). Using Prism software, the one-phase exponential decay model gave a t1/2 of 126.7 hr and an R2 value of 0.9118. When the data were analyzed by a two-phase exponential decay model, it yielded a t1/2−1 of 12.9 hr and t1/2−2 of 229 hr with an improved fit of R2 = 0.9968. Finally, to determine a theoretical longest time of detection of blood brevetoxin in animals once the exposure has ended we analyzed the data with a constraint set at our 2.25 ng/mL limit of quantitation in blood. The one-phase exponential decay analysis indicated that a maximal time limit of quantitation was 300 hr or approximately 12.5 days and the two-phase decay prolonged detection for ≥50 hr to 14.6 days.
Discussion
The studies presented here provide a first-time characterization of brevetoxin uptake and elimination in vertebrates after exposure to K. brevis. Blood was chosen as the sample for toxin analysis, first, because it is in equilibrium with different tissues and, second, because it provides a useful biomonitoring application when using blood collection cards (Fairey et al. 2001). The present study characterizes the uptake and elimination of brevetoxin after a laboratory-based exposure designed to reflect a natural exposure of an endemic fish to a brevetoxin-containing red tide.
Exposure of aquatic species.
Brevetoxins are a threat to numerous aquatic wildlife species including fish, waterfowl, and marine mammals (Landsberg 2002; Steidinger and Joyce 1973). According to Roszell et al. (1990), K. brevis produces primarily PbTx-2 during log growth phase but produces PbTx-2, PbTx-1, and PbTx-3 in the approximate ratio of 20:4:1, respectively. Aquatic species are of particular relevance because K. brevis is a fragile dinoflagellete that readily breaks, releasing toxin directly into the water or upon contact with inert or living objects (Tester et al. 2000). Aquatic species are susceptible to toxin by multiple routes of entry including gills/respiratory, oral/gastrointestinal, and dermal pathways. Physiologically based toxicokinetic (PBTK) models have been developed for organic chemicals to evaluate each of these routes of entry using several species of fish (Nichols et al. 1991, 1996, 2004). The striped mullet used for this study may be susceptible to all three routes of entry: toxin released from broken cells may enter through capillary plexi of the gills; toxin associated with cells or cell fragments is filtered through fine gill rakers into the oral cavity; and the mullet have a cutaneous surface area to volume ratio sufficient to permit a significant dermal absorption (Lien and McKim 1993; McKim et al. 1996) In the present study we used an experimental design that includes all likely routes of exposure to striped mullet, which are common in regions endemic to dense K. brevis red tides.
Accumulation of brevetoxin.
Mullet show a near immediate uptake of brevetoxin into the blood upon exposure to brevetoxin-containing K. brevis culture applied via the aquarium water. Brevetoxin is measurable in the blood as early as 1 hr of exposure and rises to a peak between 8 and 12 hr. Brevetoxin levels then fall by about 50% to reach a plateau level at 24 hr; this plateau level is maintained for at least an additional 24 hr in the continued presence of the toxin. PBTK modeling of respiratory uptake of organic chemicals shows a near immediate single-order accumulation of contaminant that reaches a steady-state level in blood as early as about 24 hr, depending on the partitioning coefficient of the test compound (Nichols et al. 1990, 1991). Although we could measure brevetoxin at the earliest time point (1 hr) and a steady-state level was found at 24 hr, the kinetics differed in that a peak value was found between 8 and 12 hr. A peak accumulation at 8–12 hr was observed with PBTK modeling of oral exposures in fish (Nichols et al. 2004). Hence, the kinetics of brevetoxin accumulation after aqueous exposure to K. brevis cells also likely includes intestinal adsorption of the toxin. This oral route of exposure is consistent with toxicity of brevetoxin producing red tides to planktivorous fish such as mullet. Mullet have narrowly spaced gill rakers that aid in the filtration of particles such as microalgae from water. Current evidence indicates that the gill rakers serve to sort and concentrate particles using a crossflow filtration mechanism that promotes the travel of the particles to the esophagus (Sanderson et al. 2001). In the exposure tanks used for this experiment, the K. brevis cells quickly break; however, brevetoxin likely associates with these particles and would be processed by the gill rakers to enter the digestive track. Striped mullet also ingest sediment for trituration and were observed foraging on the bottom of the tank.
Elimination of brevetoxin.
The elimination of toxin was determined experimentally by transferring fish at the peak time of exposure to water containing no toxin. Brevetoxin was detectable in the blood several days after removal of the toxin, reflective of a slow elimination rate. Accordingly, a one-phase elimination model yielded a t1/2 of 126 hr. Application of a two-phase elimination model yielded an improved fit of R2 = 0.9968 (vs. 0.9118 for one-phase model) and t1/2 of 12.9 hr and 229 hr. Several, more traditional, brevetoxin toxicokinetic studies have been reported using [3H]PbTx-3 in rats and the toadfish. As may be expected, intravenous exposure leads to very rapid blood elimination kinetics (Kennedy et al. 1992; Poli et al. 1990). However, oral administration of brevetoxin leads to sustained blood levels of brevetoxin for many days (Cattet and Geraci 1993). This much longer retention of blood brevetoxin after oral exposure is consistent with the present study in which mullet were exposed to K. brevis in the aquarium water, and suggests that brevetoxin is reabsorbed by the intestines during digestion as well as after biliary secretion.
The present study differed from the more traditional toxicokinetic studies in that exposure was designed to be more representative of an environmental exposure. An elimination study using aqueous exposure of oysters has been reported by Plakas et al. (2002), who compared exposure of the animals to purified K. brevis cultures and purified PbTx-2 and PbTx-3. In shellfish tissue, PbTx-3 remains largely intact, whereas the unstable aldehyde PbTx-2 is rapidly converted to PbTx-3 and cysteine conjugates. PbTx-3 was not metabolized and was eliminated from the animals within 2 weeks, whereas PbTx-2 was rapidly metabolized and the cysteine-PbTx persisted for 8 weeks after exposure. Comparison of the oyster and mullet studies is only of qualitative value; the elimination times cannot be directly compared because the toxin analysis was conducted on the whole oyster with 2 weeks as the earliest time point. Additionally, RIA of brevetoxin metabolites may not be assured as quantitative without further characterization. Nonetheless, it is likely that the slow elimination of brevetoxins from mullet exposed to K. brevis cultures may also be a reflection of differential elimination rates for PbTx-2 metabolites. The RIA shows equivalent specificity for both PbTx-2 and PbTx-3 (Woofter et al. 2003); however, its cross-reactivity with metabolites is under investigation.
Internal dose and distribution.
The blood brevetoxin levels increased as a function of dose for the three dose experiments. Maximal blood levels reached nearly 20 ng/mL at 12 hr after a 3 ng/mL aqueous exposure, which did not cause observable symptoms. The decline of blood brevetoxin levels to a plateau value between 24 and 48 hr permitted a near-equilibrium analysis of an in vivo blood:water partition coefficient. This value of 2.2 is similar to values reported for ethyl acetate and three times lower than reported for tetrachloroethane in rainbow trout (Fitzsimmons et al. 2001). Measurement of toxin in blood is of particular value because blood levels are a dynamic reflection of tissue levels. Uptake studies of organic compounds in fish have indicated that ratios of blood to well-perfused tissues in fish are relatively constant and reflect near-equilibrium conditions (Nichols et al. 1990). Indeed, Cattet and Geraci (1993) demonstrated that blood levels of brevetoxin parallel levels in heart, kidney, lung, fat, muscle, testes, brain, and skin > 192 hr after oral exposure of PbTx-3 to rats. Brevetoxin levels in stomach and intestines, which at 6 hr were much higher, declined to plasma levels between 24 and 48 hr. Only liver retained higher levels of brevetoxin than found in plasma after 96 hr. Distribution studies to determine the percentage of body burden have been conducted in the toadfish after both intravenous and oral radiolabeled PbTx-3 exposure (Kennedy et al. 1992; Washburn et al. 1994). These studies reported similar distributions for both routes of administration by percent body burden and found toxin largely in the muscle, liver, bile, stomach, and intestines. Based on our initial findings of brevetoxin uptake and elimination, further studies to determine partitioning coefficients between tissues and blood should permit the evaluation of brevetoxin partitioning in fish tissues after environmental exposure to K. brevis and other aquatic species.
Implications for monitoring.
The retention of brevetoxins in finfish has substantial ecologic implications and potential practical significance. Mullet represent an important vector in the marine food web, being a common source of food for marine waterfowl, game fish, and marine mammals. Monitoring vectors in the food web, such as mullet, may provide a means to estimate the halo effect of a red tide beyond the boundaries demarcated by the K. brevis organism. This information has potential to extend modeling studies for the causative organism to models that may predict the spread of toxicity and its impact on wildlife and protected species, providing forecasting information to resource managers. Our results indicate that the RIA analysis of mullet using blood collection cards can detect brevetoxin up to 12.5 days after cessation of exposure. This study, being the first to explore the toxicokinetics of K. brevis in marine vertebrates, will provide a foundation to characterize biologically relevant levels of brevetoxin in other species impacted by red tide events.
Figure 1 Blood brevetoxin levels after exposure to 250,000 K. brevis cells/L. Blood was collected from all four fish in each experimental group at each time point (0, 1, 4, 8, 12, and 24 hr). Blood brevetoxin levels reached a peak level of 10.37 ng/mL at 8 hr and then declined to 4.03 ng/mL after 24 hr exposure. The results shown are mean ± SE for four animals at each time point from a single experiment.
*p < 0.05 and **p < 0.01 compared with control.
Figure 2 Blood brevetoxin levels after low-dose K. brevis exposure (0.49 ± 0.02 ng/mL). Blood was collected from one fish in each of the four exposure tanks at each time point (0, 4, 8, 12, and 24 hr). Detectable levels of brevetoxin were found in blood samples after 8 and 12 hr of exposure. The results shown are mean ± SE for four animals at each time point from a single experiment.
*p < 0.05 compared with control.
Figure 3 Blood brevetoxin levels after high-dose K. brevis exposure (3.49 ng/mL). Blood was collected from one fish in each of the four exposure tanks at each time point (0, 4, 8, 12, and 24 hr). Water toxicity remained unchanged (3.49 ± 0.20 ng/mL) throughout the course of the exposure, but blood brevetoxin levels increased to 19.23 ± 1.72 ng/mL at 12 hr and then declined to 9.63 ± 1.64 ng/mL after 24 hr exposure. The results shown are mean ± SE for four animals at each time point from a single experiment.
**p < 0.01 compared with control.
Figure 4 Blood brevetoxin levels after extended exposure to K. brevis (5.54 ± 0.58 ng/mL). Blood was collected from one fish in each of the four exposure tanks at each time point (0, 24, 36, and 48 hr). Water toxicity remained constant for all time points, and blood brevetoxin levels remained unchanged (p > 0.05 for 24, 36, and 48 hr). The results shown are mean ± SE for four animals at each time point from a single experiment.
Figure 5 Elimination of blood brevetoxin after 10-hr exposure to K. brevis (5.54 ± 0.58 ng/mL). Fish were placed in control seawater after exposure. At each time point, 16, 26, 38, 72, and 116 hr postexposure, one fish per tank was removed for blood brevetoxin analysis. The results shown are mean ± SE for four animals at each time point from a single experiment.
Table 1 One- and two-phase exponential decay analysis of blood brevetoxin retention in striped mullet.
Analysis One phase Two phase
Best-fit values
Span 1 (hr) 11.62 9.569
K1 0.005469 0.003025
Span 2 (hr) — 2.927
K2 — 0.05392
Plateau 0 0
t1/2−1 (hr) 126.7 229.1
t1/2−2 (hr) — 12.86
SE
Span 1 (hr) 0.4713 0.9007
K1 0.0009164 0.0009323
Span 2 (hr) — 0.8983
K2 — 0.02295
Goodness of fit
R2 0.9118 0.9968
—, not available; K, constant used in evaluating t1/2.
==== Refs
References
Adam BW Alexander RJ Smith SJ Chance DH Loeder JG Elvers LH 2000 Recoveries of phenylalanine from two sets of dried-blood spot reference materials: prediction from hematocrit, spot volume, and paper matrix Clin Chem 46 126 128 10620584
Benson JM Tischler DL Baden DG 1999 Uptake, tissue distribution, and excretion of brevetoxin 3 administered to rats by intratracheal instillation J Toxicol Environ Health A 57 345 355 10405188
Cattet M Geraci JR 1993 Distribution and elimination of ingested brevetoxin (PbTx-3) in rats Toxicon 31 11 1483 1486 8310449
Collins MR 1985. Species Profiles: Life Histories and Environmental Requirements of Coastal Fishes and Invertebrates (South Florida)—Striped Mullet. Biological Report 82 (11.34). Washington, DC:U.S. Fish and Wildlife Service.
Davis CC 1948 Gymnodinium breve : a cause of discolored water and animal mortality in the Gulf of Mexico Bot Gaz 109 358 360
Fairey ER Shuart NG Busman M Moeller PD Ramsdell JS 2001 Biomonitoring brevetoxin exposure in mammals using blood collection cards Environ Health Perspect 109 717 720 11485871
Fitzsimmons PN Fernandez JD Hoffman AD Butterworth BC Nichols JW 2001 Branchial elimination of superhydro-phobic organic compounds by rainbow trout (Oncorhynchus mykiss ) Aquat Toxicol 55 23 34 11551619
Garthwaite I Ross KM Miles CO Briggs LR Towers NR Borrell T 2001 Integrated enzyme-linked immunosorbent assay screening system for amnesic, neurotoxic, diarrhetic, and paralytic shellfish poisoning toxins found in New Zealand J AOAC Int 84 5 1643 1648 11601487
Guillard RRL 1973. Division rates. In: Handbook of Phycological Methods. Culture Methods and Growth Measurements (Stein JR, ed). Cambridge, UK:Cambridge University Press, 289–311.
Guillard RRL Morton SL 2003. Culture techniques. In: Manual on Harmful Marine Microalgae (Hallegraeff GM, Anderson DM, Cembella AD, eds). Intergovernmental Oceanographic Commission of the United Nations Educational, Scientific and Cultural Organization. Paris:UNESCO Publishing, 77–98.
Kennedy CJ Schulman LS Baden DG Walsh PJ 1992 Toxicokinetics of brevetoxin PbTx-3 in the gulf toadfish, Ospanus beta , following intravenous administration Aquat Toxicol 22 3 14
Landsberg JH 2002 The effects of harmful algal blooms on aquatic organisms Rev Fish Sci 10 113 390
Landsberg JH Steidinger KA 1998. A historical review of Gymnodinium breve red tides implicated in mass mortalities of the manatee (Trichechus manatus latriostris) in Florida, USA. In: Proceedings of the Eighth International Conference on Harmful Algae, 25–29 June 1997, Vigo, Spain. Santiago de Compestela, Spain:Xunta de Galicia and IOC of UNESCO, 97–100.
Lien GJ McKim JM 1993 Predicting branchial and cutaneous uptake of 2,2′,5,5′-tetrachlorobiphenyl in fathead minnows (Pimephales promelas ) and Japanese medaka (Oryzias latipes ): rate limiting factors Aquat Toxicol 27 15 32
Lin Y Risk M Ray SM Van Engen D Clardy J Golik J 1981 Isolation and structure of brevetoxin B from the “red tide” dinoflagellate Ptychodiscus brevis (Gymnodinium breve ) J Am Chem Soc 103 6773 6775
Martin DF Chatterjee AB 1969 Isolation and characterization of a toxin from the Florida red tide organism Nature 221 59 5782610
McFarren EF Tanabe H Silva FJ Wilson WB Campbell JE Lewis KH 1965 The occurrence of a ciguatera-like poison in oysters, clams, and Gymnodinium breve cultures Toxicon 3 111 123 5867066
McKim JM Nichols JW Lien GJ Hoffman AD Gallinat CA Stokes GN 1996 Dermal absorption of three waterborne chloroethanes in rainbow trout (Oncorhynchus mykiss ) and channel catfish (Ictalurus punctatus ) Fundam Appl Toxicol 31 218 228 8789788
Nichols JW Fitzsimmons PN Whiteman FW 2004 A physiologically based toxicokinetic model for dietary uptake of hydrophobic organic compounds by fish: II. Simulation of chronic exposure scenarios Toxicol Sci 77 219 229 14657516
Nichols JW McKim JM Andersen ME Gargas ML Clewell HJ III Erickson RJ 1990 A physiologically-based toxicokinetic model for the uptake and disposition of water-borne organic chemicals in fish Toxicol Appl Pharmacol 106 433 447 2260091
Nichols JW McKim JM Lien GJ Hoffman AD Bertelsen SL 1991 Physiologically-based toxicokinetic modeling of three waterborne chloroethanes in rainbow trout, Oncorhynchus mykiss Toxicol Appl Pharmacol 110 374 389 1949008
Nichols JW McKim JM Lien GJ Hoffman AD Bertelsen SL Elonen CM 1996 A physiologically based toxicokinetic model for dermal absorption of organic chemicals by fish Fundam Appl Toxicol 31 229 242 8789789
Pierce RH 1986 Red tide (Ptychodiscus brevis ) toxin aerosols: a review Toxicon 24 955 965 3824403
Pierce RH 1993. Mote Marine Laboratory Red Tide Research. Technical Report no. 284. St. Petersburg, FL:Florida Department of Natural Resources, Mote Marine Laboratory. Available: http://www.mote.org/techreps/284/284.pdf [accessed 17 November 2004].
Pierce RH Henry MS Proffitt LS Hasbrouck PA 1990. Red tide toxin (brevetoxin) enrichment in marine aerosol. In: Proceedings of the Fourth International Conference on Toxic Marine Phytoplankton, 26–30 June 1989, Lund, Sweden (Graneli E, Sundstrom B, Edler L, Anderson D, eds). New York:Elsevier, 1058–1061.
Plakas SM El Said KR Jester ELE Grande HR Musser SM Dickey RW 2002 Confirmation of brevetoxin metabolism in the Eastern oyster (Crassostrea virginica ) by controlled exposures to pure toxins and Karenia brevis cultures Toxicon 40 721 729 12175608
Poli MA Mende TJ Baden DG 1986 Brevetoxins, unique activators of voltage-sensitive sodium channels, bind to specific sites in rate brain synaptosomes Mol Pharmacol 30 129 135 2426567
Poli MA Templeton CB Thompson WL Hewetson JF 1990 Distribution and elimination of brevetoxin PbTx-3 in rats Toxicon 28 903 910 2080516
Quick, JA Henderson GE 1974. Effects of Gymnodinium breve red tide on fishes and birds: a preliminary report on behavior, anatomy, hematology and histopathology. In: Proceedings of the Gulf Coast Regional Symposium on Diseases of Aquatic Animals, August 16–17, 1974, Baton Rouge, LA. (Amborski R, Hood M, Miller R, eds) Baton Rouge, LA:Louisiana State University, 85–113.
Roszell LE Schulman LS Baden DG 1989. Toxin profiles are dependent on growth stages in cultured Ptychodiscus brevis. In: Proceedings of the Fourth International Conference on Toxic Marine Phytoplankton, 26–30 June 1989, Lund, Sweden (Graneli E, Sundstrom B, Edler L, Anderson D, eds). New York:Elsevier, 403–406.
Sanderson SL Cheer AY Goodrich JS Graziano JD Callan WT 2001 Crossflow filtration in suspension-feeding fishes Nature 412 387 388 11473292
Steidinger KA Joyce EA Jr 1973. Florida Red Tides. Educational Series no. 17. St. Petersburg, FL:Florida Department of Natural Resources.
Taylor HF 1917. Mortality of Fishes on the West Coast of Florida. Report of the U.S. Commissioner of Fisheries. Bureau of Fisheries Document 848. Washington, DC:Government Printing Office.
Tester PA Turner JT Shea D 2000 Vectorial transport of toxins from the dinoflagellate Gymnodinium breve through cope-pods to fish Plankton Res 22 47 62
Washburn BS Baden DG Gassman NJ Walsh PJ 1994 Brevetoxin: tissue distribution and effect on cytochrome P450 enzymes in fish Toxicon 32 799 805 7940587
Woodcock AH 1948 Note concerning human respiratory irritation associated with high concentrations of plankton and mass mortality of marine organisms J Mar Res 7 1 56 62
Woofter R Bottein Dechraoui MY Garthwaite I Towers NR Gordon CJ Córdova J 2003 Measurement of brevetoxin levels by radioimmunoassay of blood collection cards after acute, long-term and low dose exposures in mice Environ Health Perspect 111 1595 1600 14527838
|
15626641
|
PMC1253703
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan 23; 113(1):11-16
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7274
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7301ehp0113-00001715626642ResearchArticlesNitromusk and Polycyclic Musk Compounds as Long-Term Inhibitors of Cellular Xenobiotic Defense Systems Mediated by Multidrug Transporters Luckenbach Till Epel David Hopkins Marine Station of Stanford University, Pacific Grove, California, USAAddress correspondence to D. Epel, Hopkins Marine Station of Stanford University, 120 Oceanview Blvd., Pacific Grove, CA 93950 USA. Telephone: (831) 655-6226. Fax: (831) 375-0793. E-mail:
[email protected] thank C. Chan and S. Sadasivaiah for preliminary studies; J. Watanabe for help with the statistical analyses; and I. Corsi, A. Hamdoun, T. Smital, and C. Thaler for discussions and comments on the manuscript.
This publication was supported in part by the German Academic Exchange Service (DAAD), the National Sea Grant College Program of the U.S. Department of Commerce’s National Oceanic and Atmospheric Administration under grant R/CZ-182 through the California Sea Grant College Program, and the California State Resources Agency.
The views expressed herein do not necessarily reflect the views of any of those organizations.
The authors declare they have no competing financial interests.
1 2005 30 9 2004 113 1 17 24 28 5 2004 30 9 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Synthetic musk compounds, widely used as fragrances in consumer products, have been detected in human tissue and, surprisingly, in aquatic organisms such as fish and mollusks. Although their persistence and potential to bioaccumulate are of concern, the toxicity and environmental risks of these chemicals are generally regarded as low. Here, however, we show that nitromusks and polycyclic musks inhibit the activity of multidrug efflux transporters responsible for multixenobiotic resistance (MXR) in gills of the marine mussel Mytilus californianus. The IC10 (concentration that inhibits 10%) values for the different classes of musks were in the range of 0.09–0.39 μM, and IC50 values were 0.74–2.56 μM. The immediate consequence of inhibition of efflux transporters is that normally excluded xenobiotics will now be able to enter the cell. Remarkably, the inhibitory effects of a brief 2-hr exposure to musks were only partially reversed after a 24- to 48-hr recovery period in clean seawater. This unexpected consequence of synthetic musks—a long-term loss of efflux transport activity—will result in continued accumulation of normally excluded toxicants even after direct exposure to the musk has ended. These findings also point to the need to determine whether other environmental chemicals have similar long-term effects on these transporters. The results are relevant to human health because they raise the possibility that exposure to common xenobiotics and pharmaceuticals could cause similar long-term inhibition of these transporters and lead to increased exposure to normally excluded toxicants.
chemosensitizersfragrancesMDRmultidrug resistancemultixenobiotic resistanceMXRMytilus californianusnitromuskspolycyclic musks
==== Body
Artificial musk compounds are widely used as inexpensive fragrances and fixatives in personal care products, including detergents, cleaning agents, air fresheners, and cosmetic products (names and structures are shown in Table 1). The worldwide production of musks increased from about 7,000 to 8,000 metric tons/year between 1987 and 1996, with a concurrent production shift from nitromusks to polycyclic musks (Rimkus 1999). The most widely used polycyclic musk is Galaxolide (HHCB), followed by Tonalide (AHTN) (Rimkus 1999), and production of these two polycyclics was about 1,800 metric tons in 2000 in Europe, whereas production of other polycyclic musks was < 20 metric tons (Kupper et al. 2004). Musk xylene (MX) is the most common nitromusk, but use was discontinued in Japan and a voluntary ban is in force in Germany (Käfferlein et al. 1998). Use is still high in the United States, although it is banned in products with a risk of oral uptake (e.g., lipsticks). Toxicologic data have not suggested severe health risks associated with artificial musks, although long-term carcinogenic effects cannot be ruled out (Api et al. 2004; Frosch et al. 1995; Käfferlein and Angerer 2001; Schmeiser et al. 2001); there is also concern about accumulation in adipose tissue, blood plasma, and breast milk (Käfferlein and Angerer 2001; Liebl and Ehrenstorfer 1993; Ott et al. 1999; Rimkus and Wolf 1996).
More than two decades ago Yamagishi et al. (1981, 1983) reported the presence of musks in the aquatic environment and biota in Japan, leading to similar investigations in Europe and North America (Balk and Ford 1999a; Bester et al. 1998; Draisci et al. 1998; Gatermann et al. 2002; Käfferlein et al. 1998; Kallenborn et al. 1999; Osemwengi and Steinberg 2001; Paasivirta et al. 2002; Peck and Hornbuckle 2004; Ricking et al. 2003; Rimkus 1999; Rimkus et al. 1997, 1999; Rimkus and Wolf 1995; Tas and Balk 1997; Tas et al. 1997). These studies show that synthetic musks are widespread in marine and freshwater environments and bioaccumulate to a high degree in fish and invertebrates. Because acute and chronic toxicity thresholds for musks in invertebrate and fish species are much higher than the environmentally measured levels (Balk and Ford 1999b; Behechti et al. 1998; Breitholtz et al. 2003; Chou and Dietrich 1999b; Wollenberger et al. 2003), the environmental risks posed by musks are assumed to be low (Balk et al. 2001). Musks show low binding affinity to estrogen receptors, and their environmental impact as endocrine disruptors through this pathway is also regarded as low (Bitsch et al. 2002; Chou and Dietrich 1999a), although indirect endocrine effects such as inhibition of hormone synthesis (Kester et al. 2000; Sanderson et al. 2001) have not been examined.
However, it has been proposed that pharmaceutical and personal care products (PPCPs), a vast group of environmental contaminants including the artificial musks, might affect organisms through interference with multidrug/multixenobiotic resistance (MDR/MXR) efflux transporters (Daughton and Ternes 1999; Epel and Smital 2001; Smital et al. 2004). The activity of these transporters provides a first line of defense to prevent accumulation of xenobiotics in cells. Inhibition of this cellular defense mechanism increases the sensitivity of cells to xenobiotics by permitting normally excluded toxicants to enter the cell (Epel 1998; Kurelec 1992).
The transporter proteins responsible for MXR include P-glycoprotein (P-gp), multi-drug-resistance protein (MRP), and other members of the ABC (ATP-binding cassette) family of transport proteins. A characteristic feature of these efflux transporters is affinity for a diverse array of substrates. For instance, P-gp acts on a large number of chemically unrelated substrates whose common properties are small size, moderate hydrophobicity, and positively charged domains (Bain et al. 1997). Although this low specificity may provide an advantage by enabling the system to cope with “new” chemicals (e.g., environmental pollutants), a disadvantage is that the transporter capacity is more easily saturated in the presence of many substrates, and its protective role can then be lost. This subversion of the MXR defense by multiple substrates or inhibitors of efflux transporters is referred to as chemosensitization, and compounds that cause this behavior are referred to as chemosensitizers (Epel 1998; Kurelec 1997; Smital and Kurelec 1998b). We hypothesized that the synthetic musks, which are small-molecular-weight, moderately hydrophobic compounds, might be such chemosensitizers, and preliminary studies indeed showed inhibition of efflux transporters in gill tissues of a marine mussel (Luckenbach et al. 2004).
In this article we describe the inhibitory potencies of six artificial musk compounds and report the remarkable finding of continued inhibition of transport activity for 24–48 hr after a short (2 hr) exposure to musks. Although of low toxicity themselves, musks could therefore enhance toxicity of other compounds by blocking the MXR defense system. These results strongly affirm the hypothesis of Kurelec and collaborators, that indirect effects of environmental chemicals as efflux transporter chemosensitizers could be of major importance (Epel 1998; Kurelec 1995, 1997; Smital and Kurelec 1998b), but, additionally, our results indicate that the effects of chemosensitizers might continue long after the exposure event.
Chemicals.
Musk ketone (MK), MX, HHCB (1,3,4,6,7,8-hexahydro-4,6,6,7,8,8-hexamethyl-cyclopenta-γ-[2]-benzopyran), and Celestolide (ADBI; 4-acetyl-1,1-dimethyl-6-tert-butylindane) were gifts from International Flavors & Fragrances Inc. (IFF; Union Beach, NJ); AHTN (7-acetyl-1,1,3,4,4,6-hexamethyl-1,2,3,4-tetrahydronaphthalene) was obtained from Bush Boake Allen Inc. (Jacksonville, FL); and Traseolide (ATII; 5-acetyl-1,1,2,6-tetramethyl-3-isopropylindane) was obtained from Quest International (Mount Olive, NJ). Rhodamine B, (±)-verapamil hydrochloride, and quinidine were purchased from Sigma Chemical Company (St. Louis, MO). Purity of MK, MX, verapamil, and quinidine was ≥ 99%. Purity data were not available for the other musk compounds used. Stocks of rhodamine B in ultrapure water and ethanol stocks of the musks, verapamil, and quinidine were stored in glass flasks at 4°C in the dark.
Animals and tissue preparation.
California mussels (Mytilus californianus Conrad, 1837), with valve lengths ranging from 70 to 95 mm, were collected from the rocky intertidal zone at Hopkins Marine Station (Pacific Grove, CA) and maintained in tanks with running seawater (approximately 15°C) for at least 24 hr and no longer than 2 weeks before experiments. Experiments were performed with gill tissue, which shows high efflux transporter activity (Cornwall et al. 1995).
The mussels were opened by cutting through the adductor muscles with a sharp knife, and the gills were excised with fine scissors and placed in filtered seawater (FSW; 15°C). Each gill consists of two tissue lobes, which were separated at their dorsal connection. To obtain tissue pieces of equal size, dermatology biopsy punches (Acuderm, Fort Lauderdale, FL) were used to excise disks (diameter, 5 mm) from the tissue lobes. The tissue disks that result from this procedure consist of a double layer of lamellae (descending and ascending arm) that are connected by interlamellar tissue bridges. Approximately 55–70 disks per individual were obtained from mussels of the size used for these experiments. Mucus was removed from the gills with forceps before preparing the disks; the tissue disks were flushed and kept in FSW until use.
The sex of each animal was determined from visual inspection of gametes, which are clearly distinguishable by shape (White 1937). A piece of gonad tissue was dipped into a droplet of seawater on a microscope slide, covered with a cover slip, and examined under a light microscope equipped with phase contrast at 400×.
Competitive substrate/transporter inhibition assay and long-term inhibition.
The fluorescent dye rhodamine B was used as an indicator of efflux transporter activity. Inhibition of transporter activity by a test compound is indicated by increased fluorescence due to higher accumulation of rhodamine B in the cell (Neyfakh 1988). Test solutions were prepared in FSW with 1 μM rhodamine B. Stocks of the test compounds dissolved in ethanol were added to FSW to the desired concentrations, and all solutions were adjusted to 1% ethanol along with an ethanol control. Separate experiments indicated that this ethanol concentration had no effect on transport activity (data not shown). Incubations were performed in glass petri dishes (diameter, 5 cm) in a volume of 10 mL.
Gill tissue disks were incubated in test solutions with gentle rocking for 90 min at 15°C in the dark (n = 2–5 tissue disks per dish). After exposure, the tissue disks were briefly washed twice in FSW to remove external rhodamine B, frozen on dry ice or in liquid nitrogen, and stored at −20°C in the dark. For analysis, rhodamine B was extracted by sonicating the tissue in 200 μL n-butanol until fully homogenized. n-Butanol was used for extractions because, of the several extraction media tested (water, phosphate-buffered saline, some organic solvents), fluorescence signals from rhodamine B were strongest with this solvent. The sonicates were then centrifuged at 13,000g for 5 min, and the supernatant was transferred to black 96-well microplates (Packard Instrument Co., Meriden, CT). The amount of dye in the supernatant was determined with a fluorescence microplate reader (Packard FluoroCount; emission, 540 nm; excitation, 580 nm). Rhodamine B extracts were kept dark and on ice at all times. At each reading, background fluorescence was determined with pure n-butanol and subtracted from each value. Background fluorescence values of gill tissue with no rhodamine added were similar to that of the n-butanol extraction medium.
To examine the duration of inhibitory effects after exposure to test compounds, six to nine gill tissue disks were incubated with 1 μM of test compounds for 2 hr. Transporter activity was then assayed in one-third of the disks immediately after exposure and in the others after 24 hr and 48 hr of washing in fresh FSW (50 mL). FSW was changed after 24 hr. During exposure and washing, dishes were gently rocked at 15°C in the dark. The transporter activity assay was performed with 1 μM rhodamine B as described above.
Data analysis.
Transport activities in treated gill disks were normalized relative to nontreated controls that were run for each individual. The ratios, which indicate relative increases in fluorescence, were used as a measure of inhibition by each compound at the specified concentrations. The potencies of compounds for inhibiting MXR transporter activity are calculated as concentrations causing 10% and 50% of the maximal inhibition observed for a compound (IC10 and IC50). IC10 and IC50 values were determined by probit analysis using a macro program for Microsoft Excel written by J. Greve (Fraunhofer-Institut für Umweltchemie und Ökotoxikologie, Schmallenberg, Germany).
All experiments were performed at least three times using different individuals for each experiment, and mean values and SDs were determined. Statistical analyses were performed using Student’s t-test. For correlation analyses, we determined Pearson correlation coefficients. Statistical analyses were conducted using JMP software, version 4.0.4 (SAS Institute Inc., Cary, NC).
Results
Method evaluation.
Biopsy punch and extraction procedure.
The biopsy punch assay allowed processing large numbers of samples in a standardized way to examine effects of test compounds on efflux transporter activity in gill tissue of mussels. After exposure to rhodamine B and test compounds, the dye was extracted from the biopsy tissue disks in a defined volume of solvent, and the amount of dye was then measured fluorometrically. This approach gave results comparable with the epifluorescence microscopy procedure of measuring accumulation of fluorescent dye in living mussel gills (Cornwall et al. 1995; Eufemia and Epel 1998; Galgani et al. 1996) but was less susceptible to subjective errors connected with the microscopic assay, such as the selection of a tissue area to be measured.
Sample homogeneity.
The use of biopsy punches allowed us to obtain samples of equally sized tissue disks from gills from one individual. SDs of dry weight, protein content, and the amount of MXR transporter P-gp (detected with antibody C219 using Western blot techniques) varied by < 10% of the average values in disks from the same animal (data not shown). Furthermore, we found that transporter activity, indicated by the amount of rhodamine B accumulated by the tissue, was consistent among tissue disks from the same individual (e.g., the SD from 18 disks from one individual incubated in FSW with 1 μM rhodamine B was ± 6.5%).
Individual variation in transporter activity.
There were considerable differences in basal efflux transporter activity between individual animals. In control tissues, low basal efflux transporter activity is indicated by high accumulation of rhodamine B, whereas high basal efflux activity is indicated by low levels of rhodamine fluorescence (because more dye is effluxed from the cells). We found that these basal rhodamine fluorescence levels varied up to 3.3-fold between individuals. A significant correlation was found between transporter activity and mussel size (quantified by valve length; p = 0.003, n = 27), but there was no relationship to sex (p = 0.32, n = 27).
These differences in basal activity also correlated with increased uptake of rhodamine (and correspondingly rhodamine fluorescence) when transporter activity was maximally repressed by an inhibitory compound. Using a ratio of maximal fluorescence to basal fluorescence [RF(max)/F(basal)] to compare basal and repressed transporter activity, individuals with low basal transporter activity exhibited a low RF(max)/F(basal), whereas animals with high basal activity had a high ratio. For example, in a low-activity individual with 37.3 fluorescence units in its control, the RF(max)/F(basal) was 1.5, whereas in a high-activity individual with 11.3 fluorescence units in the control, the RF(max)/F(basal) was 3.8. A strong positive correlation (p = 6.2 × 10−8; r2 = 0.7; n = 27) was found for this relationship (Figure 1).
Physiologic indices and long-term exposure studies.
Experiments in which dissected gill tissue was kept in FSW for 48 hr necessitated an assessment of physiology over this period. Oxygen consumption rates measured in isolated gill tissue kept in FSW at 15°C were stable over a period of at least 3 days. Ciliary movement in gills was similarly stable for 3 days (indeed, ciliary movement was unaffected after 7 days of incubation). There were also no evident signs of morphologic deterioration in the tissue. Efflux transporter activity tended to slightly increase over time, as indicated by the lower amounts of rhodamine B in control tissues. After 24 hr, fluorescence values were lower by an average of 8%; after 48 hr they were 13% lower than initial values. A control was therefore run at each time point, and activity was normalized relative to the control tissue.
Inhibitory effects by test compounds, dose–effect relationships.
Musks and the P-gp inhibitor reference compounds quinidine and verapamil caused a dose-dependent increase in accumulation of rhodamine B in mussel gill tissue, indicating an inhibition of efflux transporter activity. IC10 and IC50 values were determined from the dose–effect curves (range of tested concentrations, 0.01–100 μM for musk compounds and quinidine, 0.001–10 μM for verapamil; using 6–11 concentrations per series, including controls). In most cases, curve fits (r
2) of the probit regressions were between 0.7 and 0.9. Musk concentrations above 5–10 μM did not increase rhodamine B fluorescence, indicating maximum inhibition of the transporter activity at these levels (Figure 2A–F).
The IC10 values, used as indicators for low-effect concentrations, showed clear effects in the 0.1–0.4 μM concentration range for musks and quinidine and at 0.01 μM for verapamil (Figure 2, Table 2). The range of IC50 values, which were used as a measure for the inhibitory potencies of the test compounds, was 0.7–2.6 μM for the musks and quinidine and 0.08 μM for verapamil (Figure 2, Table 2).
The nitromusks were more effective inhibitors than were the polycyclic musks. When combining the values for the two musk groups, the IC50 values for the nitromusks (IC50 = 0.82 ± 0.53 μM, n = 11) were significantly lower than for the polycyclic musks (IC50 = 2.34 ± 0.82 μM, n = 12; p = 0.0001, Student’s t-test).
Combinatory effects.
Synthetic musks are usually used in combinations in fragrances, and environmental samples often contain several different musk compounds. We therefore tested whether combinations of musks act in a synergistic, antagonistic, or additive fashion in inhibiting transporter activity. We tested treatments containing a) a nitromusk mixture (MX and MK), b) a polycyclic musk mixture (HHCB and ADBI), and c) a nitromusk/polycyclic musk mixture (MX and HHCB). For these experiments, each compound was applied at 0.5 μM to achieve a final total concentration of 1 μM musks. An additional experiment was run with a mixture of two nitromusks (MX and MK) and two polycyclics (HHCB and ADBI), with each compound at 0.25 μM. All compounds were also tested separately at 1 μM.
In all cases, inhibition of transporter activity by mixtures of different musk compounds was intermediate to treatments with single compounds (Figure 3). This indicates that the inhibitory effects of the musks in the mixtures were additive.
Long-term inhibitory effects.
We exposed mussel gill disks to test compounds for 2 hr and measured rhodamine uptake directly after the exposure (0 hr) and after 24 and 48 hr of washing the tissue in FSW. Immediately after exposure (0 hr) we incubated a sample of the disks in rhodamine B for 90 min; we found rhodamine uptake to be 38–84% higher in musk treatments compared with respective controls because of transporter inhibition (Figure 4A–F). After 24 hr of washing, another sample of disks was similarly incubated in rhodamine, and levels in the tissues previously exposed to the musks were still 30–74% higher than the controls, indicating continuing inhibition of transporter activity. The differences between treatments versus controls were significant for MX, HHCB, and ATII (p < 0.05, paired t-test), and there were clear trends of increased rhodamine levels also for MK, ADBI, and AHTN, indicating an inhibitor-related effect after 24 hr (Figure 4). A similar measurement of transport activity at 48 hr showed that activity had now reached the control levels for ATII and AHTN, indicating complete recovery from the inhibitory action of the musks. However, there was still a trend of reduced activity (i.e., higher fluorescence) for the tissues previously incubated in MX, MK, HHCB, and ADBI. The higher fluorescence was consistently seen with these four compounds, indicating an inhibitory effect of these musks even after this time period (Figure 4).
Verapamil, a P-gp reference inhibitor, exhibited strong long-term inhibition, indicated by rhodamine tissue levels that were 88 and 35% higher than the controls at 24 and 48 hr, respectively. In contrast, a different P-gp reference inhibitor, quinidine, showed no long-term effects, with almost complete reversal of inhibition seen after 24 hr of washing (Figure 4).
Discussion
The present study shows that nitromusk and polycyclic musk compounds inhibit the activity of efflux transporters in the marine mussel Mytilus californianus and that these inhibitory effects last for 24–48 hr after termination of exposure to the musks. As part of this work, we also describe an improved efflux transporter assay that allows processing large numbers of tissue samples from one individual and quantifying the potency of chemicals to inhibit MXR transporter activity.
MXR efflux inhibition by musks.
Both nitromusks and polycyclic musks inhibited efflux transporter activity, with the nitromusks being the more effective inhibitors. The tested musks inhibited transporter activity at a concentration range similar to that for quinidine but were an order of magnitude less effective than verapamil (Figure 2, Table 2). Furthermore, the inhibitory effects of combinations of musks were additive (Figure 3).
Individual mussels differed in basal transporter activity and in sensitivity to treatment with test agents. Differences in size and age may partly explain the variation in activity levels, but the variability is likely to reflect the heterogeneity of the natural population. Thus, stress response levels may be determined by genetic variation and site-specific conditions, such as time of water immersion during tides, wave exposure, temperature, and so forth (Roberts et al. 1997).
Despite this variation among test animals, differences between the different musk species in blocking rhodamine efflux through MXR transporters were clearly visible. These differences in inhibitory capacity most likely result from differences in affinity to substrate binding sites of the transporter, correlated with differences in Kow (octanol–water coefficient). Bain and LeBlanc (1996) found that the inhibitory efficiency of a chemical against human P-gp activity was highest for moderately hydrophobic compounds with a log Kow in the range of 3.6–4.5. This is consistent with our data showing that the nitromusks, with log Kow values of 4.3 and 4.9, were more efficient inhibitors than the more hydrophobic polycyclic musk compounds, with log Kow values 5.6–6.3 (Table 1). In fact, IC50 values for the musk compounds were strongly correlated with respective log Kow values (p = 0.0006, r2 = 0.9, n = 6; Figure 5), consistent with the lower inhibitory potency of compounds with a higher hydrophobicity. Verapamil, which was the most effective P-gp inhibitor in our study, also fits the regression line calculated for the musks. Quinidine, however, was less effective as an inhibitor and did not fit this regression line; consistent with its Kow, which is below the Kow range for high-affinity P-gp substrates (Figure 5).
The sensitivity of rhodamine efflux to verapamil, quinidine, and other known P-gp inhibitors/substrates indicates that the MXR phenomenon in Mytilus is associated with a P-gp–like efflux transporter (Cornwall et al. 1995; Galgani et al. 1996; Minier et al. 1993; Smital et al. 2003). Other transporters, such as an MRP (Lüdeking and Köhler 2002), may be present, but the substrate and inhibitor profile suggests a dominant activity of a P-gp type transporter, which is most likely the target of the musk compounds.
Long-term inhibitory effects of musks.
Inhibitory effects of musk compounds and verapamil were still present 24–48 hr after removal of the inhibitors (Figure 4). To our knowledge, this is the first demonstration of long-term inhibitory effects of MXR modulators. These results were unexpected because efflux transporters are involved in removal of xenobiotics from cells; therefore, quicker recovery of the transporter activity would have been anticipated.
The inhibition indicates that the musks and verapamil remain accessible to the efflux transporters for 24–48 hr after removal of the compounds from the medium. This could be related to the hydrophobicity of the compounds and/or their affinity for the transporters. Hydrophobic compounds will accumulate in the cell membrane during exposure and could affect efflux transporters indirectly through membrane effects (Ferté 2000), or the membranes could directly serve as reservoirs for slow release of the chemicals, which could then bind to the active sites of the transporter proteins. Alternatively, the chemicals might have a high affinity for specific sites of the transporters such as substrate binding sites or other functional sites (e.g., ATP-binding site) from where they are only slowly released, with resultant long-term inhibition.
Potential environmental relevance of synthetic musks as chemosensitizers.
It was first suggested by Kurelec (1997) that environmental pollutants may act as chemosensitizers by compromising the MXR system, allowing other toxicants, which would normally be excluded by the MXR transporters, to enter the cell. Kurelec pointed out that chemosensitizers could include chemicals of low toxicity, which would present an unanticipated environmental or human health risk. A broad range of anthropogenic chemicals such as pesticides, pharmaceuticals, and some polyaromatic hydrocarbons have been found to inhibit MXR transporters by blocking efflux of fluorescent or radio-labeled substrates in human cells or cells of aquatic organisms (Bain and LeBlanc 1996; Britvic and Kurelec 1999; Cornwall et al. 1995; Eufemia and Epel 1998; Kurelec 1992; Smital and Kurelec 1998b; Toomey and Epel 1993). When water samples from differently contaminated field sites were tested for their inhibitory potential for MXR transporters, greater inhibition by samples containing high levels of anthropogenic pollutants was detected (Smital and Kurelec 1997). This suggests that levels of anthropogenic pollutants currently found in the environment have the potential to interfere with normal animal defense mechanisms. Recent extensions of this work have shown that these MXR chemosensitizers increased the potency of toxic or mutagenic transporter substrates (Britvic and Kurelec 1999; Smital and Kurelec 1998a).
Our data indicate that synthetic musks are also chemosensitizers and could therefore have indirect effects by allowing normally excluded toxicants to permeate cells. Earlier studies have pointed to other indirect toxic effects of nitromusks. For example, MK and MX both induce P450-dependent oxygenases (Lehman-McKeeman et al. 1995; Mersch-Sundermann et al. 1996, 2001; Suter-Eichenberger et al. 1999) and therefore could cause increased transformation of other environmental chemicals that are mutagenic in their transformed form such as benzo(a)pyrene, 2-aminoanthracene, and aflatoxin B1 (Mersch-Sundermann et al. 1996, 2001).
Do the effects of synthetic musks as MXR inhibitors apply to real-world situations? The concentration range in which musks are effective inhibitors [10−6–10−7 M (ppb) range] is several orders of magnitude higher than concentrations reported for water samples from the environment [10−9–10−12 M (ppt) range] (Rimkus 1999). However, musks are concentrated in sediments (Winkler et al. 1998), which could make them available to bottom dwellers. More important, their hydrophobicity results in bioaccumulation and levels in tissues of aquatic organisms are 101- to 104-fold higher, and in the lipid fraction may be > 105-fold above environmental levels (Gatermann et al. 2002; Rimkus 1999). Association with lipids may be especially relevant to MXR transporters, which reside in the cell membrane and hence are more directly exposed to fat-soluble compounds such as the musks. These considerations indicate that even if ambient concentrations are low, long-term exposure will lead to tissue burdens that could inhibit MXR function indirectly via membrane effects or directly via high-affinity binding to transporter sites.
The unexpected long-term effects of the musks are troubling. One consequence of such long-term inhibition of transporters is that short-term events could have continuing consequences. Thus, the effects of short-term incidents such as storm-water runoffs or chemical spills could continue after such events if there is accumulation of chemosensitizers in the tissue, or prolonged inhibition as a result of the acute exposure.
Musks are typically present in the environment with other contaminants (Fromme et al. 2001; Kallenborn et al. 1999) that could well include other transporter modulators. As shown, the effects of combinations of P-gp inhibitors are additive, and therefore musks could be part of a suite of pollutants that contribute to chemosensitizing effects in nature. In fact, as first suggested by Daughton and Ternes (1999), this could be an unanticipated consequence of chemicals such as the PPCPs. Additive effects of low concentrations of many compounds could affect the MXR transporters, and this would be magnified by the sheer numbers of different components of the PPCPs.
Musks and other environmental chemosensitizers—a human health risk?
This work on the musks, although focused on aquatic organisms, also points to unsuspected effects of these chemicals on human health. MXR efflux pumps are widely distributed in mammalian tissues, where they are a crucial part of the cellular defense against cytotoxins (Cordon-Cardo et al. 1990). The effects of environmental contaminants as chemosensitizers have not been studied in humans; however, inhibitors of efflux transporters used in cancer therapy can lead to increased permeability of healthy tissues to transporter substrates (Luker et al. 1997), indicating that chemosensitizers could pose a health threat.
Because synthetic musks are present in human tissue samples, the question arises of whether they could also be relevant as chemosensitizers in humans. Concentrations of MX found in body fat and breast milk are in the range of 0.2–0.3 μmol/kg, and are in the nanomolar range in blood plasma (Käfferlein et al. 1998). These values represent body burdens that are one to two orders of magnitude below the effective concentrations seen in the present study on mussel tissue; however, they could contribute to additive effects with other compounds.
The present study especially points to the need to screen musks and other environmental chemicals that accumulate in humans to determine if they are also chemosensitizers of MXR-related transporters. It will be especially critical to ascertain whether they cause long-term effects similar to those seen in our study. Effects on efflux systems could result in unanticipated accumulation of toxicants in humans and confound safety predictions of seemingly innocuous chemicals.
Figure 1 Correlation between basal transporter activity [F(basal)] and relative increase in fluorescence in mussel gill tissue with transporter activity inhibited maximally versus basal transporter activity [RF(max)/F(basal)]. y = −0.07x + 3.93.
Figure 2 Dose–effect curves for in vivo inhibition of MXR transporters in mussel gill tissue by nitromusks [MX (A) and MK (B)], polycyclic musks [HHCB (C), ADBI (D), AHTN (E), and ATII (F)], and reference inhibitors [verapamil (G) and quinidine (H)]. See “Materials and Methods” for details. Each curve represents data (obtained by probit regression) from an individual animal.
Figure 3 Inhibitory effects by musks as single compounds and in combinations as measured by retention of rhodamine B (see “Materials and Methods” for details). Bars represent percent increase (mean ± SD) of fluorescence versus respective controls; n = 7 for experiments with solvent, 1 μM MX, 1 μM MK, 1 μM HHCB, and 1 μM ADBI; n = 3 for MX + HHCB, MX + MK, HHCB + ADBI, and MX + MK + HHCB + ADBI. Brackets indicate experiments that are compared.
Figure 4 Long-term inhibition of efflux transporters by nitromusks [MX (A) and MK (B)], polycyclic musks [HHCB (C), ADBI (D), AHTN (E), and ATII (F)], and reference inhibitors [verapamil (G) and quinidine (H)]. Bars represent fluorescence versus respective controls (mean % ± SD); n = 3 (11 for verapamil).
*p < 0.05 by paired t-test.
Figure 5 Correlation of MXR inhibitory efficiency (indicated by IC50 values) and log Kow of test compounds. Abbreviations: QUI, quinidine; VER, verapamil. For the calculation of the regression curve, (with 95% confidence intervals) only musk compounds were included.
Table 1 Names, CAS numbers, formulas, structures, molecular weights, and log Kow values for artificial musks and MXR model substrates and inhibitors.
Chemical and trade names CAS No. Formula Structure Molecular weight Log Kow
Musk xylene (MX) 1-tert-Butyl-3,5-dimethyl-2,4,6-trinitrobenzene 81–15–2 C12H15N3O6 297.3 4.9a
Musk ketone (MK) 1-tert-Butyl-3,5-dimethyl-2,6-dinitro-4-acetylbenzene 81–14–1 C14H18N2O5 294.3 4.3a
Galaxolide (HHCB) 1,3,4,6,7,8-Hexahydro-4,6,6,7,8,8-hexamethyl-cyclopenta-γ-[2]-benzopyran 1222–05–5 C18H26O 258.4 5.9a
Celestolide, Crysolide (ADBI) 4-Acetyl-1,1-dimethyl-6-tert-butylindane 13171–00–1 C17H24O 244.4 5.9a
Tonalide, Tetralide, Fixolide (AHTN) 7-Acetyl-1,1,3,4,4,6-hexamethyl-tetrahydronaphthalene 21145–77–7 C18H26O 244.4 5.7a
Traseolide (ATII) 5-Acetyl-1,1,2,6-tetramethyl-3-isopropylindane 68140–48–7 C18H26O 258.4 6.3a
Quinidine 56–54–2 C20H24N2O2 324.4 2.8b
Verapamil 52–53–9 C27H38N2O4 454.6 4.5b
Rhodamine B 81–88–9 C28H31ClN2O3 479.0 1.5c
a Data from Balk et al. (2001).
b Data from Wang et al. (2003).
c Data from Liu (2004).
Table 2 IC10 and IC50 values (mean ± SD) of nitromusks, polycyclic musks, and reference inhibitors verapamil and quinidine for efflux transporters in mussel gills.
IC10 IC50 n
Nitromusks
MX 0.14 ± 0.12 0.97 ± 0.63 4
MK 0.09 ± 0.12 0.74 ± 0.49 7
Polycyclic musks
HHCB 0.37 ± 0.16 2.43 ± 0.45 3
ADBI 0.39 ± 0.34 2.32 ± 1.18 3
AHTN 0.35 ± 0.31 2.05 ± 0.31 3
ATII 0.32 ± 0.04 2.56 ± 0.07 3
Verapamil 0.01 ± 0.02 0.08 ± 0.07 6
Quinidine 0.24 ± 0.20 1.59 ± 0.85 3
Data were obtained by probit regression.
==== Refs
References
Api AM Smith RL Pipino S Marczylo T De Matteis F 2004 Evaluation of the oral subchronic toxicity of AHTN (7-acetyl-1,1,3,4,4,6-hexamethyl-1,2,3,4-tetrahydronaphthalene) in the rat Food Chem Toxicol 42 5 791 801 15046825
Bain LJ LeBlanc GA 1996 Interaction of structurally diverse pesticides with the human MDR1 gene product P-glycoprotein Toxicol Appl Pharmacol 141 1 288 298 8917702
Bain LJ McLachlan JB LeBlanc GA 1997 Structure–activity relationships for xenobiotic transport substrates and inhibitory ligands of P-glycoprotein Environ Health Perspect 105 812 818 9347896
Balk F Blok H Salvito D 2001. Environmental risks of musk fragrance ingredients. In: Pharmaceuticals and Personal Care Products in the Environment—Scientific and Regulatory Issues (Daughton CG, Jones-Lepp TL, eds). Washington, DC:American Chemical Society, 168–190.
Balk F Ford RA 1999a Environmental risk assessment for the polycyclic musks AHTN and HHCB in the EU. I. Fate and exposure assessment Toxicol Lett 111 1–2 57 79 10630703
Balk F Ford RA 1999b Environmental risk assessment for the polycyclic musks, AHTN and HHCB. II. Effect assessment and risk characterisation Toxicol Lett 111 1–2 81 94 10630704
Behechti A Schramm KW Attar A Niederfellner J Kettrup A 1998 Acute aquatic toxicities of four musk xylene derivatives on Daphnia magna Water Res 32 5 1704 1707
Bester K Hühnerfuss H Lange W Rimkus GG Theobald N 1998 Results of non target screening of lipophilic organic pollutants in the German Bight II: polycyclic musk fragrances Water Res 32 6 1857 1863
Bitsch N Dudas C Körner W Failing K Biselli S Rimkus G 2002 Estrogenic activity of musk fragrances detected by the E-screen assay using human MCF-7 cells Arch Environ Contam Toxicol 43 3 257 264 12202919
Breitholtz M Wollenberger L Dinan L 2003 Effects of four synthetic musks on the life cycle of the harpacticoid copepod Nitocra spinipes Aquat Toxicol 63 2 103 118 12657486
Britvic S Kurelec B 1999 The effect of inhibitors of multixenobiotic resistance mechanism on the production of mutagens by Dreissena polymorpha in waters spiked with premutagens Aquat Toxicol 47 2 107 116
Chou YJ Dietrich DR 1999a Interactions of nitromusk parent compounds and their amino-metabolites with the estrogen receptors of rainbow trout (Oncorhynchus mykiss ) and the South African clawed frog (Xenopus laevis ) Toxicol Lett 111 1–2 27 36 10630701
Chou YJ Dietrich DR 1999b Toxicity of nitromusks in early lifestages of South African clawed frog (Xenopus laevis ) and zebrafish (Danio rerio ) Toxicol Lett 111 1–2 17 25 10630700
Cordon-Cardo C O’Brien JP Boccia J Casals D Bertino JR Melamed MR 1990 Expression of the multidrug resistance gene product (P-glycoprotein) in human normal and tumor tissues J Histochem Cytochem 38 9 1277 1287 1974900
Cornwall R Toomey BH Bard S Bacon C Jarman WM Epel D 1995 Characterization of multixenobiotic/multidrug transport in the gills of the mussel Mytilus californianus and identification of environmental substrates Aquat Toxicol 31 277 296
Daughton CG Ternes TA 1999 Pharmaceuticals and personal care products in the environment: agents of subtle change? Environ Health Perspect 107 suppl 6 907 938 10592150
Draisci R Marchiafava C Ferretti E Palleschi L Catellani G Anastasio A 1998 Evaluation of musk contamination of freshwater fish in Italy by accelerated solvent extraction and gas chromatography with mass spectrometric detection J Chromatogr A 814 1–2 187 197 9718694
Epel D 1998 Use of multidrug transporters as first lines of defense against toxins in aquatic organisms Comp Biochem Physiol A 120 23 28
Epel D Smital T 2001. Multidrug-multixenobiotic transporters and their significance with respect to environmental levels of pharmaceuticals and personal care products. In: Pharmaceuticals and Personal Care Products in the Environment—Scientific and Regulatory Issues (Daughton CG, Jones-Lepp TL, eds). Washington, DC:American Chemical Society, 244–263.
Eufemia NA Epel D 1998 The multixenobiotic defense mechanism in mussels is induced by substrates and non-substrates: implications for a general stress response Mar Environ Res 46 1–5 401 405
Ferté J 2000 Analysis of the tangled relationships between P-glycoprotein-mediated multidrug resistance and the lipid phase of the cell membrane Eur J Biochem 267 2 277 294 10632698
Fromme H Otto T Pilz K 2001 Polycyclic musk fragrances in different environmental compartments in Berlin (Germany) Water Res 35 1 121 128 11257865
Frosch PJ Pilz B Andersen KE Burrows D Camarasa JG Dooms-Goossens A 1995 Patch testing with fragrances: results of a multicenter study of the European Environmental and Contact Dermatitis Research Group with 48 frequently used constituents of perfumes Contact Dermatitis 33 5 333 342 8565489
Galgani F Cornwall R Toomey BH Epel DD 1996 Interaction of environmental xenobiotics with a multixenobiotic defense mechanism in the bay mussel Mytilus galloprovincialis from the coast of California Environ Toxicol Chem 15 3 325 331
Gatermann R Biselli S Hühnerfuss H Rimkus GG Hecker M Karbe L 2002 Synthetic musks in the environment. Part 1: Species-dependent bioaccumulation of polycyclic and nitro musk fragrances in freshwater fish and mussels Arch Environ Contam Toxicol 42 4 437 446 11994785
Käfferlein HU Angerer J 2001 Trends in the musk xylene concentrations in plasma samples from the general population from 1992/1993 to 1998 and the relevance of dermal uptake Int Arch Occup Environ Health 74 7 470 476 11697449
Käfferlein HU Goen T Angerer J 1998 Musk xylene: analysis, occurrence, kinetics, and toxicology Crit Rev Toxicol 28 5 431 476 9793747
Kallenborn R Gatermann R Rimkus GG 1999 Synthetic musks in environmental samples: indicator compounds with relevant properties for environmental monitoring J Environ Monit 1 4 70N 74N
Kester M Bulduk S Tibboel D Meinl W Glatt H Falany C 2000 Potent inhibition of estrogen sulfotransferase by hydroxylated PCB metabolites: a novel pathway explaining the estrogenic activity of PCBs Endocrinology 141 5 1897 1900 10803601
Kupper T Berset JD Etter-Holzer R Furrer R Tarradellas J 2004 Concentrations and specific loads of polycyclic musks in sewage sludge originating from a monitoring network in Switzerland Chemosphere 54 8 1111 1120 14664839
Kurelec B 1992 The multixenobiotic resistance mechanism in aquatic organisms Crit Rev Toxicol 22 23 43 1352103
Kurelec B 1995 Reversion of the multixenobiotic resistance mechanism in gills of marine mussel Mytilus galloprovincialis by a model inhibitor and environmental modulators of P170-glycoprotein Aquat Toxicol 33 93 103
Kurelec B 1997 A new type of hazardous chemical: the chemosensitizers of multixenobiotic resistance Environ Health Perspect 105 suppl 4 855 860 9255572
Lehman-McKeeman LD Caudill D Young JA Dierckman TA 1995 Musk xylene induces and inhibits mouse hepatic cytochrome P-450 2B enzymes Biochem Biophys Res Commun 206 3 975 980 7832813
Liebl B Ehrenstorfer S 1993 Nitromoschusverbindungen in der Frauenmilch [in German] Gesundheitswesen 55 10 527 532 8268706
Liu Z 2004 Confocal laser scanning microscopy—an attractive tool for studying the uptake of xenobiotics into plant foliage J Microsc 213 2 87 93 14731289
Luckenbach T Corsi I Epel D 2004 Fatal attraction: synthetic musk fragrances compromise multixenobiotic defense systems in mussels Mar Environ Res 58 2–5 215 219 15178035
Lüdeking A Köhler A 2002 Identification of six mRNA sequences of genes related to multixenobiotic resistance (MXR) and biotransformation in Mytilus edulis Mar Ecol-Prog Ser 238 115 124
Luker GD Fracasso PM Dobkin J Piwnica-Worms D 1997 Modulation of the multidrug resistance P-glycoprotein: detection with technetium-99m-sestamibi in vivo J Nucl Med 38 3 369 372 9074520
Mersch-Sundermann V Emig M Reinhardt A 1996 Nitro musks are cogenotoxicants by inducing toxifying enzymes in the rat Mutat Res 356 2 237 245 8841491
Mersch-Sundermann V Schneider H Freywald C Jenter C Parzefall W Knasmuller S 2001 Musk ketone enhances benzo(a )pyrene induced mutagenicity in human derived Hep G2 cells Mutat Res 495 1–2 89 96 11448646
Minier C Akcha F Galgani F 1993 P-glycoprotein expression in Crassostrea gigas and Mytilus edulis in polluted seawater Comp Biochem Physiol B 106 4 1029 1036 7905372
Neyfakh AA 1988 Use of fluorescent dyes as molecular probes for the study of multidrug resistance Exp Cell Res 174 1 168 176 3335222
Osemwengi LI Steinberg S 2001 On-site solid-phase extraction and laboratory analysis of ultra-trace synthetic musks in municipal sewage effluent using gas chromatographymass spectrometry in the full-scan mode J Chromatogr A 932 1–2 107 118 11695855
Ott M Failing K Lang U Schubring C Gent HJ Georgii S 1999 Contamination of human milk in Middle Hesse, Germany—a cross-sectional study on the changing levels of chlorinated pesticides, PCB congeners and recent levels of nitro musks Chemosphere 38 1 13 32 10903088
Paasivirta J Sinkkonen S Rantalainen AL Broman D Zebuhr Y 2002 Temperature dependent properties of environmentally important synthetic musks Environ Sci Pollut Res Int 9 5 345 355 12391811
Peck AM Hornbuckle KC 2004 Synthetic musk fragrances in Lake Michigan Environ Sci Technol 38 2 367 372 14750709
Ricking M Schwarzbauer J Hellou J Svenson A Zitko V 2003 Polycyclic aromatic musk compounds in sewage treatment plant effluents of Canada and Sweden: first results Mar Pollut Bull 46 4 410 417 12705913
Rimkus GG 1999 Polycyclic musk fragrances in the aquatic environment Toxicol Lett 111 1–2 37 56 10630702
Rimkus GG Butte W Geyer HJ 1997 Critical considerations on the analysis and bioaccumulation of musk xylene and other synthetic nitro musks in fish Chemosphere 35 7 1497 1507
Rimkus GG Gatermann R Hühnerfuss H 1999 Musk xylene and musk ketone amino metabolites in the aquatic environment Toxicol Lett 111 1–2 5 15 10630699
Rimkus GG Wolf M 1995 Nitro musk fragrances in biota from freshwater and marine environment Chemosphere 30 4 641 651
Rimkus GG Wolf M 1996 Polycyclic musk fragrances in human adipose tissue and human milk Chemosphere 33 10 2033 2043 8930104
Roberts DA Hofmann GE Somero GN 1997 Heat-shock protein expression in Mytilus californianus : acclimatization (seasonal and tidal-height comparisons) and acclimation effects Biol Bull 192 2 309 320
Sanderson J Letcher R Heneweer M Giesy J van den Berg M 2001 Effects of chloro-s -triazine herbicides and metabolites on aromatase activity in various human cell lines and on vitellogenin production in male carp hepatocytes Environ Health Perspect 109 1027 1031 11675267
Schmeiser HH Gminski R Mersch-Sundermann V 2001 Evaluation of health risks caused by musk ketone Int J Hyg Environ Health 203 4 293 299 11434209
Smital T Kurelec B 1997 Inhibitors of the multixenobiotic resistance mechanism in natural waters: in vivo demonstration of their effects Environ Toxicol Chem 16 10 2164 2170
Smital T Kurelec B 1998a The activity of multixenobiotic resistance mechanism determined by rhodamine B-efflux method as a biomarker of exposure Mar Environ Res 46 1–5 443 447
Smital T Kurelec B 1998b The chemosensitizers of multixenobiotic resistance mechanism in aquatic invertebrates: a new class of pollutants Mutat Res 399 1 43 53 9635488
Smital T Luckenbach T Sauerborn R Hamdoun AM Vega RL Epel D 2004 Emerging contaminants—pesticides, PPCPs, microbial degradation products and natural substances as inhibitors of multixenobiotic defense in aquatic organisms Mutat Res 552 1–2 101 117 15288544
Smital T Sauerborn R Hackenberger BK 2003 Inducibility of the P-glycoprotein transport activity in the marine mussel Mytilus galloprovincialis and the freshwater mussel Dreissena polymorpha Aquat Toxicol 65 4 443 465 14568358
Suter-Eichenberger R Boelsterli UA Conscience-Egli M Lichtensteiger W Schlumpf M 1999 CYP 450 enzyme induction by chronic oral musk xylene in adult and developing rats Toxicol Lett 111 1–2 117 132 10630707
Tas JW Balk F 1997. Environmental Risk Assessment of the Polycyclic Musks AHTN and HHCB According to the EU-TGD. RIVM Report No. 601 503 008. Bilthoven, Netherlands:National Institute of Public Health and the Environment.
Tas JW Balk F Ford RA van de Plassche EJ 1997 Environmental risk assessment of musk ketone and musk xylene in the Netherlands in accordance with the EU-TGD Chemosphere 35 12 2973 3002 9415982
Toomey BH Epel D 1993 Multixenobiotic resistance in Urechis caupo embryos: protection from environmental toxins Biol Bull 185 355 364
Wang RB Kuo CL Lien LL Lien EJ 2003 Structure-activity relationship: analyses of P-glycoprotein substrates and inhibitors J Clin Pharm Ther 28 3 203 228 12795780
White KM 1937. Mytilus. Liverpool, UK:University Press of Liverpool.
Winkler M Kopf G Hauptvogel C Neu T 1998 Fate of artificial musk fragrances associated with suspended particulate matter (SPM) from the River Elbe (Germany) in comparison to other organic contaminants Chemosphere 37 6 1139 1156
Wollenberger L Breitholtz M Ole Kusk K Bengtsson BE 2003 Inhibition of larval development of the marine copepod Acartia tonsa by four synthetic musk substances Sci Total Environ 305 1–3 53 64 12670757
Yamagishi T Miyazaki T Horii S Akiyama K 1983 Synthetic musk residues in biota and water from Tama River and Tokyo Bay (Japan) Arch Environ Contam Toxicol 12 1 83 89 6830312
Yamagishi T Miyazaki T Horii S Kaneko S 1981 Identification of musk xylene and musk ketone in freshwater fish collected from the Tama River, Tokyo Bull Environ Contam Toxicol 26 5 656 662 7260436
|
15626642
|
PMC1253704
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan 30; 113(1):17-24
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7301
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7431ehp0113-00002515626643ResearchArticlesAssessment of Autoimmune Responses Associated with Asbestos Exposure in Libby, Montana, USA Pfau Jean C. Sentissi Jami J. Weller Greg Putnam Elizabeth A. Center for Environmental Health Sciences, Department of Biomedical and Pharmaceutical Sciences, University of Montana, Missoula, Montana, USAAddress correspondence to J.C. Pfau, Center for Environmental Health Sciences, Department of Biomedical and Pharmaceutical Sciences, Skaggs 154, University of Montana, Missoula, MT 59812 USA. Telephone: (406) 243-4529. Fax: (406) 243-2807. E-mail:
[email protected] thank the subjects, families, and the Center for Asbestos Related Diseases Clinic in Libby, MT; R. Hamilton [Center for Environmental Health Sciences (CEHS) biostatistics], C. Noonan (CEHS epidemiology), and M. Fritzler, University of Calgary (rheumatology) for their expertise; and T. Larson, Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry, for Tremolite Asbestos Registry data.
This work was supported by National Institutes of Health grants ES-04804 (J.C.P.) and ES-11676 (E.A.P.) and National Research Service Award ES-11249 (J.C.P.).
The authors declare they have no competing financial interests.
1 2005 30 9 2004 113 1 25 30 16 7 2004 30 9 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Systemic autoimmune responses are associated with certain environmental exposures, including crystalline particles such as silica. Positive antinuclear antibody (ANA) tests have been reported in small cohorts exposed to asbestos, but many questions remain regarding the prevalence, pattern, and significance of autoantibodies associated with asbestos exposures. The population in Libby, Montana, provides a unique opportunity for such a study because of both occupational and environmental exposures that have occurred as a result of the mining of asbestos-contaminated vermiculite near the community. As part of a multifaceted assessment of the impact of asbestos exposures on this population, this study explored the possibility of exacerbated autoimmune responses. Age- and sex-matched sets of 50 serum samples from Libby and Missoula, Montana (unexposed), were tested for ANA on HEp-2 cells using indirect immunofluorescence. Data included frequency of positive tests, ANA titers, staining patterns, and scored fluorescence intensity, all against known controls. Serum immunoglobulin A (IgA), rheumatoid factor, and antibodies to extractable nuclear antigen (ENA) were also tested. The Libby samples showed significantly higher frequency of positive ANA and ENA tests, increased mean fluorescence intensity and titers of the ANAs, and higher serum IgA, compared with Missoula samples. In the Libby samples, positive correlations were found between ANA titers and both lung disease severity and extent of exposure. The results support the hypothesis that asbestos exposure is associated with autoimmune responses and suggests that a relationship exists between those responses and asbestos-related disease processes.
asbestosANAenvironmental autoimmunityimmunotoxicology
==== Body
Asbestos-related lung disease (ARD), including fibrosis, pleural plaques, and cancer, continues to be a serious and significant problem despite increasing awareness of the health hazards of asbestos inhalation. Although the exact mechanisms leading to the progression of these conditions have not been fully explained, there is evidence that some of the lung pathologies seen with both asbestos and silica exposures are immunologically mediated (Hamilton et al. 1996; Holian et al. 1997; Perkins et al. 1993). Silica and asbestos exposures also both appear to exacerbate autoimmune responses. Epidemiologic studies have shown strong associations between silica exposure and several autoimmune diseases, including scleroderma, systemic lupus erythematosus (SLE), and rheumatoid arthritis (RA) (Koeger et al. 1995; Parks et al. 1999; Powell et al. 1999; Steenland and Goldsmith 1995). Increased serum immunoglobulins, positive antinuclear antibody (ANA) tests, and immune complexes have been reported in small cohorts of individuals exposed to asbestos (Lange 1980; Nigam et al. 1993; Zerva et al. 1989), but to our knowledge no comprehensive study has been undertaken to assess the prevalence, specificity, and significance of autoantibodies associated with asbestos exposures. The population in Libby provides a unique research opportunity because of significant exposures that occurred as a result of the mining of asbestos-contaminated vermiculite near the community. Exposures have been documented not only in the miners but also in their family members, as well as anyone who used the vermiculite or played near the mine tailings. Therefore, the Libby asbestos exposures were both occupational and environmental throughout the community (Peipins et al. 2003).
In addition to the ARD in Libby, there have been anecdotal reports of an increased prevalence of systemic autoimmune disease (SAID), but verification of these diagnoses is still in progress. When the Centers for Disease Control and Prevention/Agency for Toxic Substances and Disease Registry (ATSDR) performed its screening in Libby during 2000–2001, 494 (6.7%) of 7,307 screening participants indicated that they had been diagnosed with either SLE, scleroderma, or RA (Larson T, personal communication). In contrast, a prevalence of < 1% for these three conditions combined would be expected based on pooled estimates from 43 prevalence studies (Jacobson et al. 1997). These data, along with extensive evidence of silica-associated auto-immunity, provided the impetus to initiate a multifaceted assessment of the impact of asbestos exposures on the population of Libby, Montana, including possible autoimmune responses.
In this article we report on a study designed to assess whether there were humoral alterations in serum samples from an asbestos-exposed population (Libby samples) that might indicate autoimmune responses, providing the rationale for future full-scale studies. Serum samples of subjects from Libby and from a Montana community with no reported asbestos exposure were assayed for a variety of immune parameters, including ANA, immunoglobulin A (IgA), rheumatoid factor (RF), and antibodies to extractable nuclear antigens (ENA).
Materials and Methods
Human samples.
All samples were acquired according to approved University of Montana institutional review board protocols, protecting the well-being and confidentiality of all subjects. Appropriate informed consent was obtained from all subjects, and a questionnaire was administered regarding overall health, smoking status, asbestos exposure, age, sex, and recontact information.
Two sample pools were obtained through other studies at the Center for Environmental Health Sciences. Subjects were recruited through flyers and ads in Missoula, Montana, for a study of immune function (E. Putnam), and serum samples were collected at the same time for convenience. Missoula is similar to Libby in that it is located in a mountain valley subject to similar climatic conditions, including winter inversions, dry summers, and exposure to smoke from fall forest fires. Because prevailing winds in Missoula are from the west and Libby is well to the north, there would be no transfer of asbestos from the Libby airshed to the Missoula airshed. Therefore, on a relative basis, although one cannot exclude the possibility that there could have been some minimal asbestos exposure by the Missoula population, it is an acceptable reference population for the Libby subjects who were definitely exposed to asbestos. For this study, we selected 50 samples from subjects with no reported asbestos exposure from the Missoula pool, excluding any who had lived or worked in Libby. Concurrently, subjects were being recruited from Libby, Montana, for a genetic study of ARD susceptibility (E. Putnam), and the samples were drawn at the Center for Asbestos Related Diseases Clinic in Libby when subjects came for screening or responded to subject recruitment advertisements. From this pool, 50 Libby subjects were selected that were matched to the 50 Missoula subjects to give similar mean age and sex ratios for the two subject sets. Permission was obtained to acquire information about prescription drug use and ARD status from medical records, and these data were inserted into a coded database.
Both communities from which subjects were drawn are fairly homogeneous in terms of ethnicity; most residents are of northern European descent, with 94.7% white in Lincoln County (Libby) and 93.6% white in Missoula County (Missoula) according to Montana census data (U.S. Census Bureau 2004). The mean age for both sample sets was 55 years (Missoula, 54.8 ± 2.5 years; Libby, 55.0 ± 2.1 years), and the male:female ratio was 25:25 for both sets. An exclusion criterion was the use of medications strongly associated with drug-induced autoimmunity (Fritzler 1994). The presence of diagnosed autoimmune disease did not exclude individuals from either sample set but was noted on intake. None of the Missoula subjects recruited had diagnosed SAID. Of the Libby subjects recruited initially for the genetics study, the percentage with diagnosed SAID was 5.9%, and in the final Libby sample set of 50, there were two with SLE, 1 with multiple sclerosis, and 1 with RA. Because the individual with RA also had SLE, this means that three people in 50 had SAID (6%). These values are consistent with the ATSDR screening data for this community (Larson T, personal communication).
The lung diseases in this community have been previously described (Peipins et al. 2003) and include primarily pleural abnormalities (17.8%) and interstitial abnormalities (< 1%). In our Libby sample set, 12 (24%) had no reported abnormalities, 27 (54%) had pleural abnormalities, 8 (16%) had interstitial abnormalities, and 3 (6%) had a combination of pleural and interstitial abnormalities.
Sample and data collection.
The blood samples were collected, and serum samples were obtained and frozen by standardized clinical methods to prevent differences due to handling. The samples were blinded with only sex and age noted, and stored at −80°C until assayed. After testing, coded information regarding disease status and exposure was obtained from the questionnaire and ATSDR screening data (ATSDR 2002).
ARD and asbestos exposure rankings.
ARD status, based on data recorded in the database primarily as a result of the ATSDR screenings, was ranked on a scale of 0–3, as described in Table 1. The rankings were intentionally simplified, based on radiographic evidence of single versus extensive plaques or interstitial abnormalities, as well as spirometry evidence of functional deficits. For example, a subject with a single pleural plaque and no functional deficit would be scored at 1, whereas a subject with bilateral plaques and effects on spirometry was scored at 3. To further break down the sample sets by disease types would have made the subsets too small for statistical analysis. Exposure status was ranked on a scale of 0–4, as described in Table 2. These scores were also simplified in order to focus on duration of exposure and the existence of occupational and/or environmental exposure to asbestos. The rankings of the Libby subjects were performed independently by two of the researchers (J.C.P. and E.A.P.).
Autoantibody testing.
A clinical test for nuclear antigens (ANA assay), used to screen for antibodies commonly seen in SAID, was performed at a screening dilution of the sera. All serum samples were diluted 1:40 in phosphate-buffered saline (PBS) and tested by indirect immunofluorescence (IIF) on a single lot of commercially prepared and fixed HEp-2 cells (ImmunoConcepts Inc., Sacramento, CA), according to manufacturer’s instructions. The staining pattern and relative fluorescence intensity were compared with known positive and negative controls using a Zeiss fluorescence microscope with 40× objective and recorded as positive (1+ to 4+) or negative (0). The staining pattern was also noted and recorded. The same microscope and settings were used for all samples, and the slides were read by two independent readers. Samples showing homogeneous staining patterns were reevaluated using the Crithidia luciliae substrate (ImmunoConcepts), which specifically detects antibodies to double-stranded DNA (dsDNA), and by enzyme-linked immunosorbent assay (ELISA) to detect antibodies to chromatin (INOVA Diagnostics, San Diego, CA), both according to the manufacturers’ instructions. Samples with positive ANAs were also evaluated using a modified ANA test to determine whether any of the anti-ANA antibodies were of the IgA isotype. The samples were tested on HEp-2 slides as above, but instead of the anti-human IgG fluorescein isothiocyanate (FITC) conjugate included with the slides, we used goat anti-human IgA FITC conjugate (Southern Biotech, Birmingham, AL). The slides were read as described above.
IgA ELISA.
For detection of serum IgA, the mucosal antibody isotype, 96-well polysorb plates (Nunc, Rochester, NY) were coated with 1 μg/mL of anti-human kappa light chain (Southern Biotech) in carbonate coating buffer overnight at 4°C. Wells were then blocked with PBS containing 1% bovine serum albumin (BSA) for 1 hr. Subject samples were diluted 1:4,000, 1:8,000, and 1:16,000 in diluent buffer (PBS, 1% BSA, 0.1% Tween-20). Samples, standards, and blanks were added to wells to give 100 μL/well. After 1 hr, plates were washed with three changes of PBS containing 0.1% Tween-20. The detection antibody [goat anti-human IgA alpha chain coupled to horseradish peroxidase (HRP); Caltag, Burlingame, CA] was added and the plates were incubated for 1 hr at room temperature. The plates were washed again and developed using HRP-tetramethylbenzidine (TMB) substrate (Zymed, San Francisco, CA). The reaction was stopped with 2N H2SO4, and the plate was read on a SpectraMax plate reader (Molecular Devices, Sunnyvale, CA). All data were evaluated against a standard curve, using human IgA (Sigma, St. Louis, MO).
RF ELISA.
RF in the subjects’ serum was measured with an ELISA kit according to the manufacturer’s protocol (INOVA Diagnostics). The plates were read on the SpectraMax plate reader. Optical density (OD) values were compared with known controls provided with the kit and rated as negative or positive (marginal, moderate, or high).
ENA array.
Analyses of antibodies to five extractable nuclear proteins commonly seen in SAID (Sm, RNP, SS-A, SS-B, and Scl-70) were performed using an addressable bead array kit (QuantaPlex ENA-5; INOVA Diagnostics) according to the manufacturer’s instructions, on a Luminex multiplex system (MiraiBio, Alameda, CA). The values were compared by using MasterPlex software (MiraiBio) to negative and graduated positive control reagents provided with the kit, and determined to be low, moderate, or high positive, or negative.
Statistics.
In this study we included analysis of several different types of data, including percentages/frequencies (e.g., ANA frequencies), ordinal (e.g., disease status assessed on a 4-point scale), and scale (e.g., mg/mL IgA) data. Consequently, we used the following statistical methods: a) differences in percentages were tested using raw frequencies with Fisher’s exact test; b) contingency tables with 4- and 5-point ordinal level frequency comparisons were made via the chi-square test; and c) independent sample t-tests were used for scale measures. In the Libby samples, comparisons (correlations) between ANA levels and disease and exposure rankings were made using the nonparametric Spearman rank correlation. In all analyses we used two-tailed, unpaired analyses, and reported 0.05 type I error levels. Data reported in the text are mean ± SEM.
Results
Frequency and fluorescence intensity of positive ANAs.
The 50 serum samples in each set were tested by IIF and were determined to be positive or negative for ANA based on known controls. Figure 1A shows that the relative frequency of positive ANAs was 28.6% higher in the Libby sample set than in the Missoula set (p = 0.006). Because low-titer positive ANAs are fairly common in normal populations, the ANA slides were scored for fluorescence intensity. The scored mean fluorescence intensity of positive ANAs, rated on a scale of 1–4 against known controls, was higher in the Libby sample set (mean = 2.34 ± 0.153) compared with those from Missoula (1.76 ± 0.194; p = 0.02), and the distribution of subjects receiving the various scores was shown to be significantly different between the sample sets (p = 0.004; Figure 1B). The scored fluorescence intensity is not a direct quantification of autoantibodies but generally suggests a higher titer. Therefore, the positive samples were subsequently titered to 1:1,280 and further analyzed for ANA. In both groups, the ANA scores and titers were highly correlated, suggesting that the scoring provides a close estimation of titer (Missoula: correlation coefficient = 0.502, p < 0.001; Libby: correlation coefficient = 0.828, p < 0.001; Table 3). We found that the distribution of titers for samples in the two sample sets were significantly different (p = 0.036; data not shown). The percentage of subjects having a positive ANA at a titer ≥320 is shown in Figure 1C, again showing a significant difference between the two sample sets.
IgA levels and RF.
Because other studies of asbestos-exposed populations have shown differences in serum IgA compared with unexposed subjects, serum IgA levels were analyzed by ELISA in our sample sets. The Libby samples showed significantly higher levels of serum IgA than the Missoula samples (Figure 2). Although both sample sets had mean IgA concentrations within normal ranges (~ 0.9–4.5 mg/mL), the Libby mean was at the high end of the range (4.2 mg/mL). The ANA tests were subsequently modified to detect IgA rather than IgG, and all of the ANA tests were negative in both sample sets, indicating that the autoantibodies were most likely primarily IgG and not IgA (data not shown).
RF consists of IgM or IgG antibodies directed against the constant domain of immunoglobulin. These autoantibodies can lead to immune complex deposition in tissues and are associated with a variety of infectious and inflammatory disorders such as RA. The samples were evaluated for IgM RF by ELISA, and there were no differences in either the mean OD calculated for each sample set or the frequency of positive tests for RF (Figure 3).
Staining patterns on ANAs.
To determine the specific targets for the IgG autoantibodies, we analyzed the patterns visible on the ANA tests. In the Missoula samples, a nuclear speckled staining pattern was most common, as expected in a normal population (speckled, 14%; homogeneous, 12%; nucleolar, 10%). Other staining patterns were relatively rare, as expected. However, in the Libby samples, homogeneous (indicative of antibodies to chromatin) and nucleolar staining patterns were more prevalent, although the differences were not statistically significant (speckled, 18%; homogeneous, 22%; nucleolar, 18%). We tested for specific antibodies related to these IIF patterns using an ELISA for chromatin and an IIF assay for anti-dsDNA (Crithidia luciliae test). The results indicated that although 22% of the Libby group had homogeneous staining patterns, less than half of those were positive for either chromatin or dsDNA (Figure 4). This suggests that either individual histones not available for binding in chromatin preparations (i.e., H3, H4) or other components of chromatin may be the targets being recognized by the autoantibodies in these individuals.
Serum antibodies to ENAs.
To further explore possible targets for the autoantibodies, we used a Lumine multiplex analyzer with an addressable laser bead immunoassay to detect antibodies to five ENAs. Twelve of the Libby samples (24%) had positive ENA tests, with most of the positive samples having more than one of the antibody specificities. The Missoula sample set had only two samples (4%) with positive ENA tests. These differences were statistically significant by Fisher’s exact test (p = 0.004; data not shown). Figure 5 shows the distribution of positive tests in each group for all five antigens tested.
Immune parameter correlations.
Table 3 shows statistical correlations among tested immune parameters within the Libby sample set, using Spearman’s rho nonparametric test. As might be expected based on the epidemiology of autoimmune diseases, the age of the individual was positively correlated with the ANA titer, ANA score, and RF. RF was also correlated with ANA titer. IgA levels were not correlated with any other parameter, so the physiologic significance of the elevation seen in the Libby samples remains unclear.
Correlation of assay results with extent of exposure and ARD.
In addition to the correlations shown above, the immune parameters were analyzed against the scores of exposure levels and ARD status, as described in “Materials and Methods.” Table 4 shows that there were significant positive associations between ANA titers and both asbestos exposure and disease status. Because a central hypothesis relating to asbestos toxicology is that asbestos exposure is positively associated with ARD, we tested that correlation using our scoring system. The correlation between disease and exposure was 0.239, consistent with the hypothesis (Table 4).
The analysis for asbestos exposure was performed using the graded system described in Table 2, but in looking at the data, it was apparent that the largest effect on ANA titer was seen in terms of length of exposure rather than the source (occupational or environmental). Figure 6A shows the mean ANA titers for the Libby samples when subgrouped by duration of exposure and demonstrates that the titers were significantly higher for those subjects exposed to asbestos for > 5 years. When samples were separated according to whether the subject was exposed environmentally or occupationally, no significant difference in mean ANA titer was observed in those two groups (Figure 6B). This suggests that the duration of exposure had a greater impact on autoimmune responses than the source of exposure. It should be noted that none of the subjects reported solely occupational exposures; all also had environmental exposures as well.
Discussion
By demonstrating an association between asbestos exposure and measures of auto-immune responses, this study supports and augments other existing evidence that, like silica, asbestos is an agent of systemic auto-immunity. Asbestos-contaminated vermiculite from Libby has been shipped and processed in many sites in the United States, and this material is still used in many applications. It therefore remains a significant health risk to humans both occupationally and environmentally, and an awareness of an association with autoimmunity could impact necessary monitoring, testing, and treatment regimens for exposed individuals or populations.
In addition, this study establishes the Libby population as an excellent cohort for further study of the immunologic aspects of asbestos toxicology. It is a unique population with both occupational and environmental exposures, excellent ongoing monitoring and demographic data, enthusiasm for participation in these studies, and sufficient numbers of exposed individuals to develop sample sets with adequate power for statistical analyses of many parameters. The objective of this study was to compare the frequency of serum auto-antibodies in two matched populations, one of them having significant asbestos exposure. It was designed as an initial study in order to explore the feasibility and justification for a more extensive study of autoimmunity in the Libby population.
Previous studies have measured several immune parameters in populations exposed, primarily occupationally, to asbestos. Nigam et al. (1993) demonstrated increased IgG and IgA and positive ANAs in asbestos-exposed individuals compared with controls, even in the absence of apparent ARD. This finding suggested that immune alterations may precede the onset of ARD. A high frequency of positive ANAs was also found in a Japanese group of asbestos plant workers (Tamura et al. 1993). Interestingly, a 3-year follow-up study of the Japanese group showed significant correlation of positive ANAs with progression of the disease, leading to additional diagnoses of asbestosis in a previously healthy group (Tamura et al. 1996); this suggests that auto-immunity may play a role in ARD. Because that important observation needs to be confirmed, the present study also forms the basis for a similar progressive study of the Libby population to explore the temporal relationship between autoimmunity and ARD. If autoimmune responses play a role in the progression of ARD, this would become an important target for therapeutic strategies.
A higher frequency of positive ANA was seen in the Libby sample set compared with the samples from Missoula, even though the Missoula ANA positive frequency was fairly high (40%). This high “normal” frequency may be due to the age of the population, the low dilution used (1:40) for the screening, or other unidentified population considerations. Nevertheless, the Libby sample set showed a 28.6% increase above that seen for the Missoula samples. In addition, the mean fluorescence intensity of the ANAs, as well as the titers, were higher in the Libby samples compared with the Missoula samples. Although higher titers of autoantibodies are not necessarily correlated with an autoimmune disease process, in some cases increased titers can indicate an exacerbation, relapse, or stage of an autoimmune process.
Other immune parameters showed differences in the Libby group as well, including increases in serum IgA. Serum IgA is generally found at relatively low levels, but increased levels are associated with some chronic inflammatory disorders, such as occupational lung disease, psoriatic arthritis, Crohn’s disease, and ankylosing spondylitis (Hoffman et al. 2003; Lindqvist et al. 2002; Zhestkov 2000). The significance of increased serum IgA levels in the Libby samples is not clear, but it is consistent with other studies of asbestos-exposed subjects (Nigam et al. 1993; Zerva et al. 1989). We demonstrated that the autoantibodies detected by ANA were not of the IgA isotype, so it is possible that the IgA antibodies are simply elicited by nonspecific chronic inflammatory processes in these individuals. This possibility is supported by the lack of correlation between IgA titers and either ANA or asbestos exposure; however, a correlation between IgA titers and disease status was also lacking in our analysis.
We found no difference between the two sample sets in terms of frequency of positive tests for RF, and in general the positive samples in both groups were rated marginal to moderate when compared with known controls (data not shown). There was also no correlation between RF and asbestos exposure. These results suggest that asbestos exposure is not associated with increases in RF, especially because previous studies of asbestos-exposed populations have not consistently reported elevated RF. Interestingly, we found a positive association of RF with lung disease status. This may suggest that the presence of RF is more dependent on the chronic inflammation resulting from the ARD than on asbestos exposure itself. Alternatively, because there were positive correlations between RF and both ANA titer and ARD, the threshold of asbestos exposure impacting development of RF may simply be too low to be detected using the simplified exposure scale (Table 2). Therefore, the pathophysiologic significance of these results remains to be determined with further study. Although assaying RF is a good screening tool, it is not specific for RA. An alternative test would be an assay for cyclic citrullinated peptide (CCP), a more specific epitope characteristic of autoantibodies in RA (Bombardieri et al. 2004; Saraux et al. 2003) because CCP can antedate clinical RA.
The Libby sample set had a significantly higher number of total positive ENA subjects (24% vs. 4% in the Missoula group). ENAs are defined target antigens in a variety of autoimmune diseases, including systemic lupus, mixed connective tissue disease, systemic sclerosis, and polymyositis (Pahor et al. 1998). In HEp-2 cells, most of these antibodies produce a speckled or atypical speckled pattern. Therefore, our combined data suggest that the major responses in asbestos-exposed individuals include antibody development to targets such as chromatin components (i.e., histone) or nucleolar components (fibrillarin, DNA topo-isomerase I), which give the homogeneous and nucleolar patterns, and several ENAs that give the speckled pattern. There are auto-antibodies—other than those detected by the assay used here—that could give the speckled patterns seen in both populations. Analysis of a more comprehensive array of autoantigens may provide more insight into the spectrum of autoantibodies related to asbestos exposure.
The presence of autoantibodies does not necessarily suggest a disease process. However, to begin to explore a possible role of these antibodies in the health of the population in Libby, data regarding the extent of ARD severity were gathered as described in “Materials and Methods.” Extent of exposure included both duration and site of exposure (work vs. recreational/home). The data showed that individuals with longer exposures, and especially if exposed both at work and at home, had higher ANA titer than those with shorter exposures (< 5 years). Disease status considered the extent of fibrosis or plaquing, as well as functional deficits. Again, the data showed increasing ANA titer with increasing disease severity. The stronger correlation between ANA titer and disease than between ANA titer and exposure may be due to imprecise scoring systems. Exposure and ARD are assumed to be correlated (Peipins et al. 2003), even though this correlation was only at the 90th percentile using our scoring systems. Therefore, these data do not exclude the possibility that the correlation of ANA titer with exposure may be secondary to the chronic inflammation and tissue damage of the associated ARD. It is interesting to note, however, that of those 494 participants from the Libby Tremolite Asbestos Registry cohort with suspected SAID, 171 (35%) have had pleural and/or interstitial abnormalities indicated on chest radiographs and confirmed by two B-readers (Larson T, personal communication). These cross-sectional findings suggest that the proportion of radiographic abnormalities among participants with suspected SAID (35%) was almost double the proportion of radiographic abnormalities among the entire Libby cohort (~ 18%) (Peipins et al. 2003). Further study is required to determine if, and how, autoimmune responses are related to ARD and whether autoimmunity influences ARD progression.
Conclusion
We have established that there are significant differences in frequency and titer of positive ANA tests, frequency of positive ENA tests, and higher levels of serum IgA when an asbestos-exposed Libby cohort was compared with one from Missoula with no reported asbestos exposures. We have also shown significant associations between asbestos exposure and ANA titer. These data support the hypothesis that asbestos exposure is associated with autoimmune responses. The correlations of ARD with ANA titer, ANA score, and RF suggest the possibility that auto-immunity could play a role in the progression of ARD. This study provides the foundation and justification for a larger and more extensive study, planned to explore these associations much more rigorously. These studies will increase our understanding of the immune components of ARD and could lead to improved interventions as an ultimate goal of the discovery of interrelated pathologies.
Figure 1 Comparison of ANA in Libby samples with the Missoula samples. (A) Positive and negative tests determined based on known controls provided with the kits (*p = 0.004, Fisher’s exact test; n = 50). (B) ANA fluorescence intensity score based on known controls (p = 0.004, Pearson chi-square test). (C) Percentage in each group with a titer > 320 (**p < 0.01, Fisher’s exact test; n = 50). ANA tests were performed as described in “Materials and Methods.” Groups were screened at a serum dilution of 1:40 and read by two readers; positive tests were then titered to 1:1,280.
Figure 2 Serum IgA levels were significantly higher in the Libby group. Serum IgA was measured by ELISA using anti-human IgA capture and detection (HRP-conjugated) antibodies from Southern Biotech and Caltag, respectively. The samples were tested in duplicate, developed using TMB, and read on a SpectraMax plate reader. OD was compared with a standard curve (human IgA, Sigma) to calculate values (mg/mL, n = 50).
*p = 0.002, two-tailed t-test.
Figure 3 Evaluation for IgM RF by ELISA. Neither the percent positive (based on kit positive and negative controls) nor the mean OD calculated for each group was statistically significant (Fisher’s exact test and t-test, respectively).
Figure 4 Assessment of autoantibodies targeted to dsDNA or chromatin in subjects with homogeneous ANA patterns. See “Materials and Methods” for details. Tests for antibodies to individual histones were not performed, but that target is indicated for those homogeneous patterns without antibodies to dsDNA or chromatin itself.
Figure 5 Increased frequency of positive ENA tests in Libby samples compared with Missoula samples. Tests were performed as described in “Materials and Methods.” Numbers above the bars are p-values indicating the statistical difference between Libby samples and Missoula samples (determined by Fisher’s exact test; n = 50).
Figure 6 ANA titer (mean ± SD) for subsets of the Libby samples based on length of asbestos exposure (A) or source of exposure (B) as environmental (household contact, used in garden, etc.) or occupational (worked in vermiculite mine or processing).
*p < 0.01 by two-tailed t-test.
Table 1 Simple classification of ARD severity.
Disease severity Criteria used Ordinal value
None No reported lung pathology 0
Limited Unilateral radiograph abnormality 1
Moderate Bilateral abnormality, minimal functional deficit 2
Severe Bilateral abnormality, severe or progressive functional deficit 3
Table 2 Asbestos exposure scores determined from screening data.
Asbestos exposure Criteria used Ordinal value
None No reported occupational or environmental asbestos exposure 0
Minimal < 5 years, only occupational or environmental 1
Low < 5 years, both occupational and environmental 2
Moderate > 5 years, only occupational or environmental 3
High > 5 years, both occupational and environmental 4
Table 3 Correlation coefficients (CC) with immune parameters in the Libby cohort.
Parameter analyzed Age ANA titer
ANA score
CC 0.399** 0.828**
Significance (two-tailed) 0.004 0.00
No. 51 50
ANA titer
CC 0.381** 1.00
Significance (two-tailed) 0.006
No. 50
IgA (mg/mL)
CC −0.009 −0.278
Significance (two-tailed) 0.953 0.075
No. 43 42
RF (OD)
CC 0.331* 0.351*
Significance (two-tailed) 0.030 0.023
No. 43 42
* Correlation is significant at the 0.05 level (two-tailed Spearman’s rho test).
** Correlation is significant at the 0.01 level (two-tailed Spearman’s rho test).
Table 4 Correlation coefficients (CC) between immune parameters and scores both of asbestos exposure and of asbestos-related disease.
Parameter analyzed Exposure ARD
Age
CC −0.015 0.304*
Significance (two-tailed) 0.920 0.034
No. 51 49
ANA score
CC 0.252 0.295*
Significance (two-tailed) 0.074 0.040
No. 51 49
ANA titer
CC 0.366** 0.392**
Significance (two-tailed) 0.009 0.006
No. 50 48
RF (OD)
CC 0.129 0.388*
Significance (two-tailed) 0.410 0.010
No. 43 43
Exposure
CC 1.00 0.239
Significance (two-tailed) 0.098
No. 49
IgA
CC −0.167 −0.090
Significance (two-tailed) 0.283 0.567
No. 43 43
* Correlation is significant at 0.05 (two-tailed Spearman’s rho test).
** Correlation is significant at 0.01 (two-tailed Spearman’s rho test).
==== Refs
References
ATSDR 2002. Prelinimary Findings of Libby, Montana, Asbestos Medical Testing (Combined Testing, 2000 and 2001). Atlanta, GA:Agency for Toxic Substances and Disease Registry.
Bombardieri M Alessandri C Labbadia G Iannuccelli C Carlucci F Riccieri V 2004 Role of anti-cyclic citrullinated peptide antibodies in discriminating patients with rheumatoid arthritis from patients with chronic hepatitis C infection-associated polyarticular involvement Arthritis Res Ther 6 R137 R141 15059277
Fritzler MJ 1994 Drugs recently associated with lupus syndromes Lupus 3 455 459 7704001
Hamilton RF Iyer LL Holian A 1996 Asbestos induces apoptosis in human alveolar macrophages Am J Physiol 271 L813 L819 8944725
Hoffman IE Demetter P Peeters M De Vos M Mielants H Veys EM 2003 Anti-Saccharomyces cerevisiae IgA antibodies are raised in ankylosing spondylitis and undifferentiated spondyloarthropathy Ann Rheum Dis 62 455 459 12695160
Holian A Uthman MO Goltsova T Brown SD Hamilton RF 1997 Asbestos and silica-induced changes in human alveolar macrophage phenotype Environ Health Perspect 105 1139 1142 9400713
Jacobson DL Gange SJ Rose NR Graham NM 1997 Epidemiology and estimated population burden of selected autoimmune diseases in the United States Clin Immunol Immunopathol 84 223 243 9281381
Koeger AC Lang T Alcaix D Milleron B Rozenberg S Chaibi P 1995 Silica-associated connective tissue disease. A study of 24 cases Medicine (Baltimore) 74 221 237 7565064
Lange A 1980 An epidemiological survey of immunological abnormalities in asbestos workers. II. Serum immunoglobulin levels Environ Res 22 176 183 7418675
Lindqvist U Rudsander A Bostrom A Nilsson B Michaelsson G 2002 IgA antibodies to gliadin and coeliac disease in psoriatic arthritis Rheumatology (Oxford) 41 31 37 11792877
Nigam SK Suthar AM Patel MM Karnik AB Dave SK Kashyap SK 1993 Humoral immunological profile of workers exposed to asbestos in asbestos mines Indian J Med Res 98 274 277 8132229
Pahor A Krajnc I Gorenjak M Holc I 1998 The clinical significance of antinuclear antibodies in connective tissue disease Wien Klin Wochenschr 110 338 341 9629626
Parks CG Conrad K Cooper GS 1999 Occupational exposure to crystalline silica and autoimmune disease Environ Health Perspect 107 793 802 10970168
Peipins LA Lewin M Campolucci S Lybarger JA Miller A Middleton D 2003 Radiographic abnormalities and exposure to asbestos-contaminated vermiculite in the community of Libby, Montana, USA Environ Health Perspect 111 1753 1759 14594627
Perkins RC Scheule RK Hamilton R Gomes G Freidman G Holian A 1993 Human alveolar macrophage cytokine release in response to in vitro and in vivo asbestos exposure Exp Lung Res 19 55 65 8440202
Powell JJ Van de Water J Gershwin ME 1999 Evidence for the role of environmental agents in the initiation or progression of autoimmune conditions Environ Health Perspect 107 suppl 5 667 672 10970167
Saraux A Berthelot JM Devauchelle V Bendaoud B Chales G Le Henaff C 2003 Value of antibodies to citrulline-containing peptides for diagnosing early rheumatoid arthritis J Rheumatol 30 2535 2539 14719190
Steenland K Goldsmith DF 1995 Silica exposure and autoimmune diseases Am J Ind Med 28 603 608 8561170
Tamura M Liang D Tokuyama T Yoneda T Kasuga H Narita N 1993 Study on the relationship between appearance of autoantibodies and chest X-ray findings of asbestos plant employees [in Japanese] Sangyo Igaku 35 406 412 8230802
Tamura M Tokuyama T Kasuga H Yoneda T Miyazaki R Narita N 1996 Study on correlation between chest X-P course findings and change in antinuclear antibody in asbestos plant employees [in Japanese] Sangyo Eiseigaku Zasshi 38 138 141 8689500
U.S. Census Bureau 2004. State & County QuickFacts. Available: http://quickfacts.census.gov [accessed 14 September 2004].
Zerva LV Constantopoulos SH Moutsopoulos HM 1989 Humoral immunity alterations after environmental asbestos exposure Respiration 55 237 241 2595107
Zhestkov AV 2000. Immunological changes in dust-induced lung diseases [in Russian]. Gig Sanit Nov–Dec(6):30–33.
|
15626643
|
PMC1253705
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan 30; 113(1):25-30
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7431
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7369ehp0113-00003115626644ResearchArticlesBlood Lead Is a Predictor of Homocysteine Levels in a Population-Based Study of Older Adults Schafer Jyme H. 12Glass Thomas A. 3Bressler Joseph 456Todd Andrew C. 7Schwartz Brian S. 1231Department of Environmental Health Sciences, Division of Occupational and Environmental Health, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA2Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA3Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA4Department of Environmental Health Sciences, Division of Toxicological Sciences, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA5Department of Neurology, Johns Hopkins University, Baltimore, Maryland, USA6Department of Neurotoxicology, Kennedy Krieger Institute, Baltimore, Maryland, USA7Department of Community and Preventive Medicine, Mount Sinai School of Medicine, New York, New York, USAAddress correspondence to B.S. Schwartz, Johns Hopkins Bloomberg School of Public Health, Division of Occupational and Environmental Health, 615 North Wolfe St., Room W7041, Baltimore, MD 21205 USA. Telephone: (410) 955-4130. Fax: (410) 955-1811. E-mail:
[email protected] work was supported by R01 AG19604 (B.S.S.).
The authors declare they have no competing financial interests.
1 2005 7 9 2004 113 1 31 35 30 6 2004 7 9 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Lead and homocysteine are both associated with cardiovascular disease and cognitive dysfunction. We evaluated the relations among blood lead, tibia lead, and homocysteine levels by cross-sectional analysis of data among subjects in the Baltimore Memory Study, a longitudinal study of 1,140 randomly selected residents in Baltimore, Maryland, who were 50–70 years of age. Tibia lead was measured by 109Cd K-shell X-ray fluorescence. The subject population had a mean ± SD age of 59.3 ± 5.9 years and was 66.0% female, 53.9% white, and 41.4% black or African American. Mean ± SD blood lead, tibia lead, and homocysteine levels were 3.5 ± 2.4 μg/dL, 18.9 ± 12.5 μg/g, and 10.0 ± 4.1 μmol/L, respectively. In unadjusted analysis, blood lead and homocysteine were moderately correlated (Pearson’s r = 0.27, p < 0.01). After adjustment for age, sex, race/ethnicity, educational level, tobacco and alcohol consumption, and body mass index using multiple linear regression, results revealed that homocysteine levels increased 0.35 μmol/L per 1.0 μg/dL increase in blood lead (p < 0.01). The relations of blood lead with homocysteine levels did not differ in subgroups distinguished by age, sex, or race/ethnicity. Tibia lead was modestly correlated with blood lead (Pearson’s r = 0.12, p < 0.01) but was not associated with homocysteine levels. To our knowledge, these are the first data to reveal an association between blood lead and homocysteine. These results suggest that homocysteine could be a mechanism that underlies the effects of lead on the cardiovascular and central nervous systems, possibly offering new targets for intervention to prevent the long-term consequences of lead exposure.
blood leadcross-sectional studyhomocysteinetibia lead
==== Body
As a result of centuries of human use, lead is omnipresent in the environment. Commercial use of this substance continues even though its toxic effects have been recognized since ancient times (Nriagu 1983), and more recent studies report health effects associated with lower and lower lead doses (Canfield et al. 2003; Glenn et al. 2003; Nash et al. 2003; Schwartz et al. 2000). Lead is not rapidly cleared from the body; the biologic residence time of lead in blood is measured in days, whereas the biologic residence time of lead in bone is on the order of years to decades (Hu et al. 1998). In occupational and general population samples, low blood lead levels have been associated with increased blood pressure and elevated risk of hypertension, effects that may be progressive (Cheng et al. 2001; Glenn et al. 2003; Nash et al. 2003); increased circulatory and cardiovascular mortality (Lustberg and Silbergeld 2002); and progressive declines in cognitive function over time, even years after cessation of occupational exposure (Schwartz et al. 2000, 2002, in press). One of the key remaining problems in the research of lead toxicity is that the mechanisms for these effects are not well understood.
Interestingly, homocysteine is also associated with cardiovascular disease and cognitive dysfunction (Dufouil et al. 2003; Homocysteine Collaboration 2002). Homocysteine is an independent risk factor for vaso-occlusive disease; elevated levels of homocysteine increase the risk of heart disease, stroke, and peripheral vascular disease and, perhaps through vascular mechanisms, cognitive dysfunction (Bautista et al. 2002; Dufouil et al. 2003; Homocysteine Collaboration 2002; Prins et al. 2002; Ravaglia et al. 2003; Wald et al. 2002). Vascular damage by homocysteine may occur through impaired vascular endothelial and smooth muscle cell function (Rodrigo et al. 2003). The mechanisms of this impairment may involve inhibition of nitric oxide synthesis, increased oxidative stress, proliferation of vascular smooth muscle cells, and altered elasticity of the vascular wall (Rodrigo et al. 2003).
Despite the similarities in these health effects, the relation of homocysteine and lead dose has not been previously examined. Herein, we report associations of blood lead, tibia lead, and homocysteine in a population-based study of persons 50–70 years of age in Baltimore, Maryland. Participants were selected from the general population, and most are without occupational lead exposure.
Materials and Methods
Study design.
The Baltimore Memory Study, one of the National Institutes of Health’s disparities initiative grants, is a multilevel cohort study of risk factors for cognitive decline in Baltimore city residents of targeted neighborhoods. The methods are described elsewhere (Schwartz et al. 2004). The selected neighborhoods were chosen to provide areas with a broad range of socioeconomic status and large numbers of both whites and African Americans. A cross-sectional analysis of first-visit data was performed.
Subject selection and recruitment.
Sampling and recruitment have been previously described (Schwartz et al. 2004). In brief, individual dwellings in the study area were linked to telephone numbers, and households with telephones were randomly selected for recruitment. Eligibility was then determined on 2,351 subjects (50–70 years of age, living at selected household, lived in Baltimore at least 5 years), and of these subjects, 60.8% were scheduled for an enrollment visit. Of the 1,403 scheduled for an appointment, 1,140 (81.3%) were enrolled and subsequently tested. The study was approved by the Committee for Human Research of the Johns Hopkins Bloomberg School of Public Health. All participants provided written, informed consent before testing and were paid $50 for their participation.
Data collection.
All data were collected at the study clinic by trained research assistants. A structured interview included the following information: demographics, socioeconomic status (household income, household assets, occupational status, and educational attainment), medical history, smoking and alcohol history, and lead history. First and second visits were conducted between May 2001 and September 2002, and October 2002 and February 2004, respectively. A trained phlebotomist drew a 10-mL blood specimen into a red-top (no anticoagulant) tube, which was clotted, centrifuged, and stored at –20°C within 1 hr. Samples were transported to the Johns Hopkins Bloomberg School of Public Health and stored at –70°C. Serum homocysteine was measured by a commercial laboratory using fluorescence polarization immunoassay (Abbott AxSYM, Abbott Park, IL). The coefficients of variation for the quality control samples for three concentration levels were 3.64% (low range), 2.24% (mid range), and 2.32% (high range). Fasting was not requested of the subjects because study visits were scheduled at all times of the day for logistical reasons. The variability between fasting and nonfasting samples is not likely to exaggerate the association but instead would dampen it. Conditions that cause short-term fluctuations in homocysteine levels, such as protein intake, are not likely to be related to whole-blood lead levels. Homocysteine was measured from a sample obtained at the first study visit in most subjects; however, 254 subjects provided plasma only at the first visit so had serum obtained at the second visit for homocysteine measurement. Lead was measured in the metals laboratory of the Kennedy Krieger Institute (Baltimore, MD) from the first study visit whole-blood specimen using anodic stripping voltammetry (Schwartz et al. 2004). Tibia lead concentration was measured at the second study visit by 109Cd-induced K-shell X-ray fluorescence using previously reported methods (Todd 2000; Todd and McNeill 1993; Todd et al. 1992, 2000). In this population of older adults without occupational lead exposure, tibia lead, which has a biologic residence time of 25–30 years, should not have changed appreciably between the first and second study visits.
Statistical methods.
The main objectives of this analysis were a) to evaluate relations of blood lead and tibia lead levels with homocysteine, controlling for age, race/ethnicity, sex, and other potential confounding variables; and b) to evaluate whether these relations were modified by age, sex, or race/ethnicity. Of the 1,140 persons enrolled at the first visit, 78 subjects were missing homocysteine values; 10 were missing blood lead values; 7 missing information on alcohol consumption; 6 missing body mass index (BMI); and 1 each was missing information on education and tobacco use. A total of 1,022 (89.6%) subjects completed the second study visit, so 82 participants were missing tibia lead data. Thus, in analyses with blood lead and tibia lead, 1,037 and 955 subjects were included, respectively. Subjects with missing homocysteine data were not statistically different regarding blood lead, age, or race/ethnicity. To minimize the influence of large tibia lead values, tibia lead was log transformed before use in models. Negative values for tibia lead were converted to 0.1 before log transformation. Associations with tibia lead were also examined nonparametrically, using a percentile transformation for tibia lead; results did not differ from those using the log-transformed tibia lead and are not reported.
We used multiple linear regression to examine the relations of blood lead with homocysteine levels, controlling for covariates. Models were first constructed including known homocysteine covariates (e.g., age, sex, and race/ethnicity); then, other potential confounding variables were included in a forward stepwise fashion. Variables were retained in the final models if they were associated with homocysteine levels or significantly influenced the relation of blood or tibia lead with homocysteine (changed the lead coefficient by more than 10%). The final model included age, race/ethnicity, sex, educational level (four categories based on reported years of education and information on graduate equivalency diploma, training for trades, and additional educational certificates), alcohol (four categories based on the number of alcoholic drinks per month, with a drink being defined as one beer, one glass of wine, one wine cooler, one cocktail, or one shot of liquor), smoking (four categories based on the number of cigarettes smoked per day), and BMI (kilograms per square meter). We evaluated effect modification by including cross-product terms in the model (e.g., to evaluate effect modification by race/ethnicity, a cross-product of race/ethnicity and blood lead was included in the model). All statistical analyses were performed using Stata version 8.0 (Stata Corporation, College Station, TX). We checked final models for the assumptions of linear regression and model fit using influence diagnostic procedures, examination of residuals, and residual–residual plots.
Results
Study subjects were 66.0% female, 41.4% non-Hispanic black/African American, and 53.9% non-Hispanic white or white/Native American and had a mean (range) age of 59.3 (49–71) years. The mean ± SD blood lead and homocysteine levels were 3.5 ± 2.4 μg/dL and 10.0 (4.1) μmol/L, respectively (Table 1). Subjects had a wide range of educational levels, smoking habits, and alcohol habits; in unadjusted analysis, these were differentially associated with blood lead and homocysteine levels, evaluated in quartiles (Tables 1 and 2). Using blood lead and homocysteine as continuous measures, in unadjusted analysis, these were moderately correlated, with Pearson’s r = 0.27 (p < 0.01). Blood lead and tibia lead levels were only modestly correlated [Pearson’s r = 0.11, for the log transformed data (Figure 1), and r = 0.12 for the untransformed data; both p-values < 0.01].
Discussion
To our knowledge, this is the first study to examine relations of blood lead and tibia lead with homocysteine levels. We observed a significant association between blood lead and homocysteine in an older, community-dwelling, adult, population-based sample in a major U.S. urban area after controlling for age, sex, race/ethnicity, alcohol intake, cigarette smoking, educational level, and BMI. As previously observed, sex, age, and smoking a pack or more per day were predictors of homocysteine levels (Jacques et al. 2001). Blood lead may influence homocysteine levels at very low dose levels (Figure 2). Among study subjects, blood lead levels were generally < 15 μg/dL, as expected in the general population. The study thus provides evidence of an association at low blood lead levels, but we were unable to characterize the association at higher blood lead levels. Although tibia lead was modestly associated with blood lead levels, it was neither a predictor of homocysteine levels nor a confounder of its relation with blood lead. Tibia lead levels were obtained at the second study visit. Subjects who did not complete the second study visit were more likely to be African American (52.4 vs. 40.4%) and were slightly younger (58.5 vs. 59.4 years of age) compared with subjects who completed the visit, but there was no difference in blood lead levels. We do not believe these small differences account for the contrasting associations of blood and tibia lead levels with homocysteine. Tibia lead, a measure of cortical bone lead, is generally a less important source of blood lead levels than is lead in trabecular bone, but is a good estimate of cumulative lead dose (Hu et al. 1998). The data suggest that bioavailable lead (i.e., blood lead) was a more important predictor of homocysteine levels than was cumulative lead dose (i.e., tibia lead).
Lead and homocysteine are both associated with an increased risk of cardiovascular disease and, possibly through vascular system mechanisms, central nervous system disease. In epidemiologic studies of central nervous system disease and cardiovascular outcomes, it is interesting to note that study results for lead parallel those for homocysteine. For example, in an occupational cohort of men with previous lead exposure (on average 18 years prior), the systolic blood pressure increased on average 0.64 mm Hg (SE = 0.25) for every SD increase in blood lead at baseline (Glenn et al. 2003). In a recent meta-analysis using data from 30 prospective or retrospective studies, a 25% lower homocysteine level (~ 3 μmol/L) was associated with an approximately 11% [odds ratio (OR) = 0.89; 95% confidence interval (CI), 0.83–0.96] lower ischemic heart disease risk and a 19% (OR = 0.81; 95% CI, 0.69–0.95) lower stroke risk (Homocysteine Collaboration 2002). Another meta-analysis of 20 prospective studies found that for an increase in serum homocysteine of 5 μmol/L, the OR for ischemic heart disease was increased (OR = 1.32; 95% CI, 1.19–1.45), as was the OR for stroke (OR = 1.59; 95% CI, 1.29–1.96) (Wald et al. 2002). Other studies support the similarities between the cardiovascular effects of lead and homocysteine (Bautista et al. 2002; Cheng et al. 2001; Kopp et al. 1988; Moller and Kristensen 1992; Nash et al. 2003; Pocock et al. 1988).
Both lead and homocysteine also have similar associations with central nervous system outcomes [Agency for Toxic Substances and Disease Registry (ATSDR) 1999; Balbus-Kornfeld et al. 1995; Dufouil et al. 2003; Prins et al. 2002; Ravaglia et al. 2003; Schwartz et al. 2000, 2001]. There are suggestions that cognitive function is negatively affected by elevated levels of either lead or homocysteine. In a population-based study of 1,077 subjects, neurobehavioral test outcomes were lower in the upper quintile of homocysteine levels compared with the lower four quintiles (Prins et al. 2002). The mean ± SD homocysteine level of this population was 11.5 ± 4.1 μmol/L, with the medians of the quintiles being 7.57, 9.12, 10.54, 12.47, and 16.34 μmol/L, respectively. Comparison of the mean adjusted difference in test scores for subjects in the homocysteine upper quintile versus lower quintiles (looked at dichotomously) revealed a decrement in psychomotor speed (–0.26; 95% CI, –0.37–0.14), memory function (–0.13; 95% CI, –0.27–0.01), and global cognitive function (–0.20; 95% CI, –0.30–0.11). In a longitudinal study of 1,241 subjects (61–73 years of age), homocysteine levels > 15 μmol/L conferred 2.8 greater odds (p < 0.05) of cognitive decline compared with those subjects whose levels were < 10 μmol/L (mean homocysteine level in this study was 12.2 μmol/L) (Dufouil et al. 2003). For lead, two recent longitudinal studies of occupational cohorts with current and/or past lead exposure were associated with longitudinal decline in cognitive function (Schwartz et al. 2000, in press). One of the studies consisted of former organolead workers (mean age, 55.6 years) and used an extensive neurobehavioral test battery (Schwartz et al. 2000). In this study, an increase of 15.7 μg/g of peak tibia lead (using back-extrapolation, the estimated tibia lead level at the end of employment in lead) was equivalent in its effects on annual test decline to 5 more years of age at baseline for six neurobehavioral tests of verbal memory and learning, executive abilities, and manual dexterity. Although blood lead, but not tibia lead, was associated with homocysteine levels, in this cross-sectional study we cannot be certain whether this means that recent lead exposure, mobilization of lead from bone, or both, are the likely source of lead that explains the association. With the growing evidence that lead may cause progressive elevations in blood pressure and declines in cognitive function over time (Glenn et al. 2003; Schwartz et al. 2000, 2001, in press), this newly observed association between lead and homocysteine may offer new possibilities for preventive intervention.
Several targets that lead could be acting upon could explain this association. Lead can interact with proteins, particularly those with a sulfhydryl group (Goering 1993). An example of this occurrence is the inhibition of the δ-aminolevulinic acid dehydratase (ALAD) enzyme in the heme-synthesis pathway. ALAD is an octameric metalloenzyme that contains zinc in the activated state (Simons 1995). The active site for zinc binding contains two cysteine residues. There is competitive inhibition between lead and zinc, with the ratio of the affinity of lead to zinc at the metal-binding site being about 25:1 for the 1-1 ALAD phenotype (Simons 1995). Such sulfhydryl binding by lead could be one mechanism that could account for the observed lead–homocysteine relation. In the metabolism of methionine, homocysteine can be remethylated by two different pathways or undergo transsulferation to cysteine (Ueland and Refsum 1989). In the transsulferation pathway there is a unique heme-containing enzyme, cystathionine β-synthase, that catalyses a pyridoxal 5′-phosphate–dependent condensation of serine and homocysteine to give cystathionine (Banerjee et al. 2003). Work in the elucidation of the structure of cystathionine β-synthase has revealed two sulfhydryl groups contained within the heme-binding site (Meier et al. 2001). Furthermore, homocysteine itself contains a sulfhydryl group, so if lead has an affinity for this sulfhydryl group, the metabolism of homocysteine could be directly inhibited, leading to an accumulation of homocysteine.
It has been unclear whether homocysteine is a causative agent or only a marker of disease. In 1962, homocystinuria in mentally retarded children was discovered as an inborn error of metabolism (Carson and Neill 1962; Gerritsen et al. 1962). In 1964, cystathionine β-synthetase deficiency was demonstrated as a cause of this disorder (Mudd et al. 1964). The natural history of cystathionine β-synthetase deficiency includes a 50% chance of a vascular event (stroke, myocardial infarction, peripheral arterial or venous thrombosis) by 30 years of age (Yap 2003). Recent experimental evidence suggests homocysteine to be a causal agent. Experimentation has shown isolated hyper-homocysteinemia to be atherogenic in cystathionine β-synthetase and apolipoprotein-E double knock-out mice (Wang et al. 2003). Additionally, homocysteine has been shown to stimulate the expression and secretion of biologically active monocyte chemoattractant protein-1 (MCP-1) and interleukin-8 (IL-8) in human monocytes (Zeng et al. 2003), two chemokines that are thought to be important to the development of atherosclerotic plaques.
In conclusion, blood lead was found to be associated with homocysteine levels in a large, general population sample. Although causality cannot be determined from cross-sectional data, it is interesting to consider the possibility that this relation of lead and homocysteine could explain one of the mechanisms of the influence of lead on the central nervous and cardiovascular systems. Whether lead elevates homocysteine through enzyme inhibition, as earlier suggested, or conversely, whether homocysteine elevates lead because of intravascular binding [homocysteine has a structure similar to dimercaptosuccinic acid (DMSA) and penicillamine, compounds that are known to bind lead], it is evident that the association exists at very low blood lead levels, and if the former mechanism is operative, supports a biologic effect of lead at low levels. This knowledge may offer new targets for prevention of the progressive health effects of lead.
Figure 1 Crude relation of log10-transformed blood lead levels and log10-transformed tibia lead levels for 955 participants in the Baltimore Memory Study. Dashed line represents a locally weighted smoothing fit (lowess bandwidth, 0.10) (Cleveland 1979).
Figure 2 Smoothed plot of residuals of blood lead and homocysteine levels, controlling for covariates. Values were adjusted for age, sex, race/ethnicity, BMI, educational level, and tobacco and alcohol use. The three data points with blood lead concentrations > 15 μg/dL have been excluded from the plot (but not from the regression model) so that the portion of the plot with the most data could be more clearly visualized. The solid line is predicted linear fit, and the dashed line is from a locally weighted smoothing fit (lowess bandwidth, 0.05) (Cleveland 1979).
Table 1 Demographic characteristics for the inclusive study population and lead quartile subsets, Baltimore Memory Study, 2001–2002.
Blood lead quartile
Characteristic Total (n = 1,037) Quartile 1 (n = 241) Quartile 2 (n = 271) Quartile 3 (n = 262) Quartile 4 (n = 263) p-Valuea
Blood lead level [mean (range) μg/dL] 3.5 (0.1–27.3) 1.1 (0.1–1.9) 2.5 (2.0–3.0) 3.8 (3.1–4.4) 6.5 (4.5–27.3)
Homocysteine [mean ± SD (μmol/L)] 10.0 ± 4.1 9.2 ± 3.4 9.3 ± 3.5 9.7 ± 3.6 11.7 ± 5.1 < 0.001
Age [mean ± SD (years)] 59.3 ± 5.9 59.3 ± 5.9 59.3 ± 5.8 59.0 ± 5.9 59.8 ± 6.2 0.52
Sex (% female) 66.0 83.0 72.3 63.7 46.0 < 0.001
Race/ethnicity (%) 0.73
Non-Hispanic black/African American 41.4 44.4 39.9 38.9 42.6
Non-Hispanic white or white/Native American 53.9 49.4 55.7 56.1 54.0
African American mixed race/ethnicity 2.7 2.9 3.0 3.1 1.9
Asian, Hawaiian, Native American, or other 2.0 3.3 1.4 1.9 1.5
BMI [mean ± SD (kg/m2)] 29.8 ± 6.9 31.5 ± 7.8 30.7 ± 7.2 28.8 ± 6.4 28.3 ± 5.4 < 0.001
Current cigarette use (%) 0.008
None 79.8 85.9 80.8 82.4 70.7
< Half pack per day 5.6 3.7 7.8 3.5 7.2
Half pack to < 1 pack per day 7.6 4.2 5.9 8.0 12.2
≥ 1 pack per day 7.0 6.2 5.5 6.1 9.9
Alcoholic beverage use (%) < 0.001
None 40.6 49.9 43.9 38.5 30.8
< 4 per month 15.1 17.4 15.9 13.4 13.7
4–8 per month 12.8 11.2 15.1 14.5 10.3
> 8 per month 31.5 21.6 25.1 33.6 45.2
Education level (%) 0.9
< High school or trade school 10.2 10.4 9.2 8.4 12.9
Completed high school or trade school 41.7 41.5 43.2 41.2 40.7
Some college or associate degree 5.9 6.2 6.3 6.1 4.9
≥ College degree 42.2 41.9 41.3 44.3 41.5
a p-Value from chi-square test for categorical variables or for continuous variables analysis of variance F-test for linear trend across quartiles.
Table 2 Demographic characteristics of study subjects by homocysteine quartiles, Baltimore Memory Study, 2001–2002.
Homocysteine quartile
Characteristic Quartile 1 (n = 245) Quartile 2 (n = 269) Quartile 3 (n = 259) Quartile 4 (n = 264) p-Valuea
Homocysteine [mean (range) μmol/L] 6.6 (4.4–7.5) 8.3 (7.6–9.0) 10.0 (9.1–11.2) 15.0 (11.3–48.6)
Blood lead level [mean ± SD (μg/dL)] 2.8 ± 1.6 3.2 ± 2.4 3.7 ± 2.1 4.4 ± 2.8 < 0.001
Age [mean ± SD (years)] 57.9 ± 5.5 59.1 ± 5.8 60.0 ± 6.0 60.3 ± 6.2 < 0.001
Sex (% female) 87.8 69.1 59.5 48.9 < 0.001
Race/ethnicity (%) 0.001
Non-Hispanic black/African American 39.2 36.1 42.9 47.4
Non-Hispanic white or white/Native American 51.8 62.4 53.6 47.3
African American/mixed race/ethnicity 5.7 0.4 2.7 2.3
Asian, Hawaiian, Native American or other 3.3 1.1 0.8 3.0
BMI [mean ± SD (kg/m2)] 29.2 ± 6.6 29.6 ± 7.0 30.2 ± 6.8 30.2 ± 7.0 0.27
Current cigarette use (%) 0.001
None 84.5 85.1 79.1 70.8
< Half pack per day 6.1 4.5 4.2 7.6
Half pack to less than 1 pack per day 5.3 5.6 9.7 9.9
≥ 1 pack per day 4.1 4.8 7.0 11.7
Alcoholic beverage use (%) 0.007
None 44.5 39.0 40.9 38.3
< 4 per month 15.9 15.6 14.7 14.0
4–8 per month 18.0 13.0 12.0 8.7
> 8 per month 21.6 32.4 32.4 39.0
Education level (%) 0.002
< High school or trade school 10.2 7.1 10.4 13.2
Completed high school or trade school 39.6 37.2 40.9 48.9
Some college or associates degree 6.5 3.7 8.1 5.3
≥ College degree 43.7 52.0 40.6 32.6
a p-Value from chi-square for categorical variables or for continuous variables analysis of variance F-test for linear trend across quartiles.
Table 3 Predictorsa of homocysteine levels in subjects with complete data (n = 1,037), Baltimore Memory Study, 2001–2002.
Total (n = 1,037)
Female (n= 684)
Male (n = 353)
β(SE β) p-Value β(SE β) p-Value β(SE β) p-Value
Blood lead (μg/dL) 0.35 (0.05) < 0.001 0.24 (0.07) 0.001 0.43 (0.08) < 0.001
Age (years) 0.09 (0.02) < 0.001 0.14 (0.02) < 0.001 –0.02 (0.04) 0.61
Female –1.46 (0.27) < 0.001 — — — —
BMI (kg/m2) 0.05 (0.02) 0.004 0.05 (0.02) 0.02 0.09 (0.04) 0.03
Current cigarette useb
< Half pack per day 1.01 (0.53) 0.06 0.78 (0.62) 0.20 1.30 (0.96) 0.18
Half pack to < 1 pack per day 1.53 (0.47) 0.001 2.05 (0.56) < 0.001 0.80 (0.84) 0.35
≥1 packs per day 2.29 (0.49) < 0.001 2.12 (0.60) < 0.001 2.11 (0.83) 0.01
a Adjusted for variables in table as well as race/ethnicity (four categories), educational level (four categories), and alcohol consumption (none, < 4 per month, 4–8 per month, > 8 per month).
b Reference group is subjects with no current use.
==== Refs
References
ATSDR 1999. Toxicologic Profile for Lead (Update). Atlanta, GA:Agency for Toxic Substances and Disease Registry.
Balbus-Kornfeld JM Stewart W Bolla KI Schwartz BS 1995 Cumulative exposure to inorganic lead and neurobehavioural test performance in adults: an epidemiological review Occup Environ Med 52 2 12 7697135
Banerjee R Evande R Kabil O Ojha S Taoka S 2003 Reaction mechanism and regulation of cystathionine beta-synthase Biochim Biophys Acta 1647 30 35 12686104
Bautista LE Arenas IA Penuela A Martinez LX 2002 Total plasma homocysteine level and risk of cardiovascular disease: a meta-analysis of prospective cohort studies J Clin Epidemiol 55 882 887 12393075
Canfield RL Henderson CR Jr Cory-Slechta DA Cox C Jusko TA Lanphear BP 2003 Intellectual impairment in children with blood lead concentrations below 10 microg per deciliter N Engl J Med 348 1517 1526 12700371
Carson N Neill D 1962 Metabolic abnormalities detected in a survey of mentally backward individuals in Northern Ireland Arch Dis Childhood 37 505 513 14018926
Cheng Y Schwartz J Sparrow D Aro A Weiss ST Hu H 2001 Bone lead and blood lead levels in relation to baseline blood pressure and the prospective development of hypertension: the Normative Aging Study Am J Epidemiol 153 164 171 11159162
Cleveland WS 1979 Robust locally weighted regression and smoothing scatterplots J Am Stat Assoc 74 829 836
Dufouil C Alperovitch A Ducros V Tzourio C 2003 Homocysteine, white matter hyperintensities, and cognition in healthy elderly people Ann Neurol 53 214 221 12557288
Gerritsen T Vaughn JG Waisman HA 1962 The identification of homocysteine in the urine Biochem Biophys Res Commun 9 493 496 13960563
Glenn BS Stewart WF Links JM Todd AC Schwartz BS 2003 The longitudinal association of lead with blood pressure Epidemiology 14 30 36 12500043
Goering PL 1993 Lead-protein interactions as a basis for lead toxicity Neurotoxicology 14 45 60 8247411
Homocysteine Collaboration. 2002 Homocysteine and risk of ischemic heart disease and stroke: a meta-analysis JAMA 288 2015 2022 12387654
Hu H Rabinowitz M Smith D 1998 Bone lead as a biological marker in epidemiologic studies of chronic toxicity: conceptual paradigms Environ Health Perspect 106 1 8 9417769
Jacques PF Bostom AG Wilson PW Rich S Rosenberg IH Selhub J 2001 Determinants of plasma total homocysteine concentration in the Framingham offspring cohort Am J Clin Nutr 73 613 621 11237940
Kopp SJ Barron JT Tow JP 1988 Cardiovascular actions of lead and relationship to hypertension: a review Environ Health Perspect 78 91 99 3060356
Lustberg M Silbergeld E 2002 Blood lead levels and mortality Arch Intern Med 162 2443 2449 12437403
Meier M Janosik M Kery V Kraus JP Burkhard P 2001 Structure of human cystathionine beta-synthase: a unique pyridoxal 5′-phosphate-dependent heme protein EMBO J 20 3910 3916 11483494
Moller L Kristensen T 1992 Blood lead as a cardiovascular risk factor Am J Epidemiol 136 1091 1100 1462969
Mudd S Finklestein J Irreverre F Laster L 1964 Homocystinuria: an enzymatic defect Science 143 1443 1445 14107447
Nash D Lustberg M Sherwin RW Rubin RJ Kaufmann R Silbergeld E 2003 Blood lead, blood pressure, and hypertension in perimenopausal and postmenopausal women JAMA 289 1523 1532 12672769
Nriagu JO 1983. Lead and Lead Poisoning in Antiquity. New York:John Wiley & Sons, 378–415.
Pocock S Shaper A Ashby D Delves H Clayton B 1988 The relationship between blood lead, blood pressure, stroke, and heart attacks in middle-aged British men Environ Health Perspect 78 23 30 3203640
Prins ND Den Heijer T Hofman A Koudstaal PJ Jolles J Clarke R 2002 Homocysteine and cognitive function in the elderly: the Rotterdam Scan Study Neurology 59 1375 1380 12427887
Ravaglia G Forti P Maioli F Muscari A Sacchetti L Arnone G 2003 Homocysteine and cognitive function in healthy elderly community dwellers in Italy Am J Clin Nutr 77 668 673 12600859
Rodrigo R Passalacqua W Araya J Orellana M Rivera G 2003 Implications of oxidative stress and homocysteine in the pathophysiology of essential hypertension J Cardiovasc Pharmacol 42 453 461 14508229
Schwartz BS Glass T Bolla K Glass G Stewart W Todd A 2004 Disparities in cognitive functioning by race/ethnicity in the Baltimore Memory Study Environ Health Perspect 112 314 320 14998746
Schwartz BS Lee B Bandeen-Roche K Stewart W Bolla K Links J In press. Lead dose is associated with longitudinal decline in neurobehavioral test scores in South Korean lead workers. Epidemiology.
Schwartz BS Lee BK Lee GS Stewart WF Lee SS Hwang KY 2001 Associations of blood lead, dimercaptosuccinic acid-chelatable lead, and tibia lead with neurobehavioral test scores in South Korean lead workers Am J Epidemiol 153 453 464 11226977
Schwartz BS Stewart WF Bolla KI Simon PD Bandeen-Roche K Gordon PB 2000 Past adult lead exposure is associated with longitudinal decline in cognitive function Neurology 55 1144 1150 11071492
Schwartz BS Stewart W Hu H 2002 Neurobehavioural testing in workers occupationally exposed to lead Occup Environ Med 59 648 649 12205243
Simons TJ 1995 The affinity of human erythrocyte porpho-bilinogen synthase for Zn2+ and Pb2+ Eur J Biochem 234 178 183 8529638
Todd AC 2000 Contamination of in vivo bone-lead measurements Phys Med Biol 45 229 240 10661594
Todd AC Carroll S Godbold JH Moshier EL Khan FA 2000 Variability in XRF-measured tibia lead levels Phys Med Biol 45 3737 3748 11131196
Todd AC McNeill FE 1993 In vivo measurements of lead in bone using a 109 Cd spot source Basic Life Sci 60 299 302 8110132
Todd AC McNeill FE Palethorpe JE Peach DE Chettle DR Tobin MJ 1992 In vivo X-ray fluorescence of lead in bone using K x-ray excitation with 109 Cd sources: radiation dosimetry studies Environ Res 57 117 132 1568436
Ueland PM Refsum H 1989 Plasma homocysteine, a risk factor for vascular disease: plasma levels in health, disease, and drug therapy J Lab Clin Med 114 473 501 2681479
Wald DS Law M Morris JK 2002 Homocysteine and cardiovascular disease: evidence on causality from a meta-analysis Br Med J 325 1202 1206 12446535
Wang H Jiang X Yang F Gaubatz JW Ma L Magera MJ 2003 Hyperhomocysteinemia accelerates atherosclerosis in cystathionine beta-synthase and apolipoprotein E double knock-out mice with and without dietary perturbation Blood 101 3901 3907 12506016
Yap S 2003 Classical homocystinuria: vascular risk and its prevention J Inherit Metab Dis 26 259 265 12889665
Zeng X Dai J Remick DG Wang X 2003 Homocysteine mediated expression and secretion of monocyte chemoattractant protein-1 and interleukin-8 in human monocytes Circ Res 93 311 320 12881478
|
15626644
|
PMC1253706
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2005 Jan 7; 113(1):31-35
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7369
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7317ehp0113-00003615626645ResearchArticlesAssociations among Lead Dose Biomarkers, Uric Acid, and Renal Function in Korean Lead Workers Weaver Virginia M. 12Jaar Bernard G. 23Schwartz Brian S. 123Todd Andrew C. 4Ahn Kyu-Dong 5Lee Sung-Soo 5Wen Jiayu 1Parsons Patrick J. 6Lee Byung-Kook 51Division of Occupational and Environmental Health, Department of Environmental Health Sciences, Johns Hopkins UniversityBloomberg School of Public Health, Baltimore, Maryland, USA2Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA3Department of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, Maryland, USA4Department of Community and Preventive Medicine, Mount Sinai School of Medicine, New York, New York, USA5Institute of Industrial Medicine, SoonChunHyang University, Asan, South Korea6Lead Poisoning/Trace Elements Laboratory, Wadsworth Center, New York State Department of Health, Albany, New York, USAAddress correspondence to B.-K. Lee, Institute of Industrial Medicine, SoonChunHyang University, 646 Eupnae-Ri, Shinchang-Myun, Asan-Si, Choongnam, 336-745 South Korea. Telephone: 82-41-530-1760. Fax: 82-41-530-1778. E-mail:
[email protected] thank Y.-B. Kim, G.-S. Lee, and B.-K. Jang for assistance with data collection in South Korea.
This research was supported by grants ES07198 (B.S.S.) and 2 ES07198 (V.M.W.) from the National Institute of Environmental Health Sciences; grant KRF-2000-00545 (B.-K.L.) from the Korea Research Foundation; and the Richard Ross Clinician Scientist Award from the Johns Hopkins University School of Medicine (B.G.J.).
The authors declare they have no competing financial interests.
1 2005 30 9 2004 113 1 36 42 8 6 2004 30 9 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Recent research suggests that both uric acid and lead may be nephrotoxic at lower levels than previously recognized. We analyzed data from 803 current and former lead workers to determine whether lead biomarkers were associated with uric acid and whether previously reported associations between lead dose and renal outcomes were altered after adjustment for uric acid. Outcomes included uric acid, blood urea nitrogen, serum creatinine, measured and calculated creatinine clearances, and urinary N-acetyl-β-d-glucosaminidase (NAG) and retinol-binding protein. Mean (± SD) uric acid, tibia lead, and blood lead levels were 4.8 ± 1.2 mg/dL, 37.2 ± 40.4 μg/g bone mineral, and 32.0 ± 15.0 μg/dL, respectively. None of the lead measures (tibia, blood, and dimercaptosuccinic-acid–chelatable lead) was associated with uric acid, after adjustment for age, sex, body mass index, and alcohol use. However, when we examined effect modification by age on these relations, both blood and tibia lead were significantly associated (β= 0.0111, p < 0.01 and β= 0.0036, p = 0.04, respectively) in participants in the oldest age tertile. These associations decreased after adjustment for blood pressure and renal function, although blood lead remained significantly associated with uric acid (β= 0.0156, p = 0.01) when the population was restricted to the oldest tertile of workers with serum creatinine greater than the median (0.86 mg/dL). Next, in models of renal function in all workers, uric acid was significantly (p < 0.05) associated with all renal outcomes except NAG. Finally, in the oldest tertile of workers, associations between lead dose and NAG were unchanged, but fewer associations between the lead biomarkers and the clinical renal outcomes remained significant (p ≤0.05) after adjustment for uric acid. In conclusion, our data suggest that older workers comprise a susceptible population for increased uric acid due to lead. Uric acid may be one, but not the only, mechanism for lead-related nephrotoxicity.
kidney functionmechanismsoccupational lead exposurerenal early biologic effect markersuric acid
==== Body
Historically, gout was common among patients with lead poisoning (Batuman 1993). More recently, associations between various measures of lead dose and serum uric acid (urate) levels have been reported in studies of occupationally exposed populations (Ehrlich et al. 1998; Wang et al. 2002) as well as in general population studies (Lin et al. 2002; Shadick et al. 2000). These associations are present at much lower lead doses than those associated with gout in historical lead poisoning. Lead exposure also increases the risk for adverse renal outcomes. Lead has been reported to cause nephrotoxicity by several mechanisms, although it is not known which of these is the predominant pathway (Nolan and Shaikh 1992; Sanchez-Fructuoso et al. 2002; Vaziri 2002). Uric acid is also a nephrotoxicant, and increasing evidence suggests that this toxicity occurs at lower levels than previously recognized (Johnson et al. 2003). Several adverse renal and vascular outcomes have been reported in a recently developed rodent model of low-level hyperuricemia, including hypertension and tubulointerstitial fibrosis (Mazzali et al. 2001a), renal afferent arteriolopathy (Mazzali et al. 2002), glomerular hypertrophy, glomerulosclerosis (Nakagawa et al. 2003), and glomerular hypertension (Sanchez-Lozada et al. 2002). More important, uric acid in this model accelerates renal dysfunction from other causes (Kang et al. 2002; Mazzali et al. 2001b). This raises the intriguing possibility that increased uric acid is one mechanism by which lead causes nephrotoxicity.
In our recently reported analyses of data from the first of three evaluations in a longitudinal study of the health effects of inorganic lead exposure in 803 current and former lead workers (Weaver et al. 2003), we found associations between lead exposure and dose measures and adverse renal function outcomes. Lead measures were associated with decreased renal function, primarily in the oldest tertile of workers (> 46 years of age). Therefore, we analyzed data from the entire population of lead workers and conducted separate analyses of the oldest tertile of workers in some models to determine whether the lead biomarkers were associated with uric acid and whether uric acid levels were associated with renal function outcomes. In addition, we evaluated whether relations between the lead biomarkers and renal outcomes were altered after adjustment for uric acid.
Materials and Methods
Study overview and design.
We report data from 803 current and former lead workers who completed the first of three annual evaluations in a longitudinal study of the renal, vascular, hematopoietic, and nervous system effects of inorganic lead exposure. Participants were evaluated between 24 October 1997 and 19 August 1999. All participants provided written, informed consent. The study protocol was approved by institutional review boards at the SoonChunHyang University and the Johns Hopkins University Bloomberg School of Public Health. Participation in the study was voluntary, and workers were paid approximately $30 for their time and effort.
Study population.
As previously described (Schwartz et al. 2001; Weaver et al. 2003), workers were recruited from 26 different plants that produced lead batteries, lead oxide, lead crystal, or radiators or were secondary lead smelters. Workers were designated as lead workers based on the potential for exposure to lead in the manufacturing process. No medical exclusionary criteria were used. Study participants were not currently occupationally exposed to other known renal toxicants.
Data collection.
Data collection was completed either at the Institute of Industrial Medicine of the SoonChunHyang University in Chonan or at the study plants, using previously reported methods (Schwartz et al. 2001; Weaver et al. 2003). Data and biologic specimens collected included a standardized questionnaire on demographics, medical history, and occupational history; blood pressure measured with a Hawksley random zero sphygmomanometer (Lee et al. 2001); height and weight measurement; a blood specimen [for blood lead, blood urea nitrogen (BUN), serum creatinine, and uric acid]; a spot urine sample [for N-acetyl-β-d-glucosaminidase (NAG), retinol-binding protein (RBP), and creatinine]; and tibia lead concentration. A 4-hr urine collection after oral administration of 10 mg/kg dimercaptosuccinic acid (DMSA) was also obtained to measure DMSA chelatable lead and creatinine clearance (787 participants completed this collection).
Laboratory methods.
The lead biomarkers and renal outcomes were measured using previously reported assays (Schwartz et al. 2001; Weaver et al. 2003). In brief, blood lead was measured (Fernandez 1975) with an Hitachi 8100 Zeeman background-corrected atomic absorption spectrophotometer (Hitachi Ltd. Instruments, Tokyo, Japan) at the Institute of Industrial Medicine, a certified reference laboratory for lead in South Korea. Tibia lead was assessed via a 30-min measurement of the left mid-tibia diaphysis using 109Cd in a back-scatter geometry to fluoresce the K-shell X rays of lead. The lead X rays were recorded with a radiation detector and then quantified and compared with calibration data to estimate the concentration of lead in bone (Todd and Chettle 1994; Todd and McNeill 1993). The emitted K-shell X rays were attenuated as they passed through bone and overlying tissues. The lead X rays were therefore normalized to the amount of elastic scattering from the bone itself to yield a measurement accuracy that is independent of the distance between the radiation source and the subject, subject positioning, small subject movements, overlying tissue thickness, and bone size, shape, geometry, and density (Todd 2000a, 2000b; Todd and Chettle 1994; Todd and McNeill 1993). All point estimates, including negative values, were retained in the statistical analyses in order to minimize bias and to avoid censoring of data (Kim et al. 1995). Urine lead levels in the 4-hr collection were measured at the Wadsworth Center of the New York State Department of Health (Albany, NY, USA) by electrothermal atomic absorption spectrometry with Zeeman background correction (model 4100ZL; Perkin Elmer, Norwalk, CT, USA) (Parsons and Slavin 1999). BUN, serum creatinine, and uric acid were measured via an automatic chemical analyzer (model TBA 40FR Biochemical Analyzer; Toshiba, Tokyo, Japan). Urine creatinine was measured in spot samples (for adjustment of NAG and RBP) and in the 4-hr sample after DMSA (for determination of measured creatinine clearance and adjustment of DMSA-chelatable lead levels), using a modification of the Sigma kit (Sigma Chemical Company, St. Louis, MO, USA) assay (Weaver et al. 2000). Measured creatinine clearance was defined as [(urinary creatinine in milligrams per deciliter × urine volume in milliliters) ÷ serum creatinine in milligrams per deciliter] ÷ collection time in minutes. Calculated creatinine clearance was obtained from the Cockcroft-Gault equation (Cockcroft and Gault 1976). NAG activity (expressed in micromoles of substrate converted per hour) was measured using the PPR NAG test kit (PPR Diagnostics, Ltd., London, UK), and RBP was measured using a modification of the method of Topping et al. (1986). As previously reported by Weaver et al. (2003), the mean between-day coefficient of variation (CV) for 138 random NAG samples assayed in duplicate was 6.0%; the CV for RBP was 7.4% (75 samples assayed in duplicate).
Statistical analysis.
The overall goal of our analysis was to develop models that would allow hypotheses to be generated regarding causal pathways involving lead, uric acid, blood pressure, and renal function. As shown in Figure 1, these variables are biologically interrelated. As a result, adjustment for covariates presents unique challenges. Adjustment for renal function and blood pressure likely results in overcontrol when associations between lead measures and uric acid are being evaluated. This is because renal dysfunction and elevated blood pressure are risk factors for increased uric acid (Wortmann and Kelley 2001), and both can be caused or exacerbated by lead dose; thus, they may be in the causal pathway between lead and uric acid. On the other hand, because non-lead-related factors contribute to both renal dysfunction and elevated blood pressure, lack of adjustment for these variables in such models likely results in residual confounding. The interrelatedness of these variables, as it relates to the potential for confounding versus causality, has been extensively discussed in the literature pertaining to uric acid as a risk factor for adverse cardiac, vascular, and renal outcomes (Johnson et al. 2003). Therefore, we have presented our data both with and without additional adjustment.
Analysis in these current and former lead workers was directed toward the following steps: a) to evaluate associations of three lead dose biomarkers (tibia lead, blood lead, and DMSA-chelatable lead) with uric acid, with and without control for blood pressure and renal function, while controlling for other covariates (Figure 2A); b) to evaluate associations between uric acid and six renal function outcomes (BUN, serum creatinine, measured creatinine clearance, calculated creatinine clearance, RBP, and NAG), with and without control for lead, while adjusting for blood pressure and other covariates (Figure 2B); and c) to determine whether relations among these lead biomarkers and the six renal outcomes were altered by adjustment for uric acid, while controlling for other covariates, including blood pressure (Figure 2C). Statistical analysis was completed using SAS software (SAS Institute, Inc., Cary, NC, USA).
Initially, we examined variable distributions. The distributions of NAG and RBP showed departures from normality and were thus ln-transformed; the adequacy of this transformation was subsequently confirmed by examination of the residuals from regression models. Linear regression modeling was used to evaluate associations between lead measures and both uric acid and renal function as outcomes, in separate models. Covariate selection for regression models of uric acid as the outcome used a priori variables [age, sex, and body mass index (BMI; weight in kilograms divided by the square of height in meters)] in modeling that initially included other biologically relevant variables in separate models. Variables with p-values < 0.1 were then modeled together, and those with significant p-values in the combined model were retained. The additional covariates assessed included diabetes and hypertension (both based on participant report of physician diagnosis), use of analgesics (based on questionnaire data on medication use), work status (current vs. former lead worker), systolic and diastolic blood pressure, renal function (BUN, serum creatinine, measured creatinine clearance, and calculated creatinine clearance), tobacco use, and alcohol consumption. Serum creatinine was selected as the measure of renal function in the uric acid models because the proportion of variance explained by the model when it was included (r2 = 0.37) was the highest, compared with the other renal outcome measures. Continuous independent variables were centered at the mean or, for the effect modification models discussed below, at the tertile cut-point nearest to the mean. Covariate selection for the renal outcome models was previously reported (Weaver et al. 2003).
Finally, models with cross-product terms of the lead measures and age (age was categorized by tertiles) were evaluated, in order to assess effect modification by age on associations between the lead biomarkers and uric acid. In these models, age was also entered into the model as a centered, continuous variable, in order to avoid residual confounding.
We evaluated models for linear regression assumptions and the presence of outlying points using added variable plots (Weisberg 1985), which are graphical summaries of the relation between Y and a particular X (referred to as Xa below), adjusted for all of the other covariates. Specifically, the residuals of the regression of Y on all of the covariates except Xa are plotted on the y-axis. This is the part of Y not explained by those covariates. Next, the residuals from the regression of Xa on all the other covariates are computed. This is the part of Xa not explained by the other covariates. These residuals are plotted on the x-axis. For each plot, two lines were overlaid: the regression line, and a line determined by a scatter plot smoothing method (lowess) that calculates a locally weighted least squares estimate for each point in the scatter plot (Cleveland 1979). This allows an examination of the data for outliers that are overly influential, as evidenced by inconsistency between the lowess and regression lines (i.e., when one or two data points with both high lead dose and uric acid move the lowess line away from the regression line, they are likely to overly influence the regression line as well). When applicable, models were repeated without outliers. Models were also assessed for collinearity through examination of variance inflation factors and conditional indices.
Results
Selected demographics, exposure, and health outcome measures.
Information on demographics, lead biomarkers, uric acid levels, renal function, and selected comorbid conditions is presented in Tables 1 and 2. Mean (± SD) blood, tibia, and DMSA-chelatable lead levels were 32.0 ± 15.0 μg/dL, 37.2 ± 40.4 μg/g bone mineral, and 0.768 ± 0.862 mg/g creatinine, respectively. Values for these lead measures varied over a wide range. Mean values for uric acid and renal outcomes were normal, although the range for each included several abnormal outliers.
Lead measure associations with uric acid levels.
In linear regression modeling of uric acid levels in all 803 lead workers, after adjustment for age, sex, BMI, and alcohol use, none of the lead measures was associated (Table 3). Next, we performed regression modeling to evaluate whether age, divided into tertiles (≤36 years, 36.1–46.0 years, > 46.0 years), modified relations between the lead biomarkers and uric acid levels. In models adjusted for age, sex, BMI, and alcohol use, we found evidence of effect modification by age (Table 4, method 1). Blood and tibia lead, in separate models, were associated with uric acid in participants in the oldest age tertile. As expected, because of the biologic interrelated-ness of these variables (discussed in “Materials and Methods” and shown in Figures 1 and 2), both lead associations decreased after additional adjustment for systolic blood pressure (Table 4, method 2) and renal function (Table 4, method 3). However, blood lead remained associated with uric acid (β= 0.0156, p = 0.01) when these associations were modeled in the 133 oldest workers who had serum creatinine greater than the median value (0.86 mg/dL).
Associations between uric acid levels and renal outcomes.
The six renal function measures were modeled as outcomes to evaluate whether uric acid was associated with renal function in this population of lead workers. Uric acid levels were associated in all renal outcome models except NAG (Table 5). Higher uric acid was associated with worse renal function as assessed by the clinical measures but, conversely, with lower RBP. These associations remained significant after the lead biomarkers were added into the models.
Effect of uric acid adjustment on lead measure associations in renal function models.
Associations between the lead biomarkers and the renal outcomes, after adjustment for uric acid, were modeled in the oldest tertile of workers because the associations of lead biomarkers with uric acid were in the oldest subset and the associations between higher lead dose and worse renal function were also primarily in this group. The median age of these 266 workers was 51.1 years with a range of 46.0–64.8 years. As shown in Table 6, associations between the lead measures and NAG were unchanged after adjustment for uric acid. However, fewer associations between lead biomarkers and clinical renal outcomes remained significant (p ≤0.05) after adjustment for uric acid.
Discussion
In this study, we used data from the first of three evaluations in a longitudinal study of Korean lead workers to develop hypotheses about causal pathways among lead biomarkers, uric acid, renal function, and blood pressure. First, we evaluated associations of three lead dose biomarkers with uric acid, with and without control for blood pressure and renal function, while controlling for other covariates (Figure 2A). Next, we evaluated associations between uric acid and six renal function outcomes, with and without control for lead, while adjusting for blood pressure and other covariates (Figure 2B). Finally, we examined the effect of uric acid adjustment on associations between the lead biomarkers and renal outcomes, while controlling for other covariates, including blood pressure (Figure 2C).
Blood and tibia lead associations with uric acid were observed in participants in the oldest age tertile, after adjustment for age, sex, BMI, and alcohol ingestion. These associations were diminished after adjustment for blood pressure and renal function, although blood lead remained significantly associated with uric acid in the 133 oldest workers who had serum creatinine greater than the median. Next, uric acid was significantly associated with all renal function outcomes except NAG. Lastly, after adjustment for uric acid, fewer associations between lead biomarkers and the clinical renal outcomes remained significant (p ≤0.05).
It has been recognized for many years that individuals who have been heavily exposed to lead are at increased risk for both gout and renal disease (Batuman 1993; Shadick et al. 2000). In high-level lead exposure, urate clearance is decreased to a greater extent than can be explained by decreased glomerular filtration alone (Emmerson and Ravenscroft 1975). A defect in tubular secretion of urate is thought to be the primary factor involved (Ball and Sorensen 1969; Emmerson 1965; Emmerson and Ravenscroft 1975), although excessive tubular reabsorption (Emmerson et al. 1971) and extrarenal mechanisms such as lead effects on porphyrin metabolism (Emmerson and Ravenscroft 1975) have also been considered. Associations between lead measures and uric acid have been examined in populations encompassing a wide range of lead doses (Table 7). Relations between lead dose and gout or uric acid have also been studied in various patient populations. Increased EDTA-chelatable lead burdens have been reported in patients who have both gout and renal disease compared with other groups such as patients with gout alone or with renal disease of known non-lead-related etiology (Batuman 1993; Miranda-Carus et al. 1997; Sanchez-Fructuoso et al. 1996). Lin et al. (2001) measured blood lead and EDTA-chelatable lead in 67 patients with chronic renal insufficiency and gout and 34 patients with chronic renal insufficiency only. Mean blood lead levels were similar in the two groups (5.4 and 4.4 μg/dL, respectively), but mean EDTA-chelatable lead levels (138.1 and 64.2 μg/72 hr, respectively) were significantly (p < 0.01) different. All four uric acid measures were associated with EDTA-chelatable lead after adjustment for age, sex, BMI, daily protein intake, and creatinine clearance. Next, 30 participants with chronic renal insufficiency, gout, and EDTA-chelatable lead levels between 80.2 and 361 μg/72 hr were randomized to either a treatment group receiving 1 g EDTA per week for 4 weeks (n = 20) or a control group who received glucose in normal saline infusions. The two groups had similar uric acid, renal function, and lead measures prechelation. In the treated group, mean EDTA-chelatable lead declined from 159.2 to Each renal outcome was modeled separately. Regression results from each model are presented only for the association of uric acid with the renal outcome. BUN, serum creatinine, measured creatinine clearance, and calculated creatinine clearance models were adjusted for age, sex, BMI, current/former worker status, and hypertension. NAG and RBP models were adjusted for age, sex, BMI, systolic blood pressure, current/former worker status, alcohol ingestion, and diabetes. 41 μg/72 hr; mean serum urate decreased from 10.2 to 8.6 mg/dL (p = 0.02 for percent change, compared with the control group), and mean urate clearance increased from 2.7 to 4.2 mL/min (p < 0.01 for percent change, compared with the control group). Mean creatinine clearance also increased from 50.8 to 54.2 mL/min (p = 0.06 for percent change, compared with the control group). Similar uric acid findings, including results from chelation, were noted in a population of 111 participants with normal renal function, of whom 27 had gout (Lin et al. 2002).
The data discussed above and presented in Table 7 are generally consistent with the premise that in young, otherwise healthy workers, a higher lead dose, such as mean blood lead level > 50–60 μg/dL [or perhaps higher, because neither Wang et al. (2002) nor Ehrlich et al. (1998) adjusted for blood pressure or renal function], is required before associations with uric acid are present. However, in studies that include participants with other risk factors for elevated uric acid, such as older age or comorbid conditions, lower lead levels are associated with increases in uric acid.
High levels of uric acid are known to be nephrotoxic; however, controversy exists as to whether observed relations between lower levels of uric acid and renal dysfunction are causal or due to confounding. Recently, a rodent model of hyperuricemia was developed (Mazzali et al. 2001a). As noted in the introductory remarks, a range of adverse renal and vascular outcomes, similar to those noted in humans with primary hypertension (Mazzali et al. 2002) and/or renal dysfunction (Nakagawa et al. 2003), was observed in these rats. In humans, uric acid was found to be associated with reduced renal blood flow and increased renal vascular resistance in patients with primary hypertension (Messerli et al. 1980). Thus, uric acid may be nephrotoxic at lower levels than previously recognized, as opposed to being simply a marker for other renal risk factors.
Many mechanisms for the adverse affect of lead on the kidneys, either directly or through the vascular system, have been proposed (Nolan and Shaikh 1992; Sanchez-Fructuoso et al. 2002; Vaziri 2002). One mechanism not commonly considered in low to moderate lead exposure is increased uric acid. However, there are a number of similarities between the renal and vascular effects reported from low-level uric acid and those from lead exposure. Tubulointerstitial fibrosis, a classic (although nonspecific) finding in lead exposure, has been observed in the uric acid model in the absence of the urate crystals that are commonly seen in this pathology at higher levels of hyperuricemia (Mazzali et al. 2001a). Glomerular hypertrophy was reported in hyperuricemic rodents (Nakagawa et al. 2003), and Inglis et al. (1978) reported this in adults who survived childhood lead poisoning. Afferent renal arterial thickening has also been observed in hyperuricemic rats (Mazzali et al. 2002). Renal vascular disease in lead-exposed humans has been reported in several case series (Inglis et al. 1978; Morgan et al. 1966; Wedeen et al. 1975). Sanchez-Fructuoso et al. (2002) recently reported hypertrophy of the medium and small renal arteries and arterioles in rats whose blood lead levels ranged from 52.9 to 33.2 μg/dL at day 90 (when lead ingestion ceased). However, these vascular abnormalities were not observed in rats whose lead exposures, over a 12-month period, were either lower (blood lead levels ~ 20–30 μg/dL) (Khalil-Manesh et al. 1993) or much higher (blood lead levels of 45.5–125.4 μg/dL, averaged over a 12-month period) (Khalil-Manesh et al. 1992). Uric acid was not measured in these rodent studies; however, Goyer (1971) reported hyperuricemia that was not thought to be related to extent of renal insufficiency in lead-exposed rats, which suggests that lead may be one of the exposures that does increase uric acid in rats despite the presence of the uricase enzyme. Mazzali et al. (2001a) reported that increased systolic blood pressure was correlated with serum uric acid. Increased systolic blood pressure was associated with lead dose in the same Korean lead worker population studied in this report (Lee et al. 2001); similar associations have also been reported in other populations (Sharp et al. 1987). Increased juxtaglomerular renin staining was present in the uric acid model (Mazzali et al. 2001a). Data suggest that lead exposure also increases renin; this effect may vary with length of exposure. Several reviews have concluded that renin is increased with short- to moderate-term lead exposure in both animals and humans but is normal or decreased with prolonged exposure (Gonick and Behari 2002; Sharp et al. 1987; Vander 1988). Decreased neuronal nitric oxide synthase expression in the macula densa was reported in rodents in the uric acid model (Mazzali et al. 2001a). In contrast, the effect of lead on NO does not involve decreased NO synthase expression (Vaziri 2002). In fact, just the opposite occurs because lead exposure generates oxidants that deplete NO, and NO synthase expression is up-regulated in response.
Conclusion
Our data suggest that, at the moderate levels of lead exposure present in our population, older workers comprise a susceptible population for increased uric acid. This is consistent with the published literature, as noted above. The impact of adjustment for renal function and blood pressure suggests that the effect of lead on uric acid may be mediated through these pathways (Figure 2A). However, because blood lead remained associated with uric acid in our most susceptible group (the oldest workers who had the greatest renal dysfunction), even after adjustment for renal function and blood pressure, mechanisms other than decreased glomerular filtration, such as decreased tubular secretion or even extrarenal mechanisms, may be involved at these exposure levels. Because our data [and those of others (Shadick et al. 2000)] suggest an effect of lead on uric acid beyond that due to renal dysfunction alone, and because uric acid was associated with adverse renal outcomes and resulted in reduced significance of lead biomarker associations in our population, uric acid may be one mechanism through which lead is nephrotoxic. However, this is not the only mechanism for lead-related nephrotoxicity. In our data, the association between blood lead and serum creatinine remained significant (p < 0.05) even after adjustment for uric acid. Associations between lead dose and NAG were unchanged, and uric acid was inversely associated with RBP. The effects of lead and uric acid on the NO system are also different. Thus, other mechanisms must be involved.
Conclusions regarding causality in this study must be limited because it is cross-sectional. An additional limitation is that we were not able to adjust for the use of medications that influence uric acid because Koreans are not routinely provided with the names of their medications. However, few participants reported any prescription medication use. Our results do suggest that further evaluation of relations among the lead dose biomarkers, uric acid, and renal function in our longitudinal data set would be of value. This is particularly true because these mechanistic relations may be clinically important. EDTA chelation has been reported to improve both renal function and urate clearance in patients with renal insufficiency and gout, even when EDTA-chelatable lead body burdens were quite low (Lin et al. 2001). If this work is replicated in other populations and low-level uric acid is found to be nephrotoxic, uric acid should also be monitored in patients who are in the early stages of diseases such as early chronic renal insufficiency and whose lead body burdens are amenable to chelation.
Figure 1 Biologic relations among lead, uric acid, blood pressure, and renal function variables. Uric acid is an established nephrotoxicant at high levels (a); the threshold for renal toxicity is uncertain. The association between uric acid levels and increased blood pressure may be causal or due to confounding (b). Specifically, high uric acid levels may cause hypertension secondary to renal dysfunction but whether low-level uric acid causes primary hypertension is less certain.
Figure 2 Biologic relations among variables in models from Tables 4–6. (A) Associations of lead biomarkers with uric acid (black arrow) in method 1 (Table 4). The gray arrows represent the blood pressure pathway added in method 2, Table 4; blue arrows represent the renal function pathway added in method 3 (Table 4). (B) Relations between uric acid levels and renal function outcomes. Data in Table 5 control for blood pressure (gray arrows); lead biomarkers (blue arrow) were also added to these methods (Table 6 shows selected methods in the oldest tertile of workers). (C) Associations of lead biomarkers, uric acid, and blood pressure with renal function outcomes (presented in Table 6). These methods specifically assessed the effect of uric acid (blue arrows) on the main association between lead biomarkers and renal outcomes (black arrow), while controlling for blood pressure (gray arrows) and other covariates.
Table 1 Selected demographic, exposure, and health outcome measures (categorical variables) of 803 current and former lead workers in South Korea.
Characteristic No. (%)
Sex
Male 639 (79.6)
Female 164 (20.4)
Work status
Current lead worker 709 (88.3)
Former lead worker 94 (11.7)
Diabetes 6 (0.8)
Hypertension 58 (7.2)
Regular analgesic use 16 (2.0)
Alcohol use
Never 233 (29.1)
Current use 521 (65.0)
Past use 48 (6.0)
Tobacco use
Never 255 (31.8)
Current use 458 (57.1)
Past use 89 (11.1)
Table 2 Selected demographic, exposure, and health outcome measures (continuous variables) of 803 current and former lead workers in South Korea.
Health outcome Mean ± SD Range
Age (years) 40.4 ± 10.1 17.8–64.8
BMI (kg/m2) 23.0 ± 3.0 15.7–34.2
Systolic blood pressure (mm Hg) 123.2 ± 16.3 83.7–215.3
Diastolic blood pressure (mm Hg) 75.7 ± 12.0 36.0–126.7
Blood lead (μg/dL) 32.0 ± 15.0 4.3–85.7
Tibia lead (μg Pb/g bone mineral) 37.2 ± 40.4 −7.4–337.6
DMSA-chelatable lead (mg Pb/g creatinine)a 0.768 ± 0.862 0.02–8.98
Lead job duration (years) 8.2 ± 6.5 < 1–36.2
Uric acid (mg/dL) 4.8 ± 1.2 1.4–12.3
BUN (mg/dL) 14.4 ± 3.7 6–32.2
Serum creatinine (mg/dL) 0.90 ± 0.16 0.48–2.5
Measured creatinine clearance (mL/min)a 114.7 ± 33.6 11.8–338.9
Calculated creatinine clearance (mL/min) 94.7 ± 20.7 41.1–184.5
NAG (μmol/hr/g creatinine) 215.3 ± 188.5 13.8–2577.0
RBP (μg/g creatinine) 63.6 ± 190.6 5.2–4658.7
a n = 787.
Table 3 Linear regression models to evaluate associations of lead dose biomarkers with uric acid levels (n = 803).
Model Lead variable β-coefficient SE β p-Value Model r2
1 Tibia lead (μg Pb/g bone mineral) −0.0005 0.0010 0.62 0.32
2 Blood lead (μg/dL) 0.0027 0.0027 0.32 0.31
3 DMSA-chelatable lead (μg Pb/g creatinine) 0.0259 0.0431 0.55 0.31
Uric acid was modeled separately as the outcome, with one of the three lead biomarkers included per model. Regression results from each model are presented only for the association of the lead biomarker with uric acid. Models were also adjusted for age, sex, BMI, and alcohol use.
Table 4 Linear regression models to evaluate effect modification by age in tertiles on associations of blood and tibia lead with uric acid in all lead workers, with outliers removed (method 1), and with additional control for systolic blood pressure (method 2) and serum creatinine (model 3) (n = 803).
Method 1
Method 2
Method 3
Variable β-coefficient SE β p-Value β-coefficient SE β p-Value β-coefficient SE β p-Value
Blood lead model
Intercept 4.9217 0.0757 < 0.01 4.9350 0.0759 < 0.01 4.8528 0.0736 < 0.01
Age (years) −0.0182 0.0039 < 0.01 −0.0199 0.0040 < 0.01 −0.0210 0.0039 < 0.01
Systolic blood pressure (mm Hg) — — — 0.0047 0.0023 0.04 0.0046 0.0022 0.04
Serum creatinine (mg/dL) — — — — — — 2.1830 0.2666 < 0.01
Blood lead (μg/dL) 0.0111 0.0041 < 0.01 0.0105 0.0041 0.01 0.0071 0.0039 0.07
Blood lead × age category 2 −0.0109 0.0057 0.05 −0.0107 0.0056 0.06 −0.0063 0.0054 0.25
Blood lead × age category 1 −0.0150 0.0058 0.01 −0.0148 0.0058 0.01 −0.0107 0.0056 0.06
Tibia lead model
Intercept 4.8932 0.0749 < 0.01 4.9087 0.0750 < 0.01 4.8430 0.0735 < 0.01
Age (years) −0.0155 0.0039 < 0.01 −0.0174 0.0040 < 0.01 −0.0184 0.0038 < 0.01
Systolic blood pressure (mm Hg) — — — 0.0052 0.0022 0.02 0.0048 0.0022 0.03
Serum creatinine (mg/dL) — — — — — — 2.1808 0.3189 < 0.01
Tibia lead (μg Pb/g bone mineral) 0.0036 0.0018 0.04 0.0031 0.0018 0.08 0.0019 0.0017 0.28
Tibia lead × age category 2 −0.0057 0.0028 0.04 −0.0053 0.0028 0.06 −0.0019 0.0028 0.49
Tibia lead × age category 1 −0.0071 0.0029 0.02 −0.0067 0.0029 0.02 −0.0044 0.0029 0.13
—, Variable not included in method. Models were also adjusted for sex, BMI, and alcohol use. The oldest age tertile is the reference category. Slopes in the middle (age category 2) and youngest (age category 1) age categories are obtained by adding their respective β-coefficients (of the cross-product term for age × lead) to the β-coefficient of the reference category (oldest age group). p-Values for the cross-product terms reflect the statistical significance of the difference between the slopes of the regression line in that age category and the regression line for the oldest age group.
Table 5 Linear regression models to evaluate associations of uric acid with renal outcomes while controlling for covariates (n = 803).
Model Renal function outcome Uric acid β-coefficient SE β p-Value
1 BUN (mg/dL) 0.4186 0.1246 < 0.01
2 Serum creatinine (mg/dL) 0.0267 0.0038 < 0.01
3 Measured creatinine clearance (mL/min) −2.5300 0.9791 0.01
4 Calculated creatinine clearance (mL/min) −2.1700 0.4662 < 0.01
5 ln NAG [ln (μmol/hr/g creatinine)] −0.0262 0.0210 0.21
6 ln RBP [ln (μg/g creatinine)] −0.1067 0.0254 < 0.01
Table 6 Linear regression models to evaluate associations of lead dose biomarkers and uric acid levels with renal outcomes in 266 lead workers in the oldest tertile of age.
Method 1 (lead biomarker models)
Method 2 (uric acid models)
Method 3 (combined models)
Independent variables βcoefficient SE β p-Value βcoefficient SE β p-Value βcoefficient SE β p-Value
BUN (mg/dL) models
Blood lead (μg/dL) 0.0352 0.0183 0.05 — — — 0.0293 0.0185 0.11
Uric acid (mg/dL) — — — 0.4663 0.2307 0.04 0.3963 0.2343 0.09
Serum creatinine (mg/dL) models
Blood lead (μg/dL) 0.0016 0.0006 < 0.01 — — — 0.0012 0.0006 0.03
Uric acid (mg/dL) — — — 0.0245 0.0072 < 0.01 0.0215 0.0073 < 0.01
Tibia lead (μg Pb/g bone mineral) 0.0004 0.0002 0.03 — — — 0.0003 0.0002 0.06
Uric acid (mg/dL) — — — 0.0246 0.0072 < 0.01 0.0233 0.0072 < 0.01
Measured creatinine clearance (mL/min) models
Blood lead (μg/dL) 0.1187 0.1177 0.31 — — — 0.1697 0.1198 0.16
Uric acid (mg/dL) — — — −2.4871 1.4456 0.09 −2.9352 1.4769 0.05
Calculated creatinine clearance (mL/min) models
Blood lead (μg/dL) −0.1221 0.0594 0.04 — — — −0.0950 0.0600 0.11
Uric acid (mg/dL) — — — −2.0384 0.7487 < 0.01 −1.8095 0.7604 0.02
ln NAG [ln (μmol/hr/g creatinine)] models
Blood lead (μg/dL) 0.0089 0.0028 < 0.01 — — — 0.0092 0.0028 < 0.01
Uric acid (mg/dL) — — — −0.0115 0.0364 0.76 −0.0289 0.0361 0.42
Tibia lead (μg Pb/g bone mineral) 0.0023 0.0008 < 0.01 — — — 0.0023 0.0008 < 0.01
Uric acid (mg/dL) — — — −0.0070 0.0366 0.85 −0.0094 0.036 0.80
DMSA-chelatable lead (mg Pb/g creatinine) 0.1931 0.0511 < 0.01 — — — 0.1944 0.0512 < 0.01
Uric acid (mg/dL) — — — −0.0182 0.0373 0.63 −0.0235 0.0363 0.52
BUN, serum creatinine, measured creatinine clearance, and calculated creatinine clearance models were also adjusted for age, sex, BMI, current/former worker status, and hypertension. NAG and RBP models were adjusted for age, sex, BMI, systolic blood pressure, current/former worker status, alcohol ingestion, and diabetes. Only models in which p ≤0.05 for the lead variable without uric acid adjustment are shown, with the exception of the measured creatinine clearance model; this model is included because the p-value for the β-coefficient of the uric acid variable decreased to ≤0.05 after adjustment for blood lead.
Table 7 Summary of selected publicationsa that have evaluated lead measure associations with uric acid.
Study No. Mean age (years) Mean blood or bone leadb Association p-Value of lead measure Covariates controlled for Comments
Wang et al. 2002 229 65% 67.7 μg/dL, males 10 μg/dL increase in blood lead associated with a 0.085 mg/dL increase in uric acid 0.02 Sex and body weight Alcohol apparently not significant
< 40 48.6 μg/dL, females
Ehrlich et al. 1998 382 41 53.5 μg/dL Current and historical blood lead in quintiles associated with uric acid ≤0.01 for trend Age, height, and weight Tibia lead measured on a random sample of 40 participants
69.7 μg/g
Roels et al. 1994 76c 44 43.0 μg/dL; 66 μg/g Continuous lead measures (workers plus controls) with uric acid NS Not reported
68d 43 14.1 μg/dL; 21 μg/g
Baker et al. 1981 318 36e 22.4 μg/dLe Continuous blood lead with uric acid NS Age
37f 24.0 μg/dLf
Smith et al. 1995 691 48 7.8 μg/dL Continuous blood lead with uric acid NS Age, alcohol, ALAD
Shadick et al. 2000 777 67 5.9 μg/dL Blood lead and uric acid 0.1 Age, BMI, diastolic blood pressure, alcohol, serum creatinine Normative Aging Study
30.2 μg/g patella Patella lead and uric acid 0.02
20.8 μg/g tibia Tibia lead and uric acid 0.06
Abbreviations: ALAD, δ-aminolevulinic acid dehydrase; NS, not significant.
a Based on sample size and extent of statistical analysis.
b μg/g indicates tibia lead per bone mineral unless noted as patella.
c Lead workers.
d Controls.
e Rural residence.
f Urban residence.
==== Refs
References
Baker MD Johnston JR Maclatchy AE Bezuidenhout BN 1981 The relationship of serum uric acid to subclinical blood lead Rheumatol Rehabil 20 208 210 7302466
Ball GV Sorensen LB 1969 Pathogenesis of hyperuricemia in saturnine gout N Engl J Med 280 1199 1202 5767461
Batuman V 1993 Lead nephropathy, gout, and hypertension Am J Med Sci 305 241 247 8475950
Cleveland WS 1979 Robust locally weighted regression and smoothing scatterplots J Am Stat Assoc 74 829 836
Cockcroft DW Gault MH 1976 Prediction of creatinine clearance from serum creatinine Nephron 16 31 41 1244564
Ehrlich R Robins T Jordaan E Miller S Mbuli S Selby P 1998 Lead absorption and renal dysfunction in a South African battery factory Occup Environ Med 55 453 460 9816378
Emmerson BT 1965 The renal excretion of urate in chronic lead nephropathy Australas Ann Med 14 295 303 5861252
Emmerson BT Mirosch W Douglas JB 1971 The relative contributions of tubular reabsorption and secretion to urate excretion in lead nephropathy Aust NZ J Med 4 353 362
Emmerson BT Ravenscroft PJ 1975 Abnormal renal urate homeostasis in systemic disorders Nephron 14 62 80 1054788
Fernandez FJ 1975 Micromethod for lead determination in whole blood by atomic absorption, with use of the graphite furnace Clin Chem 21 558 561 1116290
Gonick HC Behari JR 2002 Is lead exposure the principal cause of essential hypertension? Med Hypotheses 59 239 246 12208146
Goyer RA 1971 Lead and the kidney Curr Top Pathol 55 147 176 4333698
Inglis JA Henderson DA Emmerson BT 1978 The pathology and pathogenesis of chronic lead nephropathy occurring in Queensland J Pathol 124 65 76 363988
Johnson RJ Kang DH Feig D Kivlighn S Kanellis J Watanabe S 2003 Is there a pathogenetic role for uric acid in hypertension and cardiovascular and renal disease? Hypertension 41 1183 1190 12707287
Kang DH Nakagawa T Feng L Watanabe S Han L Mazzali M 2002 A role for uric acid in the progression of renal disease J Am Soc Nephrol 13 2888 2897 12444207
Khalil-Manesh F Gonick HC Cohen AH 1993 Experimental model of lead nephropathy. III. Continuous low-level lead administration Arch Environ Health 48 271 278 8357279
Khalil-Manesh F Gonick HC Cohen AH Alinovi R Bergamaschi E Mutti A 1992 Experimental model of lead nephropathy. I. Continuous high-dose lead administration Kidney Int 41 1192 1203 1614034
Kim R Aro A Rotnitzky A Amarasiriwardena C Hu H 1995 K X-ray fluorescence measurements of bone lead concentration: the analysis of low-level data Phys Med Biol 40 1475 1485 8532760
Lee BK Lee GS Stewart WF Ahn KD Simon D Kelsey KT 2001 Associations of blood pressure and hypertension with lead dose measures and polymorphisms in the vitamin D receptor and δ-aminolevulinic acid dehydratase genes Environ Health Perspect 109 383 389 11335187
Lin JL Tan DT Ho HH Yu CC 2002 Environmental lead exposure and urate excretion in the general population Am J Med 113 563 568 12459402
Lin JL Yu CC Lin-Tan DT Ho HH 2001 Lead chelation therapy and urate excretion in patients with chronic renal diseases and gout Kidney Int 60 266 271 11422760
Mazzali M Hughes J Kim YG Jefferson JA Kang DH Gordon KL 2001a Elevated uric acid increases blood pressure in the rat by a novel crystal-independent mechanism Hypertension 38 1101 1106 11711505
Mazzali M Kanellis J Han L Feng L Xia YY Chen Q 2002 Hyperuricemia induces a primary renal arteriolopathy in rats by a blood pressure-independent mechanism Am J Physiol Renal Physiol 282 F991 F997 11997315
Mazzali M Kim YG Suga SI Gordon KL Kang DH Jefferson JA 2001b Hyperuricemia exacerbates chronic cyclosporine nephropathy Transplantation 71 900 905 11349724
Messerli FH Frohlich ED Dreslinski GR Suarez DH Aristimuno GG 1980 Serum uric acid in essential hypertension: an indicator of renal vascular involvement Ann Int Med 93 817 821 7447188
Miranda-Carus E Mateos FA Sanz AG Herrero E Ramos T Puig JG 1997 Purine metabolism in patients with gout: the role of lead Nephron 75 327 335 9069456
Morgan JM Hartley MW Miller RE 1966 Nephropathy in chronic lead poisoning Arch Intern Med 118 17 29 5940188
Nakagawa T Mazzali M Kang DH Kanellis J Watanabe S Sanchez-Lozada LG 2003 Hyperuricemia causes glomerular hypertrophy in the rat Am J Nephrol 23 2 7 12373074
Nolan CV Shaikh ZA 1992 Lead nephrotoxicity and associated disorders: biochemical mechanisms Toxicology 73 127 146 1319092
Parsons PJ Slavin W 1999 Electrothermal atomization atomic absorption spectrometry for the determination of lead in urine: results of an interlaboratory study Spectrochim Acta Part B 54 853 864
Roels H Lauwerys R Konings J Buchet JP Bernard A Green S 1994 Renal function and hyperfiltration capacity in lead smelter workers with high bone lead Occup Environ Med 51 505 512 7951773
Sanchez-Fructuoso AI Blanco J Cano M Ortega L Arroyo M Fernandez C 2002 Experimental lead nephropathy: treatment with calcium disodium ethylenediaminete-traacetate Am J Kidney Dis 40 59 67 12087562
Sanchez-Fructuoso AI Torralbo A Arroyo M Luque M Ruilope LM Santos JL 1996 Occult lead intoxication as a cause of hypertension and renal failure Nephrol Dial Transplant 11 1775 1780 8918621
Sanchez-Lozada LG Tapia E Avila-Casado C Soto V Franco M Santamaria J 2002 Mild hyperuricemia induces glomerular hypertension in normal rats Am J Physiol Renal Physiol 283 F1105 F1110 12372787
Schwartz BS Lee BK Lee GS Stewart WF Lee SS Hwang KY 2001 Associations of blood lead, dimercaptosuccinic acid-chelatable lead, and tibia lead with neuro-behavioral test scores in South Korean lead workers Am J Epidemiol 153 453 464 11226977
Shadick NA Kim R Weiss S Liang MH Sparrow D Hu H 2000 Effect of low level lead exposure on hyperuricemia and gout among middle aged and elderly men: the Normative Aging Study J Rheumatol 27 1708 1712 10914856
Sharp DS Becker CE Smith AH 1987 Chronic low-level lead exposure: its role in the pathogenesis of hypertension Med Toxicol 2 210 232 3298924
Smith CM Wang X Hu H Kelsey KT 1995 A polymorphism in the δ-aminolevulinic acid dehydratase gene may modify the pharmacokinetics and toxicity of lead Environ Health Perspect 103 248 253 7768225
Todd AC 2000a Contamination of in vivo bone-lead measurements Phys Med Biol 45 229 240 10661594
Todd AC 2000b Calculating bone-lead measurement variance Environ Health Perspect 108 383 386 10811562
Todd AC Chettle DR 1994 In vivo x-ray fluorescence of lead in bone: review and current issues Environ Health Perspect 102 172 177 8033846
Todd AC McNeill FE 1993. In vivo measurements of lead in bone using a 109Cd “spot” source. In: Human Body Composition (Ellis KJ, Eastman JD, eds). New York:Plenum Press, 299–302.
Topping MD Forster HW Dolman C Luczynska CM Bernard AM 1986 Measurement of urinary retinol-binding protein by enzyme-linked immunosorbent assay, and its application to detection of tubular proteinuria Clin Chem 32 1863 1866 3530532
Vander AJ 1988 Chronic effects of lead on the reninangiotensin system Environ Health Perspect 78 77 83 3060354
Vaziri ND 2002 Pathogenesis of lead-induced hypertension: role of oxidative stress J Hypertension 20 S15 S20
Wang VS Lee MT Chiou JY Guu CF Wu CC Wu TN 2002 Relationship between blood lead levels and renal function in lead battery workers Int Arch Occup Environ Health 75 569 575 12373319
Weaver VM Buckley T Groopman JD 2000 Lack of specificity of trans,trans muconic acid as a benzene biomarker after ingestion of sorbic acid-preserved foods Cancer Epidemiol Biomarkers Prev 9 749 755 10919747
Weaver VM Lee B-K Ahn K-D Lee G-S Todd AC Stewart WF 2003 Associations of lead biomarkers with renal function in Korean lead workers Occup Environ Med 60 551 562 12883015
Wedeen RP Maesaka JK Weiner B Lipat GA Lyons MM Vitale LF 1975 Occupational lead nephropathy Am J Med 59 630 641 1200035
Weisberg S 1985. Applied Linear Regression. New York:John Wiley & Sons.
Wortmann RL Kelley WN 2001. Gout and hyperuricemia. In: Kelley’s Textbook of Rheumatology (Ruddy S, Harris ED Jr, Sledge CB, eds). 6th ed. Philadelphia:W.B. Saunders, 1339–1346.
|
15626645
|
PMC1253707
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan 30; 113(1):36-42
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7317
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7351ehp0113-00004315626646ResearchArticlesDose-Additive Carcinogenicity of a Defined Mixture of “Dioxin-like Compounds” Walker Nigel J. 1Crockett Patrick W. 2Nyska Abraham 1Brix Amy E. 3Jokinen Michael P. 4Sells Donald M. 5Hailey James R. 1Easterling Micheal 2Haseman Joseph K. 1Yin Ming 2Wyde Michael E. 1Bucher John R. 1Portier Christopher J. 11National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA2Constella Group, Research Triangle Park, North Carolina, USA3Pathology Associates—A Charles River Company, Durham, North Carolina, USA4Experimental Pathology Laboratories, Research Triangle Park, North Carolina, USA5Battelle Columbus Laboratories, Columbus, Ohio, USAAddress correspondence to N.J. Walker, National Institute of Environmental Health Sciences, 111 Alexander Dr., Research Triangle Park, NC 27705 USA. Telephone: (919) 541-4893. Fax: (301) 451-5596. E-mail:
[email protected] thank all those involved in the conduct of these studies, with special thanks to A. Van Birgelen Braen, D. Orzech, and M. Hejtmancik. We also thank G. Kissling and L. Fischer for critical review of the manuscript.
The authors declare they have no competing financial interests.
1 2005 19 10 2004 113 1 43 48 24 6 2004 19 10 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Use of the dioxin toxic equivalency factor (TEF) approach in human risk assessments assumes that the combined effects of dioxin-like compounds in a mixture can be predicted based on a potency-adjusted dose-additive combination of constituents of the mixture. In this study, we evaluated the TEF approach in experimental 2-year rodent cancer bioassays with female Harlan Sprague-Dawley rats receiving 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), 3,3′,4,4′,5-pentachlorobiphenyl (PCB-126), 2,3,4,7,8-pentachlorodibenzofuran (PeCDF), or a mixture of the three compounds. Statistically based dose–response modeling indicated that the shape of the dose–response curves for hepatic, lung, and oral mucosal neoplasms was the same in studies of the three individual chemicals and the mixture. In addition, the dose response for the mixture could be predicted from a combination of the potency-adjusted doses of the individual compounds. Finally, we showed that use of the current World Health Organization dioxin TEF values adequately predicted the increased incidence of liver tumors (hepatocellular adenoma and cholangiocarcinoma) induced by exposure to the mixture. These data support the use of the TEF approach for dioxin cancer risk assessments.
carcinogenicitydioxinmixturesPCBspersistent organochlorine pollutantspolychlorinated biphenylsPOPsrisk assessmentTEFtoxic equivalency factor
==== Body
The human health risk posed by exposure to persistent organochlorine pollutants, including polychlorinated dioxins, polychlorinated dibenzofurans, and polychlorinated biphenyls (PCBs), present in the food and the environment is one of widespread concerns throughout the industrialized world (Hites et al. 2004; Stellman et al. 2003). Given the absence of adequate toxicology and carcinogenesis information on the vast majority of these classes, the dioxin toxic equivalency factor (TEF) approach is currently used worldwide for assessing and managing the risks posed by exposure to mixtures of certain dioxin-like compounds (DLCs) (Ahlborg et al. 1992; Birnbaum and DeVito 1995; Safe 1990; Van den Berg et al. 1998). The TEF approach is a relative potency paradigm that is based on estimates of the potency of dioxin-like effects of individual chemicals, or a mixture of chemicals assuming a common mechanism of action involving binding of the compound(s) to the aryl hydrocarbon receptor (AhR) (Schmidt and Bradfield 1996). Moreover, the risk associated with a mixture of DLCs may be estimated based on the effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), the most potent member of this class of compounds, and using a dose metric that is based on the summation of the mass of each compound in the mixture after adjustment for its potency relative to that of TCDD. This concept of potency-adjusted dose additivity has been evaluated for a number of end points (DeVito et al. 1997; Hamm et al. 2003; Toyoshiba et al. 2004) but has never been evaluated for cancer risk from chronic/lifetime exposure. Given that assessments of human cancer risk are based in part on data obtained from rodent carcinogenicity studies, it is important and appropriate to assess whether the concept of dose additivity is valid for the carcinogenicity of a mixture of DLCs within the context of a rodent cancer bioassay.
To evaluate the TEF approach for the prediction of cancer risk, the National Toxicology Program (NTP) conducted multiple 2-year lifetime rat bioassays to evaluate the chronic toxicity and carcinogenicity of DLCs and structurally related PCBs and mixtures of these compounds. Specifically we conducted four 2-year rodent bioassays to test the hypothesis of dose-additive carcinogenicity of a defined mixture of DLCs. These studies were conducted in female Harlan Sprague-Dawley rats, based on the prior observations of the carcinogenic sensitivity to TCDD in the Spartan Sprague-Dawley rat strain (Kociba et al. 1978). Animals received either TCDD, PCB-126, 2,3,4,7,8-pentachlorodibenzofuran (PeCDF), or a mixture of all three compounds. Doses were established using the current World Health Organization (WHO) TEF values (Van den Berg et al. 1998) to provide doses of the individual chemicals or the mixture estimated to be equivalent to those used in the TCDD study. The mixture study was designed such that each compound would provide a third of the total dioxin toxic equivalents (TEQs) to the mixture. These relative levels were chosen to maximize statistical power to test for interactions between the three compounds. This does not reflect the relative abundance of each of these compounds in food, the primary medium of human exposure. However, these three compounds combined do account for approximately half of the dioxin-like activity found in human tissues. In this article, we report on the comparative dose–response modeling of the increases in incidence of specific neoplasms in these studies to test the hypothesis of dose additivity of carcinogenicity of dioxins within a defined mixture.
Materials and Methods
Animal use.
The animal studies were conducted at Battelle Columbus Laboratories (Columbus, OH). All studies were conducted according to Good Laboratory Practices (Food and Drug Administration 2002). Animals were obtained from Harlan SD (Indianapolis, IN) and upon receipt were approximately 6 weeks of age. They were held under quarantine for approximately 2 weeks for health screening and were approximately 8 weeks of age at the start of the study. After quarantine, the animals were randomly assigned to control or treated groups and permanently identified by tail tattoo. They were housed five per cage in solid-bottom polycarbonate cages (Lab Products, Inc., Maywood, NJ) suspended on stainless steel racks. Filtered room air underwent at least 10 changes/hr. Animal rooms were maintained at 69–75°F with 35–65% relative humidity and 12 hr light/12 hr dark. Irradiated NTP-2000 pelleted feed (Zeigler Bros., Inc., Gardners, PA) and water were available ad libitum. All animals were observed twice daily for morbidity checks and once per month for formal clinical signs of toxicity; moribund animals were euthanized and necropsied. The health status of the animals was monitored by serologic analysis of serum samples collected from the study animals and male sentinel rats that were placed in the study rooms. Serum samples remained negative for any significant rodent pathogen. Animal husbandry and handling were conducted in accordance with the National Institutes of Health guidelines (Institute of Laboratory Animal Resources 1996).
Chemicals.
TCDD (lot no. CR82-2-2) was supplied by IIT Research Institute (Chicago, IL) and 3,3′,4,4′,5-pentachlorobiphenyl (PCB-126; lot no. 130494) by AccuStandard, Inc. (New Haven, CT). PeCDF (lot no. 080196) was purchased from Cambridge Isotope Laboratories (Cambridge, MA). Each chemical was received in one lot that was used for the entire study. Purity was determined several times during the study by gas chromatography/mass spectroscopy (GC/MS), nuclear magnetic resonance spectroscopy, and gas chromatography using flame ionization detection (PCB-126), electron capture detection (TCDD), proton and carbon-13 nuclear magnetic spectroscopy (PeCDF), and GC/MS (TEF mixture). Purities of TCDD, PCB-126, and PeCDF were determined to be approximately 98, 99.51, and 97%, respectively, with no change in purity observed over the duration of the studies. Dose formulations were prepared monthly for gavage administration by mixing the test chemical in a corn oil vehicle containing 1% USP-grade acetone. The corn oil was analyzed by potentiometric titration, and the acetone by infrared spectroscopy. Homogeneity and stability studies of dose formulations indicated that chemicals could maintain an acceptable homogeneity for dosing and stability for 35 days when stored at room temperature. Dose formulations were analyzed at least every 3 months and were within 10% of the target concentrations. For the mixture, the dose formulations were prepared by mixing volumes of the TCDD, PeCDF, and PCB-126 formulations.
Treatment.
Animals were treated by gavage (2.5 mL/kg), 5 days per week for up to 2 years. Compounds used were TCDD, PCB-126, PeCDF, or a mixture of these three compounds. Group sizes for the 2-year carcinogenicity portion of these studies were 53 animals per dose group except for the 3-ng TCDD/kg group (n = 54) and the 30 ng PCB-126/kg group (n = 55). Target doses used for the individual compound studies were 3, 10, 22, 46, and 100 ng/kg TCDD; 30, 100, 175, 300, 550, and 1,000 ng/kg PCB-126; and 6, 20, 44, 92, and 200 ng/kg PeCDF. The TEF mixture was composed of equal ratios (1:1:1) of TEQs for TCDD, PCB-126, and PeCDF. The TEQ, calculated by multiplying the TEF value (Van den Berg et al. 1998) of each specific compound by the concentration of that compound in the mixture, results in the TCDD equivalent of that compound. For the TEF mixture, doses were formulated for comparison with the 10, 22, 46, and 100 ng/kg TCDD group by using the WHO TEFs of 1.0 for TCDD, 0.1 for PCB-126, and 0.5 for PeCDF. Specific target doses used in the TEF mixture study were 10 ng TEQ/kg (3.3 ng/kg TCDD, 6.6 ng/kg PeCDF, 33.3 ng/kg PCB-126), 22 ng TEQ/kg (7.3 ng/kg TCDD, 14.5 ng/kg PeCDF, 73.3 ng/kg PCB-126), 46 ng TEQ/kg (15.2 ng/kg TCDD, 30.4 ng/kg PeCDF, 153 ng/kg PCB-126), and 100 ng TEQ/kg (33 ng/kg TCDD, 66 ng/kg PeCDF, 333 ng/kg PCB-126). Control animals received corn oil:acetone vehicle (2.5 mL/kg) alone. Batches of actual dosing formulations used were periodically sampled and analyzed every 2–3 months by GC/MS to ensure that they were within 10% of the target concentration.
Pathology.
At necropsy, all tissues were examined grossly, any lesions observed were recorded, and a full complement of tissues was removed and fixed in 10% neutral buffered formalin for microscopic evaluation. After fixation, the tissues were trimmed, processed, embedded in paraffin, sectioned at a thickness of 5 μm, stained with hematoxylin and eosin, and examined microscopically. The pathology findings from all studies were subjected to a full pathology peer review. To ensure consistency of the histopathologic diagnoses among the TEF dioxin projects, the same study pathologist, quality assurance pathologist, pathology working group (PWG) chairperson, NTP pathologist, and members of the PWG served in all studies. In addition, diagnostic criteria for the proliferative hepatocellular lesions were peer reviewed by an external expert panel advisory board.
Statistical analysis.
Dose-specific tumor incidence was survival adjusted using the poly-3 adjustment (Bailer and Portier 1988). Data were modeled using a Hill function, as described by Toyoshiba et al. (2004), using the following formula:
where P(dose) is the probability that an animal will have a tumor, b0 is the background incidence rate (E0), b2 is the half-maximal dose (ED50), and b3 is the shape parameter. Parameters were estimated using maximum likelihood techniques assuming a binomial distribution for the tumor counts and their standard errors estimated using sandwich estimators (Zhang et al. 2000). The relative potency factor (RPF) of each congener (cong) is calculated as b2,TCDD/b2,cong. In the full model (the “independent” model), equation 1 is fit to each congener and to the mixture, resulting in separate estimates of b0, b2, and b3 for each of the three congeners and for the mixture. For the mixture, the dose is an additive function of the component congener doses and the ratios of their ED50 values to that of TCDD (Toyoshiba et al. 2004). With this formula for the mixture dose, if the congeners are dose additive in the mixture, then the RPF for the mixture will be 1. That is, b2,Mix = b2,TCDD if the congeners are dose additive.
Chi-square–based likelihood ratio tests were used to evaluate all hypotheses. The hypotheses tested were as follows:
Same shape:
and
Additivity: same-shape hypothesis and
WHO: same-shape and additivity hypotheses, and
and
The statistical power of the likelihood ratio tests was investigated by simulating data using the maximum-likelihood estimates for the less restricted model (e.g., additivity) to evaluate our ability to reject the more restricted model (e.g., WHO TEFs). The power was found to be rather small, ranging from 0.1 to 0.5 for these data and this design.
Results
In all four studies, there were significant increases in the incidence of both neoplastic and nonneoplastic effects in several tissues [all data from these studies are available from the NTP website (NTP 2004)]. Four specific neoplasms were observed in all of the studies, and increases in the incidences of these neoplasms were considered to be related to treatment: cholangiocarcinoma and hepatocellular adenoma of the liver, cystic keratinizing epithelioma (CKE) of the lung, and gingival squamous cell carcinoma (SCC) of the oral mucosa (Table 1). In the studies of TCDD, PCB-126, and the TEF mixture, the incidences of these neoplasms were significantly and dose-dependently increased over controls. In the study of PeCDF, the incidence of cholangiocarcinoma and hepatocellular adenoma showed a significant dose–response trend over the dose range used, whereas the incidences of CKE and gingival SCC were not significantly elevated above controls. Neither CKE nor cholangiocarcinoma was observed in control animals from any of these studies.
The incidences of these neoplasms were used for the dose–response analysis of the several hypotheses related to the TEF approach. We tested three hypotheses in this study. First, we tested whether the shapes of the dose–response curves were the same across all four studies for each neoplasm, because this is a fundamental assumption in the TEF approach (Van den Berg et al. 1998). To achieve this, survival-adjusted (Bailer and Portier 1988) incidence data from the four studies were modeled using sigmoidal Hill functions, and differences in model fits were evaluated by maximum likelihood methods (Toyoshiba et al. 2004). Initially, each data set was modeled with parameters describing the dose response unrestricted, allowing an independent optimal fit for each chemical or mixture (Figure 1A). This model was then compared with a model in which the only parameter that was unique to each compound was the ED50 (Figure 1B). By comparing the error associated with the two model fits, we tested the null hypothesis that a common shape model was as good a fit as the optimal independent fit. This appeared to hold true (Table 2), indicating that each neoplasm had a common dose–response shape across all four studies. The shape of the dose–response curve for each neoplasm was highly nonlinear (shape parameter > 1.5). RPFs for each neoplasm were calculated based on the ratio of the ED50 (e.g., RPF PCB-126 = ED50 TCDD/ED50 PCB-126) (Table 2). In general, the RPFs for PCB-126 were similar to the WHO TEF value of 0.1 (0.11, 0.09, and 0.09 for cholangiocarcinoma, hepatocellular adenoma, and gingival SCC, respectively), except for the induction of CKE, where the RPF for PCB-126 was 0.2.
The second hypothesis to be tested was whether the increased incidence for the mixture for each neoplasm was consistent with a potency-adjusted dose-additive combination of the individual effects of TCDD, PCB-126, and PeCDF. This was achieved by comparison of the additive model to the same-shape model, for each respective neoplasm (Table 2; Figure 1C vs. Figure 1B). In both models, the administered “dose” of the mixture (on a TEQ basis) was calculated by summing the optimized RPF-adjusted dose of TCDD, PCB-126, and PeCDF
However, the ED50 for the additivity model uses the ED50 value optimized for the TCDD data set, whereas in the same-shape model the ED50 is optimized to the mixture data set. If dose additivity were true, then the fit of the dose–response curve for the mixture should be statistically the same as for TCDD.
For both liver neoplasms, the additive models could not be rejected (Table 2, p > 0.05) and showed minimal deviation from dose additivity. The optimal relative potencies for cholangiocarcinoma and hepatocellular adenoma were 0.98 and 1.02, respectively, compared with the expected value of 1.0. For CKE of the lung, there was a 1.2-fold increase over the expected value of 1.0 (Table 2), although this was not significantly different at the p < 0.01 level. Similarly, for gingival SCC the mixture showed only 47% of the response predicted under dose additivity (antagonism), but this was not significant at the p < 0.01 level.
Finally, we tested the hypothesis that the current WHO TEFs for PCB-126 (0.1) and PeCDF (0.5) (Van den Berg et al. 1998) could be used rather than the optimal RPFs. For this test, we compared the fits for the WHO model and the additive model (Figure 1D vs. Figure 1C). For the WHO model, the ED50 for the mixture was forced to be the same as that of TCDD, and the RPFs for PCB-126 and PeCDF were fixed as 0.1 and 0.5 rather than being optimized. In this case, the models for cholangiocarcinoma and CKE were rejected (Table 2, WHO model; p < 0.001). In contrast, the models for hepatocellular adenoma and gingival SCC were not rejected (Table 2, WHO model; p > 0.05), indicating that the dose response for the mixture was consistent with a TEF-adjusted dose-additive combination of individual congener effects. For cholangiocarcinoma, it is likely that the lower than predicted potency of PeCDF for this neoplasm (0.16 compared with the WHO TEF of 0.5) was driving this deviation. Similarly, for CKE, the higher potency of PCB-126 and lower predicted potency of PeCDF resulted in this rejection.
Discussion
The main objective of the present study was to test the hypothesis that the increased tumor incidence observed with a mixture of dioxins could be predicted based upon the potency-adjusted dose-additive effect of the individual compounds present within the defined mixture. A key assumption in this approach is that, across the different studies, the shape of the dose–response curves for the increased incidence of each respective neoplasm is fundamentally the same. This was indeed the case, indicating that it is appropriate to describe the relative carcinogenicity of each compound/mixture by the ratio of their ED50 values to that of TCDD. Furthermore, we showed that the observations seen for the mixture for each of the four neoplasms were, in general, consistent with the potency-adjusted dose-additive effects seen individually for TCDD, PCB-126, and PeCDF. Finally, we showed that for hepatocellular adenoma and gingival SCC, the effects seen for the mixture were generally consistent with the use of the WHO TEF values (Van den Berg et al. 1998) of 0.1 and 0.5 for PCB-126 and PeCDF, respectively. Moreover, although the use of the WHO TEFs for increased incidences of cholangiocarcinoma of the liver and CKE of the lung was statistically rejected, the estimated potency of the mixture relative to TCDD alone for these sites was 0.98 and 1.21, respectively, only marginally different from the expected value of 1.0.
It is important to note that the current WHO TEFs are based on an expert evaluation of individual studies that examined the relative potency of a given chemical to the reference compound, TCDD, which is assigned a potency of 1 (Van den Berg et al. 1998). TEF values are an order of magnitude estimate of the overall “toxic potency” of a given compound and therefore do not specifically refer to the potency from any single study with a particular end point. By comparison, an RPF is determined for a specific chemical in a single study relative to a specific end point. Consequently, it was expected that the estimated potencies would not be identical to the WHO TEF values. It is noteworthy that although RPF values for other end points used for the derivation of TEFs span several orders of magnitude, in general the RPFs for each compound across different sites varied less than half an order of magnitude.
From these analyses, it is evident that the current WHO TEF value of 0.1 for PCB-126 is an appropriate value. For cholangiocarcinoma, hepatocellular adenoma, and gingival SCC, the optimal potencies of PCB-126 were 0.11, 0.09, and 0.09, respectively. The optimal potency for induction of CKE was 0.20. The increased potency for the mixture appeared to be due to a higher than predicted observed potency of PCB-126 for this site (0.21 compared with its WHO TEF of 0.1). Although use of an overprediction of potency would ultimately be protective of human health when used in a risk assessment setting, an underprediction of risk would be less protective. Additional research is required to understand the pathogenesis of these squamous neoplasms and if this may be related to human lung cancer risk.
For PeCDF, it appears that the current WHO TEF of 0.5 (Van den Berg et al. 1998) somewhat overestimates its potency for all the analyzed neoplasms. For cholangiocarcinoma, hepatocellular adenoma, CKE, and gingival SCC, the optimal potencies of PeCDF were 0.16, 0.34, 0.30, and 0.26, respectively. This suggests that the current TEF value for PeCDF ought to be reevaluated for its application in quantitative cancer risk assessments. The lower potency of PeCDF observed here is consistent with earlier work on the promotion of altered hepatocellular foci in rat liver in a two-stage initiation–promotion model of hepatocarcinogenesis (Waern et al. 1991). In that study, the authors estimated that the potency of PeCDF relative to TCDD was approximately 0.1, when based on weekly administered dose after an initial loading dose.
Although it is beyond the scope of this article to fully compare the present TCDD study with previously reported studies of dioxins and PCB mixtures, in general the site specificity of effects from these studies was consistent with those prior studies with TCDD and related compounds. In the feed study of TCDD conducted by Dow Chemical Company, Kociba et al. (1978) observed increased incidences of neoplasms in the liver, lung, and hard palate. The increased incidence of cholangiocarcinoma that was seen in the present series of studies has not been seen before in cancer bioassays of DLCs or PCB mixtures. A detailed comparison of study design issue and comparative dose–response modeling of data from these studies will be reported separately.
Although the focus of the data reported here was evaluation of carcinogenicity, we have previously reported on the examination of induction of cytochrome P450 data from animals killed at interim time points during the conduct of these studies (Toyoshiba et al. 2004). In that analysis, we found that in general there was lack of support for common dose–response shape for induction of CYP1A1 and CYP1A2 in the liver and CYP1A1 activity in the lung. Moreover, when modeling the data under the assumption of common shape, there was in general a lack of dose additivity for the mixture. This appeared to be driven for the most part by the dose response for induction of P450 by PeCDF, which showed higher levels of induction of P450 than the other compounds. PeCDF can sequester in the liver at high levels, leading to high body burdens of this compound at higher doses. Given that the induction of these P450s is tightly linked to tissue levels of the compound, the variation in dose response likely reflects differences in short-term pharmacokinetics and pharmacodynamics. In contrast, neoplasia in these studies appears to be a more protracted response that requires longer durations of constant exposure. Hence, pharmacokinetic and pharmacodynamic differences between the compounds may not be as influential on the ultimate dose–response models.
The data presented here support additivity for compounds whose primary mechanism of action is via the AhR. However, it was not designed to address additivity for compounds that may have multiple modes of action that are also included in the current TEF scheme, for example, mono-ortho-PCBs (e.g., PCB-118). In addition, because exposure to PCBs always occurs as a mixture, this study was not designed to address whether the potency of a DLC is affected by non-DLCs such as the di-ortho-PCBs (e.g., PCB-153). To this end, additional studies as part of this evaluation of the dioxin TEF scheme being conducted by the NTP are examining the carcinogenicity of PCB-153 and PCB-118 and also mixtures of PCBs (PCB-126 and PCB-153, and PCB-126 and PCB-118).
In summary, to our knowledge this is the first study that has systematically examined the specific interactions within a mixture of compounds in the context of the chronic rodent carcinogenicity bioassay. The main conclusion from this study is that we cannot reject the hypothesis of potency-adjusted dose additivity for induction of rodent neoplasms for a defined mixture of DLCs. Moreover, the optimal potency of the defined mixture was almost the same as for TCDD alone. These analyses underscore that the use of TEFs and dose additivity for assessing mixtures of persistent AhR ligands is reasonable for cancer risk assessments and is now supported by some experimental evidence.
Figure 1 Dose–response modeling of fractional poly-3–adjusted tumor incidence showing each data set under four different model conditions: (A) independent model, (B) same-shape model, (C) additivity model, and (D) WHO model. Individual dose–response data from each respective study are shown.
Table 1 Summary of survival-adjusted neoplasm incidences.
Study, dose (ng/kg)a Cholangiocarcinoma Hepatocellular adenoma CKE Gingival SCC
TCDD (TEF = 1.0)
0 0b** 0** 0** 2.5**
3 0 0 0 5.7
10 0 0 0 2.6
22 2.9 0 0 0
46 10.3 2.6 0 10.2
100 54.9** 29.9** 21.1** 22.0**
PCB-126 (TEF = 0.1)
0 0** 3.2** 0** 0**
30 0 5.2 0 2.6
100 2.5 2.5 0 2.5
175 0 0 0 2.7
300 13.6* 5.5 2.7 5.4
550 14.0* 9.7 26.0** 4.7
1,000 60.3** 20.9* 83.5** 20.2**
PeCDF (TEF = 0.5)
0 0* 2.4** 0 2.4
6 0 0 0 5.2
20 0 2.7 0 2.7
44 2.6 0 0 0
92 2.8 5.5 0 2.8
200 5.4 10.9 2.7 8.1
TEF mixturec
0 0** 0** 0** 2.7
10 0 2.5 0 2.5
22 4.8 2.4 0 0
46 17.4 2.5 5.1 0
100 26.0** 31.0** 54.7** 6.0
a Animals were treated with each compound or a mixture with each respective dose, 5 days/week for up to 104 weeks (n = 53–55/group).
b All table values represent the poly-3–adjusted neoplasm incidence (%) after adjustment for intercurrent mortality.
c Mixture of TCDD, PCB-126, and PeCDF (ng TEQ/kg).
*p < 0.05 and
**p < 0.01 [in the 0-dose rows, p-values are for the poly-3 trend test (Bailer and Portier 1988); for other doses, these p-values represent pairwise comparisons between the individual dose groups and the control group].
Table 2 Dose–response parameter estimates of models.
Independenta
TCDD PCB-126 PeCDF TEF mixture Same shapeb Additivityc WHOd
Cholangiocarcinoma
E0 (%) 0 0 0 0 0 0 0
Shape 2.81 (0.68) 2.23 (0.58) 1.02 (1.1) 1.40 (0.43) 2.02 (0.31) 2.02 (0.3) 1.9
ED50 (ng/kg) 94 (9.0) 928 (112) 3,006 (9,686) 128 (32) 104 (13) 104 (10) 131
RPF, PCB-126 0.10 (0.02) 0.11 (0.02) 0.11 (0.02) 0.10
RPF, PeCDF 0.03 (0.10) 0.16 (0.04) 0.16 (0.04) 0.50
RPF, TEF mixture 0.74 (0.20) 0.98 (0.16) 1.0 1.0
p-Valuee 0.40 0.90 < 10−4
Hepatocellular adenoma
E0 (%) 0 0.03 0.01 0.02 0.02 0.01 0.01
Shape 3.74 (1.5) 2.24 (1.5) 1.86 (1.9) 4.90 (0.8) 2.95 (0.64) 2.91 (0.7) 2.80
ED50 (ng/kg) 125 (18) 1,896 (1,007) 645 (838) 81 (5) 141 (21) 137 (18) 155
RPF, PCB-126 0.07 (0.04) 0.09 (0.02) 0.10 (0.01) 0.10
RPF, PeCDF 0.19 (0.25) 0.34 (0.08) 0.35 (0.07) 0.50
RPF, TEF mixture 1.54 (0.24) 1.02 (0.18) 1.0 1.0
p-Value 0.17 0.32 0.19
CKE
E0 (%) 0 0 0 0 0 0 0
Shape 23.4 (—)f 4.45 (—)f 16.96 (—)f 4.16 (—)f 4.45 (0.8) 4.57 (0.88) 3.61
ED50 (ng/kg) 121 (—)f 695 (—)f 333 (—)f 110 (—)f 136 (14) 129 (10) 109
RPF, PCB-126 0.17 (—)f 0.20 (0.02) 0.19 (0.02) 0.10
RPF, PeCDF 0.36 (—)f 0.30 (0.08) 0.34 (0.05) 0.50
RPF, TEF mixture 1.27 (—)f 1.21 (0.14) 1.0 1.0
p-Value 0.99 0.033 < 10−4
Gingival SCC
E0 (%) 0.03 0.02 0.03 0.01 0.02 0.02 0.02
Shape 2.14 (—)f 2.42 (—)f 5.54 (—)f 26.6 (—)f 2.35 (1.0) 2.72 (1.0) 2.90
ED50 (ng/kg) 188 (—)f 1,905 (—)f 331 (—)f 116 (—)f 171 (51) 168 (38) 195
RPF, PCB-126 0.10 (—)f 0.09 (0.02) 0.09 (0.02) 0.10
RPF, PeCDF 0.57 (—)f 0.26 (0.12) 0.24 (0.14) 0.50
RPF, TEF mixture 1.62 (—)f 0.467 (0.25) 1.0 1.0
p-Value 0.93 0.047 0.07
SEs of parameter estimates are shown in in parentheses.
a Each curve had independent parameter estimates.
b The whole data set was modeled under the assumption that there is a common E0 and shape parameter across all four studies.
c The whole data set was modeled under the assumption that there is a common E0 and shape parameter across all four studies and that the ED50 for the mixture is based on dose additivity of the constituents (such that the RPF for the mixture is 1.0).
d The data were modeled assuming additivity and that the relative potencies for PCB-126 and PeCDF were equivalent to the WHO TEFs.
e Likelihood ratio test (analysis of the same-shape model was relative to the independent model; analysis of the additivity model was relative to the same-shape model; analysis of the WHO model was relative to the additivity model).
f Reliable SEs could not be calculated due to instability of the model.
==== Refs
References
Ahlborg UG Brouwer A Fingerhut MA Jacobson JL Jacobson SW Kennedy SW 1992 Impact of polychlorinated dibenzo-p -dioxins, dibenzofurans, and biphenyls on human and environmental health, with special emphasis on application of the toxic equivalency factor concept Eur J Pharmacol 228 179 199 1335882
Bailer AJ Portier CJ 1988 Effects of treatment-induced mortality and tumor-induced mortality on tests for carcinogenicity in small samples Biometrics 44 417 431 3390507
Birnbaum LS DeVito MJ 1995 Use of toxic equivalency factors for risk assessment for dioxins and related compounds Toxicology 105 391 401 8571375
DeVito MJ Diliberto JJ Ross DG Menache MG Birnbaum LS 1997 Dose-response relationships for polyhalogenated dioxins and dibenzofurans following subchronic treatment in mice. I. CYP1A1 and CYP1A2 enzyme activity in liver, lung, and skin Toxicol Appl Pharmacol 147 267 280 9439722
Food and Drug Administration 2002. Good Laboratory Practice for Nonclinical Laboratory Studies. 21CFR58.
Hamm JT Chen CY Birnbaum LS 2003 A mixture of dioxins, furans, and non-ortho PCBs based upon consensus toxic equivalency factors produces dioxin-like reproductive effects Toxicol Sci 74 182 191 12730615
Hites RA Foran JA Carpenter DO Hamilton MC Knuth BA Schwager SJ 2004 Global assessment of organic contaminants in farmed salmon Science 303 226 229 14716013
Institute of Laboratory Animal Resources 1996. Guide for the Care and Use of Laboratory Animals. 7th ed. Washington, DC:National Academy Press.
Kociba RJ Keyes DG Beyer JE Carreon RM Wade CE Dittenber DA 1978 Results of a two-year chronic toxicity and oncogenicity study of 2,3,7,8-tetrachlorodibenzo-p -dioxin in rats Toxicol Appl Pharmacol 46 279 303 734660
NTP 2004. National Toxicology Program Homepage. Available: http://ntp.niehs.nih.gov [accessed 22 November 2004].
Safe S 1990 Polychlorinated biphenyls (PCBs), dibenzo-p -dioxins (PCDDs), dibenzofurans (PCDFs), and related compounds: environmental and mechanistic considerations which support the development of toxic equivalency factors (TEFs) Crit Rev Toxicol 21 51 88 2124811
Schmidt JV Bradfield CA 1996 Ah receptor signaling pathways Annu Rev Cell Dev Biol 12 55 89 8970722
Stellman JM Stellman SD Christian R Weber T Tomasallo C 2003 The extent and patterns of usage of Agent Orange and other herbicides in Vietnam Nature 422 681 687 12700752
Toyoshiba H Walker NJ Bailer AJ Portier CJ 2004 Evaluation of toxic equivalency factors for induction of cytochromes P450 CYP1A1 and CYP1A2 enzyme activity by dioxin-like compounds Toxicol Appl Pharmacol 194 156 168 14736496
Van den Berg M Birnbaum L Bosveld ATC Brunstrom B Cook P Feeley M 1998 Toxic equivalency factors (TEFs) for PCBs, PCDDs, PCDFs for humans and wildlife Environ Health Perspect 106 775 792 9831538
Waern F Flodstrom S Busk L Kronevi T Nordgren I Ahlborg UG 1991 Relative liver tumour promoting activity and toxicity of some polychlorinated dibenzo-p-dioxin- and dibenzofuran-congeners in female Sprague-Dawley rats Pharmacol Toxicol 69 450 458 1766921
Zhang J Peddada S Rogol A 2000. Estimation of parameters in nonlinear regression models. In: Statistics for the 21st Century, Methodologies for Applications of the Future (Rao CR, Szekely GJ, eds). New York:Marcel Dekker, 459–483.
|
15626646
|
PMC1253708
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2005 Jan 19; 113(1):43-48
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7351
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7340ehp0113-00004915626647ResearchArticlesCancer Incidence among Glyphosate-Exposed Pesticide Applicators in the Agricultural Health Study De Roos Anneclaire J. 1Blair Aaron 2Rusiecki Jennifer A. 2Hoppin Jane A. 3Svec Megan 1Dosemeci Mustafa 2Sandler Dale P. 3Alavanja Michael C. 21Program in Epidemiology, Fred Hutchinson Cancer Research Center and the Department of Epidemiology, University of Washington, Seattle, Washington, USA2Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Bethesda, Maryland, USA3Epidemiology Program, National Institute of Environmental Health Sciences, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USAAddress correspondence to A.J. De Roos, Fred Hutchinson Cancer Research Center and University of Washington Department of Epidemiology, 1100 Fairview Ave. N, M4-B874, Seattle, WA 98109 USA. Telephone: (206) 667-7315. Fax: (206) 667-4787. E-mail:
[email protected] authors declare they have no competing financial interests.
1 2005 4 11 2004 113 1 49 54 21 6 2004 3 11 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Glyphosate is a broad-spectrum herbicide that is one of the most frequently applied pesticides in the world. Although there has been little consistent evidence of genotoxicity or carcinogenicity from in vitro and animal studies, a few epidemiologic reports have indicated potential health effects of glyphosate. We evaluated associations between glyphosate exposure and cancer incidence in the Agricultural Health Study (AHS), a prospective cohort study of 57,311 licensed pesticide applicators in Iowa and North Carolina. Detailed information on pesticide use and other factors was obtained from a self-administered questionnaire completed at time of enrollment (1993–1997). Among private and commercial applicators, 75.5% reported having ever used glyphosate, of which > 97% were men. In this analysis, glyphosate exposure was defined as a) ever personally mixed or applied products containing glyphosate; b) cumulative lifetime days of use, or “cumulative exposure days” (years of use × days/year); and c) intensity-weighted cumulative exposure days (years of use × days/year × estimated intensity level). Poisson regression was used to estimate exposure–response relations between glyphosate and incidence of all cancers combined and 12 relatively common cancer subtypes. Glyphosate exposure was not associated with cancer incidence overall or with most of the cancer subtypes we studied. There was a suggested association with multiple myeloma incidence that should be followed up as more cases occur in the AHS. Given the widespread use of glyphosate, future analyses of the AHS will allow further examination of long-term health effects, including less common cancers.
cancercohort studyfarmingglyphosatepesticide
==== Body
Glyphosate [N-(phosphonomethyl)glycine], commonly sold in the commercial formulation named Roundup (Monsanto Company, St. Louis, MO), has been a frequently used herbicide on both cropland and noncropland areas of the world since its introduction in the 1970s (Williams et al. 2000). Roundup is a combination of the active ingredient and other chemicals, including a surfactant (poly-oxyethyleneamine) that enhances the spreading of spray droplets when they contact foliage. Glyphosate is a broad-spectrum herbicide of which the primary mechanism is inhibition of the enzyme 5-enolpyruvoyl-shikimate 3-phosphate synthase, which is essential for the formation of aromatic amino acids in plants (Steinrucken and Amrhein 1980). Because this specific biologic pathway operates only in plants and microorganisms, the mechanism is not considered to be a risk for humans. Nevertheless, genotoxic, hormonal, and enzymatic effects in mammals have been reported (Bolognesi et al. 1997; Daruich et al. 2001; El Demerdash et al. 2001; Hietanen et al. 1983; Lioi et al. 1998a, 1998b; Olorunsogo et al. 1979; Peluso et al. 1998; Walsh et al. 2000; Yousef et al. 1995).
Results from genotoxicity studies of glyphosate have been conflicting. Glyphosate did not show any genotoxic activity in a battery of assays (Garry et al. 1999; Grisolia 2002; Li and Long 1988; Wildeman and Nazar 1982). However, other studies observed that glyphosate treatment of human lymphocytes in vitro resulted in increased sister chromatid exchanges (Bolognesi et al. 1997), chromosomal aberrations (Lioi et al. 1998b), and indicators of oxidative stress (Lioi et al. 1998b). Some studies found slightly greater toxicity of the Roundup formulation compared with glyphosate, in terms of both acute toxicity (Folmar et al. 1979; Martinez et al. 1990; Mitchell et al. 1987) and genotoxicity (Bolognesi et al. 1997; Vigfusson and Vyse 1980). Roundup was associated with increased DNA adducts in mice (Peluso et al. 1998) and a weak mutagenic effect in the Salmonella assay (Kale et al. 1995; Moriya et al. 1983; Rank et al. 1993), whereas glyphosate alone did not show these effects. Chronic feeding studies of glyphosate have not provided evidence of a carcinogenic effect in mice or rats (Williams et al. 2000).
The U.S. Environmental Protection Agency (U.S. EPA 1993) and the World Health Organization (WHO 1994) reviewed the toxicology data on glyphosate and concluded that glyphosate is not mutagenic or carcinogenic. The U.S. EPA classified glyphosate as category E, indicating “evidence of noncarcinogenicity for humans” (U.S. EPA 1993). Despite this conclusion, three recent case–control studies suggested an association between reported glyphosate use and the risk of non-Hodgkin lymphoma (NHL) (De Roos et al. 2003b; Hardell and Eriksson 1999; Hardell et al. 2002; McDuffie et al. 2001). Considering the widespread and frequent use of glyphosate in both the United States and the rest of the world, ongoing risk assessment is of importance. We studied site-specific cancer incidence associated with glyphosate use among pesticide applicators in the Agricultural Health Study (AHS) cohort.
Materials and Methods
Cohort enrollment and follow-up.
The AHS is a prospective cohort study in Iowa and North Carolina, which includes 57,311 private and commercial applicators who were licensed to apply restricted-use pesticides at the time of enrollment. Recruitment of the applicators occurred between 1993 and 1997 (Alavanja et al. 1996). Cohort members were matched to cancer registry files in Iowa and North Carolina for case identification and to the state death registries and the National Death Index (National Center for Health Statistics 1999) to ascertain vital status. Incident cancers were identified for the time period from the date of enrollment until 31 December 2001 and were coded according to the International Classification of Diseases, 9th Revision (WHO 1977). If cohort members had moved from the state, they were censored in the year they left. The median time of follow-up was 6.7 years.
Exposure assessment.
Using a self-administered enrollment questionnaire, we collected comprehensive-use data on 22 pesticides, ever/never use information for 28 additional pesticides, and general information on pesticide application methods, personal protective equipment, pesticide mixing, and equipment repair. Data were also collected on basic demographic and lifestyle factors. Applicators who completed this questionnaire were given a self-administered take-home questionnaire, which contained additional questions on occupational exposures and lifestyle factors. The questionnaires are available from the AHS website (National Institutes of Health 2004).
We constructed three glyphosate exposure metrics for this analysis: a) ever personally mixed or applied products containing glyphosate (ever/never); b) cumulative lifetime days of use, or “cumulative exposure days” (years of use × days per year, categorized in tertiles among users: 1–20, 21–56, 57–2,678); and c) intensity-weighted cumulative exposure days (years of use × days per year × intensity level, categorized in tertiles: 0.1–79.5, 79.6–337.1, 337.2–18,241). Tertiles were chosen a priori as the cut points with which to categorize exposure data, to avoid sparse data for rare cancers in the high-exposure categories. Intensity levels were estimated using questionnaire data from enrollment and measurement data from the published pesticide exposure literature, as follows: intensity level = [(mixing status + application method + equipment repair status) × personal protective equipment use] (Dosemeci et al. 2002).
Data analysis.
Persons whose first primary cancer occurred before the time of enrollment (n = 1,074) were excluded from analyses, as were subjects who were lost to follow-up or otherwise did not contribute any person-time (n = 298) and applicators who did not provide any information on age (n = 7) or whether they had ever used glyphosate (n = 1,678). After exclusions, 54,315 subjects were available for inclusion in the age-adjusted analyses of cancer incidence in relation to glyphosate use; however, other analyses contained fewer observations because of missing data for duration and frequency of glyphosate use or for covariates.
We compared certain baseline characteristics among three types of pesticide applicators: a) those applicators who never personally used glyphosate; b) applicators with the lowest glyphosate exposure, defined as being in the lowest tertile of cumulative exposure days; and c) those with higher glyphosate exposure, defined as being in the middle or highest tertile of cumulative exposure days. The purpose of the comparison was to identify potential confounders of glyphosate exposure–disease associations for the various analyses we conducted. Differences between the exposure groups were tested using the chi-square statistics and associated p-values.
Poisson regression analyses were carried out for all cancers combined and specific cancer sites to estimate rate ratios (RRs) and 95% confidence intervals (CIs) associated with glyphosate exposure metrics; the effect of each metric was evaluated in a separate model for each cancer. We analyzed tertile exposure variables in separate models using either the lowest-tertile–exposed or never-exposed subjects as the reference category. We investigated specific cancer sites for which there were at least 30 cases with sufficient information for inclusion in age-adjusted analyses. These cancers were then evaluated for all the exposure metrics and in adjusted analyses, despite smaller numbers of cases upon further adjustment. For each exposure metric, RRs were adjusted for demographic and lifestyle factors, including age at enrollment (continuous), education (dichotomous: ≤high school graduate or GED/education beyond high school), pack-years of cigarette smoking [indicator variables: never, pack-years at or below the median (12 pack-years), pack-years above the median], alcohol consumption in the past year [indicator variables: none, frequency at or below the median (72 drinks), frequency above the median], family history of cancer in first-degree relatives (dichotomous: yes/no), and state of residence (dichotomous: Iowa/North Carolina). There was insufficient variability in sex or applicator type to adjust for these factors.
Potential confounding from exposure to other pesticides was explored by adjusting for the five pesticides for which cumulative-exposure-day variables were most highly associated with glyphosate cumulative exposure days [(2,4-dichlorophenoxy)acetic acid (2,4-D), alachlor, atrazine, metolachlor, trifluralin]; these pesticide exposures were coded as variables indicating never, low, and high, with the split between low and high as the median of their cumulative exposure days. Additionally, of the pesticides for which only ever/never use information was available, we adjusted for the five pesticides that were most highly associated with ever use of glyphosate (benomyl, maneb, paraquat, carbaryl, diazinon). Where inclusion of all 10 other pesticides in a model changed a glyphosate exposure estimate by at least 20% (compared with a model restricted to the same observations), these results were presented as the final results for that cancer; otherwise, estimates adjusted only for demographic and lifestyle factors are presented.
Tests for trend across tertiles were conducted by creating a continuous variable with assigned values equal to the median value of cumulative exposure days (or intensity-weighted exposure days) within each tertile; the p-value for the trend test was that from the Poisson model coefficient for this continuous variable. We considered p-values < 0.10 as indicative of a trend.
Additional analyses were conducted for cancers for which we observed elevated RRs, and for NHL because of its association with glyphosate in previous studies. These included analyses stratified by state and analyses across quartiles and quintiles (where numbers allowed) of exposure days metrics.
Results
Selected characteristics of the glyphosate-exposed and never-exposed applicators are presented in Table 1. Among 54,315 subjects included in age-adjusted analyses, 41,035 (75.5%) reported having ever personally mixed or applied products containing glyphosate, and 13,280 (24.5%) did not. The cohort, both exposed and never exposed, was composed of primarily of male, middle-aged, private applicators. This is a population with relatively low smoking prevalence; in both the exposed and never-exposed groups, more than half of the subjects reported that they had never smoked. Significant differences (p < 0.05) existed between never-exposed and lowest-exposed subjects for all of the characteristics in Table 1. Lowest- and higher-exposed subjects (p < 0.05) also differed on several factors, the most notable being that higher-exposed subjects were more likely to be commercial applicators, to have consumed greater amounts of alcohol in the past year, and to have used other specific pesticides. However, lowest- and higher-exposed subjects were similar to each other (p ≥0.05) in characteristics including smoking and family history of cancer in a first-degree relative. In addition, lowest- and higher-exposed subjects were more similar to each other than to their never-exposed counterparts (by qualitative comparison of percentages only) in factors including North Carolina residence, education beyond high school, and use of other pesticides. Because of relative similarities between lowest- and higher-exposed in factors associated with socioeconomic status and other exposures, we decided to conduct some analyses using lowest-exposed rather than never-exposed applicators as the reference group, in order to avoid residual confounding by unmeasured covariates. However, we decided a priori that any association should be apparent regardless of which reference group was used.
RRs for the association of all cancers combined and specific cancers with having ever used glyphosate are presented in Table 2. RRs adjusted for age only are presented, as well as RRs adjusted for demographic and lifestyle factors and, in some cases, for other pesticides. The incidence of all cancers combined was not associated with glyphosate use, nor were most specific cancers. There was an 80% increased risk of melanoma associated with glyphosate use in the age-adjusted analysis, which diminished slightly upon further adjustment. Adjusted risk estimates for colon, rectum, kidney, and bladder cancers were elevated by 30–60%, but these estimates were not statistically significant. There was more than 2-fold increased risk of multiple myeloma associated with ever use of glyphosate in adjusted analyses, although this is based on a small number of cases. The association between myeloma incidence and glyphosate exposure was consistent in both states (ever used glyphosate, fully adjusted analyses: Iowa RR = 2.6; North Carolina RR = 2.7).
Results from analyses of tertiles of increasing glyphosate exposure level are presented in Table 3. A decreased risk of lung cancer was suggested for the highest tertile of both cumulative and intensity-weighted exposure days (p-value for trend = 0.02); however, a similar trend was not observed in analyses using never exposed as the referent (results not shown). There was a 40% increased risk of colon cancer for the highest tertile of intensity-weighted exposure; however, no clear monotonic trend was observed for either exposure metric. Elevated risks of leukemia and pancreas cancer were observed only for the middle tertiles of both cumulative and intensity-weighted exposure days, with no increased risk among those with the highest exposure. The associations we observed in the analysis of ever use of glyphosate (Table 2) for melanoma, rectum, kidney, and bladder cancers were not confirmed in analyses based on exposure-day metrics; similarly, no exposure–response patterns were observed in analyses using never exposed as the referent or in analyses across quintiles of exposure (results not shown). No association was observed between NHL and glyphosate exposure in any analysis, including an analysis comparing the highest with the lowest quintile of exposure (> 108 vs. > 0–9 cumulative exposure days: RR = 0.9; 95% CI, 0.4–2.1).
Elevated RRs were estimated for multiple myeloma, with an approximate 2-fold increased risk for the highest tertile of both cumulative and intensity-weighted exposure days (Table 3); however, small numbers precluded precise effect estimation (n = 19 in adjusted analyses of exposure-day metrics). The estimated intensity-level component of the intensity-weighted exposure-day metric was not associated with multiple myeloma (highest vs. lowest tertile: RR = 0.6; 95% CI, 0.2–1.8), and observed positive associations of the intensity-weighted exposure-day metric with myeloma relied solely on the exposure-day component; therefore, only results for cumulative exposure days are shown further. When using never exposed as the referent, the association between glyphosate use and multiple myeloma was more pronounced, with more than 4-fold increased risk associated with the highest tertile of cumulative exposure days (tertile 1: RR = 2.3; 95% CI, 0.6–8.9; tertile 2: RR = 2.6; 95% CI, 0.6–11.5; tertile 3: RR = 4.4; 95% CI, 1.0–20.2; p-value for trend = 0.09). Although the myeloma cases were sparsely distributed in analyses of quartiles and quintiles, the highest increased risks were observed in the highest exposure categories (full set of results not shown: upper quartile vs. never exposed: RR = 6.6; 95% CI, 1.4–30.6; p-value for trend across quartiles = 0.01).
Discussion
There was no association between glyphosate exposure and all cancer incidence or most of the specific cancer subtypes we evaluated, including NHL, whether the exposure metric was ever used, cumulative exposure days, or intensity-weighted cumulative exposure days. The most consistent finding in our study was a suggested association between multiple myeloma and glyphosate exposure, based on a small number of cases.
Although our study relied on self-reported exposure information, farmers have been shown to provide reliable information regarding their personal pesticide use (Blair et al. 2002; Blair and Zahm 1993; Duell et al. 2001; Engel et al. 2001; Hoppin et al. 2002). Investigators have used pesticide supplier reports (Blair and Zahm 1993) and self-reported pesticide use information provided earlier (Engel et al. 2001) to assess the validity of retrospectively reported pesticide use data. Among farmers in the AHS, Blair et al. (2002) reported high reliability for reports of ever use of a particular pesticide (ranging from 70 to > 90%). Agreement for duration and frequency of use was lower but generally 50–60% for specific pesticides. Hoppin et al. (2002) have demonstrated that farmers provide plausible data regarding lifetime duration of use, with fewer than 5% reporting implausible values for specific chemicals.
There were rather few cases of NHL for inclusion in this analysis (n = 92); nevertheless, the available data provided evidence of no association between glyphosate exposure and NHL incidence. This conclusion was consistent across analyses using the different exposure metrics and in analyses using either never exposed or low exposed as the referent. Furthermore, there was no apparent effect of glyphosate exposure on the risk of NHL in analyses stratified by state of residence or in analyses of highly exposed groups comparing the highest with the lowest quintile of exposure. These findings conflict with recent studies. The first report of an association of glyphosate with NHL was from a case–control study, but the estimate was based on only four exposed cases (Hardell and Eriksson 1999). A pooled analysis of this initial study with a study of hairy cell leukemia showed a relationship between glyphosate exposure and an increased risk of disease [unadjusted analysis: odds ratio (OR) = 3.0; 95% CI, 1.1–8.5] (Hardell et al. 2002). A more extensive study conducted across a large region of Canada found an elevated risk of NHL associated with glyphosate use more frequent than 2 days/year (OR = 2.1; 95% CI, 1.2–3.7) (McDuffie et al. 2001). Similarly, increased NHL risk in men was associated with having ever used glyphosate (OR = 2.1; 95% CI, 1.1–4.0) after adjustment for other commonly used pesticides in a pooled analysis of National Cancer Institute–sponsored case–control studies conducted in Nebraska, Kansas, Iowa, and Minnesota (De Roos et al. 2003b). These previous studies were retrospective in design and thereby potentially susceptible to recall bias of exposure reporting. Our analysis of the AHS cohort had a prospective design, which should largely eliminate the possibility of recall bias. Differences in recall bias could account for discrepant study results; however, evaluation of the potential for recall bias in case–control studies of pesticides among farmers has not uncovered evidence that it occurred (Blair and Zahm 1993).
Our finding of a suggested association of multiple myeloma incidence with glyphosate exposure has not been previously reported, although numerous studies have observed increased myeloma risk associated with farming occupation (Boffetta et al. 1989; Brownson et al. 1989; Cantor and Blair 1984; Cerhan et al. 1998; Cuzick and De Stavola 1988; Eriksson and Karlsson 1992; Figgs et al. 1994; Gallagher et al. 1983; La Vecchia et al. 1989; Nandakumar et al. 1986
Nandakumar et al. 1988; Pasqualetti et al. 1990; Pearce et al. 1985; Pottern et al. 1992; Reif et al. 1989; Vagero and Persson 1986). A possible biologic mechanism of how glyphosate might act along the causal pathway of this plasma cell cancer has not been hypothesized, but myeloma has been associated with agents that cause either DNA damage or immunosuppression (De Roos et al. 2003a). The association we observed was with ever use of glyphosate and cumulative exposure days of use (a combination of duration and frequency), but not with intensity of exposure. Estimated intensity of glyphosate exposure was based on general work practices that were not glyphosate specific, including the percentage of time spent mixing and applying pesticides, application method, use of personal protective equipment, and repair of pesticide application equipment (Dosemeci et al. 2002). Information on work practices specific to glyphosate use would clarify whether intensity of exposure contributes to myeloma risk.
The number of myeloma cases in our study was small, and it is plausible that spurious associations arose by chance; however, several aspects of our results argue against a chance association. The findings were internally consistent, with increased risk observed in both states. Adding to the credibility of the association, there was some indication of a dose–response relationship, with risk estimates increasing across categories of increasing exposure and stronger associations observed when using never-exposed subjects as the referent (as opposed to low exposed). Another possible explanation for spurious associations is unadjusted confounding. Our risk estimates were adjusted for some demographic and lifestyle factors and other pesticides. Of the other pesticides included in the fully adjusted model, only diazinon and trifluralin were important confounders of the glyphosate–myeloma association. It is certainly possible that an unknown risk factor for myeloma could have confounded our results; however, any unknown confounder would have to be linked with glyphosate use. Finally, the increased myeloma risk associated with glyphosate use could be due to bias resulting from a selection of subjects in adjusted analyses that differed from subjects included in unadjusted analyses. Table 1 shows that 54,315 subjects were included in age-adjusted models, whereas because of missing data for covariates, only 40,719 subjects were included in fully adjusted analyses. The association of glyphosate with myeloma differed between the two groups, even without adjustment for any covariates, with no association among the full group and a positive association among the more restricted group. Subjects who answered all the questions and were thus included in adjusted analyses differed from those who dropped out of such analyses in that they were more likely to be from Iowa (71.8% in included group vs. 44.6% in dropped group), were younger (average age, 51.5 vs. 57.9 years), and were more highly educated (46.7% educated beyond high school graduate vs. 30.2%); however, the two groups were similar in their use of glyphosate (75.9% vs. 74.5%). The increased risk associated with glyphosate in adjusted analyses may be due to selection bias or could be due to a confounder or effect modifier that is more prevalent among this restricted subgroup and is unaccounted for in our analyses. Further follow-up of the cohort and reevaluation of the association between glyphosate exposure and myeloma incidence after a greater number of cases develop will allow more detailed examination of the potential biases underlying the association.
Certain limitations of our data hinder the inferences we can make regarding glyphosate and its association with specific cancer subtypes. Although the AHS cohort is large, and there were many participants reporting glyphosate use, the small numbers of specific cancers occurring during the follow-up period hindered precise effect estimation. In addition, most applicators were male, precluding our ability to assess the association between glyphosate exposure and cancer incidence among women, for both non-sex-specific cancers and sex-specific cancers (e.g., of the breast or ovary). Our analysis provides no information on the timing of pesticide use in relation to disease, limiting the ability to sufficiently explore latency periods or effects resulting from glyphosate exposure at different ages. Despite limitations of our study, certain inferences are possible. This prospective study of cancer incidence provided evidence of no association between glyphosate exposure and most of the cancers we studied, and a suggested association between glyphosate and the risk of multiple myeloma. Future analyses within the AHS will follow up on these findings and will examine associations between glyphosate exposure and incidence of less common cancers.
Table 1 Selected characteristics of applicators in the AHS by glyphosate exposure, based on data from the enrollment questionnaire (1993–1997).a
Never exposed (n = 13,280)
Never exposed (n = 15,911)b Higher exposed (n = 24,465)c
Characteristic No. (%) No. (%) No. (%)
State of residence
Iowa 9,987 (75.2) 9,785 (61.5) 15,336 (62.7)
North Carolina 3,293 (24.8) 6,126 (38.5) 9,129 (37.3)
Age (years)
< 40 2,279 (17.2) 2,226 (14.0) 4,190 (17.1)
40–49 3,420 (25.8) 4,279 (26.9) 7,899 (32.3)
50–59 2,989 (22.5) 3,931 (24.7) 6,035 (24.7)
60–69 2,715 (20.4) 3,266 (20.5) 3,997 (16.3)
70 1,877 (14.1) 2,209 (13.9) 2,344 (9.6)
Sex
Male 12,778 (96.2) 15,505 (97.5) 23,924 (97.8)
Female 502 (3.8) 406 (2.6) 541 (2.2)
Applicator typed
Private 12,067 (90.9) 15,008 (94.3) 21,938 (89.7)
Commercial 1,213 (9.1) 903 (5.7) 2,527 (10.3)
Education
High school graduate or GED 8,898 (68.7) 8,997 (57.9) 11,975 (50.1)
Beyond high school 4,060 (31.3) 6,530 (42.1) 11,936 (49.9)
Smoking history
Never 7,298 (57.3) 8,241 (53.2) 12,751 (53.7)
≤ 12 pack-years 2,866 (22.5) 3,597 (23.2) 5,572 (23.5)
> 12 pack-years 2,567 (20.2) 3,643 (23.5) 5,439 (22.9)
Alcohol consumption in past year
None 4,087 (32.7) 5,352 (35.6) 7,023 (29.8)
≤ 6 drinks/month 4,461 (35.7) 5,291 (35.2) 8,149 (34.5)
> 6 drinks/month 3,936 (31.5) 4,387 (29.2) 8,422 (35.7)
Family history of cancer
No 8,701 (65.5) 9,520 (59.8) 14,668 (60.0)
Yes 4,579 (34.5) 6,391 (40.2) 9,797 (40.0)
Use of other common pesticides
2,4-D 7,030 (53.3) 11,879 (75.2) 20,699 (85.1)
Alachlor 4,896 (39.7) 7,321 (50.9) 13,790 (59.7)
Atrazine 7,707 (58.5) 10,533 (66.6) 18,237 (75.0)
Metolachlor 3,890 (31.6) 6,172 (43.1) 12,952 (56.2)
Trifluralin 4,239 (34.0) 7,109 (49.7) 14,675 (63.5)
Carbaryl 4,110 (33.7) 8,515 (58.1) 15,139 (64.8)
Benomyl 510 (4.3) 1,418 (9.9) 3,391 (14.8)
Maneb 492 (4.1) 1,412 (9.9) 2,929 (12.9)
Paraquat 1,067 (9.0) 3,021 (21.2) 8,031 (35.2)
Diazinon 1,906 (16.0) 4,615 (32.4) 9,107 (40.0)
a Includes observations for subjects included in age-adjusted Poisson regression models of cancer incidence (n = 54,315).
b Lowest tertile of cumulative exposure days.
c Highest two tertiles of cumulative exposure days; the sum of the three tertiles of cumulative exposure days (n = 40,376) does not equal the total number of subjects who reported having ever used glyphosate (n = 41,035) because of missing data on duration and frequency of use.
d “Private” refers primarily to individual farmers, and “commercial” refers to professional pesticide applicators.
Table 2 Association of glyphosate exposure (ever/never used) with common cancersa among AHS applicators.
RR (95% CI)b
Cancer site Total no. of cancersc Ever used glyphosate (% of total) Effect estimates adjusted for age (n = 54,315)d Adjusted for age, demographic and lifestyle factors,and other pesticidesd
All cancers 2,088 73.6 1.0 (0.9–1.1) 1.0 (0.9–1.2)
Lung 204 72.1 1.0 (0.7–1.3) 0.9 (0.6–1.3)
Oral cavity 59 76.3 1.1 (0.6–2.0) 1.0 (0.5–1.8)
Colon 174 75.3 1.1 (0.8–1.6) 1.4 (0.8–2.2)e
Rectum 76 77.6 1.2 (0.7–2.1) 1.3 (0.7–2.3)
Pancreas 38 76.3 1.2 (0.6–2.5) 0.7 (0.3–2.0)e
Kidney 63 73.0 1.0 (0.6–1.7) 1.6 (0.7–3.8)e
Bladder 79 76.0 1.2 (0.7–2.0) 1.5 (0.7–3.2)e
Prostate 825 72.5 1.0 (0.8–1.1) 1.1 (0.9–1.3)
Melanoma 75 84.0 1.8 (1.0–3.4) 1.6 (0.8–3.0)
All lymphohematopoietic cancers 190 75.3 1.1 (0.8–1.5) 1.1 (0.8–1.6)
NHL 92 77.2 1.2 (0.7–1.9) 1.1 (0.7–1.9)
Leukemia 57 75.4 1.1 (0.6–2.0) 1.0 (0.5–1.9)
Multiple myeloma 32 75.0 1.1 (0.5–2.4) 2.6 (0.7–9.4)f
a Cancers for which at least 30 subjects had sufficient information for inclusion in age-adjusted analyses.
b RRs and 95% CIs from Poisson regression models.
c Frequencies among subjects included in age-adjusted analyses.
d Numbers of subjects in these analyses are lower than in age-adjusted analyses because of missing observations for some covariates (models adjusted for demographic and lifestyle factors include 49,211 subjects; models additionally adjusted for other pesticides include 40,719 subjects).
e Estimates adjusted for other pesticides are shown because inclusion of other pesticide variables in the model changed the effect estimate for glyphosate by at least 20%.
f The estimate for myeloma was not confounded by other pesticides according to our change-in-estimate rule of ≥20%; however, the fully adjusted estimate is shown for the purpose of comparison with state-specific estimates (in the text), which were confounded by other pesticides and required adjustment.
Table 3 Association of glyphosate exposure (cumulative exposure days and intensity-weighted exposure days) with common cancersa among AHS applicators.
Cumulative exposure daysb Intensity-weighted exposure daysc
Cancer site Tertile cut points No. RR (95% CI)d p-Trend Tertile cut points No. RR (95% CI)d p-Trend
All cancers 1–20 594 1.0 0.1–79.5 435 1.0
21–56 372 1.0 (0.9–1.1) 79.6–337.1 436 0.9 (0.8–1.0)
57–2,678 358 1.0 (0.9–1.1) 0.57 337.2–18,241 438 0.9 (0.8–1.1) 0.35
Lung 1–20 40 1.0 0.1–79.5 27 1.0
21–56 26 0.9 (0.5–1.5)e 79.6–337.1 38 1.1 (0.7–1.9)e
57–2,678 26 0.7 (0.4–1.2)e 0.21 337.2–18,241 27 0.6 (0.3–1.0)e 0.02
Oral cavity 1–20 18 1.0 0.1–79.5 11 1.0
21–56 10 0.8 (0.4–1.7) 79.6–337.1 14 1.1 (0.5–2.5)
57–2,678 10 0.8 (0.4–1.7) 0.66 337.2–18,241 13 1.0 (0.5–2.3) 0.95
Colon 1–20 32 1.0 0.1–79.5 25 1.0
21–56 28 1.4 (0.9–2.4)e 79.6–337.1 20 0.8 (0.5–1.5)c
57–2,678 15 0.9 (0.4–1.7)e 0.54 337.2–18,241 30 1.4 (0.8–2.5)c 0.10
Rectum 1–20 20 1.0 0.1–79.5 16 1.0
21–56 17 1.3 (0.7–2.5) 79.6–337.1 18 1.0 (0.5–2.0)
57–2,678 14 1.1 (0.6–2.3) 0.70 337.2–18,241 16 0.9 (0.5–1.9) 0.82
Pancreas 0–20 9 1.0 0–79.5 6 1.0
21–56 9 1.6 (0.6–4.1) 79.6–337.1 16 2.5 (1.0–6.3)
57–2,678 7 1.3 (0.5–3.6) 0.83 337.2–18,241 3 0.5 (0.1–1.9) 0.06
Kidney 1–20 20 1.0 0.1–79.5 20 1.0
21–56 8 0.6 (0.3–1.4) 79.6–337.1 7 0.3 (0.1–0.7)
57–2,678 9 0.7 (0.3–1.6) 0.34 337.2–18,241 10 0.5 (0.2–1.0) 0.15
Bladder 1–20 23 1.0 0.1–79.5 14 1.0
21–56 14 1.0 (0.5–1.9) 79.6–337.1 8 0.5 (0.2–1.3)
57–2,678 17 1.2 (0.6–2.2) 0.53 337.2–18,241 13 0.8 (0.3–1.8) 0.88
Prostate 1–20 239 1.0 0.1–79.5 167 1.0
21–56 132 0.9 (0.7–1.1) 79.6–337.1 169 1.0 (0.8–1.2)
57–2,678 145 1.1 (0.9–1.3) 0.69 337.2–18,241 174 1.1 (0.9–1.3) 0.60
Melanoma 1–20 23 1.0 0.1–79.5 24 1.0
21–56 20 1.2 (0.7–2.3) 79.6–337.1 16 0.6 (0.3–1.1)
57–2,678 14 0.9 (0.5–1.8) 0.77 337.2–18,241 17 0.7 (0.3–1.2) 0.44
All lymphohematopoietic cancers 1–20 48 1.0 0.1–79.5 38 1.0
21–56 38 1.2 (0.8–1.8) 79.6–337.1 40 1.0 (0.6–1.5)
57–2,678 36 1.2 (0.8–1.8) 0.69 337.2–18,241 43 1.0 (0.7–1.6) 0.90
NHL 1–20 29 1.0 0.1–79.5 24 1.0
21–56 15 0.7 (0.4–1.4) 79.6–337.1 15 0.6 (0.3–1.1)
57–2,678 17 0.9 (0.5–1.6) 0.73 337.2–18,241 22 0.8 (0.5–1.4) 0.99
Leukemia 1–20 9 1.0 0.1–79.5 7 1.0
21–56 14 1.9 (0.8–4.5)e 79.6–337.1 17 1.9 (0.8–4.7)e
57–2,678 9 1.0 (0.4–2.9)e 0.61 337.2–18,241 8 0.7 (0.2–2.1)e 0.11
Multiple myeloma 1–20 8 1.0 0–79.5 5 1.0
21–56 5 1.1 (0.4–3.5)e 79.6–337.1 6 1.2 (0.4–3.8)e
57–2,678 6 1.9 (0.6–6.3)e 0.27 337.2–18,241 8 2.1 (0.6–7.0)e 0.17
a Cancers for which at least 30 subjects had sufficient information for inclusion in age-adjusted analyses.
b Numbers of subjects in analyses vary depending on missing observations for cumulative exposure days and some covariates (models adjusted for demographic and lifestyle factors include 36,823 subjects; models additionally adjusted for other pesticides include 30,699 subjects).
c Numbers of subjects in analyses vary depending on missing observations for intensity-weighted cumulative exposure days and some covariates (models adjusted for demographic and lifestyle factors include 36,509 subjects; models additionally adjusted for other pesticides include 30,613 subjects).
d Relative rate ratios and 95% CIs from Poisson regression analyses.
e Estimates adjusted for other pesticides are shown because inclusion of other pesticide variables in the model changed the effect estimate for glyphosate by at least 20%.
==== Refs
References
Alavanja MC Sandler DP McMaster SB Zahm SH McDonnell CJ Lynch CF 1996 The Agricultural Health Study Environ Health Perspect 104 362 369 8732939
Blair A Tarone R Sandler D Lynch CF Rowland A Wintersteen W 2002 Reliability of reporting on lifestyle and agricultural factors by a sample of participants in the Agricultural Health Study from Iowa Epidemiology 13 94 99 11805592
Blair A Zahm SH 1993 Patterns of pesticide use among farmers: implications for epidemiologic research Epidemiology 4 55 62 8420582
Boffetta P Stellman SD Garfinkel L 1989 A case-control study of multiple myeloma nested in the American Cancer Society prospective study Int J Cancer 43 554 559 2703267
Boffetta P Bolognesi C Bonatti S Degan P Gallerani E Peluso M Rabboni R Genotoxic activity of glyphosate and its technical formulation Roundup J Agric Food Chem 45 1957 1962
Brownson RC Reif JS Chang JC Davis JR 1989 Cancer risks among Missouri farmers Cancer 64 2381 2386 2804930
Cantor KP Blair A 1984 Farming and mortality from multiple myeloma: a case-control study with the use of death certificates J Natl Cancer Inst 72 251 255 6582313
Cerhan JR Cantor KP Williamson K Lynch CF Torner JC Burmeister LF 1998 Cancer mortality among Iowa farmers: recent results, time trends, and lifestyle factors (United States) Cancer Causes Control 9 311 319 9684711
Cuzick J De Stavola B 1988 Multiple myeloma—a case-control study Br J Cancer 57 516 520 3395559
Daruich J Zirulnik F Gimenez MS 2001 Effect of the herbicide glyphosate on enzymatic activity in pregnant rats and their fetuses Environ Res 85 226 231 11237511
De Roos AJ Baris D Weiss NS Herrinton LJ 2003a. Epidemiology of multiple myeloma. In: Myeloma: Biology and Management (Malpas JS, Bergsagel DE, Kyle RA, Anderson KC, eds). 3rd ed. Philadelphia:Saunders, 117–158.
De Roos AJ Zahm SH Cantor KP Weisenburger DD Holmes FF Burmeister LF 2003b. Integrative assessment of multiple pesticides as risk factors for non-Hodgkin’s lymphoma among men. Occup Environ Med 60:E11. Available: http://oem.bmjjournals.com/cgi/content/full/60/9/e11 [accessed 30 November 2004].
Dosemeci M Alavanja MC Rowland AS Mage D Zahm SH Rothman N 2002 A quantitative approach for estimating exposure to pesticides in the Agricultural Health Study Ann Occup Hyg 46 245 260 12074034
Duell EJ Millikan RC Savitz DA Schell MJ Newman B Tse CJ 2001 Reproducibility of reported farming activities and pesticide use among breast cancer cases and controls. A comparison of two modes of data collection Ann Epidemiol 11 178 185 11248581
El Demerdash FM Yousef MI Elagamy EI 2001 Influence of paraquat, glyphosate, and cadmium on the activity of some serum enzymes and protein electrophoretic behavior (in vitro) J Environ Sci Health B 36 29 42 11281253
Engel LS Seixas NS Keifer MC Longstreth WT Jr Checkoway H 2001 Validity study of self-reported pesticide exposure among orchardists J Expo Anal Environ Epidemiol 11 359 368 11687909
Eriksson M Karlsson M 1992 Occupational and other environmental factors and multiple myeloma: a population based case-control study Br J Ind Med 49 95 103 1536825
Figgs LW Dosemeci M Blair A 1994 Risk of multiple myeloma by occupation and industry among men and women: a 24-state death certificate study J Occup Med 36 1210 1221 7861265
Folmar LC Sanders HO Julin AM 1979 Toxicity of the herbicide glyphosphate and several of its formulations to fish and aquatic invertebrates Arch Environ Contam Toxicol 8 269 278 507937
Gallagher RP Spinelli JJ Elwood JM Skippen DH 1983 Allergies and agricultural exposure as risk factors for multiple myeloma Br J Cancer 48 853 857 6652026
Garry VF Burroughs B Tarone R Kesner JS 1999 Herbicides and adjuvants: an evolving view Toxicol Ind Health 15 159 167 10188198
Grisolia CK 2002 A comparison between mouse and fish micronucleus test using cyclophosphamide, mitomycin C and various pesticides Mutat Res 518 145 150 12113765
Hardell L Eriksson M 1999 A case-control study of non-Hodgkin lymphoma and exposure to pesticides Cancer 85 1353 1360 10189142
Hardell L Eriksson M Nordstrom M 2002 Exposure to pesticides as risk factor for non-Hodgkin’s lymphoma and hairy cell leukemia: pooled analysis of two Swedish case-control studies Leuk Lymphoma 43 1043 1049 12148884
Hietanen E Linnainmaa K Vainio H 1983 Effects of phenoxy-herbicides and glyphosate on the hepatic and intestinal biotransformation activities in the rat Acta Pharmacol Toxicol (Copenh) 53 103 112 6624478
Hoppin JA Yucel F Dosemeci M Sandler DP 2002 Accuracy of self-reported pesticide use duration information from licensed pesticide applicators in the Agricultural Health Study J Expo Anal Environ Epidemiol 12 313 318 12198579
Kale PG Petty BT Jr Walker S Ford JB Dehkordi N Tarasia S 1995 Mutagenicity testing of nine herbicides and pesticides currently used in agriculture Environ Mol Mutagen 25 148 153 7698107
La Vecchia C Negri E D’Avanzo B Franceschi S 1989 Occupation and lymphoid neoplasms Br J Cancer 60 385 388 2789947
Li AP Long TJ 1988 An evaluation of the genotoxic potential of glyphosate Fundam Appl Toxicol 10 537 546 3286348
Lioi MB Scarfi MR Santoro A Barbieri R Zeni O Di Berardino D 1998a Genotoxicity and oxidative stress induced by pesticide exposure in bovine lymphocyte cultures in vitro Mutat Res 403 13 20 9726001
Lioi MB Scarfi MR Santoro A Barbieri R Zeni O Salvemini F 1998b Cytogenetic damage and induction of pro-oxidant state in human lymphocytes exposed in vitro to gliphosate, vinclozolin, atrazine, and DPX-E9636 Environ Mol Mutagen 32 39 46 9707097
Martinez TT Long WC Hiller R 1990 Comparison of the toxicology of the herbicide Roundup by oral and pulmonary routes of exposure Proc West Pharmacol Soc 33 193 197 1703306
McDuffie HH Pahwa P McLaughlin JR Spinelli JJ Fincham S Dosman JA 2001 Non-Hodgkin’s lymphoma and specific pesticide exposures in men: cross-Canada study of pesticides and health Cancer Epidemiol Biomarkers Prev 10 1155 1163 11700263
Mitchell DG Chapman PM Long TJ 1987 Acute toxicity of Roundup and Rodeo herbicides to rainbow trout, chinook, and coho salmon Bull Environ Contam Toxicol 39 1028 1035 3440140
Moriya M Ohta T Watanabe K Miyazawa T Kato K Shirasu Y 1983 Further mutagenicity studies on pesticides in bacterial reversion assay systems Mutat Res 116 185 216 6339892
Nandakumar A Armstrong BK de Klerk NH 1986 Multiple myeloma in Western Australia: a case-control study in relation to occupation, father’s occupation, socioeconomic status and country of birth Int J Cancer 37 223 226 3080376
Nandakumar A English DR Dougan LE Armstrong BK 1988 Incidence and outcome of multiple myeloma in Western Australia, 1960 to 1984 Aust NZ J Med 18 774 779
National Center for Health Statistics 1999. National Death Index Homepage. Hyattsville, MD:National Center for Health Statistics. Available: http://www.cdc.gov/nchs/r&d/ndi/ndi.htm [accessed 30 November 2004].
National Institutes of Health 2004. Agricultural Health Study Homepage. Bethesda, MD:National Institutes of Health. Available: http://www.aghealth.org [accessed 25 September 2004].
Olorunsogo OO Bababunmi EA Bassir O 1979 Effect of glyphosate on rat liver mitochondria in vivo Bull Environ Contam Toxicol 22 357 364 223703
Pasqualetti P Casale R Collacciani A Colantonio D 1990 Work activities and the risk of multiple myeloma. A case-control study Med Lav 81 308 319 2079928
Pearce NE Smith AH Fisher DO 1985 Malignant lymphoma and multiple myeloma linked with agricultural occupations in a New Zealand Cancer Registry-based study Am J Epidemiol 121 225 237 4014117
Peluso M Munnia A Bolognesi C Parodi S 1998 32 P-Postlabeling detection of DNA adducts in mice treated with the herbicide Roundup Environ Mol Mutagen 31 55 59 9464316
Pottern LM Heineman EF Olsen JH Raffn E Blair A 1992 Multiple myeloma among Danish women: employment history and workplace exposures Cancer Causes Control 3 427 432 1525323
Rank J Jensen AG Skov B Pedersen LH Jensen K 1993 Genotoxicity testing of the herbicide Roundup and its active ingredient glyphosate isopropylamine using the mouse bone marrow micronucleus test, Salmonella mutagenicity test, and Allium anaphase-telophase test Mutat Res 300 29 36 7683765
Reif J Pearce N Fraser J 1989 Cancer risks in New Zealand farmers Int J Epidemiol 18 768 774 2621012
Steinrucken HC Amrhein N 1980 The herbicide glyphosate is a potent inhibitor of 5-enolpyruvyl-shikimic acid-3-phosphate synthase Biochem Biophys Res Commun 94 1207 1212 7396959
U.S. EPA 1993. U.S. Environmental Protection Agency Reregistration Eligibility Decision (RED) Glyphosate. EPA-738-R-93-014. Washington, DC:U.S. Environmental Protection Agency.
Vagero D Persson G 1986 Occurrence of cancer in socioeconomic groups in Sweden. An analysis based on the Swedish Cancer Environment Registry Scand J Soc Med 14 151 160 3489987
Vigfusson NV Vyse ER 1980 The effect of the pesticides, Dexon, Captan and Roundup, on sister-chromatid exchanges in human lymphocytes in vitro Mutat Res 79 53 57 7432366
Walsh LP McCormick C Martin C Stocco DM 2000 Roundup inhibits steroidogenesis by disrupting steroidogenic acute regulatory (StAR) protein expression Environ Health Perspect 108 769 776 10964798
WHO 1977. International Classification of Diseases: Manual of the International Statistical Classification of Diseases, Injuries, and Causes of Death, Vol 1, 9th revision. Geneva:World Health Organization.
WHO 1994. International Programme on Chemical Safety. Glyphosate. Environmental Health Criteria 159. Geneva:World Health Organization.
Wildeman AG Nazar RN 1982 Significance of plant metabolism in the mutagenicity and toxicity of pesticides Can J Genet Cytol 24 437 449 7172099
Williams GM Kroes R Munro IC 2000 Safety evaluation and risk assessment of the herbicide Roundup and its active ingredient, glyphosate, for humans Regul Toxicol Pharmacol 31 117 165 10854122
Yousef MI Salem MH Ibrahim HZ Helmi S Seehy MA Bertheussen K 1995 Toxic effects of carbofuran and glyphosate on semen characteristics in rabbits J Environ Sci Health B 30 513 534 7797819
|
15626647
|
PMC1253709
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan 4; 113(1):49-54
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7340
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.6937ehp0113-00005515626648ResearchArticlesImpacts of Co-Solvent Flushing on Microbial Populations Capable of Degrading Trichloroethylene Ramakrishnan Vijayalakshmi 1Ogram Andrew V. 1Lindner Angela S. 21Department of Soil and Water Sciences, and2Department of Environmental Engineering Sciences, University of Florida, Gainesville, Florida, USAAddress correspondence to A.S. Lindner, Department of Environmental Engineering Sciences, University of Florida, Center Dr., A.P. Black Hall, P.O. Box 116450, Gainesville, FL 32611 USA. Telephone: (352) 846-3033. Fax: (352) 392-3076. E-mail:
[email protected] article is based on a presentation at the conference “Bioremediation and Biodegradation: Current Advances in Reducing Toxicity, Exposure and Environmental Consequences” (http://www-apps.niehs.nih.gov/sbrp/bioremediation.html) held 9–12 June 2002 in Pacific Grove, California, and sponsored by the National Institute of Environmental Health Sciences (NIEHS) Superfund Basic Research Program. The overall focus of this conference was on exploring the research interfaces of toxicity reduction, exposure assessment, and evaluation of environmental consequences in the context of using state-of-the-art approaches to bioremediation and biodegradation. The Superfund Basic Research Program has a legacy of supporting research conferences designed to integrate the broad spectrum of disciplines related to hazardous substances.
We thank M. James and S. Roberts, directors of the University of Florida Superfund Basic Research Program, for their support and encouragement of this work. We acknowledge P. Nkedi-Kizza of the Department of Soil and Water Sciences at the University of Florida for his kind generosity and guidance during the column experiments.
This work was funded by the U.S. Environmental Protection Agency and the NIEHS Superfund Basic Research Program.
The authors declare they have no competing financial interests.
1 2005 8 12 2004 113 1 55 61 23 12 2003 7 4 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. With increased application of co-solvent flushing technologies for removal of nonaqueous phase liquids from groundwater aquifers, concern over the effects of the solvent on native microorganisms and their ability to degrade residual contaminant has also arisen. This study assessed the impact of ethanol flushing on the numbers and activity potentials of trichloroethylene (TCE)-degrading microbial populations present in aquifer soils taken immediately after and 2 years after ethanol flushing of a former dry cleaners site. Polymerase chain reaction analysis revealed soluble methane monooxygenase genes in methanotrophic enrichments, and 16S rRNA analysis identified Methylocystis parvus with 98% similarity, further indicating the presence of a type II methanotroph. Dissimilatory sulfite reductase genes in sulfate-reducing enrichments prepared were also observed. Ethanol flushing was simulated in columns packed with uncontaminated soils from the dry cleaners site that were dosed with TCE at concentrations observed in the field; after flushing, the columns were subjected to a continuous flow of 500 pore volumes of groundwater per week. Total acridine orange direct cell counts of the flushed and nonflushed soils decreased over the 15-week testing period, but after 5 weeks, the flushed soils maintained higher cell counts than the nonflushed soils. Inhibition of methanogenesis by sulfate reduction was observed in all column soils, as was increasing removal of total methane by soils incubated under methanotrophic conditions. These results showed that impacts of ethanol were not as severe as anticipated and imply that ethanol may mitigate the toxicity of TCE to the microorganisms.
co-solvent flushingmethanotrophsparticulate methane monooxygenaseperchloroethylene16S rDNAsoluble methane monooxygenasetrichloroethylene
==== Body
Co-solvent flushing, also known as in situ flushing, is a technology that has recently been considered for removal of light and dense nonaqueous phase liquids (LNAPLs and DNAPLs, respectively) from ground-water aquifers. Originally developed by the petroleum industry for enhanced oil recovery (Lake 1989), this method involves a) injection of co-solvent such as alcohol or surfactant into the source zone area of an NAPL plume; b) partitioning of the contaminant into the co-solvent–groundwater phase; and c) its recovery and ex situ separation from the co-solvent–groundwater mixture, which is subsequently recycled into the aquifer for capture of additional contaminant [U.S. Environmental Protection Agency (U.S. EPA) 2002]. This method promises to be superior to other technologies used for contaminant removal from aquifers because it is simple in concept, effective, and does not require removing contaminated soils (Falta et al. 1998; Rao et al. 1997).
Various bench and field studies have reported successful removal of LNAPLs and DNAPLs using this method (Brandes and Farley 1993; Imhoff et al. 1995; Jawitz et al. 2000; McCray and Brusseau 1998; Rao et al. 1997), and to date 16 Superfund sites reportedly have been successfully treated by this method (U.S. EPA 2002). Jawitz et al. (2000) recently reported an in situ flushing pilot study using ethanol as a co-solvent to remove perchloroethylene (PCE) DNAPLs from a shallow, unconfined aquifer at a former dry cleaners site in Jacksonville, Florida, USA. Flushing of 34 kL of a 95% ethanol/5% water mixture over a 3-day period (an equivalent of two pore volumes) resulted in 65% removal of the 68 L of PCE originally present, and these authors concluded that continued alcohol flushing would have resulted in greater NAPL removal effectiveness.
The presence of high concentrations of ethanol in an aquifer may result in significant changes in numbers and activities of microorganisms after the bulk of the contaminant has been removed. High concentrations of ethanol and certain detergents are toxic to many microorganisms. Studies have shown that such stress tends to lower the diversity in microbial communities, which are subsequently less capable of dealing with further environmental fluctuations (Atlas and Bartha 1987). Although previous work has reported positive effects of low concentrations of ethanol as an electron donor in reductive dehalogenation processes (Gibson and Sewell 1992), no study has directly observed changes in microbial populations at a site after ethanol flushing, particularly in terms of their potential to degrade residual contaminant over time. The broad objective of this study was to assess the effects of ethanol flushing over time on numbers and activity of potential PCE-and trichloroethylene (TCE)-degrading microbial populations present in soil from the former Sages Dry Cleaners site (henceforth referred to as the Sages site).
Materials and Methods
Specific objectives of this study were the following: a) to obtain samples from the Sages site after ethanol flushing treatment; b) to assess the shifts in methanogenic, sulfate-reducing, and methanotrophic bacteria, all known to transform TCE, before and after ethanol flushing using gene probe analysis on the soil samples; c) to verify the presence of potential TCE-degrading bacteria by enriching for these microorganisms from the soil samples and identifying them using polymerase chain reaction (PCR) analysis; and d) to simulate ethanol flushing in column studies to enable determination of the impacts of ethanol and TCE on bacterial counts and activity potentials. Figure 1 provides an overview of the methods performed in this study. Each method is described in more detail below.
Soil samples.
All samples were collected by Levine-Fricke-Recon, Inc. (Tallahassee, FL) from multilevel sampling locations at the Sages site, where ethanol flushing treatment was performed in August 1998. The locations of the seven recovery wells that surrounded the three injection wells were selected to be just outside the perimeter of the initial estimated horizontal extent of the PCE source zone as described by Jawitz et al. (2000), and all samples were removed at various distances from the recovery well zone. Immediately after ethanol flushing, soil samples were removed from three monitoring well (MW) sites, designated as MW-8, MW-9, and MW-11, located approximately 51, 26, and 97 feet, respectively, from the closest recovery well. Samples were also removed 2 years after flushing from seven locations, designated as C-31, C-32, C-33, C-34, C-35, C-36, and C-37. C-36 was located closest to the recovery well area at approximately 17 feet, and C-34 was farthest from the recovery well area at approximately 109 feet. Detailed descriptions of the Sages site contaminant plume and placement of injection, recovery, and monitoring wells can be found in Jawitz et al. (2000), and Ramakrishnan (2002), Sillan (1999). All samples were taken approximately 8–9 m below ground surface. Soil samples were collected in sterile glass jars, immediately sealed, and placed on ice. Upon arrival in the laboratory in Gainesville, Florida, soil samples were manually homogenized using a sterile spatula. An aliquot of each sample for immediate use was stored at 4°C, and the remainder of the soil samples was stored at −80°C.
Soil samples had a particle size distribution of fine to very fine sand, an average moisture content of 19.7%, and an average organic carbon content of 1.7% (Sillan 1999). The average pH of the soils used in this study ranged from 4.2 to 7.2; sulfate concentrations in these soils, measured by the University of Florida Extension Soils Testing Laboratory in Gainesville, Florida, ranged from 1.4 to 2.9 mg/L.
Enrichments of specific TCE degraders from Sages site soil.
Because increased concentrations of methane and TCE and decreased concentrations of sulfate were observed at the Sages site subsequent to ethanol flushing, there was strong indication of the presence of methanogenic and sulfate-reducing bacteria and even possibly methane-oxidizing bacteria, given the reported aerobic preflushing conditions (Mravik et al. 2003). Methanogens and sulfate reducers are capable of anaerobic reductive dehalogenation of PCE and TCE (e.g., Bagley and Gossett 1990; DiStefano et al. 1992; Freedman and Gossett 1989) and that MTs are capable of oxidizing TCE (e.g., Dispirito et al. 1992; Henry and Grbić-Galić 1990). Therefore, enrichments of sulfate-reducing and methanotrophic bacteria were attempted as a means of verifying their presence at the site. Because of the difficulty experienced in enriching for methanogenic bacteria, only activity assays were performed for these bacteria, as described below.
Enrichments and culturing of sulfate-reducing bacteria.
Five grams (wet weight) of soil was added to a 120-mL serum vial containing 45 mL basal carbonate yeast extract trypticase (BCYT) medium prepared anaerobically, and the headspace was flushed with N2:CO2 (70:30 v/v). This mixture was amended with acetate or lactate (20 mM), ferrous sulfate (2 mM), and sodium cysteine (0.5 g/L) (Widdel and Bak 1992). On formation of sulfide (as indicated by black precipitate), transfers were made on a regular basis to fresh BCYT medium with sodium sulfate (20 mM) instead of ferrous sulfate.
Enrichments and culturing of methanotrophic bacteria.
Ten grams (wet weight) of soil was mixed with 50 mL nitrate mineral salts medium (NMS) (Whittenbury et al. 1970) in a 250-mL Erlenmeyer flask. The flasks were sealed with a rubber stopper threaded with glass wool–filled tubing to allow removal of headspace air, using a vacuum pump and subsequent filling with 99.99% methane (Strate Welding, Jacksonville, FL), as previously described (Lindner et al. 2000). All enrichments were prepared in triplicate using 20% methane (v/v) in the headspace and incubated at 30°C with shaking at 250 rpm. Transfers of 10–14% inoculum (v/v) to fresh liquid NMS medium were prepared weekly along with streaking on solid plates of carbon-free Bacto agar (Difco, Detroit, MI) and NMS that were stored in an airtight desiccator filled with methane:air (30% v/v) at 30°C. Cultures were periodically streaked on nutrient agar plates to assess growth characteristics of heterotrophic bacteria.
A qualitative assay was performed using naphthalene and tetrazotized ortho-dianisidine to detect activity of soluble methane monooxygenase (sMMO) in the enriched methanotrophic-mixed cultures, as previously described (Bowman et al. 1993; Lindner et al. 2000).
Ethanol-flushing simulation in columns.
Laboratory-scale vertical upward flow soil columns were constructed using custom-made glass columns 5 cm long and 2.5 cm inner diameter (Kontes, Vineland, NJ) and 50 g (wet weight) of soil samples taken from an uncontaminated portion of the Sages site (2 years post-flushing). Three sets of columns were constructed and run over three time periods (1 week, 5 weeks, and 15 weeks) before being sacrificed for subsequent testing. Each set contained controls with TCE only (no ethanol) and duplicate columns containing TCE and flushed with ethanol. An additional control with ethanol treatment only was included in the 15-week column studies.
Because of the relatively small amount of soil available for these studies, samples taken from C-34, C-35, and C-37 were homogeneously mixed and subsequently treated with two different final concentrations of TCE to assess the effect of TCE concentration on population counts and activities. TCE was added to soil in a glass beaker that was immediately covered and placed on ice to avoid TCE volatilization. This soil-TCE mixture was packed into columns using a wet packing method with intermittent vibration to exclude air bubbles. No pools of free DNAPL were obvious within the TCE-treated columns. The 1- and 5-week columns were treated with 40,000 mg TCE/kg soil (99.99%; Fisher Scientific, Pittsburgh, PA) to mimic the highest average concentrations observed at the source zone of the Sages site before ethanol flushing (Jawitz et al. 2000; Levine-Fricke-Recon, Inc. 1998). The 15-week columns were treated with 4,000 mg TCE/kg soil, which were concentrations reported at the Sages site by Sillan (1999).
After the columns were packed and TCE added, 10 pore volumes of groundwater taken from the Sages site were pumped at a flow rate of 0.2 mL/min using a Gilson peristaltic pump (Gilson, Inc., Middleton, WI). Two pore volumes of 70% ethanol were then pumped through the columns. After the ethanol flushing, 500 pore volumes of Sages site groundwater were pumped through the columns each week at a flow rate of 0.2 mL/min until each set of columns was sacrificed for genetic and activity analyses.
Microbial DNA isolation.
Several methods to isolate DNA from the Sages site soil were attempted, as described in detail by Ramakrishnan (2002), including a commercial soil extraction kit marketed by Mo Bio Laboratories, Inc. (Solana Beach, CA) (used according to the manufacturer’s instructions) and modifications of previously reported methods (Berthelet et al. 1996; Cullen and Hirsch 1998; Duarte et al. 1998; Holben 1994; Miller et al. 1999; Ogram et al. 1987, 1997; Zhou et al. 1996).
DNA from enriched methanotrophic cultures was extracted using Mo Bio Laboratories DNA isolation kit. One and one-half milliliters of culture was centrifuged in Eppendorf tubes at 14,000 rpm for 2 min. Supernatant was discarded, and the pellet was added to the bead tube with buffer solution provided with the Mo Bio Laboratories kit. DNA from the cell pellet was isolated according to manufacturer’s instructions.
Molecular analysis of soil and enriched culture DNA.
Polymerase chain reaction methods.
6S rRNA genes from bacterial and archaeal groups present in the soils were amplified by PCR, using specific primers. Universal bacterial primers used were 27F (AGAGTTTGATCCMTGGCTCAG) and 1492R (TACGGYTACCTTGTTACGAC TT) (Lane 1991). The reaction mixture contained 10 μL Hotstart mastermix (Qiagen, Valencia, CA), 1 μL (1 pmol) of each primer, and 8 μL soil DNA diluted at 1:10, 1:100, and 1:1,000. PCR was conducted using a PerkinElmer model 2400 DNA Thermal Cycler (PerkinElmer, Inc., Norwalk, CT) for 30 cycles with cycling parameters of 95°C for 15 min, followed by 94°C for 30 sec for denaturation of DNA, 58°C for 30 sec for annealing, and 72°C for 30 sec for DNA chain extension, followed by a 7-min chain extension step. Similarly, PCR was conducted with the universal archaeal primers 23F (TCYGGTTGATCCTGCC) (Burggraf et al. 1991) and 1492 R (Lane 1991) with cycling conditions similar to above. Reaction products were electrophoresed through a 0.7% agarose gel.
PCR of DNA isolated from methanotrophic enrichment cultures were performed with primers specific to 16S rRNA genes of type I and type II MTs. Primers used to amplify the 16S rRNA gene of type I MTs (labeled MT-I) were Meth T1dF 5′-CCTTCGGGMGCYGACGACT-3′ and Meth T1bR 5′-GATTCYMTGSATGT CAAGG-3′ (Wise et al. 1999). To amplify the 16S rRNA gene of type II MTs (labeled MT-II), universal bacterial primer 27 F (Lane 1991) and Meth T2R 5′-CATCTCTGRC SAYCATACCGG-3′ (Wise et al. 1999) were used. PCR primers used for sMMO were mmoX f882 (5′-GGCTCCAAGTTCAAG GTCGAGC-3′) and mmoX r1403 (5′ - T G G C A C T C G T A G C G C T C C G GCTCG-3′) (McDonald et al. 1995). Primers used for methanol dehydrogenase (MDH) were mxa f1003 (5′-GCGGCAC CAACTGGGGCTGGT-3′) and mxa r1561 (5′-GGGCAGCATGAAGGGCT CCC-3′) (McDonald and Murrell 1997). PCR was performed for 30 cycles in the PerkinElmer DNA model 2400 DNA Thermal Cycler previously described, with conditions of each reaction cycle held at 95°C for 15 min followed by 94°C for 30 sec (denaturation), 58°C for 30 sec (for type II primers), or 54°C for 30 sec (for type I primers) (annealing), and 72°C for 30 sec, with a final extension step at 72°C for 7 min (chain extension). Chromosomal DNA from Methylosinus trichosporium OB3b and Methylomicrobium album BG8 were used as positive controls for type II and type I PCR, respectively. PCR products were electrophoresed through a 0.7% agarose gel.
PCR analysis of sulfate reducers from soil enrichments was also performed. A 1.9-kb dissimilatory sulfite reductase (DSR) gene was amplified from cultures exhibiting sulfate-reducing activity using DSR1F (AC[C/G] CACTGGAACGACG) and DSR4R (GTG TACGACTTACCGCA) (Wagner et al. 1998) primers. PCR conditions were similar to those used for MTs mentioned previously, with the exception of an annealing temperature of 59°C for 30 sec and extension for 90 sec at 72°C.
Molecular cloning.
PCR products of approximately 1.5 kb were cloned using 5-min TA cloning kit (Invitrogen, San Diego, CA). The PCR product was ligated into the plasmid according to the manufacturer’s instructions. Two microliters of ligated plasmids were transformed to competent Escherichia coli cells (TOP10F′) provided with the cloning kit, followed by a heat shock at 42°C for 30 sec. E. coli cells were incubated at 37°C for 1 hr at 225 rpm with additional 250 μL SOC medium (2% tryptone, 0.5% yeast extract, 10 mM NaCl, 2.5 mM KCl, 10 mM MgCl2, 10 mM MgSO4, and 20 mM glucose). Transformed E. coli cells were plated onto Luria-Bertani (LB) plates with 50 μg/mL kanamycin and 40 μg/mL each X-gal (5-bromo-4-chloro-3-indolyl-β-d-galactoside or β-galactosidase) and IPTG (isopropylthio-β-d-galactoside) for screening of transformed cells. The plates were incubated overnight at 37°C. White colonies were randomly selected and inoculated into 5 mL LB-kanamycin broth (50 μg/mL) and incubated at 37°C overnight with shaking at 225 rpm.
Plasmid DNA isolation.
Twenty clones from most probable number clonings were randomly selected for screening. Plasmid DNA from cultures was isolated using a standard alkaline lysis procedure (Sambrook et al. 1989). EcoRI (Promega, Madison, WI) was used to digest plasmids to confirm whether the plasmids harbored PCR products. Isolated plasmids were digested overnight with 11 μL EcoRI, 1 μL 10× buffer, 6 μL deionized sterile water, and 2 μL plasmid DNA at 37°C. Digested products were electrophoresed through a 0.7% agarose gel. Inserts were digested with HhaI (Promega), electrophoresed as above, and grouped according to restriction fragment length polymorphism. Representatives of unique groups were selected for sequencing. The plasmid DNA was purified and inserts were sequenced by the Interdisciplinary Consortium for Biotechnology Research core sequencing facility at the University of Florida.
Acridine orange direct counting.
Soil samples (1 g wet weight) taken from various locations in the columns were preserved with 2.5% particle-free (0.2-μm pore-size filtered) glutaraldehyde. Samples were sonicated for 30 sec and kept on ice to avoid heating and damaging cells. The soil samples were then diluted 10-fold, and 100 μL of this suspension was poured into a 25-mm microfiltration system, equipped with a 0.2-μm polycarbonate filter (Isopore membrane filters; Millipore, Bedford, MA), and connected to a vacuum. To achieve random distribution of cells on the filter, the sample volume was increased to 2 mL with particle-free water (Turley 1993), and approximately 3 drops of acridine orange solution (1 mg/mL) were added to the sample. The filter unit was covered with aluminum foil to avoid photodegradation of acridine orange and was swirled for 3 min for random distribution and proper staining of cells. Samples were then filtered under a vacuum (Bio-Rad vacuum pump; Bio-Rad, Hercules, CA), with care taken not to allow drying of filter membranes. The damp filter membrane was placed on a clean glass slide with a fine smear of nonfluorescent immersion oil. A drop of immersion oil was placed on top of the filter membrane, and a cover slip was pressed firmly on the oil, with the oil forming a seal at the edge. Mounted slides were viewed under a 100× oil immersion objective of a Nikon Optiphot epifluorescent microscope (Nikon, Garden City, NY) fitted with filters for excitation of cells stained with acridine orange. Background counts were carried out with particle-free water, acridine orange, and glutaraldehyde solution and were subtracted from sample cell counts.
Microbial activity measurements.
Methanogenic activity.
To compare the activity of methanogens in the columns, microcosms were constructed with 5 g nontreated starting soil and soil from the 1-, 5-, and 15-week column samples. Acetate (20 mM) or H2/CO2 (80:20%) (carbon/energy source) and sodium cysteine (pH 10.0) (reductant) were added to the soils in 60-mL vials that were incubated for 6 weeks at 28°C at 150 rpm.
Methane production was monitored by regular sampling and gas chromatography using a Hewlett-Packard model 5890 gas chromatograph (Hewlett-Packard, Denver, CO) equipped with a flame ionization detector and a 1/8 inch SS 45/60 Carboxen 1000 column. The temperatures of injector/detector and column were maintained at 110°C and 160°C, respectively. A standard gas (Scott Specialty Gases, Plumsteadville, PA) containing a mixture of 1% each of methane, carbon dioxide, carbon monoxide, oxygen, hydrogen, and the remainder nitrogen was used for standard curve calibration. Using gas-tight syringes (Hamilton, Reno, NV), 300 μL headspace gas was injected into the gas chromatograph.
Sulfate-reducing activity.
Sulfate-reducing microcosms were constructed using 5 g each of both Sages soil material (starting material) and column soil samples, using the same protocol described previously for enriching for these microorganisms. Vials were maintained at 28°C for 4 weeks. Dissolved sulfide concentrations were measured with a Shimadzu spectrophotometer (Shimadzu Biotech USA, Columbia, MD) at 480 nm, using the method described by Cord-Ruwisch (1985).
Methanotrophic activity.
Depletion of methane by 5 g of soil from the 1-, 5-, and 15-week columns was monitored in sealed microcosms constructed using the same protocol described previously for enriching for these microorganisms. Headspace sampling was performed regularly, followed by gas chromatographic analyses using a Hewlett-Packard model 5890 gas chromatograph equipped with a thermal conductivity detector, J&D Molesieve PLOT porous column (internal diameter, 20 m × 0.53 mm; Agilent/J&W Scientific, Palo Alto, CA), and a split/splitless injector. The temperatures of oven, injector, and detector were maintained at 25, 120, and 200°C, respectively. Head pressure was maintained at 5 psi. A certified grade 50/50 (methane/nitrogen) gas standard (Scott Specialty Gases, Inc.) was used for standard curve calibration. Initial rates of methane depletion were calculated using Excel 2000 software (Microsoft Corp., Redmond, WA) by determining the slopes of the resulting concentration-time plots using either linear or third-order polynomial fits, depending on the curvature of the methane depletion response. Standard errors of the initial slopes were determined using Simstat software (version 1.2.4e; Provalis Research, Ottawa, Ontario, Canada).
Results and Discussion
DNA isolation from Sages site soil samples.
As mentioned previously, various methods were employed to isolate amplifiable DNA from the Sages site soil samples to track changes in the microbial populations at the site with time. Regardless of the samples or methods used, however, extraction of microbial DNA from soil was problematic, as a deep brown substance co-purified with the DNA. Inability to isolate amplifiable DNA was attributed to co-purification of unknown PCR inhibitors with the DNA.
Amplifiable soil DNA was isolated only from samples MW-11 (taken immediately after flushing) and C-31 and C-35 (both taken 2 years after flushing). Results of PCR analysis showed the presence of bacterial and archaea genes in sample MW-11, only archaea genes in sample C-31, and only bacterial genes in sample C-33. No sample tested positive for the presence of the DSR gene or the type I or type II MT genes.
Enrichments of sulfate-reducing and methanotrophic bacteria and screening for specific genes.
Given this difficulty in DNA isolation from the soil samples, enrichments of sulfate reducers and MTs were attempted from the Sages site soil as a means of verifying their presence and thus the potential for TCE transformation activity at the site. Positive results in these experiments would justify simulating ethanol flushing in the laboratory as an alternative means of tracking population changes in the soil over time.
Of the three Sages soil samples taken immediately after flushing, only cultures inoculated with MW-11 showed turbidity on repeated transfers and incubation at conditions conducive for methanotrophic growth, whereas five of the seven samples removed 2 years after flushing (C-31, C-33, C-35, C-36, and C-37) showed positive growth under these conditions. DNA isolated from each mixed methanotrophic–heterotrophic culture was subjected to PCR with primers specific to only type I and type II MTs (MT-I, MT-II), MDH and sMMO. Table 1 shows the results of these experiments, with presence or absence of the specific genes indicated by + and −, respectively. With the exception of the mixed culture derived from soil sample C-36, all other cultures showed the presence of not only universal bacterial genes but also genes specific for type II MTs, MDH, and sMMO. Interestingly, the location of soil sample C-36 is the closest to the ethanol-impacted area and would have naturally been exposed to the highest concentrations of ethanol and PCE.
A standard colorimetric naphthalene oxidation assay was performed to detect activity of sMMO in these methanotrophic–heterotrophic mixed cultures (Brusseau et al. 1990; Lindner et al. 2000). As shown in Table 1, the mixed cultures enriched from samples C-31, C-33, C-35, C-37, and MW-11 formed a purple color, whereas C-36 showed no color upon addition of tetrazotized ortho-dianisidine, known to complex with naphthol. These results are consistent with the results obtained from the PCR analysis confirming the presence of type II MT genes. Furthermore, the intensity of color formed was highest in C-37 when compared with the other samples.
The mixed cultures derived from soil samples were further screened by molecular cloning and 16S rRNA sequence analysis. The BLAST results of this analysis showing matches of the most similar GenBank sequences (GenBank 2002) are shown in Table 2. As shown, a type II MT sharing 98% 16S rRNA gene sequence similarity with Methylocystis parvus was identified in these mixed cultures.
Of the three soil samples taken immediately after flushing, only MW-11 yielded positive results for sulfate-reducing activities in the enrichments, as evidenced by a formation of a black precipitate of sulfide. Of those samples taken 2 years after flushing, only C-31 and C-37 yielded enrichment cultures of sulfate-reducing bacteria. As shown in Table 1, PCR analysis of these mixed cultures indicated the presence of DSR genes of all three of these samples. As observed in the methanotrophic enrichment experiments, the sample derived from C-36, closest to the ethanol-impacted area, yielded no indication of sulfate-reducing bacteria even 2 years after flushing.
Column studies.
With the positive identification of methanotrophic and sulfate-reducing bacteria in some of the soil samples, column studies were performed with Sages site soil to simulate ethanol flushing and assess effects on microbial populations present over time. As described in “Materials and Methods,” columns were packed with soil derived from uncontaminated portions of the site, including sample C-37 that tested positively for both sulfate reducers and MTs.
Total microbial counts in soil columns.
Figure 2 shows that microbial counts in the soil column determined by acridine orange direct counting (AODC) methods did not significantly change 1 week after flushing with ethanol compared with counts in soils before flushing (8.63 × 107 ± 2.22 × 107 cells/g soil and 6.87 × 107 ± 8.91 × 106 cells/g soil, respectively). In addition, counts in columns with 40,000 mg TCE/kg soil only and no ethanol introduced (1.17 × 108 ± 2.49 × 107) were not significantly different from the ethanol-flushed column counts 1 week after flushing. However, soil removed from both flushed and nonflushed columns after 5 weeks possessed lower total counts than observed in the corresponding 1-week flushed columns. Surprisingly, these results imply that neither ethanol nor TCE immediately impacted the total microbial counts in the columns, but that these counts decreased in a 5-week period, with a greater decrease observed in the TCE-only columns. The 15-week columns pretreated with a significantly lower TCE concentration also showed higher total microbial counts in the flushed columns compared with the nonflushed columns but the lowest counts in comparison with the 1- and 5-week column cell numbers.
Although these results should be cautiously interpreted given the difficulties accompanying the AODC method (potential for human error, interference of humic acids, nonuniform distribution of microorganisms in the upflow columns), they do suggest that ethanol does not have the toxicity effects on the microorganisms as would be anticipated. In fact, higher counts observed in the flushed columns may indicate that it has a buffering effect on TCE toxicity to microorganisms.
Activity measurements in column samples.
Methanogenic and sulfate-reducing activity.
In all microcosms incubated under methanogenic conditions, no methane formation was observed. On termination of the 5-week microcosms, a strong odor of hydrogen sulfide was noticed. As confirmation, dissolved sulfide was subsequently measured after 6 weeks in the microcosms established with soil from the 15-week columns. Despite no external sulfate added to these vials, hydrogen sulfide formation was observed, ranging from 6.75 ± 1.02 mM in the microcosms with soils treated with TCE and ethanol to 9.93 ± 2.36 mM with soils treated with ethanol only. The TCE-treated, nonflushed soils produced 8.25 ± 1.02 mM hydrogen sulfide, slightly lower than the ethanol-only treated columns. Continuous introduction of dissolved oxygen in the groundwater may have inhibited methanogenesis in the columns; however, channeling of the groundwater flow in the columns was observed, resulting in isolated regions that we suspected contained little or no oxygen. It was therefore anticipated that methanogenesis would have been detected in the activity assays.
Methanogenesis may also have been inhibited because of native sulfate concentrations (1.4–2.9 mg/L) that facilitated sulfate reduction as a primary process. Sulfate reducers compete with methanogens for carbon and energy sources, and because sulfate concentrations were relatively high in these soils, sulfate reduction was likely active in suppressing methanogenesis. Reduction in concentrations of PCE and accumulation of TCE and cis-dichloroethylene were observed at the Sages site after the ethanol treatment (Mravik et al. 2003; U.S. EPA 2000). This implies that reductive dehalogenation of PCE was taking place in the field. In fact, methane concentrations were reportedly increased at the Sages site in the flushing zone approximately 4 months after flushing and only after sulfate concentrations were depleted (Mravik et al. 2003). The microcosms using soils from the ethanol-only column produced 20–40% more sulfide compared with microcosms using soils from the columns treated with TCE only and with TCE and ethanol.
In the sulfide-reducing microcosms, where 20 mM sulfate was added to the microcosms, the starting material (with no treatment of TCE or ethanol) exhibited higher amounts of sulfide production (15.55 ± 0.35 mM) than the treated column samples after 15 weeks of groundwater flushing (Figure 3), implying an inhibitive effect of both ethanol and TCE. All microcosms with treated soils exhibited similar hydrogen sulfide production. The presence of residual ethanol after flushing did not affect sulfate-reducing activity (comparing all three 15-week column results). Ethanol may be used as an energy source by some sulfate reducers (Nagpal et al. 2000), but studies with postflushing samples from the Sages site have shown higher rates of PCE dechlorination with whey as electron donor rather than with ethanol (Helton 2000).
Methanotrophic activity.
Microcosms were established with soils from the 1- and 5-week columns and incubated under a 20% initial headspace concentration of methane to assess methane depletion activities over time. An initial lag period of 1–2 days was observed in all 1- and 5-week microcosms. Table 3 shows the resulting initial rates of methane depletion and percentage of total methane removed during the 11-day testing period, after which no noticeable change in methane concentrations was observed. Rates of methane depletion were significantly higher (2.17% headspace methane removed per day) with the soils in the 5-week columns treated with TCE only compared with the 1-week column soils (0.83% headspace methane removed/day). The 5-week soils dosed with only TCE also removed a greater total percentage of methane during the experiments than the 1-week soils (45 and 17%, respectively). Little difference was observed in the methane depletion activities in the microcosms constructed with soils removed from the 1- and 5-week TCE- and ethanol-treated columns, as shown in Table 3. However, in comparison with the TCE-only soils, both “TCE + ethanol” soils (1-week and 5-week) showed much higher initial methane depletion rates. These soils treated with TCE and ethanol in the 1-week columns displayed a higher percentage removal of methane (37%) compared with the corresponding soils treated with TCE only (17%). The total methane removed by the 5-week soils treated with TCE with or without ethanol was not significantly different from the total amount of methane removed by the 1-week soils, however.
The higher methane depletion activities observed in soils 1 and 5 weeks after ethanol flushing compared with non–ethanol-treated soils indicate that ethanol has a mitigating effect on TCE toxicity to methanotrophic bacteria. The toxicity of products of TCE metabolism by MTs, including TCE epoxide, has been previously reported (Alvarez-Cohen and McCarty 1991; Oldenhuis et al. 1991; Oldenhuis and Janssen 1993), and the fact that no methanotrophic enrichments were successful at the sampling location closest to the ethanol flushing may be attributed to the higher concentrations of PCE and TCE present and not of ethanol.
The 15-week column soils showed little difference in methane depletion rates and total methane removed regardless of the treatment subjected to the soils, and no lag period was observed in any of the microcosms. In each of these microcosms, 84–88% of methane was removed, which was significantly higher than observed in the 1- and 5-week microcosms. Although it is tempting to compare these values to those of the 1- and 5-week column soils, caution should be taken in doing so because of the large difference in initial TCE dose used (40,000 mg TCE/kg soil in the 1- and 5-week columns; 4,000 mg TCE/kg soil in the 15-week columns). What can be concluded from these results, however, is that even 15 weeks after ethanol flushing, methanotrophic activity potential is present in the soils, as well as the potential for removal of residual TCE, given appropriate conditions at a treatment site.
Conclusions
Because the DNA isolation was problematic, it was not possible to test samples directly at the site as originally planned. However, the study was successful in enriching for sulfate-reducing bacteria and type II methanotrophic bacteria. Additionally, the column studies showed that no methanogenesis occurred, possibly because of the predominance of the sulfate-reducing activity, in agreement with observations taken during the pilot-scale flushing event.
The goal of this work was to determine if the introduction of the ethanol during flushing impacted the activities (and indirectly, their ability to transform residual contaminant) of the microorganisms present in the Sages site soil. Total counts of bacteria decreased in all flushed and nonflushed samples with time; however, flushed samples contained higher total counts of bacteria compared with those in nonflushed samples. Sulfide formation was observed not only in sulfate-reducing microcosms with soils from the 15-week laboratory columns and initially dosed with 4,000 mg TCE/kg soil, but also in methanogenic microcosms in as little as 1 week. Methanotrophic activity potentials increased from 1 to 5 weeks, and little difference in methane depletion was observed with the 15-week soils regardless of treatment. However, higher rates of methane depletion were observed in those microcosms with the 1- and 5-week column soils subjected to ethanol flushing. These results indicate that ethanol flushing did not have as severe an impact on the populations as was initially anticipated and did not impair the activities of the sulfate-reducing and methanotrophic microorganisms over time. Furthermore, increased activity observed in the presence of ethanol indicates the mitigating effects of ethanol to TCE toxicity.
Figure 1 Schematic of experimental methods used in this study. Samples taken both immediately after and 2 years after ethanol flushing were used in the gene probe analysis and enrichment experiments. Only 2-year postflushing samples from C-34, C-35, and C-37 were used in the column studies.
Figure 2 AODC of microbial cells in 1-, 5-, and 15-week column samples with and without ethanol flushing. “Before flushing” refers to Sages site soil from locations C-34, C-35, and C-37 used to pack the three columns. Error bars represent the 95% confidence interval of the average of seven samples.
Figure 3 Hydrogen sulfide concentrations measured in sulfate-reducing microcosms using soils from the three 15-week columns tested in comparison with the starting material (not subjected to column treatments) and a control (no TCE or ethanol treatment). “TCE only” refers to microcosms with soils derived from columns pretreated with 4,000 mg TCE/kg soil with no ethanol flushing. “TCE + ethanol” refers to microcosms with soils taken from columns pre-treated with 4,000 mg TCE/kg soil and ethanol flushed. “Ethanol only” refers to microcosms with soils taken from columns with ethanol flushing and no TCE pretreatment. Error bars represent the 95% confidence interval of the average of a minimum of two measurements.
Table 1 PCR analysis and sMMO assay results of mixed methanotrophic–heterotrophic enrichments.
Sample Bacteria Archaea DSR MT-I MT-II MDH sMMO sMMO assay
MW-11 + − + − + + + +
C-31A + − + − + + + +
C-33A + − − − + + + +
C-35A + − − − + + + +
C-36A − − − − − − − −
C-37A + − + − + + + +
Presence or absence of genes or positive or negative assay results denoted by + or −, respectively.
Table 2 BLAST results of 16S rDNA sequence analysis mixed methanotrophic cultures.
Most similar GenBank sequencea Identity (%) GenBank accession numbera
M. parvus 98 AF150805
Acinetobacter calcoaceticus 99 AF159045
Acaligenes sp. 98 AF150805
Hypomicrobium facilis 99 Y14311
a From GenBank (2002).
Table 3 Initial methane depletion rates and total percentage of methane depleted observed in the methanotrophic microcosms using 1-, 5-, and 15-week soil samples.
TCE alone
TCE + ethanol
Activity measure 1 week 5 weeks 15 weeks 1 week 5 weeks 15 weeks Ethanol alone 15 weeks
Methane depletion rate (% CH4/day) 0.83 (0.19) 2.17 (0.40) 4.03 (2.61) 14.61 (4.27) 14.14 (9.68) 4.37 (0.56) 5.09 (0.33)
Percentage of total methane removed 17 45 84 37 43 87 88
Numbers in parentheses denote the standard error on the slopes of the lines used to calculate the initial methane depletion rates.
==== Refs
References
Alvarez-Cohen L McCarty PL 1991 Effects of toxicity, aeration, and reductant supply on trichloroethylene transformation by a mixed methanotrophic culture Appl Environ Microbiol 57 228 235 2036009
Atlas RM Bartha R 1987. Microbial Ecology: Fundamentals and Applications. 2nd ed. Menlo Park, CA:Benjamin/Cummings Publishing Co., Inc.
Bagley DM Gossett JM 1990 Tetrachloroethene transformation to trichloroethene and cis -dichloroethene by sulfate-reducing enrichment cultures Appl Environ Microbiol 56 2511 2516 2403257
Berthelet M Whyte LG Greer CS 1996 Rapid, direct extraction of DNA from soils for PCR analysis using polyvinylpolypyrrolidone spin columns FEMS Microbiol Lett 138 17 22 8674967
Bowman JP Jimenez L Rosario I Hazen TC Sayler GS 1993 Characterization of the methanotrophic bacterial community present in a trichloroethylene-contaminated subsurface groundwater site Appl Environ Microbiol 59 2380 2387 8368829
Brandes D Farley KJ 1993 Importance of phase behavior on the removal of residual DNAPLs from porous media by alcohol flooding Water Environ Res 65 7 869 878
Brusseau GA Tsien HC Hanson RS Wackett LP 1990 Optimization of trichloroethylene oxidation by methanotrophs and the use of a colorimetric assay to detect soluble methane monooxygenase activity Biodegradation 1 19 29 1368139
Burggraf S Steter KO Rouvier P Woese CR 1991 Methanosyrus kandleri : an archaeal methanogen unrelated to all other known methanogens Syst Appl Microbiol 14 346 351 11540073
Cord-Ruwisch R 1985 A quick method for the determination of dissolved and precipitated sulfides in cultures of sulfate-reducing bacteria J Microbiol Methods 4 33 36
Cullen DW Hirsch PR 1998 Simple and rapid method for direct extraction of microbial DNA from soil for PCR Soil Biol Biochem 30 983 993
DiSpirito AA Gulledge J Shiemke AK Murrell JC Lidstrom ME Krema CL 1992 Trichloroethylene oxidation by the membrane-associated methane monooxygenase in type I, type I and type X methanotrophs Biodegradation 2 151 164
DiStefano TD Gossett JM Zinder SH 1992 Hydrogen as an electron donor for dechlorination of tetrachloroethene by an anaerobic mixed culture Appl Environ Microbiol 58 3622 3629 1482184
Duarte GF Rosado AS Seldin L Keijzer-Wolters AC van Elsas JD 1998 Extraction of ribosomal RNA and genomic DNA from soil for studying the diversity of the indigenous bacterial community J Microbiol Methods 32 21 29
Falta RW Lee CM Brame SE Roder E Wright CW Coates JT 1998. Field study of LNAPL remediation by in-situ co-solvent flooding. In: Nonaqueous Phase Liquids (Wickramanayake GC, Hinchee RE, eds). Columbus, OH: Battelle Press.
Freedman DL Gossett JM 1989 Biological reductive dechlorination of tetrachloroethylene and trichloroethylene to ethylene under methogenic conditions Appl Environ Microbiol 55 416 420
GenBank 2002. GenBank . Bethesda, MD:National Center for Biotechnology Information, National Library of Medicine. Available: http://www.ncbi.nlm.nih.gov/Genbank/index.html [accessed 15 October 2002].
Gibson SA Sewell GW 1992 Stimulation of reductive dechlorination of tetrachloroethene in anaerobic aquifer microcosms by addition of short-chain organic acids or alcohols Appl Environ Microbiol 58 1392 1393 16348703
Helton RR 2000. Assessment of the Microbial Communities Derived from Two Tetrachloroethene (PCE)-Contaminated Aquifers [Master’s Thesis]. Lansing, MI:Michigan State University.
Henry SM Grbić-Galić D 1990 Effect of mineral media on trichloroethylene oxidation by aquifer methanotrophs Microb Ecol 20 151 169 24193971
Holben WE 1994. Isolation and purification of bacterial DNA from soil. In: Methods of Soil Analysis, Part 2. Microbiological and Biochemical Properties (Weaver RW, Angle S, Bottomley P, Bezdicek D, Smith S, Tabatabai A, Wollum A, eds). Madison, WI:Soil Science of America, Inc.
Imhoff PT Gleyzer SN McBride JF Vancho LA Okuda I Miller CT 1995 Co-solvent enhanced remediation of residual dense nonaqueous phase liquids: experimental investigation Environ Sci Technol 29 8 1966 1976 22191343
Jawitz JW Sillan RK Annable MD Rao PSC Warner K 2000 In-situ alcohol flushing of a DNAPL source zone at a dry cleaner site Environ Sci Technol 34 17 3722 3729
Lake LW 1989. Enhanced Oil Recovery. Englewood Cliffs, NJ: Prentice Hall.
Lane DJ 1991. 16S/23S rRNA sequencing. In: Nucleic Acid Techniques in Bacterial Systematics (Stackebrandt E, Goodfellow M, eds). New York:John Wiley & Sons, Inc., 115–175.
Levine-Fricke-Recon, Inc. 1998. Pilot Test Work Plan Former Sages Dry Cleaner. Internal report prepared for Florida Department of Environmental Protection, Tallahassee, FL, 9 February 1998.
Lindner AS Adriaens P Semrau JD 2000 Transformation of ortho -substituted biphenyls by Methylosinus trichosporium OB3b: substituent effects on oxidation kinetics and product formation Arch Microbiol 174 35 41 10985740
McCray JE Brusseau ML 1998 Cyclodextrin-enhanced in situ flushing of multiple component immiscible organic liquid contamination at the field scale: mass removal effectiveness Environ Sci Technol 32 1285 1293
McDonald IR Kenna EM Murrell JC 1995 Detection of methanotrophic bacteria in environmental samples with the PCR Appl Environ Microbiol 61 116 121 7887594
McDonald IR Murrell JC 1997 The methanol dehydrogenase structure gene mxaF and its use as a functional gene probe for methanotrophs and methylotrophs Appl Environ Microbiol 63 3218 3224 9251208
Miller DN Bryant JE Madsen EL Ghiorse WC 1999 Evaluation and optimization of DNA extraction and purification procedures for soil and sediment samples Appl Environ Microbiol 65 4715 4724 10543776
Mravik SC Sewell GW Sillan RK Wood AL 2003 Field evaluation of the solvent extraction residual biotreatment (SERB) technology Environ Sci Technol 37 21 5040 5049 14620836
Nagpal S Chuichulcherm S Livingston A Peeva L 2000 Ethanol utilization by sulfate-reducing bacteria: an experimental and modeling study Biotechnol Bioeng 70 533 543 11042550
Ogram A 1997. Purification of nucleic acids from environmental matrices. In: Techniques in Environmental Microbiology (Burlage RS, ed). Oxford, UK:Oxford Press.
Ogram A Sayler GS Barkay T 1987 The extraction and purification of microbial DNA from sediments J Microbiol Methods 7 57 66
Oldenhuis R Janssen DB 1993. Degradation of trichloroethylene by methanotrophic bacteria. In: Microbial Growth on C1 Compounds (Murrell JC, Kelly DP, eds). Andover, UK:Intercept Press, Ltd.
Oldenhuis R Oedzes JY Van der Waarde JJ Janssen DB 1991 Kinetics of chlorinated hydrocarbon degradation by Methylosinus trichosporium OB3b and toxicity of trichloroethylene Appl Environ Microbiol 55 2819 2826 2624462
Ramakrishnan V 2002. Community Changes and Revival of Indigenous Microorganisms after Co-solvent Flushing [Master’s Thesis]. Gainesville, FL:University of Florida.
Rao PSC Annable MD Sillan RK Dai D Hatfield K Graham WD 1997 Field-scale evaluation of in-situ co-solvent flushing for enhanced aquifer remediation Water Resour Res 33 2673 2686
Sambrook J Fritsch EF Maniatis T 1989. Molecular Cloning: A Laboratory Manual. 2nd ed. Cold Spring Harbor, NY:Cold Spring Harbor Laboratory Press.
Sillan RK 1999. Field-Scale Evaluation of In Situ Co-solvent Flushing for Enhanced Aquifer Remediation [PhD Dissertation]. Gainesville, FL:University of Florida.
Turley CM 1993. Direct estimates of bacterial numbers in sea-water samples without incurring cell loss due to sample storage. In: Handbook of Methods in Aquatic Microbial Ecology (Kemp PF, Sherr B, Cole JJ, eds). Boca Raton, FL:Lewis Publishers, 143–147.
U.S. EPA (U.S. Environmental Protection Agency) 2000. Groundwater Currents, Issue No. 36, EPA 542-N-00-004. Washington, DC:U.S. Environmental Protection Agency.
U.S. EPA 2002. Cleanup Tools. Office of Emergency and Remedial Response. Available: http://www.epa.gov/super-fund [accessed 16 July 2003].
Wagner M Roger AJ Flax JL Brusseau GA Stahl DA 1998 Phylogeny of dissimilatory sulfite reductases supports an early origin of sulfate respiration J Bacteriol 180 2975 2982 9603890
Whittenbury R Phillips KC Wilkinson JF 1970 Enrichment, isolation, and some properties of methane-utilizing bacteria J Gen Microbiol 61 205 218 5476891
Widdel F Bak F. 1992. Gram-negative mesophilic sulfate-reducing bacteria. In: The Prokaryotes (Balows A, Truper HG, Dworkin M, Harder W, Schleifer K-H, eds). New York:Springer-Verlag, 3352–3378.
Wise MG McArthur JV Shimkets LJ 1999 Methanotroph diversity in landfill soil: isolation of novel Type I and Type II methanotrophs whose presence was suggested by culture-independent 16S ribosomal DNA analysis Appl Environ Microbiol 65 4887 4897 10543800
Zhou J Bruns MA Tiedje JM 1996 DNA recovery from soils of diverse composition Appl Environ Microbiol 62 316 322 8593035
|
15626648
|
PMC1253710
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan 8; 113(1):55-61
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.6937
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.6940ehp0113-00006215626649ResearchArticlesMetabolic Biomarkers for Monitoring in Situ Anaerobic Hydrocarbon Degradation Young Lily Y. Phelps Craig D. Biotechnology Center for Agriculture and the Environment, Cook College, Rutgers, The State University of New Jersey, New Brunswick, New Jersey, USAAddress correspondence to C.D. Phelps, Biotechnology Center for Agriculture and the Environment, 59 Dudley Rd., Foran Hall, Cook College, Rutgers, The State University of New Jersey, New Brunswick, NJ 08901 USA. Telephone: (732) 932-8165, ext. 314. Fax: (732) 932-0312. E-mail:
[email protected] thank J. Battistelli, P. Ceraulo, P. Evans, C-M. So, J. Weiss, and X. Zhang for their contributions to this work.
Research was supported by grants from the Office of Naval Research, the Defense Advanced Research Projects Agency, and the National Science Foundation.
The authors declare they have no competing financial interests.
This article is based on a presentation at the conference “Bioremediation and Biodegradation: Current Advances in Reducing Toxicity, Exposure and Environmental Consequences” (http://www-apps.niehs.nih.gov/sbrp/bioremediation.html) held 9–12 June 2002 in Pacific Grove, California, and sponsored by the National Institute of Environmental Health Sciences (NIEHS) Superfund Basic Research Program. The overall focus of this conference was on exploring the research interfaces of toxicity reduction, exposure assessment, and evaluation of environmental consequences in the context of using state-of-the-art approaches to bioremediation and biodegradation. The Superfund Basic Research Program has a legacy of supporting research conferences designed to integrate the broad spectrum of disciplines related to hazardous substances.
1 2005 8 12 2004 113 1 62 67 30 12 2003 19 5 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. During the past 15 years researchers have made great strides in understanding the metabolism of hydrocarbons by anaerobic bacteria. Organisms capable of utilizing benzene, toluene, ethylbenzene, xylenes, alkanes, and polycyclic aromatic hydrocarbons have been isolated and described. In addition, the mechanisms of degradation for these compounds have been elucidated. This basic research has led to the development of methods for detecting in situ biodegradation of petroleum-related pollutants in anoxic groundwater. Knowledge of the metabolic pathways used by anaerobic bacteria to break down hydrocarbons has allowed us to identify unique intermediate compounds that can be used as biomarkers for in situ activity. One of these unique intermediates is 2-methylbenzylsuccinate, the product of fumarate addition to o-xylene by the enzyme responsible for toluene utilization. We have carried out laboratory studies to show that this compound can be used as a reliable indicator of anaerobic toluene degradation. Field studies confirmed that the biomarker is detectable in field samples and its distribution corresponds to areas where active biodegradation is predicted. For naphthalene, three biomarkers were identified [2-naphthoic acid (2-NA), tetrahydro-2-NA, and hexahydro-2-NA] that can be used in the field to identify areas of active in situ degradation.
anaerobicbiomarkerbioremediationhydrocarbonsnaphthalenepetroleumtoluene
==== Body
In this article we illustrate how research in our laboratory and others over the past 10–15 years has advanced our knowledge of hydrocarbons and their degradation under anaerobic conditions. We hope to make the case that this field is mature enough at this point for us to begin applying some of our knowledge to field sites. Our understanding of specific degradation pathways should allow us to develop strategies to intelligently encourage degradation and monitor the progress of in situ activity.
Regarding the fate of hydrocarbons in the environment, we know that if contaminants such as polycyclic aromatic hydrocarbons (PAHs) and benzene, toluene, ethylbenzene, and xylenes (BTEXs) are not degraded aerobically, they are likely to be transported into anaerobic regions. This occurs in soils during compaction, in sediments in the marine environment, and in freshwater environments during partition and sedimentation. The question is, what happens to these contaminants in these anaerobic environments? From the results of studies that have been conducted for decades, we understand very well the aerobic fate of these kinds of compounds. Much information is available. We know that the molecules have to be activated by oxygenases (monooxygenases and dioxygenases), and molecular oxygen has to participate in these reactions (Atlas and Bartha 1992). Therefore, there must be different mechanisms for anaerobic organisms. Fortunately, we recently have been able to learn much about these mechanisms. In this article, we review the work that has occurred in the last 10 years, which makes it clear that we know enough to begin applying this information for practical purposes.
Benzene, Toluene, Ethylbenzene, and Xylenes
Many researchers have demonstrated the anaerobic metabolism of BTEXs (for reviews see Hieder et al. 1999; Phelps and Young 2001). In one such study we conducted a series of screenings of BTEX degradation in different sediments and under different anaerobic conditions (Phelps and Young 1999). The results showed that degradation can be demonstrated for all the BTEX compounds to different degrees under the different anaerobic conditions. All the tested compounds were degraded relatively quickly (loss within 21 days). In addition the profiles of contaminant loss were different between a polluted site (Arthur Kill, New York) and clean site (Tuckerton, New Jersey) and between the estuarine Arthur Kill and freshwater Onondaga Lake (New York). Results such as these emphasize the importance of the prevailing local conditions to BTEX degradation.
Another conclusion from this study is that toluene can be degraded relatively quickly under many reducing conditions (Phelps and Young 1999). This can explain why toluene was the first model compound for anaerobic hydrocarbon degradation and why we know so much about its degradation. In one early study, Evans et al. (1991a, 1991b, 1992a, 1992b) examined toluene degradation under denitrifying conditions. This resulted in isolation of the Thauera sp. strain T1 (Evans et al. 1991b), which was one of the first organisms reported that can degrade toluene under anaerobic (denitrifying) conditions. Evans et al. (1991a, 1992a) showed that the toluene could be quantitatively converted to carbon dioxide and cells and that the nitrate was reduced to nitrogen gas. One of their observations that was key in our understanding of BTEX degradation is that when a mass balance for both the nitrogen and the carbon was calculated, the carbon balance did not close completely. The missing carbon was not in the cells, it was not in CO2, and it was not left in the substrate. Eventually they determined that it resided in a metabolite, which they then identified as benzylsuccinate, and in variations of benzylsuccinic acid (Evans et al. 1992b). At that time we believed that these were dead-end products and their presence closed the mass balance on the carbon. Since then, Biegert et al. (1996) and other researchers have been able to show that benzylsuccinate is actually a key intermediate in the degradation of toluene. It is formed through a fumarate (4-carbon) addition to the methyl carbon of toluene that activates the molecule. The product of this addition undergoes a series of reactions to produce benzoyl-coenzyme-A (CoA) that then undergoes ring fission and degradation (Figure 1). The discovery of this mechanism was key because the 4-carbon addition turns out to be one of the central reactions in several different pathways for degradation of these and other reduced hydrocarbon compounds.
Polycyclic Aromatic Hydrocarbons
More recently, researchers have begun to examine the fate of PAHs under anoxic conditions (Coates et al. 1997; Sharak Genthner et al. 1997). In our laboratory Zhang investigated whether PAHs could be degraded under various specific anaerobic conditions using sediment from the Arthur Kill. He was able to show naphthalene, 2-methylnaphthalene, and phenanthrene were degraded under sulfidogenic conditions but not under the other reducing conditions. This initial study demonstrated loss of the parent compounds but not how they are broken down. Zhang and Young (1997) then showed, using 14 C-labeled substrate, that from 86 to 92% of that carbon is converted to CO2, hence the molecule was being completely mineralized and not merely transformed. They were also able to show that the activity was sulfate dependent. In the presence of SO=4, naphthalene degradation can occur after 20 hr, whereas in the absence of SO=4, there is no naphthalene loss. In autoclaved samples there is also no loss. In addition, molybdate, a specific inhibitor of sulfate respiration (Oremland and Capone 1988), prevented the degradation of the hydrocarbon (Zhang and Young 1997). All of this was demonstrated in an enriched consortium, so although it was clear that the activity was sulfate dependent, there was no information about which organism was responsible for the activity.
It is because this consortium of organisms has resisted our attempts to isolate a pure culture capable of metabolizing PAHs that we have had to find alternate ways of working out the degradation mechanisms. Zhang and Young followed an approach of looking for metabolites using gas chromatography-mass spectrometry (GC-MS) analysis. Key to the study of these kinds of consortia was the use of stable isotope–labeled substrates. The label allowed us to conclusively determine that the compounds detected in the culture media were derived from the added substrate. Zhang and Young performed a number of experiments where 2H (deuterated) substrate was added to the various cultures. These experiments were used to prove that 2H-2-naphthoic acid (2-NA) was produced during metabolism of 2H-naphthalene (Zhang and Young 1997).
Although naphthalene conversion to 2-NA was demonstrated in these experiments using deuterated substrates, the mechanism of carboxylation was still unknown. To determine the source of the carboxyl group, Zhang et al. (2000) added either 13C-labeled or unlabeled carbon sources, then looked for the label in the mass spectrum of the resulting 2-NA. When 13C-labeled bicarbonate was added, the carboxyl group was labeled 13C. This approach was extremely useful in a whole series of experiments. By looking for 13C-labeled compounds in cultures amended with 13C bicarbonate, Zhang et al. identified a sequence of metabolites during the degradation process. We then put together this sequence of metabolites into a pathway for naphthalene degradation (Figure 2) (Zhang et al. 2000; Zhang and Young 1997). In this pathway the naphthalene is carboxylated to 2-NA followed by a series of reduction steps where hydrogen is added to the unsubstituted ring first and then to the ring with the carboxyl group. This process produces a fully saturated decalin-2-carboxylic acid, which then gets further metabolized to CO2. Mineralization was demonstrated with the quantitative recovery of 14CO2 from cultures fed 14C-labeled naphthalene (Zhang and Young 1997).
Using these stable isotope techniques, we were able to work out the fate of 2-methylnaphthalene and phenanthrene in addition to naphthalene (Figure 2) (Sullivan et al. 2001; Zhang and Young 1997). We showed that 2-methylnaphthalene was also oxidized to 2-NA and that the methyl carbon remained on the ring; hence, an external carboxylation did not occur. The resulting carboxylic acid then underwent the same degradation sequence to CO2 as observed with naphthalene (Sullivan et al. 2001). Phenanthrene was also carboxylated via the addition of an external bicarbonate molecule. We were not able to confirm the position of this addition because no standards were available (Zhang and Young 1997).
All these experiments were carried out with consortia. Since then, others have confirmed the carboxylation pathway (Annweiler et al. 2002; Meckenstock et al. 2000). In addition, a pure culture that carries out naphthalene degradation in this manner has been isolated (Galushko et al. 1999). Hence, there is increasing evidence that these pathways and mechanisms may be widely distributed in the environment.
Alkanes
While the PAH degradation mechanisms were being studied, a graduate student in our laboratory was investigating alkane degradation. He was able to isolate an alkane-degrading sulfate reducer that we named strain AK-01 (So and Young 1999b). It is related to strain HXD-3, which is another alkane-degrading sulfate reducer (Rueter et al. 1994). Both strains fall within the same subgroup of delta Proteobacteria. They are both gram-negative, nonmotile sulfate reducers, and they both have very long generation times on the order of several days. However, although they are closely related, they have very different methods of attack on the alkane molecule.
Through a long series of experiments using 13C-labeled substrate, So was able to show how hexadecane is anaerobically metabolized by both AK-01 and HXD-3 (So et al. 2003; So and Young 1999a). In AK-01, there is an attack on the subterminal carbon (Figure 3). There is a carbon donor that we could not identify. (Experiments with 13C showed that inorganic bicarbonate was not the donor as in the PAHs.) The attack at the C-2 position results in the addition of a carboxyl group and the terminal carbon is displaced to become a methyl group on the subterminal carbon. This was followed by using substrate with a 13C label in the C-1 or C-2 position, then analyzing the fatty acids of the cell to determine the position of the label. We showed that the fatty acids in the cells fed hexadecane have a methyl group in the C-2, the C-4, or the C-6 position. The methyl group gets “moved” along the carbon chain by two-carbon additions. Alternatively, the C-1 and C-2 positions can be removed through β-oxidation, and then these two carbons are lost (So and Young 1999a).
In strain HXD-3 a very different mechanism is used. This strain attacks the C-3 carbon of the alkane, then removes the two terminal carbons (Figure 4) (So et al. 2003). Most interestingly, we have shown that the initial attack involves the addition of an external bicarbonate molecule. This was demonstrated using the same stable isotope label techniques as we used to discern the naphthalene degradation mechanism. The resulting fatty acid can then undergo β-oxidation, fatty-acid transformation, or 2-C additions to make larger fatty acids. Thus, we have two different mechanisms of attack on these alkanes by two different but related sulfate reducers.
A recent discovery adds an interesting element to these investigations. It has now been shown that an enriched consortium that grows on dodecane under sulfate-reducing conditions carries out a 4-C/fumarate addition to the C-2 carbon of that alkane (Kropp et al. 2000). On the basis of this finding, it appears that in our hexadecane degrader, AK-01, the carbon donor that we could not identify was actually fumarate, the same mechanism that Evans et al. (1992b) recognized in toluene 10 years ago. In addition, Annweiler et al. (2000) were able to show that the reaction responsible for oxidizing the methyl group of 2-methylnaphthalene to form 2-NA is also a fumarate addition. The mechanism is highly analogous to that which occurs in toluene because of the position of the methyl group on an aromatic ring. What is emerging is a mechanism that appears to be used by a wide range of anaerobic bacteria to activate several very-reduced hydrocarbon compounds that they could not otherwise utilize.
Summary
There are several methods of attack on hydrocarbon substrates such as toluene, alkanes, and PAHs by anaerobic bacteria. Two of these appear to have very broad specificity to both aliphatic and aromatic hydrocarbons. One method is carboxylation with inorganic carbon. We have demonstrated this mechanism of attack on alkanes, naphthalene, and phenanthrene (So et al. 2003; Zhang and Young 1997). The other method is fumarate addition, seen in toluene, xylenes, methylnaphthalene, and alkane degradation (Annweiler et al. 2000; Beller and Edwards 2000; Beller and Spormann 1997a, 1997b; Evans et al. 1992b; Krieger et al. 1999; So and Young 1999a). These reactions are mediated by anaerobes that are widely different both physiologically and phylogenetically. They have been seen in denitrifyers, sulfate reducers, iron reducers, phototrophs, and methanogenic consortia (Beller and Edwards 2000; Beller et al. 1992, 1996; Rabus and Widdel 1995; Seyfried et al. 1994; Zengler et al. 1999).
All these observations indicate several fundamental mechanisms underpinning anaerobic hydrocarbon degradation. The implications are widespread. An understanding of the basic mechanisms can obviously help us understand processes such as global carbon turnover and biogeochemical processes and provides insight into environmental remediation. The remainder of this article focuses on how we have used this information to develop applications and potential applications for in situ biodegradation.
Biomarkers
For demonstrating in situ biodegradation, a National Academy of Sciences (NAS) report in 1993 (NAS 1993) indicated that certain criteria must be met. These criteria include a) documenting loss of contaminants from the site, b) demonstrating that onsite microbes can transform the contaminant, and c) showing that the biodegradation potential is realized in the field. We are interested in using metabolic biomarkers as a means of meeting this third criterion.
An ideal metabolic biomarker should be a) formed during active biodegradation of the target compound, b) specific to the process being monitored, c) normally absent in unimpacted environments; d) water soluble for ease of sampling, and e) biodegradable. This last criterion may seem counterintuitive from a standpoint of being able to detect the biomarker, but it ensures that the activity being detected is current. If the metabolite is not biodegradable, it is impossible to tell if the activity happened 2 weeks ago or 20 years ago.
Benzene, Toluene, Ethylbenzene, and Xylene Biomarkers
A convenient aspect of studying in situ toluene degradation is that the benzylsuccinate synthase (fumarate addition) pathway is widely distributed. It has been found in denitrifyers, sulfidogens, iron reducers, methanogenic consortia, and even an anoxygenic photosynthetic organism (Beller and Edwards 2000; Beller et al. 1992, 1996; Rabus and Widdel 1995; Seyfried et al. 1994; Zengler et al. 1999). The pathway is well distributed in the environment; therefore, the intermediates can be used as biomarkers under a variety of conditions. Indeed, in 1995 Beller et al. (1995) published an article in which they specifically suggested that the by products of alkylbenzene metabolism could be useful as indicators of in situ bioremediation. They showed that toluene and all xylenes have benzylsuccinate-like metabolites and that these can be used as indicators that metabolism is occurring in situ. Their demonstration involved making a single bolus injection of BTEXs at the experimental site at Seal Beach, California, and following the loss of the parent compounds and the transient presence of the corresponding fumarate addition products.
We were interested in following this to determine if the same methods could be used to detect ongoing activity at older sites such as abandoned manufactured gas plants (MGPs) common in New Jersey. Rather than search for all the potential toluene and xylene metabolites, we concentrated on measuring the occurrence of 2-methylbenzyl-succinate (2-MBS) because laboratory studies indicated that this isomer accumulated in higher concentrations than the others. Initially, laboratory studies used sediments from Onondaga Lake, which is a freshwater superfund site in Syracuse, New York; Pile’s Creek, a polluted tributary of the Arthur Kill; and Blue Mountain Lake, a nearly pristine lake in the Adirondack Mountains of New York. The results of these experiments showed that in the two polluted sediments where toluene loss was complete, o-xylene concentrations declined and 2-MBS was transiently formed. This pattern was consistent with 2-MBS being produced co-metabolically from o-xylene during toluene degradation, then being degraded by other organisms in the sediment. No activity was seen in the Blue Mountain Lake sediment, suggesting that the relevant organisms were not present.
Field Tests
Site characteristics.
The site chosen for examining 2-MBS as an in situ biomarker is located in Glassboro, New Jersey. The contamination present in the groundwater is the result of waste disposal at an abandoned MGP that operated for over 40 years prior to 1951. In the 1980s, all surface and subsurface structures were removed during remediation of the unsaturated soil. The contaminant plume originating from the MGP extends northward from the source through a residential area. Pollutants present include BTEX, PAHs, styrene, phthalates, ethers, and chlorinated solvents.
A great deal of heterogeneity is present in the size of particles in the upper 70 ft of sediment, ranging from gravel to clay. Therefore, the flow of water through this site is expected to be far from uniform. Another result of this heterogeneity is that measurements of the groundwater showed only a general spatial trend toward anoxia, lower redox potential, and increased anaerobic activity in the downgradient direction. It is likely that individual flow paths and areas within the plume are much more reduced and therefore anaerobic. Ion data from individual wells in different parts of the plume did indeed show that, in the area directly downgradient of the contamination, nitrate and sulfate have been depleted and iron has been solubilized, indicating anaerobiosis.
Sampling.
Six monitoring wells were chosen for sampling. Two (MW-12 and MW-24) are located within 500 ft of the contaminant source and had measurable amounts of toluene present in the groundwater. Another two of the wells (MW-42 and MW-44) are approximately 4,000 ft downgradient of the source and had no detectable toluene present. One well (MW-47) is located far downgradient from the source and contains some toluene, likely from off-site contamination. The sixth well (MW-25) is located outside the plume area (Figure 5).
Four liters of groundwater were drawn from each sampling site and acidified to a pH < 2 with concentrated hydrochloric acid on site. The samples were stored in precleaned amber glass bottles at 4°C until analysis.
Extraction and analysis.
A 1-L sample of the acidified groundwater was extracted three times with 200 mL anhydrous diethyl ether. The pooled ether was concentrated under vacuum and passed through anhydrous sodium sulfate to remove any residual water. The remaining solvent was dried under a stream of argon gas. This dry extract was derivatized with bis(trimethylsilyl)trifluoroacetamide (BSTFA; Sigma Chemical Co., St. Louis, MO) according to the manufacturer’s instructions. The derivatized extracts were analyzed by injection into a Hewlett-Packard 5890 series II gas chromatograph coupled to a series 591 mass selective detector (Hewlett-Packard, Wilmington, DE). The column was a J&W Scientific DB-5MS that measured 30 m × 0.25 mm (inner diameter) with a film thickness of 0.25 μm (VWR International, West Chester, PA). 2-MBS was quantified by the area of the 351 ion peak, which represents a derivatized fragment. Benzylsuccinate spiked into groundwater could be measured at concentrations as low as 5 nM. We assume that the recovery of the 2-MBS would be similar.
Results.
As illustrated in Figure 5, the biomarker 2-MBS was detected in two (MW-12 and MW-24) of the six monitoring wells tested. Both these wells were immediately downgradient from, and closest to, the contaminant source. The abundance of 2-MBS in well MW-24 was approximately 6 times that of well MW-12. This is consistent with the observation that toluene concentrations were also much higher in that well (200 ppb vs. 8 ppb). No 2-MBS was found in wells far downgradient (MW-42, MW-44, and MW-47) or in the well outside the plume (MW-25).
Because toluene is more easily biodegraded than the PAHs that make up the majority of the hydrocarbons present at the MGP site, it is not surprising that it is found only near the source of the plume. We would expect that the toluene and xylenes would be consumed soon after leaving the MGP site. These expectations match very well with the distribution of both toluene and 2-MBS in the plume.
Naphthalene Biomarkers
Sampling and analysis.
We examined the same MGP site for evidence of PAH degradation. Samples were taken in the same manner as for the toluene metabolite study. The map in Figure 6 shows the naphthalene concentrations that range from 1,400 ppb at the source to nondetectable far downgradient.
We first showed that it is possible to reliably identify the initial intermediate 2-NA from a groundwater matrix at exceedingly low concentrations using a modification of U.S. EPA method 3510C (U.S. EPA 2000). One liter of acidified water was extracted 3 times with 60 mL methylene chloride. The pooled solvent was concentrated under vacuum and passed through a column packed with sodium sulfate to remove any residual water. After drying under a stream of argon, the samples were dissolved in 100 μL methylene chloride and derivatized with BSTFA following the manufacturer’s instructions. Derivatized samples were analyzed on a Hewlett-Packard 5890 series II gas chromatograph in the same configuration used for toluene biomarkers. The temperature program was capable of separating each of the proposed biomarkers.
Identification of 2-NA was based on GC retention time and comparison of the mass spectral pattern to the spectra of an authentic standard. 2-NA can be quantified with a detection limit as low as 2 μg/L from groundwater.
Results.
The data show a correlation between naphthalene and 2-NA concentrations (Figure 6). 2-NA is most abundant close to the contamination source and decreases with distance. However, it extends farther than the range of detectable naphthalene, which is expected because it is more water soluble.
Another, much smaller site that we examined is the South Jersey Gas Maintenance Yard (SJGMY) (Phelps et al. 2002). This is the site of an underground gasoline storage tank leak that is much more recent than the contamination at the MGP site. At this site we were able to detect metabolites in addition to 2-NA. The mass spectra of tetrahydro-2-NA (TH-2-NA), hexahydro-2-NA (HH-2-NA), and methylnaphthoic acid (MNA) were identified in samples from this site. High concentrations of all the biomarkers are found in the wells closest to the source of contamination, with much lower concentrations as we go farther downgradient.
To summarize, at the MGP site the highest concentration of 2-NA was found at the wells with high levels of naphthalene contamination, and the concentration declined with distance from the source. Levels of 2-NA were very low far downgradient. At the SJGMY site, which is a newer site, we saw 2-NA, TH-2-NA, HH-2-NA, and MNA detected in wells contaminated with naphthalene. Lower concentrations were seen at nearby wells, but none were found outside the plume (Phelps et al. 2002). The presence of all four metabolites collectively in the naphthalene-impacted wells is evidence that the anaerobic microbial activity is present in these anoxic groundwaters. Although the presence of one compound may not be convincing, we believe that because all four compounds appear and follow the same pattern, there is indeed in situ activity.
Conclusions
The laboratory studies of the past 4 years have provided fundamental information on anaerobic biodegradation pathways for reduced hydrocarbon compounds such as BTEXs, PAHs, and alkanes. These pathways include a series of metabolites unique to the anaerobic degradation of these hydrocarbons. Because they are specific and identifiable with these anaerobic processes, the metabolites can be used to assess the in situ biodegradation of these contaminants in anoxic subsurface or perhaps sediment environments. Field samples from several sites show their presence and support the conclusion that microbial degradation of hydrocarbons is actively taking place in these anoxic environments.
Figure 1 Toluene degradation pathway. The initial reaction of anaerobic toluene degradation involves the addition of fumarate to the methyl group. The resulting benzylsuccinate is activated with CoA, after which it is reduced to phenylitaconyl-CoA. This intermediate then undergoes a series of reactions analogous to β-oxidation to benzozyl-CoA. Figure adapted from Biegert et al. (1996).
Figure 2 Summary pathways for naphthalene, 2-methylnaphthalene, and phenanthrene. Both naphthalene and 2-methylnaphthalene are initially converted to 2-NA. Naphthalene is transformed by a direct addition of CO2, whereas 2-methylnaphtha-lene undergoes a fumarate addition analogous to that seen in toluene. The common intermediate, 2-NA, is further degraded by sequential ring-reduction steps to decahydro-2-NA before ring cleavage takes place. Phenanthrene is also directly carboxylated as the initial step toward mineralization.
Figure 3 Proposed pathway for anaerobic alkane metabolism by strain AK-01. The terminal methyl group of the alkane substrate is set in bold type to help demonstrate the reaction mechanism. In strain AK-01, alkanes are degraded via an initial attack at the second carbon, resulting in the formation of a carboxylic acid with a subterminal methyl group. The initial attack is presumed to involve fumarate addition. Once the fatty acid is formed, it may be degraded through a number of β-oxidation steps, or it may be incorporated into the cell membrane (So and Young 1999a).
Figure 4 Proposed pathway for the oxidation of alkane to fatty acid by strain HXD-3. The added carboxyl groups are shown in bold type to help demonstrate the reaction mechanism. The mechanism for alkane degradation in strain HXD-3 begins with the addition of CO2 to the third carbon of the chain followed by the loss of the two terminal carbons. This results in formation of a fatty acid one carbon shorter than the original alkane. The first intermediate shown in this pathway is hypothetical (So et al. 2003).
Figure 5 Distribution of 2-MBS in the contaminant plume at the MGP site. (A) Diagram of the contaminated site. The MPG, which is the source of contamination, is located at the left; the general direction of ground-water flow is indicated by the arrow. Approximate distances from the MGP site are indicated by the arcs at 100, 500, 1,000, and 5,000 ft. Roads are indicated as parallel lines. Each sample well is shown with the concentration of toluene found at that position at an earlier time. (B) graph showing the abundance of 2-MBS at each well. The abundance is expressed as the area of the 351 mass peak from the chromatogram.
Figure 6 Distribution of 2-NA in the contaminant plume at the MGP site. (A) Diagram of the contaminated site. The MGP, which is the source of contamination, is located at the left; the general direction of ground-water flow is indicated by the arrow. Approximate distances from the MGP site are indicated by the arcs at 100, 500, 1,000, 2,000, and 5,000 ft. Roads are indicated as parallel lines. Each of the sample wells is shown with the concentration of naphthalene found at that position at an earlier time. (B) Graph showing the abundance of 2-NA at each well.
==== Refs
References
Annweiler E Materna A Safinowski M Kappler A Richnow HH Michaelis W 2000 Anaerobic degradation of 2-methylnaphthalene by a sulfate-reducing enrichment culture Appl Environ Microbiol 66 5329 5333 11097910
Annweiler E Michaelis W Meckenstock RU 2002 Identical ring cleavage products during anaerobic degradation of naphthalene, 2-methylnaphthalene, and tetralin indicate a new metabolic pathway Appl Environ Microbiol 68 2 852 858 11823228
Atlas R Bartha R 1992. Hydrocarbon biodegradation and oil spill bioremediation. In: Advances in Microbial Ecology, Vol 12 (Marshall KC, ed). New York:Plenum Press, 287–338.
Beller HR Ding WH Reinhard M 1995 Byproducts of anaerobic alkylbenzene metabolism useful as indicators of in situ bioremediation Environ Sci Technol 29 2864 2869 22206536
Beller HR Edwards EA 2000 Anaerobic toluene activation by benzylsuccinate synthase in a highly enriched methanogenic culture Appl Environ Microbiol 66 5503 5505 11097937
Beller HR Reinhard M Grbic-Galic D 1992 Metabolic by-products of anaerobic toluene degradation by sulfate-reducing enrichment cultures Appl Environ Microbiol 58 3192 3195 1444436
Beller HR Spormann AM 1997a Anaerobic activation of toluene and o -xylene by addition to fumarate in denitrifying strain T J Bacteriol 179 670 676 9006019
Beller HR Spormann AM 1997b Benzylsuccinate formation as a means of anaerobic toluene activation by sulfate-reducing strain PRTOL1 Appl Environ Microbiol 63 3729 3731 16535701
Beller HR Spormann AM Sharma PK Cole JR Reinhard M 1996 Isolation and characterization of a novel toluene-degrading, sulfate-reducing bacterium Appl Environ Microbiol 62 1188 1196 8919780
Biegert T Fuchs G Heider J 1996 Evidence that anaerobic oxidation of toluene in the denitrifying bacterium Thauera aromatica is initiated by formation of benzylsuccinate from toluene and fumarate Eur J Biochem 283 661 668 8706665
Coates JD Woodward J Allen J Philip P Lovley DL 1997 Anaerobic degradation of polycyclic aromatic hydrocarbons and alkanes in petroleum-contaminated marine harbor sediments Appl Environ Microbiol 63 3589 3593 9341091
Evans PJ Ling W Goldschmidt B Ritter ER Young LY 1992b Metabolites formed during anaerobic transformation of toluene and o -xylene and their proposed relationship to the initial steps of toluene mineralization Appl Environ Microbiol 58 496 501 1610173
Evans PJ Ling W Palleroni NJ Young LY 1992a Quantification of denitrification by strain T1 during anaerobic degradation of toluene Appl Microbiol Biotechnol 37 136 140 1368498
Evans PJ Mang DT Kim KS Young LY 1991b Anaerobic degradation of toluene by a denitrifying bacterium Appl Environ Microbiol 57 1139 1145 2059037
Evans PJ Mang DT Young LY 1991a Degradation of toluene and m -xylene and transformation of o -xylene by denitrifying enrichment cultures Appl Environ Microbiol 57 450 454 2014990
Galushko A Minz D Schink B Widdel F 1999 Anaerobic degradation of naphthalene by a pure culture of a novel type of marine sulphate-reducing bacterium Environ Microbiol 1 5 415 420 11207761
Heider J Spormann AM Beller HR Widdel F 1999 Anaerobic bacterial metabolism of hydrocarbons FEMS Microbiol Rev 22 459 473
Krieger CJ Beller HR Reinhard M Spormann AM 1999 Initial reactions in anaerobic oxidation of m -xylene by the denitrifying bacterium Azoarcus sp. strain T J Bacteriol 181 6403 6410 10515931
Kropp KG Davidova IA Suflita JM 2000 Anaerobic oxidation of n -dodecane by an addition reaction in a sulfate-reducing bacterial enrichment culture Appl Environ Microbiol 66 5393 5398 11097919
Meckenstock RU Annweiler E Michaelis W Richnow HH Schink B 2000 Anaerobic naphthalene degradation by a sulfate-reducing enrichment culture Appl Environ Microbiol 66 7 2743 2747 10877763
NAS (National Academy of Sciences) 1993. In Situ Bioremediation: When Does It Work? Washington, DC: National Academy Press.
Oremland R Capone D 1988 Use of specific inhibitors in bio-geochemistry and microbial ecology Adv Microb Ecol 10 285 383
Phelps CD Batistelli J Young LY 2002 Metabolic biomarkers for monitoring anaerobic naphthalene biodegradation in situ Environ Microbiol 4 532 537 12220410
Phelps CD Young LY 1999 Anaerobic biodegradation of BTEX and gasoline in various aquatic sediments Biodegradation 10 15 25 10423837
Phelps CD Young LY 2001. Biodegradation of BTEX under anaerobic conditions: a review. In: Advances in Agronomy, Vol 70 (Sparks D, ed). San Diego, CA:Academic Press, 329–357.
Rabus R Widdel F 1995 Conversion studies with substrate analogues of toluene in a sulfate-reducing bacterium, strain Tol2 Arch Microbiol 164 448 451 8588748
Rueter P Rabus R Wilkes H Aekersberg F Rainey FA Jannasch HW 1994 Anaerobic oxidation of hydrocarbons in crude oil by new types of sulphate-reducing bacteria Nature 372 455 458 7984238
Seyfried B Glod G Schocher R Tschech A Zeyer J 1994 Initial reactions in the anaerobic oxidation of toluene and m -xylene by denitrifying bacteria Appl Environ Microbiol 60 4047 4052 7993091
Sharak Genthner BR Townsend GT Lantz SE Meuller JG 1997 Persistence of polycyclic aromatic hydrocarbon components of creosote under anaerobic enrichment conditions Arch Environ Contam Toxicol 32 99 105 9002440
So CM Phelps CD Young LY 2003 Anaerobic transformation of alkanes to fatty acids by a sulfate-reducing bacterium, strain HXD3 Appl Environ Microbiol 69 3892 3900 12839758
So CM Young LY 1999a Initial reactions in anaerobic alkane degradation by a sulfate-reducer, strain AK-01 Appl Environ Microbiol 65 5532 5540 10584014
So CM Young LY 1999b Isolation and characterization of a sulfate-reducing bacterium that anaerobically degrades alkanes Appl Environ Microbiol 65 2969 2976 10388691
Sullivan ER Zhang X Phelps C Young LY 2001 Anaerobic mineralization of stable-isotope-labeled 2-methylnaphthalene Appl Environ Microbiol 67 4353 4357 11526046
U.S. EPA (U. S. Environmental Protection Agency) 2000. Test methods for evaluating solid waste, physical/chemical methods. Available: http://www.epa.gov/epaoswer/hazwaste/test/main.htm [accessed 6 May 2004].
Zengler K Heider J Roselló-Mora R Widdel F 1999 Phototrophic utilization of toluene under anoxic conditions by a new strain of Blastochloris sulfoviridis Arch Microbiol 172 204 212 10525736
Zhang X Sullivan ER Young LY 2000 Evidence for aromatic ring reduction in the biodegradation pathway of carboxylated naphthalene by a sulfate reducing consortium Biodegradation 11 117 124 11440239
Zhang X Young LY 1997 Carboxylation as an initial reaction in the anaerobic metabolism of naphthalene and phenanthrene by sulfidogenic consortia Appl Environ Microbiol 63 4759 4764 9471963
|
15626649
|
PMC1253711
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan 8; 113(1):62-67
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.6940
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7475ehp0113-00006815626650ResearchArticlesBone as a Possible Target of Chemical Toxicity of Natural Uranium in Drinking Water Kurttio Päivi 1Komulainen Hannu 2Leino Aila 3Salonen Laina 1Auvinen Anssi 4Saha Heikki 51STUK–Radiation and Nuclear Safety Authority, Research and Environmental Surveillance, Helsinki, Finland2Division of Environmental Health, National Public Health Institute, Kuopio, Finland3Department of Clinical Chemistry, Turku University Hospital, Turku, Finland4School of Public Health, University of Tampere, Tampere, Finland5Department of Internal Medicine, Tampere University Hospital, Tampere, FinlandAddress correspondence to P. Kurttio, STUK–Radiation and Nuclear Safety Authority, Research and Environmental Surveillance, Laippatie 4, FIN-00881 Helsinki, Finland. Telephone: 358-9-75988554. Fax: 358-9-75988464. E-mail:
[email protected] thank D. Pawel, U.S. Environmental Protection Agency, for useful discussions on statistical analyses of the data, and the study persons and laboratories in the primary health centers for participating in the study.
The Ministry of Social Affairs and Health of Finland and Medical Research Fund of Tampere University Hospital financially supported this study.
The authors declare they have no competing financial interests.
1 2005 30 9 2004 113 1 68 72 5 8 2004 30 9 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Uranium accumulates in bone, affects bone metabolism in laboratory animals, and when ingested in drinking water increases urinary excretion of calcium and phosphate, important components in the bone structure. However, little is known about bone effects of ingested natural uranium in humans. We studied 146 men and 142 women 26–83 years of age who for an average of 13 years had used drinking water originating from wells drilled in bedrock, in areas with naturally high uranium content. Biochemical indicators of bone formation were serum osteocalcin and amino-terminal propeptide of type I procollagen, and a marker for bone resorption was serum type I collagen carboxy-terminal telopeptide (CTx). The primary measure of uranium exposure was uranium concentration in drinking water, with additional information on uranium intake and uranium concentration in urine. The data were analyzed separately for men and women with robust regression (which suppresses contributions of potential influential observations) models with adjustment for age, smoking, and estrogen use. The median uranium concentration in drinking water was 27 μg/L (interquartile range, 6–116 μg/L). The median of daily uranium intake was 36 μg (7–207 μg) and of cumulative intake 0.12 g (0.02–0.66 g). There was some suggestion that elevation of CTx (p = 0.05) as well as osteocalcin (p = 0.19) could be associated with increased uranium exposure (uranium in water and intakes) in men, but no similar relationship was found in women. Accordingly, bone may be a target of chemical toxicity of uranium in humans, and more detailed evaluation of bone effects of natural uranium is warranted.
bonebone turnover markersCTxdrinking waterosteocalcinP1NPuranium
==== Body
Increased uranium levels in groundwater are associated with uranium-rich ores and high solubility of uranium under oxidizing conditions in soft and bicarbonate-rich waters (Salonen 1994). Consequently, exceptionally high uranium concentrations have been found in private drilled wells located mostly in the southern part of Finland (Salonen and Huikuri 2002). We identified earlier a cohort of people who live in that area and use drilled wells for drinking water (Kurttio et al. 2002).
In long-term exposure, uranium accumulates in the bone and kidneys (Leggett and Pellmar 2003; Pellmar et al. 1999). The kidney has been considered the main target organ of chemical toxicity of uranium in humans, but effects in other tissues or organs remain poorly known. The intake of natural uranium through drinking water is associated with kidney function, particularly increased fractional excretion of calcium and phosphate in urine (Kurttio et al. 2002). The implications of the accumulation of natural uranium in the bone in humans are not known. The early distribution of uranium in the skeleton is similar to that of calcium (Leggett 1994). Uranium is assumed to deposit on the bone surface, and the uranyl ion (UO22+) is assumed to be exchanged with calcium ions at the surfaces of bone mineral crystals but not to participate in crystal formation (Leggett 1994). Gradually, uranium is redistributed in the bone and other tissues. The current biokinetic model of the International Commission on Radiological Protection suggests three compartments for uranium in human bone: bone surface, exchangeable bone volume, and nonexchangeable bone volume (Leggett 1994). It also suggests that uranium leaves bone surfaces more slowly than does calcium and that the removal from the nonexchangeable bone compartment may occur but with the rate of bone turnover.
The resemblance of uranium metabolism to that of calcium in bone enables the effects of uranium on bone. Indeed, uranium administration in rats is known to affect the bone. Acute (Guglielmotti et al. 1984) or continuous (Diaz Sylvester et al. 2002) exposure to uranium may lead to decreased bone formation rate and also increased bone resorption (Ubios et al. 1991) in rats.
The aim of this study was to assess whether uranium intake through drinking water affects the biochemical markers of bone turnover in humans. The present study extends our previous study, which suggested that uranium exposure is associated with altered proximal renal tubular function (Kurttio et al. 2002). To our knowledge, this is the first report on the possible effects of ingested natural uranium on bone in humans.
Materials and Methods
Study population.
The source population was identified from the drinking water database of STUK–Radiation and Nuclear Safety Authority, with radionuclide analyses of more than 5,000 drilled wells. This study was limited to southern Finland, where uranium concentrations are highest. The study population was a subpopulation of our previous study on effects of natural uranium on kidney function, with a more detailed description published earlier (Kurttio et al. 2002). The first questionnaire was mailed to 798 households. Based on the first questionnaire, 436 persons were selected, with a maximum of two persons per household where a drilled well had been used for drinking water at least for the previous year (median duration of use, 11 years). The second questionnaire was used to collect information on residential history and use of drilled well water and its daily consumption, use of other beverages, smoking history, education, occupation, disease history, and use of medication and herbal products. Seventy-eight percent of the persons who received the second questionnaire agreed to participate in the study (samples were received from these persons). Further information on, for example, bone fracture history and information on menopause and on physical activity was also collected (67% replied to this third questionnaire). We do not have information on type or date of the bone fractures.
Subjects were excluded if they were < 25 years of age (n = 11); had diabetes mellitus (n = 4); reported long-term use of glucocorticoids (n = 11), thiazide diuretics (n = 7), methotrexate (n = 1), or sodium aurothiomalate (n = 1); were currently pregnant (n = 4); or used effective equipment for removing uranium from well water (n = 4). The final study population consisted of 288 persons from 179 households. Most of the study persons had never smoked, and their average body mass index was 25 kg/m2 (Tables 1 and 2). Twenty-six women used estrogen (oral contraceptives or hormonal replacement therapy) regularly during the previous year, and the women had had two deliveries on average. None of the subjects reported hyperparathyroidism.
The study protocol was approved by the National Public Health Institute Standing Committee on Ethics (project 8/030399).
Sample collection and preparation.
The water, urine, and nonfasting blood samples were collected between 14 September and 1 December 1999. The samples were collected at a time when the study persons had consumed water from the drilled well throughout the previous week. Samples were not taken unless at least 1 week had elapsed since an acute infection. The study persons brought the water and urine samples collected overnight to the laboratory in the morning. At the same visit, blood samples were taken (77% of the samples were taken before 1100 hr). In addition, body weight and height were measured in a standardized fashion. The water and overnight urine samples for uranium analyses were conserved with concentrated HNO3. Water samples were stored at room temperature but serum and urine samples frozen at −20°C until analyzed.
Uranium exposure assessment.
Uranium in drinking water and urine were analyzed blind with inductively coupled plasma mass spectrometry. The analysis and quality control procedure are described by Kurttio et al. (2002). The primary measure of uranium exposure was uranium concentration in drinking water (micrograms per liter). In addition, we measured daily intake of uranium from drinking water (volume used × concentration, micrograms), cumulative intake from drinking water (daily intake × duration of the water consumption, grams), and uranium concentration in urine (micrograms per liter or micrograms per millimole creatinine). The exposure variables were highly correlated with each other (Table 3).
Outcome variables.
Serum osteocalcin and amino-terminal propeptide of type I procollagen (P1NP) were used as indicators of bone formation, reflecting different stages of osteoblast differentiation. We analyzed osteocalcin using an immunoradiometric assay, which measures human osteocalcin (1–49) and human osteocalcin peptide (1–43) (ELSA-OSTEO; CIS Bio International, Gifsur-Yvette, France). At the 15-μg/L level, the intra- and interassay variations were 2.0 and 3.1%, respectively. P1NP was analyzed with a commercial radio-immunoassay (Procollagen Intact P1NP; Orion Diagnostica, Oulunsalo, Finland); intra- and interassay variations at the 40-μg/L level were 2.0 and 4.9%, respectively.
Serum type I collagen carboxy-terminal telopeptide (CTx) was used as an indicator of bone resorption. CTx was analyzed with an enzyme immunoassay (Serum CrossLaps One Step ELISA; Osteometer Biotech, Herlev, Denmark); intra- and interassay variations at the 2.4-nmol/L level were 6.4 and 7.2%, respectively.
In men, the correlation between the log-transformed osteocalcin and P1NP was 0.70; between osteocalcin and CTx, 0.38; and between P1NP and CTx, 0.32. In women, the correlations were 0.63, 0.46, and 0.36, respectively.
Urine calcium was measured with atomic absorption spectrophotometry (EFOX 5053; Eppendorf, Hamburg, Germany) (detection limit, 0.1 mmol/L). Urine phosphate was measured based on a colored complex with ammonium molybdate (Konelab 60I; Konelab Co., Espoo, Finland) (detection limit, 2.0 mmol/L). Urinary excretions of calcium and phosphate (millimoles per hour) were calculated from the volume of urine divided by the overnight collection time. The mean ± SD excretion of urine was 79 ± 36 mL/hr in men and 78 ± 37 mL/hr in women.
Statistics.
For all the parameters determined, the observations below the detection limits were recorded as half of the detection limit. An analysis of the residuals indicated that they were not normally distributed and that some of the observations were highly influential. Therefore, the robust regression method using iteratively reweighted least squares (Huber and Tukey bi-square weight function) with rreg routine in Stata/SE 8.1 for Windows (Stata Corp., College Station, TX, USA) was used. Robust regression assigns a weight to each observation, with lower weights given to possible influential observations. Some results from the conventional linear regression are also given in “Results.”
The analyses were performed separately for men and women. For men, markers of bone metabolism levels were modeled using linear and quadratic terms for age and a variable for current smoking. The model used for women included a categorical age term [< 45 (reference), 45–55, 55–65, and ≥65 years], with additional variables for recent regular estrogen use and current smoking.
Algebraically these are as follows:
in which y is the indicator of bone metabolism, α is a constant, b is the regression coefficient, x is continuous uranium exposure, agecat is age category (45–55, 55–65, and ≥65 years), smo is current smoking status, and estro is use of estrogens, the last two being binary indicator (dummy) variables. R2 and p-values of the models are described in Table 4.
Analyses were also carried out using the above-mentioned models with log-transformed urinary calcium or phosphate excretions as explanatory variables.
Results
Background.
For men, the levels of osteocalcin, P1NP, and CTx tended to decrease with age until about 60 years of age, after which bone turnover appeared to increase gradually but age accounts for a relatively small proportion of the variation in the bone turnover measurements (Figure 1). All p-values were < 0.01 for associations between the linear age variable and all outcome variables. In men, current smoking was associated with decreased levels of osteocalcin (p = 0.01), P1NP (p = 0.11), and CTx (p = 0.03).
For women, the levels of osteocalcin, P1NP, and CTx were highest in the age group of 55–65 years, but the differences between the age groups were not statistically significant (Figure 1). Smoking in women was not statistically significantly associated with any marker of bone turnover. Estrogen use was associated with significantly decreased levels of osteocalcin, P1NP, and CTx (Figure 1).
Uranium exposure.
The uranium concentration in water varied from 0.001 to 1,920 μg/L (Table 2), with 27% of the concentrations > 100 μg/L and 59% > 15 μg/L. The median daily intake of uranium from drinking water was 36 μg, and the cumulative intake was 120 mg. The median annual committed equivalent radiation dose of bone surfaces was 0.36 mSv/year (maximum, 41 mSv/year), based on the uranium intake and the average uranium isotope activity ratios measured in Finnish drilled well waters (234U:238U = 2) and dose conversion factors (234U, 7.4 × 10−7 Sv/Bq; 238U, 7.1 × 10−7 Sv/Bq) (International Commission on Radiological Protection 1994).
In men, uranium exposure was associated with elevated CTx levels (Figure 2) with the p-values in the robust regression 0.05 for uranium in water, 0.16 for daily intake, and 0.16 for cumulative intake. The corresponding p-values in conventional linear regression analyses were 0.01, 0.02, and 0.03. There was an indication of an association between increased levels of osteocalcin and uranium concentrations in drinking water (p = 0.19; p-value in the conventional linear regression was 0.04). Levels of P1NP were not associated with uranium exposure. Uranium concentrations in urine expressed as micrograms per liter or micrograms per millimole creatinine were not associated with the markers of bone turnover.
Increased urinary excretion of calcium tended to be associated with increased CTx levels (p-value from the robust regression was 0.10), and some indication was found for increased urinary excretion of phosphate with decreased osteocalcin levels (p = 0.16) in men. The other associations between calcium or phosphate excretion and bone turnover were not close to the statistical significance in the robust regression.
In women, uranium exposure was not associated with any indicators of bone turnover (Figure 2). Urinary excretion of neither calcium nor phosphate was associated with bone markers.
Those 32 study persons who reported a history of any bone fractures in adulthood were not statistically significantly more exposed to uranium than those without such history (median cumulative doses of uranium of 124 mg in those with fractures vs. 117 mg in those without). There were no differences in the levels of the markers of bone metabolism among those with or without past fractures (data not shown).
Discussion
The uranium exposure covered a wide range of concentrations in this study. More than half of the study persons used drinking water with uranium concentration exceeding 15 μg/L, which is the new provisional World Health Organization (WHO) guideline value for uranium in drinking water (WHO 2004).
In men, chronic uranium exposure indicated by uranium level in drinking water as well as daily and cumulative uranium intakes tended to be associated with the increased levels of the bone resorption marker CTx and to a lesser degree of the bone formation marker osteocalcin. The association of uranium exposure and CTx reached a marginal significance at the 5% level in the robust analysis that down-weights the influence of possible outliers and was significant in the conventional regression analysis. This finding may indicate that bone is a possible target of chemical toxicity of natural uranium.
In contrast to men, no statistically significant associations with uranium exposure and the measured bone turnover markers were observed in women. In women, subtle effects may be masked by other strong determinants of bone turnover, such as menopause and hormone use. Potential confounding factors including menopausal status, recent body weight changes, physical activity, and calcium and vitamin D supplementation could not be effectively controlled in the present study, although they all have an influence on bone metabolism (Delmas 2000; Watts 1999).
The subtle effects of uranium on bone markers in men could be explained by different mechanisms. Accumulation of uranium in bone may have a local effect on bone metabolism or structure. Direct effect of uranium on bone has been shown in animal studies, with accumulation of uranium into bone (Leggett and Pellmar 2003; Pellmar et al. 1999). In laboratory animals exposure has been shown to modify bone formation and resorption (Diaz Sylvester et al. 2002; Guglielmotti et al. 1984; Ubios et al. 1991). Direct bone effect is also supported by the present observation that the change in bone markers was more strongly associated with uranium concentration in drinking water and daily or cumulative intake than with uranium concentration in urine. Concentration in water and intake likely describe long-term exposure to uranium and consequently accumulation to bone better than concentration in urine, which reflects recent exposure.
Uranium might have an effect on bone also via its influence on kidneys. Chronic renal insufficiency has been reported to affect bone metabolism (Malluche 1995; Malluche and Faugere 1990). On the other hand, elevated levels of bone markers have been observed in patients with kidney damage due to chronic exposure to cadmium, another metal toxic to the kidney (Aoshima et al. 2003; Kido et al. 1990). Cadmium-induced osteoporosis is associated specifically with tubular damage, including increased excretion of calcium in urine (Jin et al. 2004). However, uranium in drinking water does not cause severe kidney damage or cytotoxicity even at high exposure levels (Kurttio et al. 2002; Zamora et al. 1998), nor had the subjects in the present study significant kidney insufficiency. We have earlier shown that intake of natural uranium in drinking water is associated with increased fractional excretion of calcium and phosphate (Kurttio et al. 2002). By increasing leakage of calcium into urine by disturbing its tubular reabsorption, uranium exposure could secondarily lead to bone resorption. However, the increased excretion of calcium and phosphate in urine has been suggested to be associated most strongly with the recent uranium exposure (uranium in urine) (Kurttio et al. 2002), and in the present study CTx was associated with long-term exposure to uranium (concentration in water, and daily and cumulative intake). Accordingly, on the basis of earlier animal studies and the present results, we propose that the relationship between uranium intake and bone markers reflects the direct effect of uranium on bone.
Only uranium was analyzed from the water samples. It is possible that other elements or constituents in drinking water confound the results. To be a confounding factor, it should be associated with both uranium concentration and the outcome measures. However, other heavy metals, including cadmium and lead, occur extremely rarely in substantial concentrations in Finnish drilled wells and are not correlated with uranium concentrations (Kurttio et al., unpublished data). Therefore, other elements in drinking water are very unlikely to confound the results.
In this study population, drinking water is expected to be the predominant source of uranium, especially among those with elevated uranium concentrations in well water. The study persons had used drinking water from the drilled wells with measured uranium concentrations for at least 1 year. Therefore, a steady state uranium exposure can be anticipated.
Uranium concentration in the private wells drilled in bedrock may vary considerably over time, and therefore a spot sampling may not accurately represent the long-term uranium exposure. Additionally, the daily and cumulative intakes of uranium are based on study persons’ own estimates on their drinking water consumption, which also adds uncertainty. Although urinary uranium concentration is unaffected by these sources of uncertainty, it is limited mainly to current uranium exposure. Yet there is a high correlation between uranium exposure indicators.
Substantial variation in age complicates the interpretation of the results because several age-dependent factors influencing the bone turnover may mask possible effects of uranium. As was seen in this study, the levels of bone turnover markers remain approximately stable from 25 years of age to menopausal age (~ 55 years) in women and to 65 years of age in men. Obviously focusing on limited ages would facilitate the interpretation of the results.
Conclusions
We found some evidence for an association between increased bone turnover and exposure to natural uranium through drinking water among men. The fact that similar effects were not observed in women may be due to other stronger factors in bone metabolism of women that may mask the effects of uranium. This study suggests that in addition to kidneys, bone may be another target for uranium toxicity.
Figure 1 Background levels of the markers of bone turnover in men (A–C) and women (D–F). The lines represent the estimates from the robust regression models described in the text. In A–C, curvature lines and p-values represent the estimates of squared age variable. All p-values for associations between the linear age variable and all outcome variables were < 0.01. In D–F, open circles represent women who do not use estrogen, and shaded circles, women who use estrogen. Error bars are 95% confidence intervals of age groups. p-Values are given for the of 55–65-year age group compared with the < 45-year age group and for the estrogen users compared with nonusers (estro): (A) p = 0.06; (B) p = 0.13; (C) p = 0.03; (D) p = 0.08 (55–65 years), p = 0.005 (estro); (E) p = 0.09 (55–65 years), p < 0.001 (estro); (F) p = 0.07 (55–65 years), p = 0.001 (estro).
Figure 2 Associations between biochemical markers of bone turnover and uranium (U) exposure expressed as concentration in drinking water or as daily intake in men (A–F) and women (G–I). Regression lines and p-values were taken from the robust regression models. (A) p = 0.19; (B) p = 0.46; (C) p = 0.05; (D) p = 0.23; (E) p = 0.71; (F) p = 0.16; (G) p = 0.58; (H) p = 0.60; (I) p > 0.99.
Table 1 Description of age and smoking by sex in the study population.
Men [no. (%)] Women [no. (%)]
Age (years)
< 45 42 (29) 46 (32)
45–55 34 (23) 40 (28)
55–65 50 (34) 30 (21)
≥65 20 (14) 26 (18)
Smoking
Never 69 (47) 94 (66)
Ex 53 (36) 31 (22)
Current 18 (12) 14 (10)
Missing 6 (4) 3 (2)
Total 146 (100) 142 (100)
Table 2 Basic information on the study population, uranium exposure, and levels of indicators of bone turnover and urinary calcium, phosphate, and creatinine.
Percentile
Characteristic No. Mean Median 25th 75th Minimum Maximum
Men
Age (years) 146 53 54 44 61 26 78
Body mass index (kg/m2) 143 26 25 24 28 20 35
Duration of the use of drilled well (years) 146 13 11 6 20 2 34
Uranium in drinking water (μg/L) 146 124 28 6 122 0.087 1,920
Daily intake of uranium from drinking water (μg) 146 216 36 8 207 0.2 4,128
Cumulative intake of uranium from drinking water (g) 146 1.33 0.12 0.02 0.60 0.001 33
Uranium in urine (μg/L) 146 0.29 0.06 0.01 0.27 0.001 4.54
Uranium in urine (μg/mmol creatinine) 146 0.041 0.007 0.002 0.032 0.0001 0.333
Urine calcium (mmol/hr) 146 0.7 0.3 0.1 0.6 0.04 19
Urine phosphate (mmol/hr) 146 3.9 2.6 1.3 4.6 0.3 19
Urine creatinine (mmol/L) 146 8.5 7.8 5.4 10.4 1.2 28
Serum osteocalcin (μg/L) 146 21 20 16 25 7 54
Serum P1NP (μg/L) 146 42 37 31 48 15 178
Serum CTx (nmol/L) 146 3.4 2.4 1.7 3.3 0.4 65
Women
Age (years) 142 52 53 43 61 28 83
Body mass index (kg/m2) 128 25 24 22 26 18 41
No. of deliveries 82 2 2 2 3 0 6
Duration of the use of drilled well (years) 142 13 11 6 19 1 34
Uranium in drinking water (μg/L) 142 113 26 5 115 0.001 930
Daily intake of uranium from drinking water (μg) 142 212 36 7 207 0.0 2,748
Cumulative intake of uranium from drinking water (g) 142 1.21 0.12 0.03 0.73 0.000 30
Uranium in urine (μg/L) 142 0.38 0.09 0.02 0.42 0.001 3.25
Uranium in urine (μg/mmol creatinine) 142 0.075 0.019 0.004 0.087 0.0003 0.571
Urine calcium (mmol/hr) 141 0.4 0.2 0.1 0.5 0.03 3.0
Urine phosphate (mmol/hr) 141 3.0 1.7 1.0 3.3 0.1 17
Urine creatinine (mmol/L) 142 6.3 5.4 3.7 7.8 0.9 24
Serum osteocalcin (μg/L) 142 21 19 15 24 6 121
Serum P1NP (μg/L) 142 38 34 26 47 9 152
Serum CTx (nmol/L) 142 2.8 2.3 1.5 3.3 0.4 40
Table 3 Correlation matrix for the log-transformed uranium (Ln U) exposure variables.
Ln U in water (μg/L) Ln U intake (μg/day) Ln U cumulative intake (g) Ln U in urine (μg/L)
Ln U in water (μg/L) 1
Ln U intake (μg/day) 0.98 1
Ln U cumulative intake (g) 0.93 0.95 1
Ln U in urine (μg/L) 0.89 0.89 0.84 1
Ln U in urine (μg/mmol creatinine) 0.86 0.88 0.84 0.96
Table 4 R2 and p-values for the robust regression models of men and women including uranium concentration in water adjusted for age and smoking and estrogen use (for women).
Men
Women
Outcome R2 p-Value R2 p-Value
Osteocalcin 0.21 < 0.001 0.10 0.02
P1NP 0.13 < 0.001 0.12 0.008
CTx 0.14 < 0.001 0.12 0.00
==== Refs
References
Aoshima K Fan J Cai Y Katoh T Teranishi H Kasuya M 2003 Assessment of bone metabolism in cadmium-induced renal tubular dysfunction by measurements of biochemical markers Toxicol Lett 136 183 192 12505271
Delmas PD 2000 Markers of bone turnover for monitoring treatment of osteoporosis with antiresorptive drugs Osteoporos Int 11 suppl 6 S66 S76 11193241
Diaz Sylvester PL Lopez R Ubios AM Cabrini RL 2002 Exposure to subcutaneously implanted uranium dioxide impairs bone formation Arch Environ Health 57 320 325 12530598
Guglielmotti MB Ubios AM de Rey BM Cabrini RL 1984 Effects of acute intoxication with uranyl nitrate on bone formation Experientia 40 474 476 6723911
International Commission on Radiological Protection 1994. Age-Dependent Doses to Members of the Public from Intake of Radionuclides, Part 3: Ingestion Dose Coefficients. Radiation Protection, A Report of a Task Group of Committee 2 of the International Commission on Radiological Protection. Oxford, UK:Pergamon.
Jin T Nordberg G Ye T Bo M Wang H Zhu G 2004 Osteoporosis and renal dysfunction in a general population exposed to cadmium in China Environ Res 96 353 359 15364604
Kido T Nogawa K Honda R Tsuritani I Ishizaki M Yamada Y 1990 The association between renal dysfunction and osteopenia in environmental cadmium-exposed subjects Environ Res 51 71 82 2404753
Kurttio P Auvinen A Salonen L Saha H Pekkanen J Mäkeläinen I 2002 Renal effects of uranium in drinking water Environ Health Perspect 110 337 342 11940450
Leggett RW 1994 Basis for the ICRP’s age-specific biokinetic model for uranium Health Phys 67 589 610 7960780
Leggett RW Pellmar TC 2003 The biokinetics of uranium migrating from embedded DU fragments J Environ Radioact 64 205 225 12500806
Malluche HH 1995 Renal bone disease—an ongoing challenge to the nephrologist Clin Nephrol 44 suppl 1 S38 S41 8608661
Malluche H Faugere MC 1990 Renal bone disease 1990: an unmet challenge for the nephrologist Kidney Int 38 193 211 2205749
Pellmar TC Fuciarelli AF Ejnik JW Hamilton M Hogan J Strocko S 1999 Distribution of uranium in rats implanted with depleted uranium pellets Toxicol Sci 49 29 39 10367339
Salonen L 1994. 238U series radionuclides as a source of increased radioactivity in groundwater originating from Finnish bedrock. In: Future Groundwater Resources at Risk (Soveri J, Suokko T, eds). IAHS Publication 222. Oxford, UK:IAHS Press, 71–84.
Salonen L Huikuri P 2002. Elevated levels of uranium series radionuclides in private water supplies in Finland. In: The 5th International Conference on High Levels of Natural Radiation and Radon Areas: Radiation Dose and Health Effects. Munich, Germany, 4–7 September 2000. Vol. 2: Poster Presentations. BfS Report 24/2002 BfS Schriften, Strahlenhygine. Bremerhaven, Germany:Wirtschaftsverlag NW/Verlag für neue Wissenschaft GmbH, 87–91.
Ubios AM Guglielmotti MB Steimetz T Cabrini RL 1991 Uranium inhibits bone formation in physiologic alveolar bone modeling and remodeling Environ Res 54 17 23 2004634
Watts NB 1999 Clinical utility of biochemical markers of bone remodeling Clin Chem 45 1359 1368 10430819
WHO 2004. Guidelines for Drinking-Water Quality. Vol. 1: Recommendations. 3rd ed. Geneva:World Health Organization.
Zamora ML Tracy BL Zielinski JM Meyerhof DP Moss MA 1998 Chronic ingestion of uranium in drinking water: a study of kidney bioeffects in humans Toxicol Sci 43 68 77 9629621
|
15626650
|
PMC1253712
|
CC0
|
2021-01-04 23:40:55
|
no
|
Environ Health Perspect. 2005 Jan 30; 113(1):68-72
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7475
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7186ehp0113-00007315626651ResearchArticlesHealth-Related Benefits of Attaining the 8-Hr Ozone Standard Hubbell Bryan J. 1Hallberg Aaron 2McCubbin Donald R. 2Post Ellen 21U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards, Innovative Strategies and Economics Group, Research Triangle Park, North Carolina, USA2Abt Associates, Inc., Bethesda, Maryland, USAAddress correspondence to B.J. Hubbell, U.S. EPA/ OAQPS, 4930 Old Page Rd., Research Triangle Park, NC 27703 USA. Telephone: (919) 541-0621. Fax: (919) 541-0839. E-mail:
[email protected] Material is available online at http://ehp.niehs.nih.gov/docs/2004/7186/suppl.pdf
We thank A. Davis for providing technical editing that greatly improved the readability of the article and M. Johnson for his careful editing and formatting of the final manuscript.
The opinions expressed in this article are the authors’ and do not necessarily represent those of the U.S. EPA.
B.J.H. works for the Air Office of the U.S. EPA, which sets the National Ozone Air Quality Standard. Abt Associates is a contractor to the U.S. EPA, and some of the work for this article was completed under that contract.
1 2005 7 10 2004 113 1 73 82 14 4 2004 7 10 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. During the 2000–2002 time period, between 36 and 56% of ozone monitors each year in the United States failed to meet the current ozone standard of 80 ppb for the fourth highest maximum 8-hr ozone concentration. We estimated the health benefits of attaining the ozone standard at these monitors using the U.S. Environmental Protection Agency’s Environmental Benefits Mapping and Analysis Program. We used health impact functions based on published epidemiologic studies, and valuation functions derived from the economics literature. The estimated health benefits for 2000 and 2001 are similar in magnitude, whereas the results for 2002 are roughly twice that of each of the prior 2 years. The simple average of health impacts across the 3 years includes reductions of 800 premature deaths, 4,500 hospital and emergency department admissions, 900,000 school absences, and > 1 million minor restricted activity days. The simple average of benefits (including premature mortality) across the 3 years is $5.7 billion [90% confidence interval (CI), 0.6–15.0] for the quadratic rollback simulation method and $4.9 billion (90% CI, 0.5–14.0) for the proportional rollback simulation method. Results are sensitive to the form of the standard and to assumptions about background ozone levels. If the form of the standard is based on the first highest maximum 8-hr concentration, impacts are increased by a factor of 2–3. Increasing the assumed hourly background from zero to 40 ppb reduced impacts by 30 and 60% for the proportional and quadratic attainment simulation methods, respectively.
air pollutionbenefit analysishealth impact assessmentozonestandards
==== Body
The Clean Air Act [U.S. Environmental Protection Agency (EPA) 1970] identified tropospheric ozone as one of six “criteria pollutants”—pervasive pollutants considered harmful to human health. Tropospheric ozone forms as a result of atmospheric reactions of nitrogen oxides (NOx) and volatile organic compounds (VOCs) in the presence of sunlight. Both local emissions sources, such as traffic, and emissions transported from upwind sources, such as electric utilities, contribute to ambient ozone levels in populated areas.
In 1997, the U.S. EPA changed the ozone standard to 80 ppb to reflect new scientific studies showing that ozone causes health effects at levels lower than the previous 120 ppb standard. Additionally, the form of the standard was changed to reflect studies showing that exposure times longer than 1 hr are of concern. The U.S. EPA set the form of the standard, which is the threshold for compliance and violations, at the fourth highest daily maximum 8-hr average occurring each year, averaged over a 3-year period.
New scientific studies published since 1996 have increased the body of evidence supporting the association between ambient ozone and a number of serious health effects (Anderson et al. 2004). For example, studies examining the association between ambient ozone and premature mortality have increased the weight of evidence supporting this important health impact (Anderson et al. 2004; Thurston and Ito 2001).
Our purpose for this analysis was to assess the human health benefits of attaining the 8-hr ozone standard. We applied a damage function approach similar to those used in several recent U.S. EPA regulatory impact analyses, including those for the proposed Clean Air Interstate Rule and the final Clean Air Nonroad Diesel Rule (U.S. EPA 2004a, 2004b). We focused the assessment on the benefits that might have been achieved if current monitored ozone levels (represented by the years 2000–2002) were reduced just to the levels required to meet the 8-hr standard. We conducted analyses to examine the sensitivity of our results to a number of different assumptions about the form of the standard, background levels of ozone, methods for simulating attainment of the 8-hr ozone standard, and the choice of health effects and effect estimates from published epidemiologic studies.
In this article, we provide detailed descriptions of the data and methods in this analysis, along with the results. We describe monitored ozone levels in 2000, 2001, and 2002, provide details on how we assigned monitored ozone levels to populations to estimate population-level exposures, and outline the two approaches we used to simulate attainment. We then discuss the literature on ozone-related health effects, describe the specific set of health impact functions we used in the benefits analysis and the economic values selected to estimate the dollar value of ozone-related health impacts, and discuss how we addressed uncertainty in the analysis. Finally, we present the results and implications of the analysis.
Simulation of Changes in Population-Level Exposures to Ambient Ozone Due to Attainment
Selecting monitoring data.
To estimate population-level ozone concentrations, we began by obtaining ozone monitoring data from the U.S. EPA’s Air Quality System (AQS) (U.S. EPA 2004c), a database of ambient air pollution data collected by the U.S. EPA, state, local, and tribal air pollution control agencies from > 1,000 monitoring stations across the country. We analyzed these data using the Environmental Benefits Mapping and Analysis Program (BenMAP), developed by the U.S. EPA for use in estimating the health impacts and economic benefits associated with changes in ambient air pollution (you may obtain a copy of BenMAP by e-mailing a request to B.J.H.). We used SAS (release 8.02; SAS Institute Inc., Cary, NC) to process the AQS data for use in BenMAP.
To characterize ozone levels, we selected monitors following criteria generally consistent with those the U.S. EPA uses to determine attainment and nonattainment of the 8-hr standard. We selected monitors that had a sufficient number of observations during the ozone “season,” which stretches from 1 May through 30 September, 153 days. Many areas of the United States, including Southern California and Texas, have a longer ozone season. Accounting for the longer ozone season in these areas would lead to an increase in the estimated benefits of attaining the standards.
Because missing monitor observations are common, we selected only those monitors that had observations on at least half the days in this period. Specifically, each monitor had to have at least 77 valid days, with a valid day defined as having at least nine hourly observations between 0800 and 1950 hr. We did not use data from any monitor with a parameter occurrence code (POC) > 4 to avoid errors that may be introduced by using nonstandard monitors. (POC codes are used to distinguish among multiple monitors at the same site that are measuring the same parameter. In general, a higher POC code is assigned to monitors that are not the primary ozone monitor.) For those locations with more than one ozone monitor, we selected the monitor with the lowest POC code (e.g., we chose POC 1 rather than 2), and dropped any others.
Table 1 summarizes the distribution of monitored fourth highest maximum daily 8-hr average ozone concentrations across the 3 study years. In all years, at least 35% of monitors failed to meet the level of the standard. However, there was some variability between years in the proportion of nonattainment monitors and in the amount by which monitors exceeded the standard. In 2000 and 2001, < 40% of monitors exceeded the standard, and ≤5% of the monitors exceeded 100 ppb. In 2002, 56% of monitors had ozone levels that exceeded the standard, and 14% had ozone levels > 100 ppb. Monitored ozone levels in 2002 were higher in part because of meteorologic conditions favorable for ozone formation and transport of ozone precursors (U.S. EPA 2003).
Ozone concentrations show spatial patterns, with certain areas of the United States, including California, having consistently high ozone values from 2000 through 2002. Other areas, such as the Southeast and Northeast, varied a great deal across those years. This may result from differences in climatic variability, natural phenomena such as wildfires, or differences in ozone precursor (NOx and VOC) emissions. Year-to-year precursor emissions may vary because of economic cycles; changes in electricity generation, such as switching from coal to natural gas; or changes in vehicle use.
Applying spatial interpolation.
Monitor data represent ambient ozone levels at a series of discrete points in space. However, benefits analysis requires an estimate of ambient ozone concentrations for populations across the United States. For each year of monitoring data (2000, 2001, and 2002), we generated estimates of average ambient ozone levels for every county in the United States using applied spatial interpolation methods. Our base case analysis used Voronoi neighbor averaging (VNA), an algorithm that estimates ambient ozone levels by selecting the closest neighboring monitors surrounding the center of each county and then calculating the inverse distance weighted average of the monitor values for the selected neighboring monitors (e.g., Chen et al. 2004; Gold 1997). This method provides a relatively smooth surface in densely monitored areas.
We analyzed the accuracy of the VNA interpolation procedure by dropping individual monitors and predicting their ambient ozone levels using the remaining monitors. The national average differences between predicted and observed annual averages are < 1% in all cases, with standard deviations ranging from 10 to 12%. The largest differences occurred in rural areas and large portions of the western United States, where few monitors are present; ozone estimates in these cases are often based partially on monitors that are quite distant.
Most populations live within 50 km of an ozone monitor, however, so we can be reasonably confident that estimates of ambient ozone levels will be acceptable for most populated areas. We explored the sensitivity of the results to the choice of spatial interpolation method by estimating ambient ozone levels using a distance limited version of VNA (where all monitors farther than 50 km are discarded when choosing neighbors), as well as using a simple closest monitor assignment. A detailed explanation of each of these methods is provided in the Supplemental Material (http://ehp.niehs.nih.gov/docs/2004/7186/suppl.pdf).
Reducing ozone levels to meet the standard.
To demonstrate the benefits of attaining the 8-hr standard in 2000, 2001, and 2002, we specified how ozone levels would be reduced to bring the specific attainment “metric” (fourth highest daily maximum 8-hr average) down to the level of the standard. The U.S. EPA’s primary (for health protection) and secondary (for environmental and welfare protection) 8-hr ozone standards both are 80 ppb. In determining attainment and nonattainment, however, the U.S. EPA must use rounding. As a result, we consider ozone values ≤84 ppb as meeting the standard.
There are several ways to reduce the distribution of hourly ozone values to simulate attainment. For simplicity we treated the form of the standard as simply the fourth highest daily maximum 8-hr average, rather than the fourth highest daily maximum 8-hr average averaged over the 3 previous years.
We investigated two different methods: percentage (or proportional) rollback and quadratic rollback. Percentage rollback simply reduces all daily metric values by the percentage required to bring the violating day (the day with the fourth highest value) down to 84 ppb. The quadratic rollback method reduces larger metric values proportionally more than smaller values.
It is not clear which method provides a more realistic simulation of an attainment strategy. If control strategies affect emissions on all days during the ozone season, then using percentage rollback may be appropriate. If control strategies affect emissions on days with higher ozone levels more than on days with lower levels, then quadratic rollback may be more realistic. Both of these approaches represent implementation strategies that areas may select to meet the ozone standard. See Supplemental Material (http://ehp.niehs.nih.gov/docs/2004/7186/suppl.pdf) for more details on the two methods.
For both methods, we assume a constant background 8-hr daily maximum ozone level of 40 ppb, representing the amount of ozone (for this averaging period) that is not attributable to U.S. anthropogenic sources. It is assumed that this background cannot be affected by attempts to attain the ozone standards, and thus this portion of the estimated ambient ozone levels is not adjusted by either rollback method.
Vingarzan (2004) surveyed recent literature on background ozone concentrations and concluded that based on data from 1983 to 2001, median background levels in the United States ranged between 13 and 47 ppb. Vingarzan (2004) notes that background levels appear to be increasing over time because of increased contributions from international transport of ozone precursors. Therefore, we selected a background ozone level toward the upper end of the observed range because our monitor data are based on later years. The background level likely varies across the United States, and our assumption of 40 ppb adds uncertainty to the analysis (Vingarzan 2004). We investigated the impact of different assumptions about background levels of the attainment metric in a sensitivity analysis.
Once BenMAP has calculated how the attainment metric will be affected for each day, it calculates how the other ozone metrics required for the various health impact functions will be affected. These include daily maxima for 1-hr and 8-hr periods, as well as daily averages over different time periods, including the 24-hr average, the 5-hr average (1000–1450 hours), and the 8-hr average (0900–1650 hours). To calculate, BenMAP rolls back individual hourly ozone observations such that they meet the target metric values. For details on this process, see Supplemental Material (http://ehp.niehs.nih.gov/docs/2004/7186/suppl.pdf).
In adjusting individual hourly ozone values to meet the target metric value, we assumed that there is no fixed background level of ozone for any particular hour and set the background to zero. Any given hourly value may have a specific background component; however, we are unable to determine what this component might be. We examined the impact of assuming alternative hourly background levels as a sensitivity analysis.
Finally, BenMAP uses the adjusted hourly values to calculate the adjusted ozone summary measures—for example, 24-hr average, 1-hr maximum, and the like. Using the three methods described above, BenMAP then spatially interpolates the set of adjusted summary measures to the center of each county. The differences between the spatially interpolated baseline and the adjusted summary measures are the basic air quality inputs to the health benefits model.
Note that BenMAP does not adjust monitors that meet the attainment test (those with fourth highest maximum daily 8-hr average ≤84 ppb). However, these monitors are included in the interpolation process, so the ozone levels assigned to a population in a given county will, in most cases, reflect an average of monitors with ozone reductions and those with no reduction. In reality, there will be reductions in ozone levels at monitors in a non-attainment area because of controls applied to meet the standard. Therefore, we are likely underestimating the change in ambient ozone that would occur as the result of implementing attainment strategies.
Health Impact Functions
Health impact functions measure the change in a health end point of interest, such as hospital admissions, for a given change in ozone. Health impact functions are derived from the epidemiology literature. A standard health impact function has four components: an effect estimate from a particular epidemiologic study, a baseline incidence rate for the health effect (obtained from either the epidemiology study or a source of public health statistics, e.g., the Centers for Disease Control and Prevention), the affected population, and the estimated change in the relevant ozone summary measures.
A typical health impact function might be as follows:
where y0 is the baseline incidence, equal to the baseline incidence rate times the potentially affected population; β is the effect estimate; and Δx is the estimated change in the summary ozone measure. There are other functional forms, but the basic elements remain the same. The following subsections describe the sources for each of the elements other than the ozone air quality inputs to the health impact functions just described: affected populations, effect estimates, and baseline incidence rates.
Affected Populations
The starting point for estimating affected populations is the 2000 U.S. Census block-level data set (Geolytics Inc. 2002). BenMAP incorporates 250 age/sex/race categories to match specific populations potentially affected by ozone and other air pollutants. The software constructs specific populations matching the populations in each epidemiologic study by accessing the appropriate age-specific populations from the overall population database. BenMAP projects populations to 2001 and 2002 using growth factors based on economic projections (Woods and Poole Economics Inc. 2001).
Effect Estimate Sources
The most significant benefits of reducing ambient concentrations of ozone are attributable to reductions in health risks. The U.S. EPA’s Ozone Criteria Document (U.S. EPA 1996b) and the World Health Organization’s recent reports (Anderson et al. 2004) outline numerous health effects known or suspected to be linked to exposure to ambient ozone.
More than 1,000 new health and welfare studies have been published since the U.S. EPA issued the 8-hr ozone standard in 1997. Many of these studies investigated the impact of ozone exposure on health effects, such as changes in lung structure and biochemistry, lung inflammation, asthma exacerbation and causation, respiratory-illness–related school absence, hospital and emergency department (ED) visits for asthma and other respiratory causes, and premature death.
We excluded some health effects from this analysis for four reasons: the possibility of double counting (e.g., hospital admissions for specific respiratory diseases), uncertainties in applying effect relationships that are based on clinical studies to the affected population, a lack of an established concentration–response relationship, or the inability to appropriately value the effect (e.g., changes in forced expiratory volume) in economic terms. Table 2 lists the health end points included in the primary and sensitivity analyses for this article.
In selecting epidemiologic studies as sources of effect estimates, we applied several criteria to develop a set of studies that is likely to provide the best estimates of impacts in the United States. To account for the potential impacts of different health care systems or underlying health status of populations, we gave preference to U.S. studies over non-U.S. studies. In addition, because of the potential for confounding by copollutants, we gave preference to effect estimates from models including both ozone and particulate matter over single-pollutant models.
A number of end points that are not health related also may significantly contribute to monetized benefits. These include decreased outdoor worker productivity, decreased yields for commercial and noncommercial crops, decreased commercial forest productivity, damage to urban ornamental plants, impacts on recreational demand from damaged forest aesthetics, and damage to ecosystem functions (U.S. EPA 1996a, 1999). Estimation of these impacts is beyond the scope of this analysis.
Effect estimates: premature mortality.
Although particulate matter is the air pollutant most clearly associated with premature mortality, recent research suggests that repeated ozone exposure likely contributes to premature death. Several recent analyses have found consistent statistical associations between ozone exposure and increased mortality (Fairley et al. 2003; Toulomi et al. 1997). In addition, Bell et al. (2004) found an overall significant impact of ozone on mortality using an extended version of the National Morbidity, Mortality, and Air Pollution Study database. Their results were significant even after controlling for PM levels.
Although they do not constitute a database as extensive as that for particulate matter, these recent studies provide supporting evidence for including mortality in ozone health benefits analyses. Thurston and Ito (2001) reviewed previously published time-series studies examining the effect of daily ozone levels on daily mortality. They hypothesized that much of the variability in published estimates of the ozone–mortality effect could be explained by how well each model controlled for the influence of weather, an important confounder, and that earlier studies, which used less sophisticated approaches to controlling for weather, consistently underpredicted the ozone–mortality effect.
Thurston and Ito (2001) also found that models incorporating a nonlinear temperature specification appropriate for the U-shaped nature of the temperature–mortality relationship (i.e., increased deaths at both very low and very high temperatures) produced ozone–mortality effect estimates that were both more strongly positive (a 2% increase in relative risk over the pooled estimate for all studies evaluated) and consistently statistically significant. Further accounting for the interaction effects between temperature and relative humidity strengthened the positive effect. Including a particulate matter index to control for particulate matter (PM)–mortality effects had little effect on these results, suggesting a relationship between ozone and mortality independent of that for PM. However, most of the studies that Thurston and Ito (2001) examined controlled only for PM ≤10 μm (PM10) or broader measures of particles and did not directly control for PM ≤2.5 μm (PM2.5). Therefore, there still may be potential for confounding of PM2.5 and ozone mortality effects, given that ozone and PM2.5 are highly correlated during summer months in some areas.
Two recent World Health Organization reports found that “recent epidemiologic studies have strengthened the evidence that there are short-term O3 effects on mortality and respiratory morbidity and provided further information on exposure–response relationships and effect modification” (Anderson et al. 2004; WHO 2003). In addition, Levy et al. (2001) assessed the epidemiologic evidence regarding the link between short-term exposures to ozone and premature mortality. Based on four U.S. studies (Ito and Thurston 1996; Kelsall et al. 1997; Moolgavkar 2000; Moolgavkar et al. 1995a), they concluded that an appropriate pooled effect estimate is a 0.5% increase in premature deaths per 10 μg/m3 increase in 24-hr average ozone concentrations, with a 95% confidence interval (CI) between 0.3 and 0.7%.
We included ozone mortality in the base health effects estimate for the ozone benefits reanalysis, with the recognition that the exact magnitude of the effects estimate is subject to continuing uncertainty. We used results from three U.S. studies to calculate the base-case ozone mortality estimate. We selected these studies (Ito and Thurston 1996; Moolgavkar et al. 1995a; Samet et al. 1997) based on the logic that the demographic and environmental conditions existing when these studies were conducted would, on average, be most similar (relative to international studies) to the conditions prevailing when the ozone standards would be implemented. We examined the impact of including a fourth U.S. study by Kinney et al. (1995) in a sensitivity analysis. We excluded Kinney et al. (1995) from the primary analysis because, as Levy et al. (2001) noted, that study included only a linear term for temperature. Because Kinney et al. (1995) found no significant ozone effect, including this study in the primary analysis would lead to an underestimate of true mortality impacts and increase the uncertainty surrounding the estimated mortality reductions.
We then estimated the change in mortality incidence resulting from application of the effect estimate from each study and combined the results using a random-effects weighting procedure, discussed in the Supplemental Material (http://ehp.niehs.nih.gov/docs/2004/7186/suppl.pdf), that accounts for both the precision of the individual effect estimates and between-study variability. However, it is important to note that this procedure only captures the uncertainty in the underlying epidemiologic work and does not capture other sources of uncertainty, such as that in the estimation of air pollution exposure (Levy et al. 2001).
Effect estimates: respiratory hospital admissions.
Detailed hospital admission and discharge records provide data for an extensive body of literature examining the relationship between hospital admissions and air pollution. This is especially true for the population ≥65 years of age, because of the availability of detailed Medicare records. Because the number of hospital admission studies is so large, we used results from a number of studies to pool some hospital admission end points. In addition, there is one study (Burnett et al. 2001) providing an effect estimate for respiratory hospital admissions in children ≤2 years of age.
To estimate total respiratory hospital admissions associated with changes in ozone for adults ≥65 years of age, we first estimated the change in hospital admissions for the separate effect categories that each study provided for each city: Minneapolis, Minnesota; Detroit, Michigan; Tacoma, Washington; and New Haven, Connecticut. To estimate all respiratory hospital admissions for Detroit, we added the pneumonia and chronic obstructive pulmonary disease (COPD) estimates, based on the effect estimates given by Schwartz (1994b). Similarly, we summed the estimated hospital admissions based on the effect estimates that Moolgavkar et al. (1997) reported for Minneapolis. To estimate all respiratory hospital admissions for Minneapolis using Schwartz (1994a), we simply estimated pneumonia hospital admissions based on the effect estimate. Making this assumption that pneumonia admissions represent the total impact of ozone on hospital admissions will give some weight to the possibility that there is no relationship between ozone and COPD, reflecting the equivocal evidence represented by the different studies. We then used a fixed-effects pooling procedure to combine the two all-respiratory hospital-admission estimates for Minneapolis. Finally, we used random-effects pooling to combine the results for Minneapolis and Detroit, in addition to results for Tacoma and New Haven. As noted above, this pooling approach accounts for both the precision of the individual-effect estimates and the between-study variability characterizing differences across study locations.
Effect estimate: asthma-related ED visits.
We used three studies as the source for the concentration–response functions we used to estimate the effects of ozone exposure on asthma-related ED visits: Cody et al. (1992), Weisel et al. (1995), and Stieb et al. (1996). We estimated the change in ED visits using the effect estimate from each study and then pooled the results using the random-effects pooling procedure described in the Supplemental Material (http://ehp.niehs.nih.gov/docs/2004/7186/suppl.pdf). A more recent study by Jaffe et al. (2003) examined the relationship between ED visits and air pollution for people 5–34 years of age in the Ohio cities of Cleveland, Columbus, and Cincinnati from 1991 through 1996. We did not use this particular study in our primary analysis because it represents a more limited population and excludes potentially important impacts on the population ≥35 years of age. However, because many asthma-related ED visits involve children, this study was included in a sensitivity analysis showing the magnitude of results for all ages relative to those for a population more heavily weighted toward children. We included both hospital admissions and ED visits as separate end points associated with ozone exposure, because our estimates of hospital admission costs do not include the costs of ED visits.
Effect estimate sources: minor restricted activity days.
Minor restricted activity days (MRADs) occur when individuals reduce most usual daily activities and replace them with less strenuous activities or rest but do not miss work or school. We estimated the effect of ozone on MRADs using a concentration–response function derived from Ostro and Rothschild (1989). These researchers estimated the impact of ozone and PM2.5 on MRAD incidence in a national sample of the adult working population (18–65 years of age) living in metropolitan areas. We developed separate coefficients for each year of the Ostro and Rothschild (1989) analysis (1976–1981), which we then combined for use in the U.S. EPA’s analysis. The effect estimate used in the impact function is a weighted average of the coefficients in Ostro and Rothschild (1989, their Table 4), using the inverse of the variance as the weight.
Effect estimate: school absences.
Children may be absent from school because of respiratory or other acute diseases caused or aggravated by exposure to air pollution. Several studies have found a significant association between ozone levels and school absence rates. We use two recent studies (Chen et al. 2000; Gilliland et al. 2001) to estimate changes in school absences resulting from changes in ozone levels. Gilliland et al. (2001) estimated the incidence of new periods of absence, whereas Chen et al. (2000) examined absence on a given day. We converted the Gilliland et al. estimate to days of absence by multiplying the absence periods by the average duration of an absence. We estimated 1.6 days as the average duration of a school absence, the result of dividing the average daily school absence rate from Chen et al. (2000) and Ransom and Pope (1992) by the episodic absence rate from Gilliland et al. (2001). Thus, each Gilliland et al. period of absence is converted into 1.6 absence days.
Following recent advice from the National Research Council (2002), we calculated reductions in school absences for the full population of school-age children (5–17 years of age). This is consistent with recent peer-reviewed literature on estimating the impact of ozone on school absences (Hall et al. 2003). We estimated the change in school absences using both Chen et al. (2000) and Gilliland et al. (2001) and then pooled the results using the random-effects pooling procedure described in Supplemental Material (http://ehp.niehs.nih.gov/docs/2004/7186/suppl.pdf).
Baseline Incidence Rates
Epidemiologic studies of the association between pollution levels and adverse health effects generally provide a direct estimate of the relationship of air quality changes to the relative risk of a health effect, rather than estimating the absolute number of avoided cases. For example, a typical result might be that a 100 ppb decrease in daily ozone levels might in turn decrease hospital admissions by 3%. The baseline incidence of the health effect is necessary to convert this relative change into a number of cases. A baseline incidence rate is the estimate of the number of cases of the health effect per year in the assessment location, because it corresponds to baseline pollutant levels in that location. To derive the total baseline incidence per year, this rate must be multiplied by the corresponding population number. For example, if the baseline incidence rate is the number of cases per year per 100,000 people, that number must be multiplied by the number of 100,000s in the population.
Table 3 summarizes the sources of baseline incidence rates and provides average incidence rates for the end points included in the analysis. For both baseline incidence and prevalence data, we used age-specific rates where available. We applied concentration–response functions to individual age groups and then summed over the relevant age range to provide an estimate of total population benefits. In most cases, we used a single national incidence rate, because of a lack of more spatially disaggregated data. Whenever possible, the rates used are national averages, because these data are most applicable to a national assessment of benefits. For some studies, however, the only available incidence information comes from the studies themselves; in these cases, incidence in the study population is assumed to represent typical incidence at the national level. Regional incidence rates are available for hospital admissions, and county-level data are available for premature mortality.
Economic Values for Health Outcomes
Reductions in ambient concentrations of air pollution generally lower the risk of future adverse health effects for a large population. Therefore, the appropriate economic measure is willingness to pay (WTP) for changes in risk of a health effect rather than WTP for a health effect that would occur with certainty (Freeman 1993). Epidemiologic studies generally provide estimates of the relative risks of a particular health effect that is avoided because of a reduction in air pollution. We converted those to units of avoided statistical incidence for ease of presentation. We calculated the value of avoided statistical incidences by dividing individual WTP for a risk reduction by the related observed change in risk. For example, suppose a pollution-reduction regulation is able to reduce the risk of premature mortality from 2 in 10,000 to 1 in 10,000 (a reduction of 1 in 10,000). If individual WTP for this risk reduction is $100, then the WTP for an avoided statistical premature death is $1 million ($100/0.0001 change in risk).
WTP estimates generally are not available for some health effects, such as hospital admissions. In these cases, we used the cost of treating or mitigating the effect as a primary estimate. These cost-of-illness (COI) estimates generally understate the true value of reducing the risk of a health effect, because they reflect the direct expenditures related to treatment but not the value of avoided pain and suffering (Berger et al. 1987; Harrington and Portney 1987). We provide unit values for health end points (along with information on the distribution of the unit value) in Table 4. All values are in constant year 2000 US$, adjusted for growth in real income. Economic theory argues that WTP for most goods (e.g., environmental protection) will increase if real income increases. Many of the valuation studies used in this analysis were conducted in the late 1980s and early 1990s. Because real income has grown since the studies were conducted, people’s WTP for reductions in the risk of premature death and disease likely has grown as well. We did not adjust COI-based values, because they are based on current costs. Similarly, we did not adjust the value of school absences, because that value is based on current wage rates. Table 4 presents the values for individual end points adjusted to year 2000 income levels.
Mortality.
To estimate the monetary benefit of reducing the risk of premature death, we used the “value of statistical lives” saved (VSL) approach, which is a summary measure for the value of small changes in mortality risk for a large number of people. The VSL approach applies information from several published value-of-life studies to determine a reasonable monetary value of preventing premature mortality. The mean value of avoiding one statistical death is estimated to be roughly $6 million in 2000 US$. This represents an intermediate value from a variety of estimates in the economics literature (U.S. EPA 1999).
Respiratory hospital admissions.
In the absence of estimates of societal WTP to avoid hospital visits/admissions for specific illnesses, estimates of total COI (total medical costs plus the value of lost productivity) typically are used as conservative, or lower bound, estimates. These estimates are biased downward because they do not include the WTP value of avoiding pain and suffering.
The International Classification of Diseases, 9th Revision (ICD-9; International Classification of Diseases 1979) code-specific COI estimates we used in this analysis consist of estimated hospital charges and the estimated opportunity cost of time spent in the hospital (based on the average length of a hospital stay for the illness). We based all estimates of hospital charges and length of stays on statistics provided by the Agency for Healthcare Research and Quality (2000). We estimated the opportunity cost of a day spent in the hospital as the value of the lost daily wage, regardless of whether the hospitalized individual is in the workforce. To estimate the lost daily wage, we divided the 1990 median weekly wage by 5 and inflated the result to 2000 US$ using the urban consumer price index (CPI-U) (U.S. Bureau of Labor Statistics 2004) for “all items.” The resulting estimate is $109.35. The total COI estimate for an ICD code–specific hospital stay lasting n days, then, was the mean hospital charge plus $109 × n.
Asthma-related ED visits.
To value asthma ED visits, we used a simple average of two estimates from the health economics literature. The first estimate comes from Smith et al. (1997), who reported approximately 1.2 million asthma-related ED visits in 1987, at a total cost of $186.5 million (1987 US$). The average cost per visit that year was $155; in 2000 US$, that cost was $311.55 (using the CPI-U for medical care to adjust to 2000 US$). The second estimate comes from Stanford et al. (1999), who reported the cost of an average asthma-related ED visit at $260.67, based on 1996–1997 data. A simple average of the two estimates yields a (rounded) unit value of $286.
Minor restricted activity days.
No studies are reported to have estimated WTP to avoid an MRAD. However, Industrial Economics Inc. (unpublished data) has derived an estimate of WTP to avoid a minor respiratory restricted activity day, using estimates from Tolley et al. (1986) of WTP for avoiding a combination of coughing, throat congestion, and sinusitis. The IEc estimate of WTP to avoid a minor respiratory restricted activity day is $38.37 (1990 US$), or about $52 (2000 US$).
Although Ostro and Rothschild (1989) statistically linked ozone and MRADs, it is likely that most MRADs associated with ozone exposure are, in fact, minor respiratory restricted activity days. For the purpose of valuing this health end point, we used the estimate of mean WTP to avoid a minor respiratory restricted activity day.
School absences.
To value a school absence, we a) estimated the probability that if a school child stays home from school, a parent will have to stay home from work to care for the child; and b) valued the lost productivity at the parent’s wage. To do this, we estimated the number of families with school-age children in which both parents work, and we valued a school-loss day as the probability that such a day also would result in a work-loss day. We calculated this value by multiplying the proportion of households with school-age children by a measure of lost wages.
We used this method in the absence of a preferable WTP method. However, this approach is likely to understate the value of school-loss days in three ways: First, it omits WTP to avoid the symptoms/illness that resulted in the school absence; second, it effectively gives zero value to school absences that do not result in work-loss days; and third, it uses conservative assumptions about the wages of the parent staying home with the child.
For this valuation approach, we assumed that in a household with two working parents, the female parent will stay home with a sick child. From the Statistical Abstract of the United States (U.S. Census Bureau 2001), we obtained a) the numbers of single, married, and “other” (widowed, divorced, or separated) working women with children; and b) the rates of participation in the workforce of single, married, and “other” women with children. From these two sets of statistics, we calculated a weighted average participation rate of 72.85%.
Our estimate of daily lost wage (wages lost if a mother must stay at home with a sick child) is based on the year 2000 median weekly wage among women ≥25 or more years of age (U.S. Census Bureau 2001). This median weekly wage is $551. Dividing by 5 gives an estimated median daily wage of $103. To estimate the expected lost wages on a day when a mother has to stay home with a school-age child, we first estimated the probability that the mother is in the workforce and then multiplied that estimate by the daily wage she would lose by missing a work day: 72.85% times $103, for a total loss of $75.
Methods for Describing Uncertainty
Any complex analysis is likely to reflect many sources of uncertainty, and this analysis is no exception. We used numerous inputs to derive the benefits estimate, including measured ozone concentrations at monitor sites, interpolation methods, estimates of values (both from WTP and COI studies), population estimates, baseline incidence rate estimates, and income estimates. Each of these inputs may be uncertain, and depending on its location in the benefits analysis, each may have a disproportionately large impact on final estimates of total benefits. For example, we used measured ozone concentrations at monitor sites in the first stage of the analysis, meaning that any uncertainty in those measurements will propagate as the analysis continues. When compounded with uncertainty in later stages of analysis, even small uncertainties in monitored ozone levels can lead to large impacts on total benefits.
Given the wide variety of sources for uncertainty and the potentially large degree of uncertainty about any specific estimate, we characterized uncertainty in two ways, using both a limited scope Monte Carlo analysis and sensitivity analyses.
More than one source of uncertainty usually exists, even for individual end points. This makes it difficult to provide an overall quantified uncertainty estimate, for either individual end points or total benefits. For example, the health impact function used to estimate avoided premature deaths has an associated standard error that represents the statistical error around the effect estimate in the underlying epidemiologic study. In our results, we report a CI based on this standard error, reflecting the uncertainty in the estimated change in incidence of avoided premature deaths. However, this CI omits the contribution of air quality changes, baseline incidence rates, populations exposed, and transferability of the effect estimate to diverse locations. As a result, the reported CI gives a potentially misleading picture about the overall uncertainty in the estimates. This information should be interpreted within the context of the larger uncertainty surrounding the entire analysis.
We used Monte Carlo methods to generate CIs around the estimated health impact and dollar benefits. Monte Carlo simulation uses random sampling from distributions of parameters to characterize the effects of uncertainty on output variables, such as incidence of premature mortality. Distributions for individual effect estimates are based on the reported standard errors in the epidemiologic studies. Distributions for unit values are described in Table 4.
Results and Implications
Table 5 summarizes the incidence and valuation for each year associated with two attainment simulation methods, percentage and quadratic. Table 6 provides the results averaged across the 3 years. In addition to the mean incidence and valuation estimates, we have included a 5th and 95th percentile estimate in Table 6, based on the Monte Carlo simulations described above. To calculate the air quality values under each attainment scenario, we rolled back the ozone monitor data so that the fourth highest daily maximum 8-hr average just met the level required to attain the standard. This approach will likely understate the benefits that would occur because of implementation of actual controls to reduce ozone precursor emissions. These controls would likely reduce ozone concentrations at all monitors within a nonattainment area, rather than just at those monitors with out-of-attainment ozone values. Therefore, our results are an underestimate of the likely benefits of attaining the ozone standard. In all of the primary analytical cases, we used VNA with no distance limit and assumed a 40 ppb background level for the attainment metric and an hourly background level of zero.
The results for 2000 and 2001 are similar in magnitude, whereas the results for 2002 are roughly twice that of each of the prior 2 years. The simple average of benefits (including premature mortality) across the 3 years is $5.7 billion (90% CI, 0.6–15.0) for the quadratic rollback simulation method and $4.9 billion (90% CI, 0.5–14.0) for the percentage rollback simulation method. Average benefits without premature mortality are $200 million (90% CI, 72–350) for the quadratic rollback method and $160 million (90% CI, 65–310) for the percentage rollback method. Including premature mortality in our estimates had the largest impact on the overall magnitude of benefits: Premature mortality benefits account for more than 95% of the total benefits we can monetize.
Table 7 shows the impact on incidence of health impacts of a range of assumptions regarding how we rolled back the ozone monitor values. We considered the impact of ordinality—that is, of choosing the first versus the fourth highest daily maximum 8-hr average—and we chose a range of alternative background levels. Regardless of attainment simulation method, ordinality had the largest apparent impact, with roughly a factor of 2–3 separating results between the first highest and fourth highest 8-hr maximum. It is important to note that health impacts are likely to occur whenever the 8-hr daily maximum is elevated, not just when the number of exceedances is greater than four. Although the standard reflects the underlying health science and seeks to protect public health, it does not guarantee zero health impacts. That said, the magnitude of the difference in this analysis is still somewhat surprising.
Two elements contribute to this result. First, certain monitors will meet the standard with an ordinality of four but will not meet the standard with an ordinality of one. That is, some monitors may have one metric value > 84 ppb but will not have four such values. As discussed above, monitors that meet the standard are not adjusted at all, so these monitors will have a large impact on the results. Second, certain monitors have a small number of outlier metric values that are much higher than all of the rest. Because the rollback strategies both adjust all metric values, basing a rollback on these outlier values can cause much higher reductions across the entire year.
The impact of attainment metric background and the hourly background depended on attainment simulation method. Under the percentage rollback attainment simulation method, shifting the attainment metric background from 40 to 0 increased impacts by roughly a factor of 2, but the same shift under the quadratic rollback method had no significant impact on results. However, shifting the hourly background level from 0 to 40 under the quadratic rollback method resulted in a roughly 60% reduction in impacts, while making the same background shift using the percentage rollback method reduced impacts by around a third.
For any particular assumption of background ozone levels, our estimates are likely to understate the actual benefits that would occur from implementing control strategies to attain the 8-hr standard, because of our assumption that only the specific monitors that are out of attainment in any area will realize reductions in ozone levels. Our estimates of benefits in areas of the country with longer ozone seasons, such as California and Texas, will also be underestimates due to our assumption of a fixed ozone season from 1 May to 30 September for the entire nation. Analyses of specific attainment strategies should allow for changes in ambient ozone across all monitors in a nonattainment area, as well as accounting for the variable length of the ozone season. Because there is currently no known threshold for most ozone-related health effects, there is likely to be a significant benefit to reducing ozone concentrations beyond the standard at monitors that currently attain the standard.
Applying a distance limit of 50 km to the VNA method reduced benefits by 3–10%, depending on the year of analysis. Use of a closest monitor algorithm with a 50-km limit reduced benefits by 10–15%, depending on the year of analysis. Most of this difference occurs because approximately 10% of the population lives > 50 km away from an ozone monitor. Detailed sensitivity analyses examining the choice of interpolation method are available on request.
Our estimates of mortality-related benefits of attaining the standards may change, based on emerging meta-analyses of the ozone mortality literature. If these meta-analyses confirm the results of Thurston and Ito (2001), Levy et al. (2001), or the WHO report (2003) meta-analyses, the mean mortality benefits may increase by a factor of 2, suggesting that reductions in premature mortality associated with attainment of the ozone standards might be as high as 1,600 premature deaths avoided annually. This increase would substantially increase the economic value of health impacts as well, potentially up to $10 billion. Using the Jaffe et al. (2003) effect estimates for asthma ED visits in the population 5–34 years of age would have increased the estimated number of avoided admissions by approximately 4.5 times. This suggests that the all-ages estimates based on earlier studies may underestimate impacts in younger populations. Details of the sensitivity analyses examining alternative mortality and morbidity effect estimates are available from the authors.
In this analysis we estimated the health benefits of reducing ozone levels in areas with monitored values that exceed the 8-hr ozone standard. The increasing need to understand the public health impacts of air pollution regulations requires the merging of models and data from many disciplines. Although necessary, this type of multidisciplinary methodology is challenging in complexity and scope. Our approach illustrates the integration of models and data and highlights uncertainties inherent in the end results. The result suggests there may be significant health benefits arising from actions that reduce ozone concentrations in nonattainment areas.
The results of our analysis suggest that moving from current monitored ozone levels to full attainment of the 8-hr standard may yield substantial health benefits. We estimate total benefits (including premature mortality) of meeting the standard as reaching up to $5.7 billion (averaged over 3 years, 2000–2002). These dollar benefits are associated with average annual reductions in health effects, including > 800 avoided premature deaths, > 4,000 avoided hospital admissions, approximately 500 avoided asthma ED visits per year, > 1 million avoided restricted activity days, and > 900,000 avoided school absences.
We provide sensitivity analyses to examine key modeling assumptions. In addition, we could not quantify other uncertainties, such as the importance of unquantified effects and uncertainties in the interpolation of ambient air quality. Inherent in any analysis of health impacts are uncertainties in affected populations, health baselines, incomes, effect estimates, and other factors. The assumptions used to capture these elements are reasonable based on the available evidence. However, these data limitations prevent a full-scale quantitative estimate of the uncertainty associated with estimates of total economic benefits. If one is mindful of these limitations, the magnitude of the benefit estimates presented here can be useful information in expanding the understanding of the public health impacts of attaining the 8-hr ozone standard.
Table 1 Distribution of fourth highest maximum daily average O3 values across monitors.
Monitors with value in range (%)
Range of O3 values (ppb) 2000 (1,089 monitors) 2001 (1,120 monitors) 2002 (1,146 monitors)
≤84 (in attainment) 64 61 44
84–89.9 17 18 15
90–99.9 15 16 27
100–109.9 3 4 11
> 110 1 1 3
Table 2 Ozone-related health end points included in primary and sensitivity analyses.
Health effect Applied ages (years) Description Ozone metric
Premature mortality All Pooled estimate
Ito and Thurston (1996) 1-hr daily maximum
Moolgavkar et al. (1995b) 24-hr daily average
Samet et al. (1997) 24-hr daily average
All Sensitivity
WHO (2003) 8-hr average
Respiratory hospital admissions ≥65 Pooled estimate
Schwartz (1995): ICD-9 460–519 (all respiratory disease) 24-hr daily average
Schwartz (1994a, 1994b): ICD-9 480–486 (pneumonia)
Moolgavkar et al. (1997): ICD-9 480–487 (pneumonia)
Schwartz (1994b): ICD-9 491–492, 494–496 (COPD)
Moolgavkar et al. (1997): ICD-9 490–496 (COPD)
0 to < 2 Burnett et al. (2001) 24-hr daily average
Asthma-related ED visits All Pooled estimate
Weisel et al. (1995) 5-hr daily average
Cody et al. (1992) 5-hr daily average
Stieb et al. (1996) 24-hr daily average
5–34 Sensitivity
Jaffe et al. (2003) 8-hr daily maximum
Other health effects School loss daysa Pooled estimate
5–17 Gilliland et al. (2001) 8-hr daily average
5–17 Chen et al. (2000) 1-hr daily maximum
MRADs 18–65 Ostro and Rothschild (1989) 24-hr daily average
COPD, chronic obstructive pulmonary disease.
a Gilliland et al. (2001) studied children 9 and 10 years of age. Chen et al. (2000) studied children 6–11 years of age. Based on recent advice from the National Research Council (2002) and the U.S. EPA Science Advisory Board Health Effects Subcommittee, we have calculated reductions in school absences for all school-age children based on the biologic similarity among children 5–17 years of age.
Table 4 Unit values for economic valuation of health end points (2000 US$).
Health end point Description Mean estimate adjusted for income growth to 2000a Distribution
Mortality VSL based on 26 studies $6.5 million per statistical life The $6.5 million estimate is the mean of a Weibull distribution fitted to the estimates from 26 value-of-life studies identified in U.S. EPA section 812 reports (e.g., U.S. EPA 1999) as “applicable to policy analysis.” Five of the 26 studies are contingent valuation studies, which directly solicit WTP information from surveyed subjects. The remainder are wage-risk studies, which base WTP estimates on estimates of the additional compensation demanded for riskier jobs.
Hospital admissions All respiratory, ≥65 years of age $18,353 per admission No distributions available. The COI point estimates (lost earnings plus direct medical costs) are based on ICD-9 code-level information (e.g., average hospital care costs, average length of hospital stay, and weighted share of total COPD category illnesses) reported in Agency for Healthcare Research and Quality (2000).
All respiratory, 0 to < 2 years of age $7,741 per admission
ED visits Asthma-related $286 per visit No distribution available. The COI point estimate is the simple average of two unit COI values: $312 from Smith et al. (1997), and $261 from Stanford et al. (1999).
Minor effects MRAD $52 per day Median WTP estimate to avoid one MRAD from Tolley et al. (1986). Distribution is assumed to be triangular with a minimum of $22 and a maximum of $83. Range is based on assumption that value should exceed WTP for a single mild symptom (the highest estimate for a single symptom —for eye irritation—is $16.00) and be less than that for a work loss day. The triangular distribution acknowledges that the actual value is likely to be closer to the point estimate than either extreme.
School absences $75 per day No distribution available.
a The derivation of each of the estimates is discussed in the text. COI-based unit values are not adjusted for income growth because they are based on current costs and wage rates. These include hospital admissions, ED visits, and school absences.
Table 3 National average baseline incidence rates.
Rate per 100 people per year by age group (years)b
End point Sourcea Notes < 18 18–24 25–34 35–44 45–54 55–64 ≥ 65
Mortality CDC compressed mortality file, nonaccidental, accessed through CDC WONDER (1996–1998) Nonaccidental 0.025 0.022 0.057 0.150 0.383 1.006 4.937
Respiratory hospital admissions 1999 NHDS public use data files Incidence 0.043 0.084 0.206 0.678 1.926 4.389 11.629
Asthma ED visits 2000 NHAMCS public use data files 1999 NHDS public use data files Incidence 1.011 1.087 0.751 0.438 0.352 0.425 0.232
MRADs Ostro and Rothschild (1989) Incidence NA 780 780 780 780 780 NA
School loss days U.S. Department of Education (1996) and 1996 HIS (Adams et al. 1999, Table 47), estimate of 180 school days per year All-cause 990.0 NA NA NA NA NA NA
Abbreviations: CDC, Centers for Disease Control and Prevention; NA, not applicable.
a The following abbreviations are used to describe the national surveys conducted by the National Center for Health Statistics: CDC WONDER, CDC Wide-Ranging Online Data for Epidemiological Research (CDC 2004a); HIS, National Health Interview Survey (CDC 2004b); NHDS, National Hospital Discharge Survey (CDC 2004c); NHAMCS, National Hospital Ambulatory Medical Care Survey (CDC 2004d).
b All of the rates reported here are population-weighted incidence rates per 100 people per year. Additional details on the incidence and prevalence rates, as well as the sources for these rates are available upon request.
Table 5 Summary of estimated annual health benefits of attaining the 8-hr standard.
2000
2001
2002
End point Cases Economic valuea Cases Economic valuea Cases Economic valuea
Quadratic rollback
Premature mortality 560 3,600 670 4,400 1,300 8,400
Hospital admissions, respiratory, adults 1,500 27 1,900 34 3,600 67
Total hospital admissions, respiratory, children 1,700 13 1,600 13 2,900 23
ED visits for asthma 370 0.11 410 0.12 750 0.22
School absences 740,000 55 780,000 59 1,400,000 110
MRADs 950,000 49 1,100,000 55 2,000,000 100
Total economic value of health changes
With premature mortality 3,700 4,600 8,700
Without premature mortality 140 160 300
Percentage rollback
Premature mortality 500 3,200 590 3,300 1,160 7,600
Hospital admissions, respiratory, adults 1,300 24 1,600 17 3,200 60
Total hospital admissions respiratory, children 1,500 12 1,500 3 2,700 21
ED visits for asthma 330 0.10 360 0.05 680 0.20
School absences 660,000 50 700,000 27 1,300,000 97
MRADs 850,000 44 950,000 18 1,800,000 93
Total economic value of health changes
With premature mortality 3,300 3,400 7,900
Without premature mortality 130 70 270
a Million (2000 US$).
Table 6 Estimated average annual health benefits of attaining 8-hr standard (2000–2002 monitor data).
Cases
Economic value (million 2000 US$)
Endpoint Age range (years) 5th Mean 95th 5th Mean 95th
Quadratic rollback
Premature mortality All 290 840 1,600 500 5,500 15,000
Hospital admissions, respiratory, adults ≥65 530 2,300 4,600 10 43 84
Total hospital admissions, respiratory, children 0 to <2 1,100 2,100 3,100 8.70 16 24
ED visits for asthma All 180 510 870 0.05 0.15 0.26
School absences 5–17 350,000 970,000 1,700,000 26 75 130
MRADs 18–64 670,000 1,400,000 2,000,000 28 68 110
Total economic value of health changes
With premature mortality 570 5,700 15,000
Without premature mortality 70 200 350
Percentage rollback
Premature mortality All 260 750 1,400 470 4,700 13,000
Hospital admissions, respiratory, adults ≥65 470 2,000 4,100 8.70 34 76
Total hospital admissions, respiratory, children 0 to <2 970 1,900 2,800 7.70 12 22
ED visits for asthma All 150 460 770 0.04 0.12 0.23
School loss days 5–17 310,000 890,000 1,500,000 23 58 120
MRADs 18–64 610,000 1,200,000 1,800,000 26 52 110
Total economic value of health changes
With premature mortality 530 4,900 14,000
Without premature mortality 65 160 310
5th and 95th percentile estimates based on the Monte Carlo simulations described in the text.
Table 7 Sensitivity of mean estimated annual health effects of attaining the 8-hr standard relative to 2001 monitor values, to ordinality, attainment metric background (AMB), and hourly background (HB) (cases).
End point Base A B C D
Quadratic rollback
Premature mortality 700 1,600 700 300 500
Hospital admissions, respiratory
Adults 1,900 4,600 2,000 700 1,300
Children 1,630 3,890 1,730 1,110 2,010
ED visits for asthma 410 970 430 220 400
School loss days 780,000 1,900,000 840,000 520,000 950,000
MRADs 1,100,000 2,600,000 1,100,000 430,000 760,000
Percentage rollback
Premature mortality 600 2,800 1,100 400 900
Hospital admissions, respiratory
Adults 1,600 8,100 3,100 1,100 2,500
Children 1,460 6,840 2,620 1,770 4,010
ED visits for asthma 360 1,900 650 340 750
School loss days 700,000 3,300,000 1,300,000 840,000 1,900,000
MRADs 950,000 4,500,000 1,700,000 660,000 1,400,000
Sensitivity tests (Base, A–D) were conducted using the VNA interpolation method with no distance limit. Ordinality refers to the nth highest value used to determine attainment with the level of the standard. For example, the form of the 8-hr standard specifies the fourth highest maximum 8-hr average. The ordinality in this case is 4. Attainment metric background (AMB) refers to the assumed level of the attainment standard (fourth highest maximum 8-hr average) that would exist in the absence of domestic man-made emissions of ozone precursors. Hourly background (HB) refers to the assumed level of ozone at any hour that would exist in the absence of domestic man-made emissions of ozone precursors. Ordinality, AMB, and HB are, respectively, 4, 40, 0 for Base; 1, 0, 0 for A; 4, 0, 0 for B; 4, 40, 40 for C; and 1, 40, 40 for D.
==== Refs
References
Adams PF Hendershot GE Marano MA 1999 Current estimates from the National Health Interview Survey, 1996 Vital Health Stat 10 200 1 212
Agency for Healthcare Research and Quality 2000. HCUPnet, Healthcare Cost and Utilization Project. Rockville, MD: Agency for Healthcare Research and Quality. Available: http://www.ahrq.gov/HCUPnet/ [accessed 29 September 2004].
Anderson HR Atkinson RW Peacock JL Marston L Konstantinou K 2004. Meta-analysis of Time-Series Studies and Panel Studies of Particulate Matter (PM) and Ozone (O3): Report of a WHO Task Group. Copenhagen:World Health Organization.
Bell ML McDermott A Zeger SL Samet JM Dominici F 2004 Ozone and short-term mortality in 95 U.S. urban communities, 1987–2000 JAMA 292 2372 2378 15547165
Berger MC Blomquist GC Kenkel D Tolley GS 1987 Valuing changes in health risks: a comparison of alternative measures South Econ J 53 977 984
Burnett RT Smith-Doiron M Stieb D Raizenne ME Brook JR Dales RE 2001 Association between ozone and hospitalization for acute respiratory diseases in children less than 2 years of age Am J Epidemiol 153 5 444 452 11226976
CDC 2004a. CDC WONDER. Atlanta, GA:Centers for Disease Control and Prevention. Available: http://wonder.cdc.gov [accessed 29 November 2004].
CDC 2004b. National Health Interview Survey (NHIS). Atlanta, GA:Centers for Disease Control and Prevention. Available: http://www.cdc.gov/nchs/nhis.htm [accessed 29 November 2004].
CDC 2004c. National Hospital Discharge Survey. Atlanta, GA:Centers for Disease Control and Prevention. Available: ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Datasets/NHDS/ [accessed 29 November 2004].
CDC 2004d. National Hospital Ambulatory Medical Care Survey. Atlanta, GA:Centers for Disease Control and Prevention. Available: ftp://ftp.cdc.gov/pub/Health_Statistics/NCHS/Datasets/NHAMCS [accessed 29 November 2004].
Chen J Zhao R Li Z 2004 Voronoi-based k-order neighbour relations for spatial analysis ISPRS J Photogrammetry Remote Sensing 59 1–2 60 72
Chen L Jennison BL Yang W Omaye ST 2000 Elementary school absenteeism and air pollution Inhal Toxicol 12 11 997 1016 11015140
Cody RP Weisel CP Birnbaum G Lioy PJ 1992 The effect of ozone associated with summertime photochemical smog on the frequency of asthma visits to hospital emergency departments Environ Res 58 2 184 194 1511672
Dominici F McDermott A Daniels M Zeger SL Samet JM 2003. Revised analyses of the National Morbidity, Mortality, and Air Pollution Study (NMMAPS), Part II: Mortality among residents of 90 cities. In: Revised Analyses of Time-Series Studies of Air Pollution and Health. Special Report. Boston:Health Effects Institute, 9–20.
Fairley D 2003. Mortality and air pollution for Santa Clara County, California, 1989–1996. In: Revised Analyses of Time-Series Studies of Air Pollution and Health. Special Report. Boston: Health Effects Institute, 97–106.
Freeman AM III 1993. The Measurement of Environmental and Resource Values: Theory and Methods. Washington, DC:Resources for the Future.
GeoLytics Inc 2002. Geolytics CensusCD® 2000 Short Form Blocks. CD-ROM Release 1.0. East Brunswick, NJ:GeoLytics, Inc. Available: http://www.geolytics.com/ [accessed 29 September 2004].
Gilliland FD Berhane K Rappaport EB Thomas DC Avol E Gauderman WJ 2001 The effects of ambient air pollution on school absenteeism due to respiratory illnesses Epidemiology 12 1 43 54 11138819
Gold C 1997. Voronoi methods in GIS. In: Algorithmic Foundation of Geographic Information Systems (van Kreveld M, Nievergelt J, Roos T, Widmayer P, eds). Lecture Notes in Computer Science, Vol. 1340. Berlin:Springer-Verlag, 21– 35.
Hall JV Brajer V Lurmann FW 2003 Economic valuation of ozone-related school absences in the south coast air basin of California Contemp Econ Pol 21 4 407 417
Harrington W Portney PR 1987 Valuing the benefits of health and safety regulation J Urban Econ 22 101 112
International Classification of Diseases, 9th Revision 1979. Hyattsville, MD:National Center for Health Statistics. Available: http://www.cdc.gov/nchs/about/major/dvs/icd9des.htm [accessed 29 September 2004].
Ito K Thurston GD 1996 Daily PM(10)/mortality associations: an investigation of at-risk subpopulations J Expo Anal Environ Epidemiol 6 1 79 95 8777375
Jaffe DH Singer ME Rimm AA 2003 Air pollution and emergency department visits for asthma among Ohio Medicaid recipients, 1991–1996 Environ Res 91 1 21 28 12550084
Kelsall J Samet JM Zeger SL 1997 Air pollution and mortality in Philadelphia, 1974–1988 Am J Epidemiol 146 750 762 9366623
Kinney PL Ito K Thurston GD 1995 A sensitivity analysis of mortality Pm-10 associations in Los Angeles Inhal Toxicol 7 1 59 69
Levy JI Carrothers TJ Tuomisto JT Hammitt JK Evans JS 2001 Assessing the public health benefits of reduced ozone concentrations Environ Health Perspect 109 1215 1226 11748028
Moolgavkar SH 2000 Air pollution and daily mortality in three U.S. counties Environ Health Perspect 108 777 784 10964799
Moolgavkar SH Luebeck EG Anderson EL 1997 Air pollution and hospital admissions for respiratory causes in Minneapolis St. Paul and Birmingham Epidemiology 8 4 364 370 9209848
Moolgavkar SH Luebeck EG Hall TA Anderson EL 1995a Air pollution and daily mortality in Philadelphia Epidemiology 6 5 476 484 8562622
Moolgavkar SH Luebeck EG Hall TA Anderson EL 1995b Particulate air pollution, sulfur dioxide, and daily mortality—a reanalysis of the Steubenville data Inhal Toxicol 7 1 35 44
National Research Council 2002. Estimating the Public Health Benefits of Proposed Air Pollution Regulations. Washington, DC:National Academies Press.
Ostro BD Rothschild S 1989 Air pollution and acute respiratory morbidity—an observational study of multiple pollutants Environ Res 50 2 238 247 2583069
Ransom MR Pope CA 1992 Elementary school absences and PM(10) pollution in Utah Valley Environ Res 58 2 204 219 1511674
Samet JM Zeger SL Kelsall JE Xu J Kalkstein LS 1997. Air Pollution, Weather, and Mortality in Philadelphia 1973–1988. Cambridge, MA:Health Effects Institute.
Schwartz J 1994a PM(10) Ozone, and hospital admissions for the elderly in Minneapolis St Paul, Minnesota Arch Environ Health 49 5 366 374 7944569
Schwartz J 1994b Air pollution and hospital admissions for the elderly in Detroit, Michigan Am J Respir Crit Care Med 150 3 648 655 8087333
Schwartz J 1995 Short term fluctuations in air pollution and hospital admissions of the elderly for respiratory disease Thorax 50 5 531 538 7597667
Smith DH Malone DC Lawson KA Okamoto LJ Battista C Saunders WB 1997 A national estimate of the economic costs of asthma Am J Respir Crit Care Med 156 3 pt 1 787 793 9309994
Stanford R McLaughlin T Okamoto LJ 1999 The cost of asthma in the emergency department and hospital Am J Respir Crit Care Med 160 1 211 215 10390402
Stieb DM Burnett RT Beveridge RC Brook JR 1996 Association between ozone and asthma emergency department visits in Saint John, New Brunswick, Canada Environ Health Perspect 104 1354 1360 9118879
Thurston GD Ito K 2001 Epidemiological studies of acute ozone exposures and mortality J Expo Anal Environ Epidemiol 11 4 286 294 11571608
Tolley GS Babcock L Berger M Bilotti A Blomquist G Brien M 1986. Valuing Health Symptoms and Risks. Washington, DC:U.S. Environmental Protection Agency. Available: http://yosemite1.epa.gov/ee/epa/eed.nsf/webpages/valuinghealthrisks.html [accessed 29 November 2004].
Toulomi G Katsouyanni K Zmirou D Schwartz J 1997 Short-term effects of ambient oxidant exposure on mortality: a combined analysis within the APHEA project Am J Epidemiol 146 177 183 9230780
U.S. Bureau of Labor Statistics 2004. Consumer Price Indexes. Available: http://www.bls.gov/cpi/home.htm [accessed 29 November 2004].
U.S. Census Bureau 2001. Statistical Abstract of the United States, 2001, Section 12: Labor Force, Employment, and Earnings, Table 521. Washington, DC:U.S. Census Bureau.
U.S. Department of Education 1996. The Condition of Education 1996, Indicator 42: Student Absenteeism and Tardiness. Washington, DC:National Center for Education Statistics.
U.S. EPA 1970. Clean Air Act. 40CFR50.
U.S. EPA 1996a. Review of National Ambient Air Quality Standards for Ozone: Assessment of Scientific and Technical Information. OAQPS Staff Paper. EPA-452/R-96-007. June. Research Triangle Park, NC:U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards.
U.S. EPA 1996b. Air Quality Criteria for Ozone and Related Photochemical Oxidants. Vol III. EPA-/600/P-93/004cF. Washington, DC:U.S. Environmental Protection Agency, Office of Research and Development.
U.S. EPA 1999. The Benefits and Costs of the Clean Air Act, 1990–2010. EPA-410-R-99-001. Washington, DC:U.S. Environmental Protection Agency, Office of Air and Radiation/Office of Policy Analysis and Review.
U.S. EPA 2003. Latest Findings on National Air Quality: 2002 Status and Trends. EPA 454/K-03-001. Washington, DC:U.S. Environmental Protection Agency, Office of Air and Radiation.
U.S. EPA 2004a. Benefits of the Proposed Inter-state Air Quality Rule. EPA 452/-03-001. Washington, DC:U.S. Environmental Protection Agency, Office of Air and Radiation. Available: http://www.epa.gov/interstateairquality/tsd0175.pdf [accessed 29 September 2004].
U.S. EPA 2004b. Final Regulatory Analysis: Control of Emissions from Nonroad Diesel Engines. EPA420/R-04-007. Washington, DC:U.S. Environmental Protection Agency, Office of Air and Radiation. Available: http://www.epa.gov/nonroad-diesel/2004fr/420r04007.pdf [accessed 29 September 2004].
U.S. EPA 2004c. Technology Transfer Network: Air Quality System. Washington, DC:U.S. Environmental Protection Agency. Available: http://www.epa.gov/ttn/airs/airsaqs/sysoverview.htm [accessed 29 November 2004].
Vingarzan R 2004 A review of surface ozone background levels and trends Atmos Environ 38 3431 3442
Weisel CP Cody RP Lioy PJ 1995 Relationship between summertime ambient ozone levels and emergency department visits for asthma in central New Jersey Environ Health Perspect 103 suppl 2 97 102 7614954
WHO 2003. Health Aspects of Air Pollution with Particulate Matter, Ozone and Nitrogen Dioxide: Report on a WHO Working Group. EUR/03/5042688. Bonn, Germany:World Health Organization.
Woods & Poole Economics Inc 2001. Population by Single Year of Age CD. CD-ROM. Washington, DC:Woods & Poole Economics, Inc.
|
15626651
|
PMC1253713
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan 7; 113(1):73-82
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7186
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7280ehp0113-00008315626652ResearchArticlesDietary Fat Interacts with PCBs to Induce Changes in Lipid Metabolism in Mice Deficient in Low-Density Lipoprotein Receptor Hennig Bernhard 12Reiterer Gudrun 2Toborek Michal 3Matveev Sergey V. 4Daugherty Alan 5Smart Eric 4Robertson Larry W. 61Molecular and Cell Nutrition Laboratory, College of Agriculture,2Graduate Center for Nutritional Sciences,3Department of Surgery,4Department of Pediatrics, and5Department of Cardiovascular Medicine, University of Kentucky, Lexington, Kentucky, USA6Department of Occupational and Environmental Health, College of Public Health, University of Iowa, Iowa City, Iowa, USAAddress correspondence to B. Hennig, Molecular and Cell Nutrition Laboratory, College of Agriculture, University of Kentucky, 591 Wethington Health Sciences Building, 900 South Limestone, Lexington, KY 40536-0200 USA. Telephone: (859) 323-4933 ext. 81387. Fax: (859) 257-1811. E-mail:
[email protected] study was supported in part by grants from the National Institute of Environmental Health Sciences/ National Institutes of Health (ES 07380), the U.S. Department of Agriculture (2001-35200-10675), and the Kentucky Agricultural Experimental Station.
The authors declare they have no competing financial interests.
1 2005 23 9 2004 113 1 83 87 24 5 2004 23 9 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. There is evidence that dietary fat can modify the cytotoxicity of polychlorinated biphenyls (PCBs) and that coplanar PCBs can induce inflammatory processes critical in the pathology of vascular diseases. To test the hypothesis that the interaction of PCBs with dietary fat is dependent on the type of fat, low-density lipoprotein receptor–deficient (LDL-R−/−) mice were fed diets enriched with either olive oil or corn oil for 4 weeks. Half of the animals from each group were injected with PCB-77. Vascular cell adhesion molecule-1 (VCAM-1) expression in aortic arches was non-detectable in the olive-oil–fed mice but was highly expressed in the presence of PCB-77. PCB treatment increased liver neutral lipids and decreased serum fatty acid levels only in mice fed the corn-oil–enriched diet. PCB treatment increased mRNA expression of genes involved in inflammation, apoptosis, and oxidative stress in all mice. Upon PCB treatment, mice in both olive- and corn-oil–diet groups showed induction of genes involved in fatty acid degradation but with up-regulation of different key enzymes. Genes involved in fatty acid synthesis were reduced only upon PCB treatment in corn-oil–fed mice, whereas lipid transport/export genes were altered in olive-oil–fed mice. These data suggest that dietary fat can modify changes in lipid metabolism induced by PCBs in serum and tissues. These findings have implications for understanding the interactions of nutrients with environmental contaminants on the pathology of inflammatory diseases such as atherosclerosis.
atherosclerosisdietary fatgene expressionlipid metabolismPCBpolychlorinated biphenylvascular endothelial cells
==== Body
From epidemiologic studies, there is substantial evidence that cardiovascular diseases are linked to environmental pollution and that exposure to polycyclic and/or polyhalogenated aromatic hydrocarbons can lead to human cardiovascular toxicity. For example, one study found a significant increase in mortality from cardiovascular diseases among Swedish capacitor manufacturing workers exposed to polychlorinated biphenyls (PCBs) for at least 5 years (Gustavsson and Hogstedt 1997), and in another study most excess deaths were due to cardiovascular disease in power workers exposed to phenoxy herbicides and PCBs in waste transformer oil (Hay and Tarrel 1997). The increased prevalence of atherosclerosis may be associated with the ability of PCBs to modulate plasma and tissue lipids, events that can result in compromised lipid metabolism and lipid-dependent cellular signaling pathways. In a study with rhesus monkeys, Bell et al. (1994) found a causal relationship between plasma lipid changes and PCB intake after oral exposure of Aroclor 1254. Moreover, a report by Tokunaga et al. (1999) confirms many other studies with chronic Yusho patients (accidental ingestion of rice-bran oil contaminated with PCBs), which showed in this population that elevated serum levels of triglycerides and total cholesterol were significantly associated with the blood PCB levels. Serum lipids also have been shown to be affected by PCBs, which apparently can modify the regulatory mechanisms of synthesis and degradation of cholesterol (Jenke 1985). A major route of exposure to PCBs in humans is via oral ingestion of contaminated food products (Safe 1994). Therefore, circulating environmental contaminants derived from diets, such as PCBs, are in intimate contact with the vascular endothelium.
In addition to serum and vascular lipid changes, a number of studies have reported an increase in liver and hepatic microsomal lipids (total lipids, phospholipids, neutral lipids, and cholesterol) after PCB administration (Garthoff et al. 1977; Ishidate et al. 1978). Asais-Braesco et al. (1990) reported that a single injection of PCB-77 resulted in a marked change in the fatty acid composition of rat hepatic microsomal fractions. Also, Matsusue et al. (1999) found that coplanar PCBs have a significant effect on the reduced synthesis of physiologically essential long-chain unsaturated fatty acids, such as arachidonic acid in rat liver, by suppressing delta-5 and delta-6 desaturase activities and thus allowing the omega-6 parent fatty acid, linoleic acid, to accumulate.
Little is known about the interaction of dietary fats and PCBs in the pathology of atherosclerosis. We have reported a significant disruption in endothelial barrier function when cells were exposed to linoleic acid (Hennig et al. 2001a). In addition to endothelial barrier dysfunction, another functional change in atherosclerosis is the activation of the endothelium that manifests as an increase in the expression of specific cytokines and adhesion molecules. These cytokines and adhesion molecules are proposed to mediate the inflammatory aspects of atherosclerosis by regulating the vascular entry of leukocytes. We reported previously that coplanar PCBs and linoleic acid induce the expression of cytokines and adhesion molecules in cultured endothelial cells (Hennig et al. 2002; Toborek et al. 2002). In addition, both linoleic acid and PCB-77—and more markedly when applied in combination—can generate reactive oxidative species that can trigger oxidative-stress–sensitive proinflammatory signaling pathways (Hennig et al. 2002a). These studies suggest that environmental contaminants such as PCBs are atherogenic in part by their ability to alter endothelial cell lipid profile and metabolism and by inducing oxidative stress and pro-inflammatory genes.
Exposure to physiologic concentrations of specific fatty acids, such as linoleic acid, can trigger inflammatory pathways leading to the up-regulation of inflammatory cytokines [e.g., interleukin-6 (IL-6), IL-8] and adhesion molecules [e.g., vascular cell adhesion molecule-1 (VCAM-1), E-selectin]. These genes initiate the chemoattraction and adhering of monocytes, events occurring early in the pathogenesis of atherosclerosis. The differential effect of various fatty acids is most likely due to different susceptibility to oxidation and thus generation of oxidative stress as well as their role in precursors of lipid-derived second messengers (Hennig and Toborek 2001). Therefore, we hypothesize that selected dietary lipids may modulate the atherogenicity of environmental chemicals by interfering with metabolizing and inflammatory pathways and thus leading to dysfunction of the vasculature and related tissues.
The present data indicate that dietary fat can modify changes in lipid metabolism induced by PCB in a low-density-lipoprotein (LDL)-receptor–deficient (LDL-R−/−) mouse model, that is, mice that develop atherosclerosis as a result of increased sensitivity to different types of dietary fat (Daugherty 2002). Our data also support our hypothesis that dietary oils rich in linoleic acid can further compromise gene expression during PCB cytotoxicity.
Materials and Methods
Animal model and PCB treatment.
The LDL-R−/− mice used in this study were originally obtained from the Jackson Laboratory (stock no. 002207; Bar Harbor, ME) and bred at the University of Kentucky. LDL-R−/−mice have become a preferred model for atherosclerosis because their elevated LDL fraction resembles the lipoprotein profile of hypercholesterolemic humans (Daugherty 2002). All animal procedures were in compliance with the institutional animal care and use committee guidelines of the University of Kentucky. Mice were divided into four groups of five mice per treatment: olive-oil–rich diet, olive-oil–rich diet plus PCB injection, corn-oil–rich diet, and corn-oil–rich diet plus PCB injection. Mice were injected intraperitoneally with PCB-77 [170 μmol/kg body weight (bw)] or the vehicle (olive oil or corn oil; Dyets Inc., Bethlehem, PA) at weeks 1 and 3 of the 4-week feeding study.
After completion of the study, animals were euthanized using intraperitoneal ketamine injections. Serum and aortic and liver tissues were obtained for analysis. According to our combined experience with several animal species, long-term intraperitoneal injections of 100–300 μmol/kg bw per injection are sufficient to initiate disease states, such as tumor promotion (Robertson et al. 1991). In our preliminary studies, we saw adhesion molecule expression at 170 μmol/kg bw per injection; thus, this concentration was chosen for the present study. This amount of PCB was based on calculated values from our in vitro experiments that were themselves based on levels that are usually found in humans after acute exposure (Jensen 1989; Wassermann et al. 1979).
Experimental diets.
We chose corn and olive oils because of previous cell culture work with individual fatty acids (Toborek et al. 2002). In these experiments, linoleic acid was able to amplify the inflammatory response of endothelial cells exposed to PCB-77. In addition, we have evidence that a high-corn-oil diet is proinflammatory and induces atherosclerotic pathology relative to a high-olive-oil diet (B. Hennig, unpublished data). We therefore chose corn oil because it contains about 50% linoleic acid as triglycerides, and thus is a significant dietary source of linoleic acid. As a control, we chose olive oil, with the predominant fatty acid being oleic acid. Oleic acid is also an 18-carbon fatty acid but acted “neutral” when endothelial cells were coexposed to oleic acid and PCB-77 (B. Hennig, unpublished data). In fact, our previous studies suggest that oleic acid has little effect or even can decrease an inflammatory response (Toborek et al. 2002).
Diets were custom prepared and vacuum packed (Dyets Inc.). Diets were based on a modified AIN-76A purified rodent diet (Reeves 1997) with varying sources of fat. The dietary fat content, either olive oil or corn oil, was 150 g/kg total diet. The antioxidant content of each oil was adjusted by the manufacturer. The fatty acid composition in the different oils is shown in Figure 1.
Serum fatty acid analysis.
Total plasma lipids were extracted by the method of Bligh and Dyer (1959) as modified by Williams et al. (1984). Internal standard (heneicosanoic acid, 5 μg in methanol) was added to the samples before lipid extraction. All solvents for liquid extraction contained 50 mg/L butylated hydroxytoluene as an antioxidant (Silversand and Haux 1997). Lipids were dried under nitrogen followed by fatty acid esterification with boron trifluoride–methanol. Fatty acid methyl esters were extracted with hexane for gas chromatography injection. The gas chromatograph (Agilent 6890 GC G2579A system; Agilent Technologies, Palo Alto, CA) was equipped with an OMEGAWAX 250 capillary column. The following temperature program was used: 160°C for 5 min, an increase in temperature to 220°C at a rate of 2°C/min, followed by 220°C for 15 min. A model 5973 mass-selective detector (Agilent Technologies) was used for detection of separated lipids.
Neutral lipid staining of liver tissues.
Liver sections were fixed overnight in 4% para-formaldehyde in phosphate-buffered saline (PBS) before embedding in OCT (optimal cutting temperature) compound (Fisher Scientific, Pittsburgh, PA). Serial (10 μm) sections were mounted on MicroProbe slides (Fisher Scientific), and neutral lipids were stained with Oil Red O, as described previously (Daugherty et al. 2000).
Immunostaining of aortic tissue.
Aortic tissue from the thoracic regions was excised, immersed in OCT embedding medium, and frozen at −20°C, and 8 μm sections were cut on a cryostat. Immunocytochemistry was performed as described previously (Daugherty et al. 2000). Briefly, endogenous peroxidase was inactivated using hydrogen peroxide (3%) in methanol. Samples were blocked in the serum of the secondary antibody host. Primary antibodies for VCAM-1 (PharMingen, San Diego, CA) were detected using biotinylated secondary antibodies and peroxidase ABC kits (Vectastain, Burlingame, CA). Aminoethylcarbazole was used as chromogen, and sections were counterstained with hematoxylin.
Gene expression analysis.
For microarray analysis, total RNA was isolated from snap frozen liver tissue using RNAeasy (Quiagen, Valencia, CA). RNA samples were pooled for analysis of two data sets per treatment group. RNA integrity analysis and biotin-labeling of cRNA was performed by the Microarray Core Facility at the University of Kentucky. Labeled RNA was spotted on Murine Genome MOE 430 chips and detected in the Affymetrix 428 fluorescence reader (both from Affymetrix, Santa Clara, CA).
Microarray data were confirmed by conventional reverse-transcription polymerase chain reaction (RT-PCR). RNA was isolated from liver samples. cDNA was generated by RT and amplified by PCR using the following primers: cytochrome P450 1A1 (CYP1A1), forward 5′-CAGATGATAAGGTCAT-CACGA-3′, reverse 5′-TTGGGGATAT-AGAAGCCATTC-3′; acetyl-coenzyme A (CoA)-carboxylase, forward 5′-ACAG-TGAAGGCTTACGTCTG-3′, reverse 5′-AGGATCCTTACAACCTCTGC-3′; and β-actin, forward 5′-ATGGATGAC-GATATCGCT-3′, reverse 5′-ATGAGG-TAGTCTGTCAGGT-3′. PCR products were separated on a 2% agarose gel, stained with SYBR gold, and visualized using a phosphoimager (Fuji FLA-5000; Fuji Medical Systems, Stamford, CT).
Quantitations and statistical analyses.
Numeric data were analyzed using SYSTAT 7.0 (SPSS, Inc., Chicago, IL). Comparisons between treatments were made by one-way ANOVA with post hoc comparisons of the means made by Bonferroni least significance difference procedure. Student t-tests were employed to compare gene expression data showing a PCB-dependent change. Statistical probability of p < 0.05 was considered significant.
Photomicrographs of VCAM-1 and neutral lipid staining in aortic roots and livers, respectively, were evaluated by individuals who were blinded to the specimen identification.
Results
PCB treatment increases diet-dependent clearance of serum fatty acids.
As expected, feeding a diet enriched with olive oil or corn oil resulted in serum fatty acid profiles (Figure 2) comparable with the fatty acid profile in the respective oils (Figure 1). PCB treatment had little effect on fatty acid patterns in animals fed the olive oil diet. In contrast, PCB treatment of corn-oil–fed mice resulted in marked decreases in major serum fatty acids, with a quantitatively most significant serum clearance of serum linoleic acid.
PCBs increase neutral lipid staining in liver tissue.
Baseline or control lipid staining (Oil Red O) appeared to be similar in liver tissues from both olive-oil– and corn-oil–fed mice. In contrast to the olive oil group, PCB exposure further increased neutral lipid staining only in LDL-R−/− mice fed the corn-oil–enriched diet (Figure 3).
VCAM-1 expression is affected by diet and PCBs.
VCAM-1 expression was negligible in mice fed the olive-oil–enriched diet (Figure 4A), whereas, corn-oil–fed mice exhibited elevated VCAM-1 expression (Figure 4C). In corn-oil–fed mice, PCB treatment further increased VCAM-1 staining in aortic tissues (Figure 4D). PCB treatment markedly increased VCAM-1 expression at the vascular surface in all animals, independent of dietary fat. Interestingly, PCB treatment increased VCAM-1 expression in smooth-muscle–rich areas of the vessel in mice fed the corn-oil–enriched diet (Figure 4D). This phenomenon was not observed in mice fed the olive-oil–enriched diet.
Gene expression change in response to PCB-77 in mice fed a high-corn or high-olive-oil diet.
PCB treatment markedly increased expression of selected genes involved in inflammation, apoptosis, and oxidative stress in both diet groups (Table 1). Data represent expression values of both dietary groups compared with both dietary groups receiving PCBs. The oil-dependent effect of PCB-77 was most apparent in mRNA levels of genes involved in lipid metabolism (Table 2). Feeding diets rich in either corn or olive oil induced fatty acid degradation but with up-regulation of different key enzymes. For example, PCB treatment induced carnitine palmitoyltransferase in corn-oil–fed animals, whereas glycerol-3-P-dehydrogenase and fatty acid CoA ligase 4 were induced in olive-oil–fed mice. Genes involved in fatty acid synthesis, such as acetyl-CoA-carboxylase and elongation of long-chain fatty acids were reduced only by PCB-77 in corn-oil–fed mice, whereas lipid transport/export genes such as fatty acid binding protein 2 and 4, ATP-binding cassette A1, and apolipoprotein A-IV were altered in olive-oil–fed mice in response to PCBs.
Microarray analysis of selected genes was confirmed by conventional RT-PCR. For example, PCB treatment only decreased expression of the acetyl-CoA-carboxylase gene in mice fed the corn oil diet (Figure 5A). As expected, PCB treatment increased CYP1A1 gene expression in all mice (Figure 5B).
Discussion
There is substantial evidence that environmental pollution can be correlated with the incidence of cardiovascular diseases (Hennig et al. 2001b). This might be due to a PCB-mediated impairment of lipid metabolism. In the vasculature, alterations in lipid profile and lipid metabolism as a result of exposure to PCBs may be important components of endothelial cell dysfunction (Hennig et al. 2002a). Endothelial cell dysfunction is an important factor in the overall regulation of vascular lesion pathology. We have reported recently that PCB-77 can increase expression of cytokines, such as IL-6, and adhesion molecules, such as VCAM-1, in cultured endothelial cells (Hennig et al. 2002b). Little is known about the interaction of dietary fats and PCBs in the pathology of atherosclerosis. We hypothesize that selected dietary lipids, and especially oils rich in linoleic acid, may increase the atherogenicity of environmental chemicals, such as PCBs, by cross-amplifying mechanisms leading to dysfunction of the vasculature and related tissues. Indeed, immunohistochemistry data from the present study demonstrate the cumulative effect of corn oil and PCB-77 on aortic VCAM-1 expression. Although olive-oil–fed mice did not show expression of this adhesion molecule unless they were injected with PCBs, corn oil feeding alone already resulted in a strong staining for VCAM-1. In corn-oil–fed mice injected with PCBs, VCAM-1 expression could even be detected in the sub-endothelial space, suggesting a progressed state of atherosclerosis with adhesion molecule expression on smooth muscle cells. These data are in agreement with epidemiologic studies that suggest diets high in olive oil or oleic acid protect against cardiovascular diseases (Massaro and De Caterina 2002). However, the interaction of different dietary fats with environmental contaminants and the effect on the pathogenesis of atherosclerosis is unknown and has not been studied in LDL-R−/− mice.
There is considerable evidence that exposure to PCBs can lead to lipid changes in plasma and tissues and that this may be linked to lipophylic properties of PCBs and their interaction with lipids and especially with fatty acids. For example, exposure to Aroclor 1242 modified adipose tissue fatty acids, with a decrease of highly unsaturated fatty acids and an increase in monounsaturated fatty acids in membrane phospholipids (Kakela and Hyvarinen 1999). Our microarray analysis of liver mRNA suggests that PCB–lipid interactions are dependent on the type of dietary fat. For example, the PCB-mediated up-regulation of genes involved in fatty acid uptake and catabolism, as well as down-regulation of genes involved in fatty acid synthesis, involved different key enzymes depending on the oil that was used in the diet. It appears that PCBs had more effect on fatty acid synthesis in corn-oil–fed animals, whereas there was a greater change in genes involved in fatty acid transport in olive-oil–fed mice.
Overall, lipid metabolism was affected to a greater extent in corn-oil–fed animals as demonstrated also by serum and liver lipid analyses. Lipids appear to be removed from the plasma and accumulate in tissues in corn-oil–fed animals receiving PCB injection. A number of studies have reported an increase in liver and hepatic microsomal lipids (total lipids, phospholipids, neutral lipids, and cholesterol) after PCB administration (Asais-Braesco et al. 1990; Garthoff et al. 1977; Hinton et al. 1978; Ishidate et al. 1978; Robertson et al. 1991). The amplified toxicity of linoleic acid and PCBs to endothelial cells could thus be mediated by cellular accumulation of this fatty acid and its subsequent transformation to toxic cytotoxic epoxide metabolites (Viswanathan et al. 2003). Because of the very low basal activity of endothelial cell delta-6 desaturase, arachidonic acid is not produced from linoleic acid significantly in this type of cell (Debry and Pelletier 1991; Spector et al. 1981), which can result in linoleic acid accumulation within endothelial cells (Hennig and Watkins 1989; Spector et al. 1981). Furthermore, Matsusue et al. (1999) demonstrated that coplanar PCBs can suppress delta-5 and delta-6 desaturase activities. The decreased expression of the long-chain fatty acid elongase detected in corn-oil–fed mice treated with PCBs also suggests an impairment in fatty acid metabolism. Using endothelial cell culture models, we showed previously that linoleic acid uptake and cellular accumulation of this fatty acid are markedly increased in the presence of PCB-77, further supporting our hypothesis that PCB-induced endothelial cell dysfunction can be modulated by the cellular lipid milieu (Slim et al. 2001).
In summary, our data clearly demonstrate a selective interaction of diet, and especially dietary fats, with PCB-induced cellular functions. These findings may contribute to a better understanding of the interactive mechanisms of dietary fats and environmental contaminants as mediators of vascular endothelial cell dysfunction and vascular pathologies such as atherosclerosis.
Figure 1 Fatty acid analysis of the two oils used in the feeding study. Fatty acids are measured in g/100 g total fatty acids; palmitic acid, 16:0; stearic acid, 18:0; oleic acid, 18:1; linoleic acid, 18:2; arachidonic acid, 20:4.
Figure 2 Fatty acid profile in serum. See “Materials and Methods” for details. Values are mean ± SEM (n = 5). Palmitic acid, 16:0; stearic acid, 18:0; oleic acid, 18:1; linoleic acid, 18:2; arachidonic acid, 20:4.
*Significantly different from respective diet treatment without PCBs.
Figure 3 Lipid staining of mouse liver sections. (A) Olive oil. (B) Olive oil plus PCB. (C) Corn oil. (D) Corn oil plus PCB. See “Materials and Methods” for details. Magnification, 200×.
Figure 4 Immunoreactivity of VCAM-1 antiserum against sections of mouse aortic arches. (A) Olive oil. (B) Olive oil plus PCB. (C) Corn oil. (D) Corn oil plus PCB. See “Materials and Methods” for details. Red staining reflects positive chromogen development for VCAM-1 immunostaining on the endothelial surface (B–D) and in subendothelial tissue (D). Magnification, 400×.
Figure 5 mRNA expression of acetyl-CoA-carboxylase (A) and CYP1A1 (B) as analyzed by RT-PCR; gels below show one representative sample per treatment group of RT-PCR. Abbreviations: CO, corn oil; OO, olive oil. See “Materials and Methods” for details. Values are mean ± SEM (n = 5); values are normalized to β-actin.
*Significantly different from all other groups, p < 0.05.
Table 1 PCB-mediated up-regulation of mRNA expression of selected genes involved in inflammation, apoptosis, and oxidative stress.
High-fat diets (mean ± SEM) High-fat diets + PCB (mean ± SEM) p-Value
Inflammation
Neuronal pentraxin 33.0 ± 5.3 118.2 ± 8.2 0.01
Amyloid beta (A4) precurser 1315.6 ± 3.0 1954.6 ± 2.0 0.12
IL-6 signal transducer 129.6 ± 31.3 229.4 ± 20.5 0.04
IL-2 receptor, gamma chain 177.9 ± 28.6 331.1 ± 42.5 0.02
Matrix metalloproteinase 19 95.8 ± 23.9 124.95 ± 28.9 0.47
Membrane metalloendopeptidase 110.9 ± 13.2 159.13 ± 30.0 0.19
Apoptosis
Caspase 6 490.9 ± 67.7 703.5 ± 41.6 0.04
Caspase 7 183.8 ± 40.6 326.9 ± 1.9 0.01
Caspase 8 and FADD-like 79.4 ± 13.0 134.0 ± 32.5 0.17
Apoptosis inhibitor 5 83.7 ± 11.5 147.9 ± 13.6 0.01
Oxidative stress
CYP1A1 692.1 ± 465.0 2999.8 ± 691.1 0.03
CYP1A2 8823.9 ± 2118.8 16927.4 ± 979.0 0.01
NADPH oxidase 4 625.8 ± 150.4 844.5 ± 50.6 0.22
Superoxide dismutase 2 125.1 ± 15.6 204.9 ± 18.3 0.02
Table 2 Relative expression changes of genes involved in lipid metabolism upon PCB-77.
Gene Function Olive oil Corn oil
Carnitine palmitoyl-transferase 1 Fatty acid degradation — ↑↑
Glycerol-3-P-dehydrogenase Fatty acid degradation ↑↑ —
Fatty acid CoA ligase 4 Fatty acid degradation ↑↑ —
Acetyl-CoA-carboxylase β Fatty acid synthesis — ↓↓
Long-chain fatty acyl elongase Fatty acid elongation — ↓↓
CD 36 Fatty acid uptake — ↑
Fatty acid binding protein 4 Fatty acid transport ↓ —
Fatty acid binding protein 2 Fatty acid transport ↓↓ —
ATP-binding cassette A1 Cholesterol export ↓↓ —
Apolipoprotein A-IV Lipoprotein metabolism ↑↑ —
HDL binding protein Lipoprotein metabolism ↓↓ —
CYP1A1 Fatty acid metabolism ↑↑ ↑↑
Data shown refer to ratios of diet alone compared with diet plus PCB-77 within each dietary treatment: —, no change; ↑ and ↓, ≥1.5-fold change; ↑ ↑ and↓↓, ≥2-fold change.
==== Refs
References
Asais-Braesco V Macaire JP Bellenand P Robertson LW Pascal G 1990 Effects of two prototypic polychlorinated biphenyls (PCBs) on lipid composition of rat liver and serum J Nutr Biochem 1 350 354 15539224
Bell FP Iverson F Arnold D Vidmar TJ 1994 Long-term effects of Aroclor 1254 (PCBs) on plasma lipid and carnitine concentrations in rhesus monkey Toxicology 89 139 153 8197591
Bligh EG Dyer WJ 1959 A rapid method of total lipid extraction and purification Can J Med Sci 37 911 917
Daugherty A 2002 Mouse models of atherosclerosis Am J Med Sci 323 3 10 11814139
Daugherty A Manning MW Cassis LA 2000 Angiotensin II promotes atherosclerotic lesions and aneurysms in apolipo-protein E-deficient mice J Clin Invest 105 1605 1612 10841519
Debry G Pelletier X 1991 Physiological importance of omega-3/omega-6 polyunsaturated fatty acids in man. An overview of still unresolved and controversial questions Experientia 47 172 178 2001722
Garthoff LH Friedman L Farber TM Locke KK Sobotka TJ Green S 1977 Biochemical and cytogenetic effects in rats caused by short-term ingestion of Aroclor 1254 or Firemaster BP6 J Toxicol Environ Health 3 769 796 201769
Gustavsson P Hogstedt C 1997 A cohort study of Swedish capacitor manufacturing workers exposed to polychlorinated biphenyls (PCBs) Am J Ind Med 32 234 239 9219652
Hay A Tarrel J 1997 Mortality of power workers exposed to phenoxy herbicides and polychlorinated biphenyls in waste transformer oil Ann NY Acad Sci 837 138 156 9472337
Hennig B Hammock BD Slim R Toborek M Saraswathi V Robertson LW 2002a PCB-induced oxidative stress in endothelial cells: modulation by nutrients Int J Hyg Environ Health 205 95 102 12018021
Hennig B Meerarani P Slim R Toborek M Daugherty A Silverstone AE 2002b Proinflammatory properties of coplanar PCBs: in vitro and in vivo evidence Toxicol Appl Pharmacol 181 174 183 12079426
Hennig B Slim R Toborek M Hammock B Robertson LW 2001b. PCBs and cardiovascular disease: endothelial cells as a target for PCB toxicity. In: PCBs: Recent Advances in Environmental Toxicity and Health Effects (Robertson LW, Hansen LG, eds). Lexington, KY:University Press of Kentucky, 211–220.
Hennig B Toborek M 2001 Nutrition and endothelial cell function: implications in atherosclerosis Nutr Res 21 279 293
Hennig B Toborek M McClain CJ 2001a High-energy nutrients, fatty acids and endothelial cell function: implications in atherosclerosis J Am Coll Nutr 20 97 105 11349944
Hennig B Watkins BA 1989 Linoleic acid and linolenic acid: effect on permeability properties of cultured endothelial cell monolayers Am J Clin Nutr 49 301 305 2563626
Hinton DE Glaumann H Trump BF 1978 Studies on the cellular toxicity of polychlorinated biphenyls (PCBs). I. Effects of PCBs on microsomal enzymes and on synthesis and turnover of microsomal and cytoplasmic lipids Virchows Arch B Cell Pathol 27 279 306 98901
Ishidate K Yoshida M Nakazawa Y 1978 Effect of typical inducers of microsomal drug-metabolizing enzymes on phospholipid metabolism in rat liver Biochem Pharmacol 27 2595 2603 103554
Jenke HS 1985 Polychlorinated biphenyls interfere with the regulation of hydroxymethylglutaryl-coenzyme A reductase activity in rat liver via enzyme-lipid interaction and at the transcriptional level Biochim Biophys Acta 837 85 93 3931687
Jensen AA 1989. Background levels in humans. In: Halogenated Biphenyls, Terphenyls, Naphthalenes, Dibenzodioxins and Related Products (Kimbrough RD, Jensen AA, eds). Amsterdam:Elsevier Science, 345–364.
Kakela R Hyvarinen H 1999 Fatty acid alterations caused by PCBs (Aroclor 1242) and copper in adipose tissue around lymph nodes of mink Comp Biochem Physiol C Pharmacol Toxicol Endocrinol 122 45 53 10190027
Massaro M De Caterina R 2002 Vasculoprotective effects of oleic acid: epidemiological background and direct vascular antiatherogenic properties Nutr Metab Cardiovasc Dis 12 42 51 12125230
Matsusue K Ishii Y Ariyoshi N Oguri K 1999 A highly toxic coplanar polychlorinated biphenyl compound suppresses delta5 and delta6 desaturase activities which play key roles in arachidonic acid synthesis in rat liver Chem Res Toxicol 12 1158 1165 10604864
Reeves PG 1997 Components of the AIN-93 diets as improvements in the AIN-76A diet J Nutr 127 5 suppl 838S 841S 9164249
Robertson LW Silberhorn EM Glauert HP Schwarz M Buchmann A 1991 Do structure-activity relationships for the acute toxicity of PCBs and PBBs also apply for induction of hepatocellular carcinoma? Environ Toxicol Chem 10 715 726
Safe S 1994 Polychlorinated biphenyls (PCBs)- environmental impact, biochemical and toxic responses and implications for risk assessment Crit Rev Toxicol 24 87 149 8037844
Silversand C Haux C 1997 Improved high-performance liquid chromatographic method for the separation and quantification of lipid classes: application to fish lipids J Chromatogr B Biomed Sci Appl 703 7 14 9448057
Slim R Hammock BD Toborek M Robertson LW Newman JW Morisseau CH 2001 The role of methyl-linoleic acid epoxide and diol metabolites in the amplified toxicity of linoleic acid and polychlorinated biphenyls to vascular endothelial cells Toxicol Appl Pharmacol 171 184 193 11243918
Spector AA Kaduce TL Hoak JC Fry GL 1981 Utilization of arachidonic and linoleic acids by cultured human endothelial cells J Clin Invest 68 1003 1011 6793627
Toborek M Lee YW Garrido R Kaiser S Hennig B 2002 Unsaturated fatty acids selectively induce an inflammatory environment in human endothelial cells Am J Clin Nutr 75 119 125 11756069
Tokunaga S Hirota Y Kataoka K 1999 Association between the results of blood test and blood PCB level of chronic Yusho patients twenty five years after the outbreak Fukuoka Igaku Zasshi 90 157 161 10396871
Viswanathan S Hammock BD Newman JW Meerarani P Toborek M Hennig B 2003 Involvement of CYP 2C9 in mediating the proinflammatory effects of linoleic acid in vascular endothelial cells J Am Coll Nutr 22 502 510 14684755
Wassermann M Wassermann D Cucos S Miller HJ 1979 World PCBs map: storage and effects in man and his biologic environment in the 1970s Ann NY Acad Sci 320 69 124 110205
Williams RD Wang E Merrill AH Jr 1984 Enzymology of long-chain base synthesis by liver: characterization of serine palmitoyltransferase in rat liver microsomes Arch Biochem Biophys 228 282 291 6421234
|
15626652
|
PMC1253714
|
CC0
|
2021-01-04 23:40:55
|
no
|
Environ Health Perspect. 2005 Jan 23; 113(1):83-87
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7280
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7387ehp0113-00008815626653ResearchArticlesEstimating the Exposure–Response Relationships between Particulate Matter and Mortality within the APHEA Multicity Project Samoli Evangelia 1Analitis Antonis 1Touloumi Giota 1Schwartz Joel 2Anderson Hugh R. 3Sunyer Jordi 4Bisanti Luigi 5Zmirou Denis 6Vonk Judith M. 7Pekkanen Juha 8Goodman Pat 9Paldy Anna 10Schindler Christian 11Katsouyanni Klea 11Department of Hygiene and Epidemiology, University of Athens, Athens, Greece2Harvard School of Public Health, Boston, Massachusetts, USA3Community Health Sciences, St. George’s Hospital Medical School, University of London, London, United Kingdom4Institut Municipal Investigacio Medica (IMIM), Barcelona, Spain5Azienda Sanitaria Locale della Città di Milano, Milano, Italy6INSERM U420, Nancy, France7Department of Epidemiology and Statistics, University of Groningen, Groningen, the Netherlands8National Public Health Institute, Unit of Environmental Epidemiology, Kuopio, Finland9Dublin Institute of Technology, Dublin, Ireland10National Institute of Environmental Health, Budapest, Hungary11University of Basel, Institut fur Sozial-und Praventivmedizin, Basel, SwitzerlandAddress correspondence to E. Samoli, Department of Hygiene and Epidemiology, University of Athens Medical School, 75 Mikras Asias St., 115 27 Athens, Greece. Telephone: 30-210-7462085. Fax: 30-210-7462205. E-mail:
[email protected] work was funded by Environment and Climate Programme contracts ENV4-CT97-0534 and QLK4-CT-2001-30055 from the European Commission.
The authors declare they have no competing financial interests.
1 2005 21 10 2004 113 1 88 95 5 7 2004 21 10 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Several studies have reported significant health effects of air pollution even at low levels of air pollutants, but in most of theses studies linear nonthreshold relations were assumed. We investigated the exposure–response association between ambient particles and mortality in the 22 European cities participating in the APHEA (Air Pollution and Health—A European Approach) project, which is the largest available European database. We estimated the exposure–response curves using regression spline models with two knots and then combined the individual city estimates of the spline to get an overall exposure–response relationship. To further explore the heterogeneity in the observed city-specific exposure–response associations, we investigated several city descriptive variables as potential effect modifiers that could alter the shape of the curve. We conclude that the association between ambient particles and mortality in the cities included in the present analysis, and in the range of the pollutant common in all analyzed cities, could be adequately estimated using the linear model. Our results confirm those previously reported in Europe and the United States. The heterogeneity found in the different city-specific relations reflects real effect modification, which can be explained partly by factors characterizing the air pollution mix, climate, and the health of the population.
air pollutionexposure–responseheterogeneityhierarchical modelingmortalitysplines
==== Body
Many epidemiologic studies in recent years have documented adverse effects of ambient particulate matter (PM) concentrations on mortality (Katsouyanni et al. 2001; Pope et al. 1995; Samet et al. 2000). The indications of adverse health effects even at below-guideline levels have led to revisions of air quality guidelines and standards and scheduled dates for regular revisions in the future [Commission of European Communities 1999; U.S. Environmental Protection Agency (EPA) 1996; World Health Organization (WHO) 2000]. Most of these studies have assumed linear associations between air pollution and daily deaths, although in cases where concentrations reached high levels, logarithmic transformations have frequently been used (Touloumi et al. 1994). However, the shape of the exposure–response relationship is crucial for public health assessment, and there has been growing demand for providing the relevant curves. Whether or not there is a threshold makes a large difference to the estimate of attributable deaths, and the shape of the exposure–response association is important for predicting the benefits of policies reducing exposure.
Recently, multicity national or international programs have provided results based on data from many cities (Katsouyanni et al. 2001; Samet et al. 2000). Combined evidence was obtained using hierarchical models implemented in two stages. In the first stage, data from each city were analyzed separately, whereas in the second stage, the city-specific air pollution estimates were regressed on city-specific covariates to obtain overall estimates and to explore sources of possible heterogeneity.
In the United States, several multicity studies have explored the exposure–response association between particulate air pollution and mortality (Daniels et al. 2000; Dominici et al. 2002a; Schwartz and Zanobetti 2000). A linear association without threshold was seen. Particulate characteristics differ considerably between Europe and the United States, and the high penetration of diesel engines in Europe makes mobile sources a much more important source of urban particles there. Schwartz et al. (2001) confirmed that the exposure–response relation between airborne particles and total daily deaths is essentially linear, at least at low to moderate concentrations in eight cities in Spain. Similarly, Rossi et al. (1999) found that in Milan, Italy, the association for all causes and cause-specific deaths was almost identical to that noted by Schwartz et al. (2001).
One key limitation of these European studies (Rossi et al. 1999; Schwartz et al. 2001) has been the use of data from a single or a few locations. We address this limitation by presenting the results of analyses examining the exposure–response relationship between daily deaths and airborne particles within the APHEA-2 (Air Pollution and Health—A European Approach) project (Short-Term Effects of Air Pollution on Health: A European Approach to Methodology, Exposure–Response Assessment and Evaluation of Public Health Significance) that uses an extensive European database from 30 cities. This database also allows a comprehensive and structured approach at the second stage of the analysis, in which we explore the role of effect modifiers in explaining the heterogeneity in the shape of the exposure–response relation of air pollution and mortality across cities.
Materials and Methods
Data.
The APHEA-2 project was a multicenter study including 30 cities across Europe and associated regions (i.e., Istanbul, Turkey, and Tel Aviv, Israel) that studied health effects of air pollution. Data were collected on daily counts of all-cause mortality (excluding deaths from external causes) [International Classification of Diseases, 9th Revision (ICD-9; WHO 2002) codes > 800], cardiovascular mortality (ICD-9 390–459), and respiratory mortality (ICD-9 460–519). The data covered at least 3 consecutive years for each city within the years 1990–1997. Details about the data have been published elsewhere (Katsouyanni et al. 2001).
Daily air pollution measurements were provided by the monitoring networks established in each town participating in the APHEA-2 project. A monitor was included if certain completeness criteria were fulfilled (Katsouyanni et al. 1996). Time-series data on daily temperature (degrees centigrade, daily mean) and relative humidity (percent) were used to control for the potential confounding effects of weather. External information on influenza epidemics or other unusual events (e.g., heat waves, strikes) was also collected, if available (Katsouyanni et al. 2001).
In the present study we used the average of lags of 0 and 1 day for black smoke (BS) and PM < 10 μm in aerodynamic diameter (PM10) for all cities, because there is evidence that the average of 2 days’ pollution correlates better with mortality than a single day’s exposure (Schwartz 2000a).
Table 1 presents descriptive characteristics of the analyzed cities. The Netherlands is considered one urban area because of its relatively small size and dense population. Together, all 30 areas have a population of > 60 million people. The mean daily total number of deaths ranged from 6 (in Erfurt and Geneva) to 342 in the Netherlands. For respiratory mortality, daily rates ranged from 0 to 29. The median levels of BS and PM10 concentrations ranged from 9 to 63 μg/m3 and from 14 to 65 μg/m3, respectively. BS levels represent concentrations of black particles with an aerodynamic diameter < 4.5 μm (Department of Health 1995). These measurements have a long history in Europe, and although standards for BS have been replaced recently by those for PM10 (Commission of European Communities 1999), the results are displayed here both for continuity and because there is evidence that BS exposure is more relevant to health effects than is PM10 (Bremner et al. 1999; Brunekreef et al. 1997). BS is a better marker of primary combustion products and small particles (Reponen et al. 1996). Because domestic or industrial burning of coal is minimal in most of the cities studied, BS is more specific for traffic-related particles than PM10 and provides a means of addressing the question of particle composition.
Methods.
We used a hierarchic modeling approach. First, we fit regression models in each city separately to control for potential confounders. We used the results of the individual city analysis in a second-stage analysis to provide overall estimates and to investigate potential effect modifiers.
Individual city analysis.
We investigated the pollution–mortality associations for each city using Poisson regression models allowing for overdispersion. The city-specific model is of the form
where E[Ytc] is the expected value of the Poisson distributed variable Ytc indicating the count of the health outcome on day t at city c with var(Ytc) = ϕE[Ytc], ϕ being the overdispersion parameter; xitc is the value of the xi meteorologic ovariate on day t at city c;Ptc is the air pollution level on day t at city c;f
c is the function defining the exposure–response relation between the pollutant and the health outcome; and βoc represents the baseline mortality in city c. The smooth functions s capture the nonlinear relationship with covariates and can be defined as a linear combination of a set of functions {bj} with convenient properties; that is, s = ∑jajbj (Wood and Augustin 2002). Then k is the number of these basis functions {bj}. We also included dummy variables for the day of the week effect, holidays, and influenza epidemics.
In the last decade, the use of generalized additive models (GAM), which allow non-parametric smooth functions to control for possible confounders, was a standard approach on air pollution time series analysis. Recently, Dominici et al. (2002b) identified that the application of GAM models in the S-Plus software (MathSoft, Inc., Cambridge, MA, USA) with the default convergence criteria leads to biased parameters’ estimates, whereas Ramsay et al. (2003) found in addition that this function underestimated the parameters’ variances. In response to these findings, we used the penalized regression splines as smoothing functions, as implemented by Wood (2000) in R, a public-domain implementation of the S language on which S-Plus is based.
We followed the general methodologic guidelines developed within the framework of the APHEA-2 project, described in detail elsewhere (Touloumi et al. 2004). The basic difference from the APHEA-2 methodology is the use of penalized regression splines instead of the nonparametric function loess as smoothing functions to control for possible confounding. According to the APHEA-2 methodology, these smooth functions of time serve as a proxy for any time-dependent outcome predictors with long-term trends and seasonal patterns not explicitly included in the model. Hence, we remove long-term trends and seasonal patterns from the data to guard against this confounding by omitted variables. Weather variables, which we believe are causally connected to deaths, were also included. In particular, same-day temperature and humidity and a lagged value of these meteorologic variables were also included in the models. We used thin-plate regression splines as basis functions for the penalized regression splines (Wood 2003). In the case of penalized regression splines, as implemented by Wood (2000), k in Equation 1 denotes the number of basis functions used for the corresponding variable fit. The choice of a small number of basis functions can have a substantial effect on the final model, because it places an upper bound on how variable the solution can be. Given our experiences from the previous analyses of the APHEA-2 data, we chose the number of basis functions (k) to be 40 for the time variable and 10 for the weather variables. We then chose the smoothing parameters that minimized the absolute value of the sum of partial autocorrelations (PACs) of the residuals from lags 3 to 30 days. The choice of lags was based on the fact that in mortality health outcomes there was usually strong remaining PAC in the first two lags of the residuals, which could influence the sum disproportionally. To account for serial correlation in the cases that it remained in the final model residuals, we added autoregressive terms into the model, based on the methodology described by Brumback et al. (2000). In the special case of the small cities (and especially in cause-specific mortality), where the above criterion may lead to almost linear fit for the seasonality, we allowed more degrees of freedom for time provided that this imposed only a minor burden in the sum of the residual PACs. When such a case occurred, we allowed as minimum 1 degree of freedom per year.
Day of the week effects, holidays, and epidemics were controlled for by using dummy variables. We used the APHEA-2 method for influenza control, including a dummy variable taking the value of one when the 7-day moving average of the respiratory mortality was greater than the 90th percentile of its city-specific distribution. Because influenza control as described was based on the distribution of respiratory mortality, we included the influenza dummy variable only when we analyzed total and cardiovascular mortality. Based on previously published results (Braga and Zanobetti 2000; Touloumi et al., In press), there is no indication that omitting control for influenza when we analyzed respiratory mortality would influence the association between air pollution and mortality. It is unclear why the specific time within a winter that an epidemic occurs in a particular city should have much to do with air pollution levels and hence confound the relation under investigation.
Regression cubic splines were used to estimate the exposure–response relationship for each city (Samoli et al. 2003), defined by the function f in Equation 1. The regression cubic spline function of a variable P is (Durrleman and Simon 1989)
where k is the number of knots, and using the + notation of Smith (1979),
For each health outcome, the knots were pre-specified and were the same for each city. This had the advantage that similar terms were pooled in the second stage of the analysis. The number and location of the knots were determined according to exploratory graphical analysis results. Three distinct patterns were dominant across cities in each case—that is, linear and two parabolas. Figure 1 shows the patterns of the particles–total-mortality exposure–response relations in London, England, Athens, Greece, and Cracow, Poland, the largest cities in each of the three distinct geographic areas (western, southern, and eastern European cities). When exploring the PM10–mortality relationship we decided to use a cubic spline with two knots at 30 and 50 μg/m3, for all mortality outcomes, to sufficiently capture the association in our data. When exploring the relation of BS with mortality we used a regression cubic spline with two knots at 40 and 70 μg/m3 in the case of total mortality, at 30 and 60 μg/m3 for cardiovascular mortality and at 20 and 50 μg/m3 for respiratory mortality.
To further explore indications of potential threshold levels, we fitted threshold models by applying piecewise linear models. We also fitted models with a linear association between the pollutant and mortality to compare the goodness of fit of the different approaches.
Second-stage analysis.
In the second stage we regressed the city-specific air pollution effect estimates produced form the first stage of the analysis (βc) on city-specific covariates (Zc) to obtain the overall exposure–response (curve and to explore potential heterogeneity in the city-specific curves (Samoli et al. 2003). For the linear model, βc is the log-relative rate in city c, whereas for the spline model, βc is the vector of the regression coefficients corresponding to the spline function.
For the spline method, we fitted multivariate second stage regression models based on the method described by Berkey et al. (1998). More specifically, the models are of the form
where βc is the (5 × 1) vector of the five spline estimates in each city c (the intercept term in Equation 2 was ignored because only relative risks are considered); Zc is a 5 × 5p matrix, where p is the number of city level covariates for city c (including the intercept); α is the vector of regression coefficients to be estimated; δc is a vector of five random effects associated with city c representing, for each spline estimate, the city’s deviation from the overall model; and ɛc (assumed independent from δc) is the vector of sampling errors within each city.
The 5 × 5 matrix cov(δc) = D represents the within-city covariances of the random effects capturing determinants of the city-specific regression coefficients other than sampling error and the city-level covariates considered. It is assumed that δc follows the multivariate normal distribution (MVN) with mean 0 and variance-covariance matrix D—that is, δc ~ MVN (0, D), and ɛc ~ MVN (0, Sc), βc ~ MVN (Zcα, D + Sc) where Sc is the covariance matrix of the five regression coefficients of the spline function in city c that is estimated in the first stage of the analysis. When D ≈ 0 we get the corresponding fixed effects estimates, whereas when D ≠ 0 we get the random effects estimates.
The iterative generalized least squares method was applied to estimate model parameters. The parameters of the between-city covariance matrix D are estimated by maximum likelihood (Berkey et al. 1998). We applied an overall chi-square test to examine heterogeneity (Touloumi et al. 2004).
When assuming a linear exposure–response relation model, Equation 4 collapses to a univariate one that expresses the usual meta-regression. In this case D denotes the between-city variance in the effects estimates and can be estimated from the data using the maximum likelihood method described by Berkey et al. (1995).
After obtaining an overall curve that draws information from all cities, we also compared the two types of models: the linear and the cubic regression spline, within each city and over all cities to determine which best fits the data. We used the Akaike information criterion (AIC) (Akaike 1973) to compare the cubic spline to the linear exposure–response model without threshold representing the standard approach in time series analyses estimating effects of air pollution on mortality or morbidity. For an overall comparison of the different models, we computed the sum of the city-specific AIC values.
As an alternative way to compare the two approaches—the linear and spline models—we computed the difference between the deviances of the fitted models. This difference follows a chi-square distribution with degrees of freedom the difference in the degrees of freedom of the fitted models. For an overall comparison of the different models, we computed the sum of the city-specific differences in deviance, which again follows the chi-square distribution with degrees of freedom the sum of the city-specific difference in the degrees of freedom.
Results
There was significant heterogeneity for all pollutant–mortality relationships under investigation. Although the observed heterogeneity was either explained or substantially reduced when we investigated the effect modification patterns, all results presented are from the random effects models for consistency reasons. When there was no significant heterogeneity left, results from the fixed-effects models were almost identical to those obtained under the random effects models.
Figure 2 shows the estimated overall exposure–response curves between PM10 and total, cardiovascular, and respiratory mortality and their 95% confidence intervals (CIs). Not all cities have values for the pollutant at both ends of the distribution, which is obvious from the wide CIs in the end points of the data. Excluding Stockholm, Sweden, from the analysis, which is the city with the lowest values, the resulting curves were almost identical. Within the range of 36 to 83 μg/m3—that is, the common range of the pollutant levels across the analyzed cities—the combined exposure–response curves could be adequately approximated by a linear association. Although all three curves are similar in that range, a steeper slope is indicated for cardiovascular mortality. Overall, for total and cardiovascular mortality, the spline curves are roughly linear, consistent with the absence of a threshold. The curve for respiratory mortality suggests that a threshold model might be reasonable. The downward curve for the exposure–response relationship between respiratory mortality and PM10 in the lower end of the distribution of the pollutant is also evident in most of the city-specific exposure–response curves. In the case of total or cardiovascular mortality, this shape is evident in only about five (out of the 22) cities, whereas a linear or logarithmic shape is evident in about half of the analyzed cities. Based on the estimated overall exposure–response curves, an increase from 50 to 60 μg/m3 is associated with an increase of about 0.4% in total deaths and with increases of about 0.5% in both cardiovascular and respiratory deaths. These are consistent with the results from regressions assuming a linear relation giving an estimated increase of about 0.5% for total mortality and 0.7% for cardiovascular and respiratory mortality, for a 10-μg/m3 increment in PM10.
Figure 3 shows the estimated combined overall exposure–response curves between BS and total, cardiovascular, and respiratory mortality along with their 95% CIs. As with PM10, the spline curves are roughly linear, consistent with the absence of a threshold. In the case of BS, though, the association is steeper between respiratory mortality and the pollutant. This is consistent also with the results assuming a linear association, which indicate a higher increase for respiratory mortality. The bump in the exposure–response relation between respiratory mortality and PM10 is not so apparent in the case of BS. Nevertheless, in the lower end of the distribution of the pollutant this association shows a small curvature not observed with the other two outcomes; hence, there is suggestion of a possible threshold.
We examined the hypothesis of linearity in the pollutant–mortality relation more formally by comparing the AIC values obtained under the linear and the spline models. In all cases, both models gave very similar AIC values. Overall the linear model gave a slightly better fit, because the AIC was lower by about 0.1% in all pollutant–mortality combinations. On the other hand, the deviance under the spline model was smaller. In all pollutant–mortality relations, apart from respiratory mortality and BS for which no significant departures from linearity were observed, the overall difference in the deviance between the linear and the spline models was statistically significant, whereas the great majority of the city-specific differences in the deviance of the two models was not statistically significant and in accordance with the findings from the AIC.
We further tested the sensitivity of the results to the number and location of the knots of the spline specification. We re-ran the analysis by specifying one knot at 40 μg/m3, and the results were largely similar to the ones presented.
To further explore the indication of a threshold, especially in the case of the association between PM10 and respiratory mortality, we applied threshold models with a threshold level at 20 μg/m3, because this was indicated by the pooled spline curves. The model comparisons between the linear and the threshold models, based on both the AIC and the difference in the deviance, always chose the linear exposure–response model.
To contribute to the ongoing discussion on whether there is a threshold below current limit values (40 or 50 μg/m3), we also fitted threshold models after excluding data at concentrations > 50 μg/m3. We tried two threshold models defining the threshold level at 20 and 10 μg/m3 because those were indicated by our spline analysis. In any case, the linear models gave a better fit.
We investigated the observed heterogeneity by taking into account the potential effect modifiers through second stage regression models. Potential effect modifiers used in the APHEA-2 analysis included variables describing the air pollution level and mix in each city, the health status of the population, the geographic area, and the climatic conditions (Katsouyanni et al. 2001). We present here the exposure–response curves as shaped by the most important effect modifier from each of the above four distinct categories described above. Namely, we present the associations as they are shaped by the geographic region, the temperature levels, the mean level of nitrogen dioxide (24 hr), and the age-standardized annual mortality rate per 100,000. All the reported effect modifiers were statistically significant apart from the effect of NO2 on the association between respiratory mortality and BS. The mean temperature levels in the cities included in the analysis ranged from 6°C in Helsinki, Finland, to 20°C in Tel Aviv, the mean level of NO2 (24 hr) ranged from 26 μg/m3 in Stockholm to 94 μg/m3 in Milan, Italy, and the standardized mortality rate ranged from 430 in Tel Aviv to 1,231 in Lodz, Poland (Table 1). The temperature levels differed significantly among the three geographic areas, whereas the standardized mortality rate differed between the eastern and other cities and the mean NO2 24 hr levels differed between the southern and other cities. The highest correlations (Spearman r = 0.86) were observed between temperature and mean NO2 24-hr levels in the cities that provided BS data.
Each of the presented effect modifiers explained in most cases > 20% of the observed heterogeneity. We present the exposure–response curves as observed in the three distinct geographic regions included in the analysis (western cities, southern cities, and central-eastern European cities). We also present the exposure–response curves as shaped for cities with corresponding levels of the presented effect modifier equal to the 25th and the 75th percentile of the distribution of the relevant effect modifier.
Figure 4 shows the resulting exposure–response curves (and 95% CIs) for PM10 and total mortality. The exposure–response curves for the western and southern cities are similar, although the latter is steeper. The corresponding curve for the eastern cities is very steep in the lower end of the pollutant distribution—that is, at levels < 30 μg/m3. However, the minimum value for the pollutant in those areas is 10 μg/m3, so in fact the part of the curve below that point is an extrapolation, whereas between 10 and 30 μg/m3 only a small proportion of the total data contribute to the estimation, making estimates unstable. The remaining effect modification patterns indicate that the effect of the pollutant on mortality is greater in areas with higher temperature and mean NO2 (24-hr) levels, and lower standardized mortality rate. These results are in agreement with those observed when a linear association of PM10 and total mortality is assumed (APHEA, unpublished data; Katsouyanni et al. 2001).
When we investigated the heterogeneity of the relation between PM10 and respiratory mortality by geographic region, as in total mortality, the exposure–response curves for the western and southern cities were similar, although the latter was steeper. The corresponding curve for the eastern cities had the steepest slope. However, the whole curve was poorly estimated, because of the small counts. The remaining effect modification patterns were not so clear, with lines crossing over the range of the relevant effect modifier. The curve corresponding to the 25th percentile of the NO2 (24-hr) distribution is steeper from the level of 50 μg/m3 until the level of approximately 150 μg/m3, whereas in the range from 20 to 50 μg/m3 the slope of the curve corresponding to the 75th percentile is steeper. The curves corresponding to the effect modification by temperature levels are similar, although, as before, in the lower level of the pollutant distribution the slope corresponding to higher temperature is steeper, and in the higher level of the pollutant the slope corresponding to lower temperature is steeper. The effect modification pattern of the standardized mortality rate indicates a steeper slope for higher ratios, except for the range of the pollutant from about 20 to 50 μg/m3, where the slope corresponding to lower ratios is steeper.
Figure 5 shows the resulting exposure–response curves (and 95% CIs) for BS and total mortality. The effect modification patterns for BS are more linear than the ones observed for PM10. Apart from the edges, the exposure–response curves for the western and eastern cities are similar, although the latter is slightly steeper. The corresponding curve for the southern cities indicates the strongest effect of the pollutant on mortality. The other effect modification patterns indicate that the effect of the pollutant on mortality is greater in areas with higher temperature levels and mean NO2 (24-hr) levels and lower standardized mortality rates. These results are in agreement with those observed when a linear association of BS and total mortality is assumed (APHEA, unpublished data; Katsouyanni et al. 2001).
When we investigated the heterogeneity in the BS–respiratory mortality association, the curvature observed in the lower end of the overall exposure–response curve of PM10 and BS with respiratory mortality (Figure 1) was also apparent in about half of the relationships as those were shaped by the different effect modifiers. As was the case with PM10, the exposure–response curve for the eastern cities had the steepest slope. However, also southern cities had, on average, a substantially steeper slope than the western cities, where in fact no relation was observed. The remaining effect modification patterns were not so clear. The curve corresponding to the 25th percentile of the NO2 (24-hr) distribution was steeper up to approximately 30 μg/m3, and above that the slope of the curve corresponding to the 75th percentile was steeper. Similarly, the curves corresponding to the effect modification by temperature levels indicated that in the lower level of the pollutant distribution the slope corresponding to lower temperature was steeper and in the higher level of the pollutant the slope corresponding to higher temperature was steeper. The effect modification pattern of the standardized mortality rate indicated a steeper slope for higher rates.
Discussion
In recent years there has been growing demand from policy makers for better understanding of the exposure–response relationship between air pollution and various adverse health effects, including mortality. Most of the relevant studies in Europe were carried out within a small number of locations and consequently have limited statistical power to provide evidence in support of a particular model. We used the most extensive database available in Europe until today (Katsouyanni et al. 2001) to investigate the exposure–response relation between ambient particle concentrations and the daily number of deaths. By use of multiple locations, power is gained and generalizability is enhanced.
We used cubic splines to estimate nonlinear relations of particulate air pollution with mortality. Our results (Figures 2 and 3) indicate that the spline curves for both PM10 and BS with total and cardiovascular mortality are roughly linear, consistent with the absence of a threshold. The curve for respiratory mortality suggests that there is some evidence for deviation from linearity in the lowest levels of the pollutants distribution.
There was significant heterogeneity in all associations under investigation. However, the chi-square test applied for the investigation of heterogeneity has very high power when many studies are included in the meta-analysis, and especially when these studies are large, as in our case (Higgins et al. 2003). Formal comparison between spline and linear models based on the AIC indicated that the linear models fit better. The result under the chi-square test indicating that in most of the pollutant–mortality associations the deviance of the spline models is significantly smaller may be an artifact due to the sensitivity of the chi-square test. This claim is supported by the city-specific results, where the conclusions derived from the AIC and the chi-square tests are in agreement. In the great majority of the cities analyzed, the linear and spline models gave very similar fit; hence, the sensitivity of the overall chi-square test picks up the difference in the few other cities. Another possible explanation is that the spline model captures the logarithmic shape of the relation in the higher end of the pollutant’s distribution better, because fitting a logarithmic association with the pollutant gave the best fit.
It is well understood that the measured particle indicators represent a mixture, with varying chemical and physical characteristics, reflected on different toxicity of parts of this mixture. Similarly, the populations studied in our analysis consist of subgroups with different sensitivity to PM exposure. It is likely that the exposure profile and sensitivity of each subgroup (indeed, of each individual) result in various thresholds of effects that cannot be identified with this methodology. The linear curve resulting from our analysis may be seen as a composition of these postulated “partial” curves and may be used effectively for the protection of the whole population. Clearly, more research is needed to identify the most dangerous components of the PM mixture and the most sensitive population subgroups. On the other hand, the biologic mechanisms underlying the PM–health outcome associations are not yet completely clear.
The curvature of the exposure–response relationship between ambient particles and respiratory mortality in the lower levels of the pollutants, not so strongly observed for total and cardiovascular mortality, suggests that there may be different mechanisms underlying the association of particulate pollution exposure to different mortality health outcomes. Goodman et al. (2004) reported a different time response for cardiovascular mortality compared with respiratory mortality, where cardiovascular mortality occurs within the first few days of exposure, whereas respiratory mortality showed a lag of up to 2 weeks. This observed curvature could also be caused by the composition of the air pollution mix at the low concentrations. This rationale is based on the fact that PM10 measurements represent all particles with aerodynamic diameter < 10 μm, a mixture of primary and secondary particles from different sources with varying characteristics and levels of toxicity. Unfortunately, the present study does not have enough information to sufficiently investigate this possibility.
Nevertheless, in the range of the pollutants common to all the cities included in the analyses, all associations were approximately linear. The above results are consistent with those reported in previous studies in Europe (Rossi et al. 1999; Schwartz et al. 2001) and in the United States (Daniels et al. 2000; Dominici et al. 2002a; Schwartz and Zanobetti 2000). The slope of the association between ambient particles and total or cardiovascular mortality is higher for levels < 50 μg/m3 (and > 10 μg/m3 where there is enough information). This is consistent from the results from 10 U.S. cities analyzed by Schwartz (2000b).
Formal comparison between threshold and linear models, based either on the AIC or on the deviance chi-square test, showed that linear models would on average fit better than the threshold ones.
We investigated several factors that potentially influence the exposure–response relations and might provide some explanations for the different shapes observed in different locations. Specifically, in the range of the pollutants common in all analyzed cities, the exposure–response curves between ambient particles and total or cardiovascular mortality were steeper in southern European cities. The association between particles and total and cardiovascular mortality was steeper in locations with hotter climates, higher mean NO2 (24-hr) levels, and lower standardized mortality rates. The effect of NO2 suggests that particles originating from vehicle exhausts are more toxic than those from other sources. A possible explanation for the temperature effect on the exposure–response association may be that in warmer countries, outdoor fixed-site air pollution measurements may represent the average population exposure better than the measurements in colder climates, because people tend to keep their windows open and spend more time outdoors in warmer climates. Finally, in this study a large age-standardized mortality rate was related to a smaller proportion of elderly persons and probably to the presence of competing risks for the same disease entities. It is therefore related to a smaller proportion of people belonging to vulnerable groups who are more susceptible to air pollution effects. The above-reported effect modification patterns are in accordance with the corresponding ones when a linear pollutant–mortality association was assumed (APHEA, unpublished data; Katsouyanni et al. 2001).
When we investigated the relation with respiratory mortality, the exposure–response curves were steeper in Eastern European cities. The effect modification patterns between ambient particles and respiratory mortality are less clear and need further investigation. In the range of the pollutants common in all analyzed cities, the exposure–response curves are steeper in eastern European cities. Also, in cities with higher standardized mortality rates, the slopes were steeper. These findings supplement each other, because in the cities included in our analysis, all eastern cities had high standardized mortality rates. The effect on the particles–respiratory mortality association of the remaining potential effect modifiers investigated is analogous to the ones observed in the cases of total and cardiovascular mortality. Namely, in the range of the pollutants most commonly observed, cities with higher temperatures and mean NO2 (24-hr) levels present steeper slopes.
In conclusion, the association between ambient particles and mortality in the cities included in the present analysis could be adequately estimated using the linear model. Our results confirm those previously reported from Europe and the United States. The heterogeneity found in the different city-specific relations reflects real effect modification, which can be explained partly by factors characterizing the air pollution mix, climate, and the health of the population. Hence, measures that focus on lowering air pollution concentrations have greater public health benefits than those that focus on a few days with the highest concentrations (Clancy et al. 2002). The tendency for a curvature at levels < 20 μg/m3, if true, is likely to reflect differences in the mixture and toxicity at different levels. Further study focusing on the composition of particles is needed to further our understanding of the etiologic mechanism through which particles affect mortality and particularly respiratory mortality.
Figure 1 Exposure–response curves of PM10 (A) and BS (B) with total mortality in London, Athens, and Cracow.
Figure 2 Exposure–response curves and 95% CIs of PM10 and total, cardiovascular, and respiratory mortality.
Figure 3 Exposure–response curves and 95% CIs of BS and total, cardiovascular, and respiratory mortality.
Figure 4 Exposure–response curves and their 95% CIs of PM10 and total mortality in different geographic areas (A), and in the 25th and 75th percentiles of the distribution of temperature (B), standardized mortality rate (C), and mean NO2 24-hr levels (D).
Figure 5 Exposure–response curves and their 95% CIs of BS and total mortality in different geographic areas (A), and in the 25th and 75th percentiles of the distribution of temperature (B), standardized mortality rate (C), and mean NO2 24-hr levels (D).
Table 1 City descriptive data on the study period, population, exposure (PM10 and BS), outcome (daily number of deaths), and selected effect modifiers (region, mean temperature, mean NO2 over 24 hr, and directly standardized mortality rate).
No. of deaths per day
PM10 (μg/m3) percentile
BS (μg/m3) percentile
City Study period (month/year) Population (× 1,000) Total CVD Respiratory 50th 90th 50th 90th Geographic region Mean temperature NO2 (24-hr) SDR
Athens 1/92–12/96 3,073 73 64 5 40a 59 64 122 South 18 74 784
Barcelona 1/91–12/96 1,644 40 32 4 60 95 39 64 South 16 69 740
Basel 1/90–12/95 360 9 8 1 28a 55 West 11 38 678
Bilbao 4/92–3/96 667 15 11 1 23 39 South 15 49 711
Birmingham 1/92–12/96 2,300 61 50 9 21 40 11 22 West 10 46 895
Budapest 1/92–12/95 1,931 80 57 3 40a 52 East 11 76 1,136
Cracow 1/90–12/96 746 18 13 0 54a 86 36 101 East 8 44 1,009
Dublin 1/90–12/96 482 13 10 2 10 26 West 10 — 940
Erfurt 1/91–12/95 216 6 — — 48 98 West 9 40 972
Geneva 1/90–12/95 317 6 4 0 33a 71 West 10 45 608
Helsinki 1/93–12/96 828 18 14 2 23a 49 West 6 33 915
Ljubljana 1/92–12/96 322 7 5 0 13 42 East 11 46 823
Lodz 1/90–12/96 828 30 20 1 30 77 East 8 39 1,231
London 1/92–12/96 6,905 169 139 29 25 46 11 22 West 12 61 851
Lyon 1/93–12/97 416 9 7 1 39 63 West 12 63 579
Madrid 1/92–12/95 3,012 61 46 6 33 59 South 15 70 636
Marseille 1/90–12/95 855 22 18 2 34 56 West 16 71 666
Milan 1/90–12/96 1,343 29 23 2 47a 88 West 14 94 632
Netherlands 1/90–9/95 15,400 342 140 29 34 67 63 122 West 10 43 757
Paris 1/92–12/96 6,700 124 91 9 22 46 21 45 West 12 53 644
Poznan 1/90–12/96 582 17 12 1 23 76 East 9 47 1,106
Prague 2/92–12/95 1,213 38 30 1 66 124 East 10 58 984
Rome 1/92–12/96 2,775 56 44 3 57a 81 South 17 88 585
Stockholm 1/94–12/96 1,126 30 25 3 14 27 West 8 26 666
Tel Aviv 1/93–12/96 1,141 27 22 2 43 75 South 20 70 430
Teplice 1/90–12/97 625 18 13 1 42 83 East 9 32 1,173
Torino 1/90–12/96 926 21 17 1 65a 129 West 14 76 724
Valencia 1/94–12/96 753 16 14 2 40 70 South 19 66 820
Wroclaw 1/90–12/96 643 15 10 1 33 97 East 9 27 970
Zurich 1/90–12/95 540 13 10 1 28a 54 West 11 40 666
Abbreviations: —, no data; CVD, cardiovascular deaths; SDR, directly standardized mortality rate. Mean temperature in degrees centigrade.
a PM10 were estimated using a regression model relating collocated PM10 measurements to the BS or total suspended particles.
==== Refs
References
Akaike H 1973. Information theory and an extension of the maximum likelihood principal. In: Second International Symposium on Information Theory, Tsahkadsor, Armenia, USSR, September 2–8, 1971 (Petrov BN, Csáki F, eds). Budapest:Akadémiai Kiadó, 267–281.
Berkey CS Hoaglin DC Antczak-Bouckoms A Mosteller F Colditz GA 1998 Meta-analysis of multiple outcomes by regression with random effects Stat Med 17 2537 2550 9839346
Berkey CS Hoaglin DC Mosteller F Colditz GA 1995 A random-effects regression model for meta-analysis Stat Med 14 395 411 7746979
Braga A Zanobetti A 2000 Do respiratory epidemics confound the association between air pollution and daily deaths? Eur Respir J 16 723 726 11106219
Bremner SA Anderson HR Atkinson RW McMichael AJ Bland JM Strachan DP 1999 Short-term associations between outdoor air pollution and mortality in London 1992–94 Occup Environ Med 56 237 244 10450240
Brumback BA Ryan LM Schwartz JD Neas LM Stark PC Burge HA 2000 Transitional regression models, with application to environmental time series JASA 95 16 27
Brunekreef B Janssen NA de Hartog J Harssema H Knape M Van Vliet P 1997 Air pollution from truck traffic and lung function in children living near motorways Epidemiology 8 298 303 9115026
Clancy L Goodman P Sinclair H Dockery DW 2002 Effect of air-pollution control on death rates in Dublin, Ireland: an intervention study Lancet 360 9341 1210 1214 12401247
Commission of the European Communities 1999 Council Directive 1999/30/EC Relating to Limit Values for Sulphur Dioxide, Oxides of Nitrogen, Particulate Matter and Lead in Ambient Air Official J Eur Communities 163 41 60
Daniels MJ Dominici F Samet JM Zeger SL 2000 Estimating particulate matter-mortality dose-response curves and threshold levels: an analysis of daily time-series for the 20 largest US cities Am J Epidemiol 152 5 397 405 10981451
Department of Health 1995. Committee on the Medical Effects of Air Pollution: Non-Biological Particles and Health. London:Her Majesty’s Stationery Office.
Dominici F Daniels M Zeger SL Samet JM 2002a Air pollution and mortality: estimating regional and national dose-response relationships J Am Stat Assoc 97 100 111
Dominici F McDermott A Zeger S Samet J 2002b On the use of generalized additive models in time-series studies of air pollution and health Am J Epidemiol 156 193 203 12142253
Durrleman S Simon R 1989 Flexible regression models with cubic splines Stat Med 8 551 561 2657958
Goodman PG Dockery DW Clancy L 2004 Cause-specific mortality and the extended effects of particulate pollution and temperature exposure Environ Health Perspect 112 179 185 14754572
Higgins J Thompson S Deeks J Altman D 2003 Measuring inconsistency in meta-analyses Br Med J 327 557 560 12958120
Katsouyanni K Schwartz J Spix C Touloumi G Zmirou D Zanobetti A 1996 Short-term effects of air pollution on health: a European approach using epidemiologic time-series data: the APHEA protocol J Epidemiol Community Health 50 suppl 1 S12 S18 8758218
Katsouyanni K Touloumi G Samoli E Gryparis A Le Tertre A Monopolis Y 2001 Confounding and effect modification in the short-term effects of ambient particles on total mortality: results from 29 European cities within the APHEA2 project Epidemiology 12 521 531 11505171
Pope CA III Dockery DW Schwartz J 1995 Review of epidemiological evidence of health effects of particulate air pollution Inhal Toxicol 7 1 18
Ramsay T Burnett R Krewski D 2003 The effect of concurvity in generalized additive models linking mortality and ambient air pollution Epidemiology 14 1 18 23 12500041
Reponen A Ruuskanen J Mirme A Parjala E Hoek G Roemer W 1996 Comparison of five methods for measuring particulate matter concentrations in cold winter climate Atmos Environment 30 3873 3879
Rossi G Vigotti MA Zanobetti A Repetto F Gianelle V Schwartz J 1999 Air pollution and cause-specific mortality in Milan, Italy, 1980–1989 Arch Environ Health 54 3 158 164 10444036
Samet JM Dominici F Curriero F Coursac I Zeger SL 2000 Particulate air pollution and mortality: findings from 20 U.S. cities N Engl J Med 343 1742 1757 11114312
Samoli E Touloumi G Zanobetti A Le Tertre A Shindler C Atkinson R 2003 Investigating the dose-response relation between air pollution and total mortality in the APHEA-2 multicity project Occup Environ Med 60 977 982 14634192
Schwartz J 2000a The distributed lag between air pollution and daily deaths Epidemiology 11 320 326 10784251
Schwartz J 2000b Assessing confounding, effect modification, and thresholds in the association between ambient particles and daily deaths Environ Health Perspect 108 563 568 10856032
Schwartz J Ballester F Saez M Perez-Hoyos S Bellido J Cambra K 2001 The concentration–response relation between air pollution and daily deaths Environ Health Perspect 109 1001 1006 11675264
Schwartz J Zanobetti A 2000 Using meta-smoothing to estimate dose-response trends across multiplie studies, with application to air pollution and daily death Epidemiology 11 6 666 672 11055627
Smith PL 1979 Splines as a useful and convenient statistical tool Am Stat 33 57 62
Touloumi G Atkinson R Le Tetre A Samoli E Schwartz J Schndler C 2004 Analysis of health outcome time series data in epidemiological studies Environmetrics 15 101 117
Touloumi G Pocock SJ Katsouyanni K Trichopoulos D 1994 Short-term effects of air-pollution on daily mortality in Athens time-series analysis Int J Epidemiol 23 5 957 967 7860176
Touloumi G Samoli E Quenel P Paldy A Anderson HR Zmirou D In press. Short-term effects of air pollution on total and cardiovascular mortality: the confounding effects of influenza epidemics. Epidemiology.
U.S. EPA 1996. Review of the National Ambient Air Quality Standards for Particulate Matter: Policy Assessment of Scientific and Technical Information. WAWPS Staff Paper. EPA-45/R-1996:96-013. Research Triangle Park, NC:U.S. Environmental Protection Agency, Office of Air Quality Planning and Standards.
WHO 2000. Air Quality Guidelines for Europe. 2nd ed. WHO Regional Publications European Series No 91. Copenhagen:World Health Organization.
WHO 2002. International Classification of Diseases, 9th Revision. ICD-9-CM. Geneva:World Health Organization.
Wood SN 2000 Modelling and smoothing parameter estimation with multiple quadratic penalties J R Stat Soc Ser B 62 1 413 428
Wood SN 2003 Thin plate resgression splines J R Stat Soc Ser B 65 1 95 114
Wood SN Augustin NH 2002 GAMs with integrated model selection using penalized regression splines and applications to environmental modelling Ecol Model 157 157 177
|
15626653
|
PMC1253715
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2005 Jan 21; 113(1):88-95
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7387
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7373ehp0113-00009615626654Environmental MedicineCase ReportSquamous Cell Carcinoma of the Skin and Coal Tar Creosote Exposure in a Railroad Worker Carlsten Chris 12Hunt Stephen Carl 12Kaufman Joel D. 121Department of Environmental and Occupational Health Sciences, and2Department of Medicine, Occupational and Environmental Medicine Program, University of Washington, Seattle, Washington, USAAddress correspondence to C. Carlsten, Pulmonary, Occupational and Environmental Medicine, Campus Box 359739, University of Washington, 1959 Pacific St., Seattle, WA 98195 USA. Telephone: (206) 541-0704. Fax: (206) 328-4352. E-mail:
[email protected] authors declare they have no competing financial interests.
1 2005 22 11 2004 113 1 96 97 1 7 2004 22 11 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. A 50-year-old male railroad worker presented to his primary care physician with an erythematous, tender skin lesion on the right knee; a biopsy of this lesion revealed squamous cell carcinoma in situ. The site of the lesion was sun-protected but had been associated with 30 years of creosote-soaked clothing. In this article, we review dermal and other malignancies associated with creosote, along with creosote occupational exposures and exposure limits. This is a unique case, given the lack of other, potentially confounding, polyaromatic hydrocarbons and the sun-protected location of the lesion.
carcinomacoal tarcreosoteenvironmentalexposureoccupationalrailroadsquamous cell
==== Body
Case Report
A 50-year-old male railroad worker presented to his primary care physician with an erythematous, tender skin lesion on the anteromedial aspect of the right knee. The patient reported that the lesion had been present and intermittently tender over several years prior to presentation. The lesion was initially thought to be a simple cyst and was aspirated by the treating physician; antibiotics were also prescribed. The lesion did not resolve and was subsequently biopsied, revealing squamous cell carcinoma in situ (Figures 1 and 2).
The patient was referred to a surgeon; a definitive excision was performed, with subsequent completion of postoperative localized radiation therapy. The lesion did not recur.
The patient gave a history of having worked for a railroad company for 30 years before noting the skin lesion; most of this time had been spent on the “building and bridges” unit. This work involved the replacement of railroad track ties and the repair and construction of bridges and trestles, all of which involved the use of, and nearly daily handling of, coal tar creosote–treated ties and lumber. He reported that on a nearly daily basis, he carried, handled, kneeled on, or sat on this treated lumber. He also reported that the ties and timbers were heavily coated with creosote and that creosote commonly coated his work clothes at the end of his work shifts. He gave a history of wearing overalls, leather work-gloves, and long sleeves for a majority of his time at work. He stated that, despite wearing protective work clothes, he generally found creosote that had “filtered through” his clothing, particularly on his hands, wrists, and knees, and that he noticed this discoloration on his hands and knees at the end of most workdays. He was not aware of any other rashes or skin changes related to the exposures in these areas.
He had no history of other occupational exposures and reported having no significant sun exposure to the area of the lesion. He had no personal or family history of other skin disease or skin cancers. He was otherwise healthy, was a lifelong nonsmoker, and had no other significant medical history.
The physical examination revealed a healthy-appearing 50-year-old male with no medical concerns other than the skin lesion. Physical findings were unremarkable, with the exception of a well-healed 2-cm scar on the anteromedial aspect of the right knee (the focus of medial pressure upon kneeling). There were no other pertinent skin findings.
Discussion
Polycyclic aromatic hydrocarbons (PAHs) were among the earliest work-related health hazards identified by contemporary occupational epidemiologic methods in the 18th century. Sir Percival Potts observed an apparent association between scrotal cancers and tar and soot exposures among chimney sweeps in London in 1775 (Harrison 2004). Although neither the precise chemical nature of the exposure nor a histologic analysis of the cancer is available, Potts’ report was ground-breaking.
Skin disease associated with creosote exposure was specifically reported as early as 1898, when MacKenzie published (in the British Journal of Dermatology) a case involving scrotal papillomatosis in a creosote worker (Mackenzie 1898). There have been limited subsequent case reports linking coal tar creosote with squamous cell cancers (Cookson 1924; Lenson 1956; Shimauchi et al. 2000). However, all of the lesions reported in these few cases were located in sun-exposed areas of skin, and it is possible that the lesions were secondary to the effects of sun rather than to creosote.
Animal studies have supported an exposure–disease link between creosote and skin cancers. Rous (1956) observed that study mice housed in creosote-impregnated wooden boxes developed surprising numbers of skin papillomas. Boutwell and Bosch (1958) documented skin carcinomas in mice exposed to creosote oils. In a human skin model, Schoket et al. (1988) observed that creosote induced adducts at levels thought to correlate with carcinogenicity in mice. In a cohort study involving 922 “creosote-exposed workers,” Karlehagen et al. (1992) found a standardized incidence ratio of 2.37 for skin cancer among exposed individuals compared with those not exposed, although no reliable data on individual exposure were available. As in prior case reports, sun exposure may have contributed to the elevated rates in the exposed group (Karlehagen et al. 1992).
PAHs result from the incomplete combustion of coal tar, pitch, coke, asphalt, and oil. Emitted as vapors of incomplete combustion, or pysolysis, PAHs precipitate as particles or condense onto soot particles. The term “creosote” is often used to describe these PAH-rich products of combustion and their distillates, and encompasses such products as wood creosote (from the combustion of beech and other woods), coal tar creosote (from the combustion of coal or coal tar), and coal tar pitch volatiles.
Coal tar creosote (containing over 300 different compounds, the majority of which are PAHs such as phenols, cresols, xylenols, pyridines, and benzene) is the most commonly used wood preservative in the United States [Agency for Toxic Substances and Disease Registry (ATSDR) 2002]. It is a thick, oily liquid that is amber or dark in color and is widely used in the treatment of telephone poles, railroad ties, marine pilings, and fence posts.
Occupational exposures to coal tar creosote are usually associated with work in wood preservation/pressure treatment facilities, fence building, bridge construction, utility work (telephone poles), aluminum smelting, and creosote site remediation. The ATSDR reported approximately 25,000 workers in nearly 100 wood treatment facilities using coal tar creosote in 1996 (ATSDR 2002). Additionally, nonoccupational exposures may result from the use of railroad ties in landscaping, burning of creosote-treated scrap lumber in fireplaces or woodstoves, and ingestion of contaminated groundwater (ATSDR 2004).
Non-cancer effects of coal tar creosote exposure involve primarily dermal and mucosal irritation manifested by dermatoses, photosensitivities, rhinitis, and conjunctivitis. The phototoxicity, in particular, is important because it compounds the irritative effects of coal tar creosote and presumably, therefore, increases its carcinogenicity (ATSDR 2002). Malignancies potentially associated with occupational coal tar pitch exposure include lung and prostate cancer in coke oven workers, lung cancer in foundry workers, lung and bladder cancer in aluminum smelter workers, and lung and stomach cancer in roofers (Harrison 2004). Other cancers suggested as being related to these compounds include renal cell carcinoma (Steineck et al. 1989), neuroblastoma (following parental occupational exposure) (Kerr et al. 2000), and non-Hodgkin lymphoma (Persson et al. 1989). The International Agency for Research on Cancer (IARC) has concluded that there is “sufficient” evidence for coal tar pitch (IARC 1998a) to be considered carcinogenic in humans, but that creosotes (IARC 1998b) have only “limited evidence” for human carcinogenicity, despite demonstrating “sufficient” evidence to establish carcinogenicity in animals.
Coal tar creosote exposures are regulated with an Occupational Safety and Health Administration (OSHA) permissible exposure limit (PEL) of 0.2 mg/m3 8-hr time-weighted average (TWA; benzene soluble fraction; OSHA 1986) and a National Institute for Occupational Safety and Health (NIOSH) recommended exposure limit of 0.1 mg/m3 TWA (NIOSH 2002). Of note, there are no specific limits for dermal exposure. Nonetheless, engineering and personal protective equipment requirements established by a 1986 U.S. Environmental Protection Agency (EPA) “special review” (U.S. EPA 2000) are thought to have lowered exposures to levels below the established PEL. In the European Union, there are concerns that exposure limits may understate the carcinogenic risks of creosote exposure (Holme et al. 1999).
Conclusion
In many occupational settings, workers are exposed to combinations of coal tar, coal tar pitch, and coal tar creosote, making it difficult to ascertain the mutagenic and carcinogenic risks associated with coal tar creosote exposure alone. There are, however, case reports as well as human and animal studies suggesting that creosote alone may be carcinogenic. The present case report, involving a railroad worker with a relatively “pure” long-term coal tar creosote exposure and a subsequent squamous cell carcinoma in situ in a non–sun-exposed skin area, further supports the relationship between coal tar creosote exposure and squamous cell carcinoma of the skin. Along with having such biological plausibility, it specifically eliminates the possibility of a primarily sun-related carcinogenesis. This case also emphasizes the value of a careful and detailed history in documenting the chronology, latency, circumstances, and relative dose characteristics that help establish causality is such cases.
Because there are significant numbers of individuals who have previously been exposed or are currently experiencing occupational and environmental exposures to coal tar creosote, the potential health effects of these exposures warrant attention. In cases for which substitutes for coal tar creosote is truly unfeasible, adoption of less permeable clothing may prevent such cases in the future.
Figure 1 Hematoxylin and eosin stain, right knee skin biopsy. Magnification, 40×.
Figure 2 Hematoxylin and eosin stain, right knee skin biopsy. Magnification 100×.
==== Refs
References
ATSDR 2002. Potential for human exposure. In: Toxicological Profile for Wood Creosote, Coal Tar Creosote, Coal Tar, Coal Tar Pitch, and Coal Tar Pitch Volatiles. Atlanta, GA:Agency for Toxic Substances and Disease Registry. Available: http://www.atsdr.cdc.gov/toxprofiles/tp85-c6.pdf [accessed 30 March 2004].
ATSDR 2004. Preliminary Health Assessment: Texarkana Wood Preserving Site, Texarkana, Bowie County, Texas. Atlanta, GA:Agency for Toxic Substances and Disease Registry. Available: http://www.atsdr.cdc.gov/HAC/PHA/texarkana/texarkana.html [accessed 30 March 2004].
Boutwell RK Bosch DK 1958 The carcinogenicity of creosote oil: its role in the induction of skin tumors in mice Cancer Res 18 1171 1175 13596959
Cookson HA 1924 Epithelioma of skin after prolonged exposure to creosote Br Med J 1 368 20771487
Harrison RJ 2004. Polycyclic aromatic hydrocarbons. In: Current Occupational and Environmental Medicine (LaDou J, ed). New York:McGraw-Hill, 492–493.
Holme JA Refsnes M Dybing E 1999 Possible carcinogenic risk associated with production and use of creosote-treated wood [in Norwegian] Tidsskr Nor Laegeforen 119 2664 2666 10479980
IARC (International Agency for Research on Cancer) 1998a. Coal Tar Pitches (Group 1). Available: http://monographs.iarc.fr/htdocs/monographs/suppl7/coaltarpitches.html [accessed 5 October 2004].
IARC (International Agency for Research on Cancer) 1998b. Creosotes (Group 2A). Available: http://monographs.iarc.fr/htdocs/monographs/suppl7/creosotes.html [accessed 5 October 2004].
Karlehagen S Anderson A Ohlson CG 1992 Cancer incidence among creosote-exposed workers Scand J Work Environ Health 18 26 29 1553509
Kerr MA Nasca PC Mundt KA Michalek AM Baptiste MS Mahoney MC 2000 Parental occupational exposures and risk of neuroblastoma: a case-control study (United States) Cancer Causes Control 11 635 643 10977108
Lenson N 1956 Multiple cutaneous carcinoma after creosote exposure N Engl J Med 254 520 522 13297146
Mackenzie S 1898 Case of tar eruption Br J Dermatol 10 417
NIOSH (National Institute for Occupational Safety and Health) 2002. NIOSH Pocket Guide to Chemical Hazards: Coal Tar Pitch Volatiles. Available: http://www.cdc.gov/niosh/npg/npgd0145.html [accessed 5 October 2004].
OSHA (Occupational Safety and Health Administration) 1986. Coal Tar Pitch Volatiles (CTPV), Coke Oven Emissions (COE), Selected Polynuclear Aromatic Hydrocarbons (PAHs). Available: http://www.osha.gov/dts/sltc/methods/organic/org058/org058.html [accessed 5 October 2004].
Persson B Dahlander AM Fredriksson M Brage HN Ohlson CG Axelson O 1989 Malignant lymphoma and occupational exposures. Br J Ind Med 46 516 520
Rous P 1956 Influence of hereditary malformations on carcinogenesis in “CREW” mice and deer mice of hairless strains Proc Am Assoc Cancer Res 2 143
Schoket B Hewer A Grover PL Phillips DH 1988 Formation of DNA adducts in human skin maintained in short-term organ culture and treated with coal-tar, creosote or bitumen Int J Cancer 42 622 626 3170032
Shimauchi T Rikihisa W Yasuda H Yamamoto O Asahi M 2000 A case of squamous cell carcinoma that developed on chronic tar dermatosis [in Japanese] J UOEH 22 183 187 10862413
Steineck G Plato N Alfredsson L Norell SE 1989 Industry-related urothelial carcinogens: application of a job-exposure matrix to census data Am J Ind Med 16 209 224 2773949
U.S. EPA 2000. Status of Chemicals in Special Review. Washington, DC:U.S. Environmental Protection Agency. Available: http://www.epa.gov/oppsrrd1/docs/sr00status.pdf [accessed 30 March 2004].
|
15626654
|
PMC1253716
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan 22; 113(1):96-97
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7373
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7210ehp0113-00009815626655Children's HealthArticlesExposure to Environmental Tobacco Smoke and Cognitive Abilities among U.S. Children and Adolescents Yolton Kimberly 12Dietrich Kim 13Auinger Peggy 4Lanphear Bruce P. 12Hornung Richard 1341Cincinnati Children’s Environmental Health Center, Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio, USA2Department of Pediatrics and3Department of Environmental Health, University of Cincinnati College of Medicine, Cincinnati, Ohio, USA4Department of Pediatrics, University of Rochester School of Medicine and the American Academy of Pediatrics Center for Child Health Research, Rochester, New York, USA5Institute for Health Policy and Health Services Research, University of Cincinnati, Cincinnati, Ohio, USAAddress correspondence to K. Yolton, Cincinnati Children’s Hospital Medical Center, 3333 Burnet Ave., MLC 7035, Cincinnati, OH 45229-3039 USA. Telephone: (513) 636-2815. Fax: (513) 636-4402. E-mail:
[email protected] paper was presented in part at the annual meeting of the Pediatric Academic Society, May 2002.
The authors declare they have no competing financial interests.
1 2005 7 10 2004 113 1 98 103 27 4 2004 7 10 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. We used the Third National Health and Nutrition Examination Survey (NHANES III), conducted from 1988 to 1994, to investigate the relationship between environmental tobacco smoke (ETS) exposure and cognitive abilities among U.S. children and adolescents 6–16 years of age. Serum cotinine was used as a biomarker of ETS exposure. Children were included in the sample if their serum cotinine levels were ≤15 ng/mL, a level consistent with ETS exposure, and if they denied using any tobacco products in the previous 5 days. Cognitive and academic abilities were assessed using the reading and math subtests of the Wide Range Achievement Test–Revised and the block design and digit span subtests of the Wechsler Intelligence Scale for Children–III. Analyses were conducted using SUDAAN software. Of the 5,365 6- to 16-year-olds included in NHANES III, 4,399 (82%) were included in this analysis. The geometric mean serum cotinine level was 0.23 ng/mL (range, 0.035–15 ng/mL); 80% of subjects had levels < 1 ng/mL. After adjustment for sex, race, region, poverty, parent education and marital status, ferritin, and blood lead concentration, there was a significant inverse relationship between serum cotinine and scores on reading (β= −2.69, p = 0.001), math (β= −1.93, p = 0.01), and block design (β= −0.55, p < 0.001) but not digit span (β= −0.08, p = 0.52). The estimated ETS-associated decrement in cognitive test scores was greater at lower cotinine levels. A log-linear analysis was selected as the best fit to characterize the increased slope in cognitive deficits at lower levels of exposure. These data, which indicate an inverse association between ETS exposure and cognitive deficits among children even at extremely low levels of exposure, support policy to further restrict children’s exposure.
childrencognitionenvironmentenvironmental tobacco smokeepidemiology
==== Body
Despite extensive evidence that environmental tobacco smoke (ETS) is associated with an increased risk of detrimental health effects, > 40% of U.S. children are exposed to ETS in their homes (Pirkle et al. 1996). Exposure to ETS has consistently been linked with adverse health effects in children, including middle ear disease (Cook and Strachan 1999), colic (Reijneveld et al. 2000), sudden infant death syndrome (McMartin et al. 2002; Mitchell et al. 1993; Schoendorf and Kiely 1992; Wisborg et al. 2000), asthma exacerbations (Chilmonczyk et al. 1993; Ehrlich et al. 1996; Martinez et al. 1992), and various respiratory difficulties (Cook and Strachan 1999; Gergen et al. 1998; Mannino et al. 2001; Martinez et al. 1988; Rylander et al. 1995). There is increasing but inconsistent evidence that tobacco smoke exposure is linked with intellectual impairments and behavioral problems in children.
Tobacco smoke exposure has been linked to a variety of behavioral (Eskenazi and Castorina 1999; Fried et al. 1992; Orlebeke et al. 1999; Wakschlag et al. 1997; Wasserman et al. 2001; Williams et al. 1998) and developmental (Byrd and Weitzman 1994; Drews et al. 1996; Fried and Watkinson 2000; Fried et al. 1997, 1998; Makin et al. 1991; Olds et al. 1994; Rush and Callahan 1989) consequences for children. Associations with cognitive and achievement problems such as early grade retention (Byrd and Weitzman 1994), reduced vocabulary and reasoning abilities (Eskenazi and Bergmann 1995), and cognitive and intellectual deficits among children (Bauman et al. 1991; Johnson et al. 1999) have also been reported. Still, questions about the role of ETS exposure remain (Eskenazi and Castorina 1999).
Various methodologic limitations of prior studies contribute to the lack of clarity in the findings. Previous research on the effects of tobacco smoke on child outcomes has been limited by small to moderate sample sizes and reliance on parental reports of child exposure. Reports of ETS exposure are complicated by poor recall, an inattention to crucial details such as adjustment for the amount of tobacco exposure, the child’s proximity to the smoker, room ventilation, and other factors that may compromise the validity of exposure measures (Matt et al. 2000). It is difficult to distinguish between effects of prenatal and postnatal tobacco smoke exposure because children who are exposed prenatally also tend to be exposed postnatally. Studies with large sample sizes are therefore needed to separate the independent effects of prenatal and postnatal exposure.
The purpose of this study was to investigate the impact of ETS exposure on children’s cognitive skills, using a large, nationally representative sample of children and adolescents, using serum cotinine, a biomarker of ETS exposure.
Materials and Methods
The data source for this analysis, the Third National Health and Nutrition Examination Survey (NHANES III), conducted from 1988 to 1994 (Ezzati et al. 1992; National Center for Health Statistics 1994), was a cross-sectional, household survey of the civilian, noninstitutionalized U.S. population. Participant enrollment employed a stratified, multistage, probability sampling design. Data collection included parent and child interviews, direct assessment, health evaluation, and collection of biologic samples in participants’ homes and in a mobile examination center. The present study included data on all eligible children and adolescents 6–16 years of age.
The primary analysis relied on serum cotinine as a measure of ETS exposure. Cotinine, a metabolite of nicotine, can be measured in a number of bodily fluids, as well as in hair, and is the best currently available biomarker of exposure to ETS (Benowitz 1996). We measured serum cotinine with an isotope dilution, liquid chromatography, tandem mass spectrometry method developed and conducted by the National Center for Environmental Health, Centers for Disease Control (Bernert et al. 1997). This method has a reported detection limit of 0.05 ng/mL cotinine. Cotinine values below the limit of detection (left censored data) were imputed by randomly sampling values from the left tail of a log-normal distribution. Results from the imputed method are reported in this article.
Participants were administered two subtests of the Wide Range Achievement Test–Revised (WRAT-R) (Jastak and Wilkinson 1984). The reading subtest assessed letter recognition and word reading, and the math subtest contained oral and written problems ranging from simple addition to calculus. Two subtests from the Wechsler Intelligence Scale for Children–III (WISC-III) (Wechsler 1991) were also administered. The block design subtest assessed visual construction abilities using a set of modeled three-dimensional or printed two-dimensional geometric patterns that the child replicated using a set of red and white cubes. The digit span subtest assessed short-term and working memory by asking the child to repeat a series of increasingly long number sequences forward and backward.
Trained examiners administered tests in a standardized environment using uniform procedures. Ninety-five percent of the children were tested in English; the rest were tested in Spanish. Throughout the study, adherence to the standardized assessment protocol was maintained. Scores on the WRAT-R subtests were standardized to a mean ± SD of 100 ± 15. Scores on the WISC-III subtests were standardized to a mean of 10 ± 3. Appropriate age-standardized scores were used in all analyses.
Children with complete cognitive tests and serum cotinine values were included in the sample. Serum cotinine levels ≤15 ng/mL were used to identify the sample of children exposed to ETS but who were not active smokers, as in a previous NHANES analysis on ETS exposure and child health outcomes (Pirkle et al. 1996). Children were also excluded if they reported using tobacco products in the 5 days before cognitive assessment and blood collection regardless of cotinine level.
Statistical methods.
All analyses were performed using the SUDAAN statistical package (Shah et al. 1997) to account for the complex sampling design. Appropriate sample weights were applied according to the National Center for Health Statistics guidelines [Centers for Disease Control and Prevention (CDC) 1996] to produce accurate national estimates adjusting for the oversampling of specific population groups within NHANES III. Regression diagnostics were carried out to ensure that results did not depend on influential points, and correlation analyses confirmed lack of collinearity among variables included in the regression models.
Preliminary analyses revealed a nonlinear relationship between mean cognitive scores by various cotinine thresholds. Therefore, cotinine values were log-transformed for analyses to better represent the steeper increase in cognitive scores at lower cotinine values. Analyses using nontransformed cotinine values were performed separately by cotinine values above and below 1 ng/mL (~ 80th percentile) to calculate the linear slopes for these two ranges and test whether there was a significant difference in slope.
We calculated geometric mean serum cotinine concentrations and mean cognitive test scores for potential covariates based on a review of the literature. These variables included sex, race and ethnicity, poverty index (based on a ratio of family income and family size), parent educational level and marital status, region of the country, ferritin as a measure of iron status, and blood lead level. Poverty index, ferritin, and lead levels were categorized into terciles based on the sample distribution.
We investigated the effects of potential confounding factors identified from bivariate analyses by multiple linear regression analyses with log-transformed serum cotinine (nanograms per milliliter) concentration treated as a continuous independent variable. Graphical displays of the independent relationship between log-transformed cotinine and each cognitive outcome were generated. We also calculated adjusted mean cognitive scores for various levels of cotinine thresholds.
Parental interview data on prenatal exposure to tobacco smoke, birth weight, and history of neonatal intensive care unit (NICU) stay were available for a subsample of children 6–11 years of age. We conducted a secondary analysis to verify that inclusion of perinatal variables available only for this subsample did not alter findings of the larger sample.
Results
Of the 5,683 children and adolescents in NHANES III who were 6–16 years of age, 4,619 (81.3%) completed at least one test of cognitive abilities and had available serum cotinine values. Children with serum cotinine levels > 15 ng/mL (n = 155) or who reported active smoking during the 5 days before testing (n = 65) were excluded from this analysis. This yielded a final sample of 4,399 children (77.4% of all 6- to 16-year-olds) in the primary analysis. Children who were excluded from the final sample had lower scores on tests of math (p < 0.001), reading (p = 0.003), and block design (p = 0.02) than did children in the analysis. Excluded children were also more likely to live in households with lower marriage rates (p = 0.02). Because of our eligibility criteria, excluded children also had significantly higher levels of serum cotinine (p < 0.001).
Serum cotinine was detectable in 84% of children in the final sample, with 16% having cotinine levels below the limit of detection (< 0.05 ng/mL). After imputing randomly selected values from the left tail of a log-normal distribution, the geometric mean serum cotinine level for the sample was 0.23 ng/mL (SE = 0.01). Serum cotinine concentrations varied by children’s characteristics (Table 1). Serum cotinine concentrations were significantly higher among African Americans than Hispanics or non-Hispanic whites, among children of parents with a lower household income or lower educational achievement, among children living in the Midwest United States, and among those with higher blood lead concentrations. Children exposed to both prenatal and postnatal smoke and those exposed to postnatal smoke alone also had higher serum cotinine levels.
Consistent with previous research (Jordaan et al. 1999), mean serum cotinine levels were significantly higher among children who had at least one smoker living in their home (p < 0.001). Children’s serum cotinine levels also increased as the number of smokers in a household increased (p < 0.001) and as the number of cigarette packs smoked per day in a household increased (p < 0.001).
Overall mean scores for math, reading, block design, and digit span are presented in Table 1. In unadjusted analyses, cognitive performance scores differed significantly by sex, race or ethnicity, poverty status, parent marital status and educational level, and blood lead concentration. There was also a significant inverse relationship between serum cotinine and cognitive test scores. Children with the highest serum cotinine levels received significantly lower performance scores on all four tests than did children in the lowest cotinine level.
In multiple regression analyses using the log-transformation of cotinine and adjusting for covariates, serum cotinine was significantly associated with lower scores for reading, math, and visuospatial skills (Table 2). An increase in the log serum cotinine from level 1 to 10 ng/mL was associated with a 1.93-point loss in math scores (p ≤0.001) and a 2.7-point loss in reading scores (p ≤0.001) for tests with a standardized mean of 100. The same change in the log serum cotinine level was associated with a 0.55-point loss in block design scores (p ≤0.001) and a 0.08-point loss in digit span scores for tests with a standardized mean of 10.
There was a significant inverse relationship between the log of serum cotinine and cognitive abilities at lower levels of exposure. Children with serum cotinine levels < 0.1 ng/mL had an adjusted average reading score of 94.7. Children with cotinine levels between 0.1 and 1 ng/mL had an average 2.6-point drop in reading scores, children with levels 1–3 ng/mL had an additional 0.2-point drop in reading, and children with cotinine values > 3 ng/mL had an additional 4.8-point drop in reading score. Although the greatest decrease in reading scores was observed among children with higher cotinine levels (range, 3–15 ng/mL), there was a greater proportional change in reading scores per unit of cotinine exposure at levels in the range of 0.1–1 ng/mL. According to population estimates employing the appropriate sampling weights, we estimated that > 33.3 million children are at risk for ETS-related reading deficits (i.e., children with cotinine levels ≤15 ng/mL). Math and block design scores showed similar trends in decreasing cognitive scores with increasing cotinine levels (Table 3).
Questionnaire data on maternal smoking during pregnancy, birth weight, and NICU stay were available for a subsample of 2,738 children 6–11 years of age. Among this sub-sample of children, the covariate-adjusted relationship between the log of serum cotinine and cognitive scores indicates that an increase in the log serum cotinine from 1 to 10 ng/mL was associated with a related 2.4-point decrease in reading scores (p ≤0.05), a 1.6-point decrease in math scores, and a 0.42-point decrease in block design scores (p ≤0.05). In secondary analyses, inclusion of prenatal tobacco smoke exposure, birth weight, and NICU stay had little effect on the relationship between ETS exposure and reading scores (p ≤0.05). In contrast, the association of ETS exposure with block design was attenuated (Table 4).
The ETS-associated decrements in reading scores appeared to be greater at lower levels of serum cotinine (Figure 1). Math and block design also showed a steeper decline in scores at lower cotinine values than at higher values. To test whether the difference in the slopes was statistically significant, we conducted a stratified adjusted analysis including linear (non-transformed) cotinine values above and below 1 ng/mL (~80th percentile). Children with cotinine values ≤1 ng/mL (< 80th percentile) had an average 5.0-point decrease in reading scores for each 1-ng/mL increase in serum cotinine compared with an average 0.8-point decrease in reading scores for children with cotinine values above 1 ng/mL (> 80th percentile) (Figure 2). The difference between these averages was statistically significant (t = 2.38, p = 0.02).
Discussion
In this study we used serum cotinine, a bio-marker of ETS exposure, to examine the relationship between ETS exposure and cognitive abilities in a large, nationally representative sample of children and adolescents. A dose–response relationship was found in which higher levels of ETS exposure were associated with greater deficits in reading, math, and visuospatial reasoning but not short-term memory. The inverse relationship persisted at extremely low levels of exposure. Indeed, the estimated decrement appeared to be greater at lower serum cotinine levels. These data, in combination with other experimental and human studies linking ETS exposure with decreased performance in tests of reasoning ability and language development (Bauman et al. 1991; Eskenazi and Bergmann 1995) and tests of intelligence (Johnson et al. 1999) and an increased risk for grade retention (Byrd and Weitzman 1994) suggest that ETS may be causally associated with impairments in cognitive skills.
Reading ability was especially sensitive to ETS exposure. We observed a significant inverse ETS-associated decrement in reading scores that persisted at levels of ETS exposure < 0.5 ng/mL. We also found that the decrements in reading scores were greater in magnitude at the lowest levels of ETS exposure. Similarly, tobacco exposure during pregnancy has an effect on infant birth weight that demonstrates a steeper slope at lower levels of exposure (England et al. 2001). A similar phenomenon has been observed recently in the area of lead research, where children with blood lead levels < 10 μg/dL experience greater decrements in cognitive abilities for each 1-μg/dL increase in blood lead compared with children with higher blood lead levels (Canfield et al. 2003; Lanphear et al. 2000). The reason for the strikingly large decrement in reading scores and birth weight at lower serum cotinine levels is unclear and needs to be carefully evaluated in prospective studies including more frequent measures of biomarkers of exposure.
The relationship between tobacco smoke exposure and childhood reading skills has been previously explored. Researchers found links between postnatal ETS exposure and decrements in receptive vocabulary (Bauman et al. 1991; Eskenazi and Bergmann 1995). In a longitudinal study by Fried et al. (1997), a significant negative dose–response relationship with prenatal tobacco smoke exposure and specific reading functions was reported. Exposure to tobacco smoke products in utero was related to deficits in children’s abilities to use contextual cues and comprehension skills in understanding written passages. In this instance, reading was more seriously affected in the broad sense of understanding words in context rather than understanding individual words. Because the NHANES III used an instrument to measure letter recognition and word reading, we are unable to specifically test reading comprehension; however, children who have difficulties recognizing and reading individual words are also likely to have problems with comprehension.
We also found an inverse relationship between ETS exposure and visuospatial reasoning skills. The ETS-associated impairment in visuospatial skills persisted to lower levels of exposure, increasing in magnitude among children who had the lowest levels of exposure. This finding supports previous studies that found children exposed to ETS during childhood performed significantly more poorly on reasoning tasks compared with children who were either unexposed to tobacco smoke or exposed during the prenatal period only (Bauman et al. 1991; Eskenazi and Bergmann 1995). In a more detailed investigation of tobacco smoke’s impact on visuoperceptual skills, Fried and Watkinson (2000) found that children exposed to tobacco smoke prenatally experienced a great deal of difficulty in aspects of visual discrimination, visual memory, and visual–spatial relationships. It is plausible that a similar effect may arise from postnatal ETS exposure, but this will require further investigation.
The negative association between ETS exposure and math skills found in this study was highly significant. It did not, however, persist at the lowest levels of exposure in our sample. The overall log-linear regression line nonetheless suggested a general decrease in math scores as cotinine levels rise. Fried et al. (1998) found no relationship between prenatal tobacco smoke exposure and math skills. Other researchers have reported a positive effect of tobacco smoke on alertness and cognitive function among the elderly or impaired as well as in animal studies (Picciotto and Zoli 2002). Additional studies are needed to validate our findings that ETS exposure has a negative impact on math skills.
Three main aspects of the present study add strength to the conclusion that ETS exposure is a neurotoxin that is linked with cognitive deficits. First, the large sample size allows for the inclusion of numerous potential covariates while retaining statistical power. Second, this is the first study to rely primarily on a bio-marker of postnatal ETS exposure in examining this association, thus reducing recall bias. Third, our findings are consistent with specific adverse effects observed in other studies, including deficits in reading and visuospatial reasoning skills (Bauman et al. 1991; Eskenazi and Bergmann 1995; Fried and Watkinson 2000; Fried et al. 1997).
This study has some limitations. The NHANES III design did not include measures of cognitive abilities of parents or of the quality of the home environment. Instead, we relied on maternal education, income, and marital status as surrogate markers in our analyses. ETS exposure was assessed through the measurement of serum cotinine, an indicator of exposure within a few days. It is unclear whether short-term exposure (i.e., serum cotinine, which has a half-life of 48–72 hr) is representative of the child’s chronic exposure or is indicative of the short-term toxicity of ETS exposure. Other studies have found serum cotinine levels to be stable over time among smokers and nonsmokers (de Leon et al. 2002; Kemmeren et al. 1994). In future studies, markers of both short-term and long-term exposure should be evaluated with cognitive outcomes, and further exploration of potential mechanisms underlying these effects is needed.
One of the difficulties in performing research on childhood ETS exposure is the challenge of distinguishing the effects of prenatal tobacco smoke exposure from childhood (postnatal) ETS exposure. Because children exposed to ETS are often those who were also exposed to tobacco smoke prenatally, large sample sizes are necessary to distinguish any adverse effects of prenatal ETS exposure from postnatal ETS exposure. Among the subsample of 6- to 11-year-olds with prenatal data, 23.6% of children had been exposed to tobacco smoke during pregnancy. This is equivalent to the current adult smoking rate in the United States (CDC 2001) and twice the reported rate of smoking during pregnancy when the NHANES III data were being collected (Matthews 2001). Nevertheless, the significant negative association between ETS exposure and reading ability persisted even when the prenatal variables of exposure to tobacco smoke, birth weight, and NICU stay were included among this subsample. These prenatal data were obtained by parental report and may result in an underestimate of the intensity of tobacco smoke exposure. To confirm the causal role of ETS in diminished cognitive abilities among children, prospective birth cohort studies will be necessary.
The mechanisms by which ETS may exert its effects on cognitive function are unknown. Research into the effects of nicotine and cotinine (Audesirk and Cabell 1999) on neurite length suggest that exposure to these substances during prenatal development, as with lead exposure (Schneider et al. 2003), may affect both the survival and growth of essential nervous system components even at very low levels of exposure. Although prenatal exposure to tobacco smoke has been found to affect neurite growth and neuronal connections, more research is needed to explore the mechanism by which postnatal ETS affects cognitive ability and whether this is a similar or different mechanism from the effects during prenatal development.
ETS is recognized as a serious threat to public health. Still, acceptable levels of exposure have not been established. From the present analysis, we are unable to recommend a safe level of exposure to ETS because there is no discernable threshold for the impact of ETS on the cognitive functioning of children. It is likely that further analyses of the data being acquired through the ongoing NHANES will provide an opportunity to explore ETS-related impairments at even lower serum cotinine levels because ETS exposure has declined significantly over the past decade (CDC 2002).
Conclusion
The findings of this study confirm previous research indicating an inverse relationship with ETS exposure and cognitive outcomes. We also provide new information indicating that ETS is neurotoxic at extremely low levels. Exposure to ETS in U.S. children therefore has substantial public health impact beyond asthma, otitis media, and other widely recognized adverse consequences. According to population estimates employing the appropriate sampling weights, we estimated that > 21.9 million children are at risk for ETS-related reading deficits. Although further research is necessary to confirm these findings, this analysis along with other studies provides adequate evidence to support policy to further reduce childhood exposure to ETS.
Figure 1 Log-linear regression line for reading scores by serum cotinine levels. Dashed lines indicate 95% confidence interval.
Figure 2 Log-linear model for cotinine (solid line) versus linear models for cotinine among children with cotinine above and below 1 ng/mL (dashed lines; ~ 80th percentile).
Table 1 Mean serum cotinine concentrations and cognitive test scores for children and adolescents, 6–16 years of age, NHANES III (1988–1994).
Variable Geometric mean serum cotinine level (ng/mL) Math Reading Block design Digit span
Total (n = 4,399) 0.23 94.6 92.5 9.6 8.7
Sex
Male 0.22 94.2 92.1 10.0## 8.6*
Female 0.24 95.0 92.9 9.2## 8.8*
Race/ethnicity
Non-Hispanic black 0.45## 86.5## 84.9## 7.1## 8.0##
Non-Hispanic white (referent) 0.22 97.6 95.6 10.3 9.1
Hispanic 0.14# 87.6## 86.3## 8.7## 7.5##
Non-Hispanic other 0.16 99.5 90.4 10.2 8.2**
Region
Midwest 0.32* 96.0 93.2 10.1 9.0*
South 0.28 93.0 91.8 8.9* 8.5
West 0.15 95.8 92.0 10.1* 8.7
Northeast (referent) 0.20 94.3 93.7 9.6 8.6
Parent marital status
Married 0.20## 96.1## 93.6## 9.8## 8.8##
Not married 0.41## 88.9## 88.1## 8.7## 8.2##
Parent education level
< High school graduate 0.39## 86.2## 83.6## 8.3## 7.7##
High school graduate 0.30## 92.8## 91.1## 9.2## 8.5##
> High school graduate (referent) 0.14 100.5 98.1 10.6 9.5
Poverty index ratio
Lower tercile 0.37## 87.8## 84.8## 8.4## 8.0##
Middle tercile 0.22* 94.3## 92.5## 9.5## 8.6##
Higher tercile (referent) 0.15 101.2 99.7 10.8 9.8
Lead
Lower tercile (referent) 0.16 97.7 96.2 9.9 9.0
Middle tercile 0.24 # 94.7** 92.3## 9.8 8.7*
Higher tercile 0.48## 87.7## 84.6## 8.5 ## 8.1##
Ferritin
Lower tercile (referent) 0.21 94.5 92.2 9.7 8.7
Middle tercile 0.23 94.9 92.9 9.7 8.8
Higher tercile 0.24 94.6 92.5 9.4 8.7
Smokinga
Prenatal and postnatal 1.48## 92.1** 87.5# 8.9## 8.5*
Prenatal only 0.14 92.0 93.9 10.1 8.8
Postnatal only 0.77## 92.0## 89.1## 9.1## 8.4##
None (ref) 0.10 96.5 92.6 10.2 9.1
Received care in NICUa
Yes 0.30 93.4 89.1 9.9 8.7
No 0.24 94.7 91.4 9.7 8.9
Birth weighta
< 2,500 g 0.41* 88.9# 87.2* 8.2## 8.1*
> 2,500 g 0.24* 95.0# 91.6* 9.9## 9.0*
A significant association is compared with the referent group. For bivariate categories the referent group for one category is the other group.
a Includes only children 6–11 years of age.
* p ≤0.05;
** p ≤0.01;
# p ≤0.005;
## p ≤0.001.
Table 2 Log-linear effect of cotinine ≤15 ng/mL [β-coefficient (SE β)] and potential covariates on cognitive test scores at 6- to 16 years of age, NHANES III (1988–1994).
Math Reading Block design Digit span
Log cotinine (ng/mL) −1.93 (0.70)** −2.69 (0.75)## 0.55 (0.12)## −0.08 (0.13)
Sex
Male −1.09 (0.80) −0.78 (0.83) 0.76 (0.18)## −0.34 (0.13)*
Female (referent) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00)
Race/ethnicity
African American −5.41 (1.05)## −4.90 (0.91)## −2.26 (0.18)## −0.56 (0.17)#
Hispanic −4.91 (1.27)## −3.89 (1.11)## −0.96 (0.29)# −0.90 (0.23)##
Other 4.06 (1.92)* −0.98 (3.04) 0.22 (0.36) −0.63 (0.45)
White (referent) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00)
Parent education 0.90 (0.13)## 0.87 (0.16)## 0.14 (0.03)## 0.15 (0.02)##
Poverty status 1.81 (0.42)## 2.25 (0.36)## 0.33 (0.08)## 0.20 (0.07)**
Region
Midwest 2.38 (2.28) 0.61 (2.31) 0.95 (0.23)## 0.49 (0.23)*
South 0.68 (1.87) −0.12 (2.30) −0.01 (0.21) 0.12 (0.23)
West 1.47 (2.35) −1.56 (2.63) 0.63 (0.22)** 0.30 (0.26)
Northeast (referent) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00)
Parent marital status
Not married −1.62 (1.29) 0.94 (1.03) 0.36 (0.20) −0.001 (0.16)
Married (referent) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00) 0.00 (0.00)
Blood lead (ng/L) −0.57 (0.17)# −0.80 (0.21)## −0.08 (0.03)* −0.03 (0.02)
Ferritin (ng/L) 0.01 (0.01) 0.01 (0.01) −0.002 (0.001) −0.001 (0.001)
* p ≤0.05;
** p ≤0.01;
# p ≤0.005;
## p ≤0.001.
Table 3 Adjusted mean cognitive test scores (mean ± SE) at increasing log cotinine levels for children 6–16 years of age, controlling for potential covariates, NHANES III (1988–1994).
Cotinine level (ng/mL) Math Reading Block design Digit span
< 0.1 95.83 ± 0.94 94.67 ± 0.81 9.91 ± 0.15 8.87 ± 0.13
0.1–1 94.69 ± 0.79 92.12 ± 0.82 9.59 ± 0.10 8.67 ± 0.09
1–3 94.72 ± 1.05 91.88 ± 1.34 9.43 ± 0.21 8.87 ± 0.22
3–15 88.69 ± 1.93 87.13 ± 1.93 8.52 ± 0.30 8.00 ± 0.29
Table 4 Adjusted slope of log cotinine [β-coefficient (SE β)] on cognitive test scores between the full sample of 6–16-year-olds and subsample of 6–11-year-olds.
Full sample (n = 4,399) Subsample (n = 2,738) Subsample including prenatal data
Math −1.93 (0.70)** −1.63 (0.88) −1.15 (1.03)
Reading −2.69 (0.75)## −2.37 (0.93)* −1.94 (0.87)*
Block design −0.55 (0.12)## −0.42 (0.16)* −0.28 (0.16)
Digit span −0.08 (0.13) −0.11 (0.16) −0.07 (0.18)
* p ≤0.05;
** p ≤0.01;
## p ≤0.001.
==== Refs
References
Audesirk T Cabell L 1999 Nanomolar concentrations of nicotine and cotinine alter the development of cultured hippocampal neurons via non-acetylcholine receptor-mediated mechanisms Neurotoxicology 20 639 646 10499362
Bauman KE Flewelling RL LaPrelle J 1991 Parental cigarette smoking and cognitive performance of children Health Psychol 10 282 288 1915215
Benowitz NL 1996 Cotinine as a biomarker of environmental tobacco smoke exposure Epidemiol Rev 18 188 204 9021312
Bernert JT Jr Turner WE Pirkle JL Sosnoff CS Akins JR Waldrep MK 1997 Development and validation of sensitive method for determination of serum cotinine in smokers and nonsmokers by liquid chromatography/atmospheric pressure ionization tandem mass spectrometry Clin Chem 43 2281 2291 9439445
Byrd RS Weitzman ML 1994 Predictors of early grade retention among children in the United States Pediatrics 93 481 487 8115209
Canfield RL Henderson CR Jr Cory-Slechta DA Cox C Jusko TA Lanphear BP 2003 Intellectual impairment in children with blood lead concentrations below 10 microg per deciliter N Engl J Med 348 1517 1526 12700371
CDC 1996. The Third National Health and Nutrition Examination Survey (NHANES III, 1988–94) Reference Manuals and Reports. Atlanta, GA:Centers for Disease Control and Prevention National Center for Health Statistics. Available: http://www.cdc.gov/nchs/about/major/nhanes/NHANESIII_Reference_Manuals.htm [accessed 30 November 2004].
CDC (Centers for Disease Control and Prevention) 2001 Cigarette smoking among adults—United States, 2000 MMWR Morb Mortal Wkly Rep 51 642 645
CDC 2002. Second National Report on Human Exposure to Environmental Chemicals. Atlanta, GA:Centers for Disease Control and Prevention.
Chilmonczyk BA Salmun LM Megathlin KN Neveux LM Palomaki GE Knight GJ 1993 Association between exposure to environmental tobacco smoke and exacerbations of asthma in children [see comments] N Engl J Med 328 1665 1669 8487825
Cook DG Strachan DP 1999 Health effects of passive smoking—10: summary of effects of parental smoking on the respiratory health of children and implications for research Thorax 54 357 366 10092699
de Leon J Diaz FJ Rogers T Browne D Dinsmore L Ghosheh OH 2002 Total cotinine in plasma: a stable biomarker for exposure to tobacco smoke J Clin Psychopharmacol 22 496 501 12352273
Drews CD Murphy CC Yeargin-Allsopp M Decoufle P 1996 The relationship between idiopathic mental retardation and maternal smoking during pregnancy Pediatrics 97 547 553 8632944
Ehrlich RI Du Toit D Jordaan E Zwarenstein M Potter P Volmink JA 1996 Risk factors for childhood asthma and wheezing. Importance of maternal and household smoking Am J Respir Crit Care Med 154 681 688 8810605
England LJ Kendrick JS Gargiullo PM Zahniser SC Hannon WH 2001 Measures of maternal tobacco exposure and infant birth weight at term Am J Epidemiol 153 954 960 11384951
Eskenazi B Bergmann JJ 1995 Passive and active maternal smoking during pregnancy, as measured by serum cotinine, and postnatal smoke exposure. I. Effects on physical growth at age 5 years Am J Epidemiol 142 S10 S18 7572982
Eskenazi B Castorina R 1999 Association of prenatal maternal or postnatal child environmental tobacco smoke exposure and neurodevelopmental and behavioral problems in children Environ Health Perspect 107 991 1000 10585903
Ezzati TM Massey JT Waksberg J Chu A Maurer KR 1992 Sample design: Third National Health and Nutrition Examination Survey Vital Health Stat 2 1 35
Fried PA Watkinson B 2000 Visuoperceptual functioning differs in 9- to 12-year olds prenatally exposed to cigarettes and marihuana [published erratum Neurotoxicol Teratol 22:267] Neurotoxicol Teratol 22 11 20 10642110
Fried PA Watkinson B Gray R 1992 A follow-up study of attentional behavior in 6-year-old children exposed prenatally to marihuana, cigarettes, and alcohol Neurotoxicol Teratol 14 299 311 1454038
Fried PA Watkinson B Gray R 1998 Differential effects on cognitive functioning in 9- to 12-year olds prenatally exposed to cigarettes and marihuana Neurotoxicol Teratol 20 293 306 9638687
Fried PA Watkinson B Siegel LS 1997 Reading and language in 9- to 12-year olds prenatally exposed to cigarettes and marijuana Neurotoxicol Teratol 19 171 183 9200137
Gergen PJ Fowler JA Maurer KR Davis WW Overpeck MD 1998 The burden of environmental tobacco smoke exposure on the respiratory health of children 2 months through 5 years of age in the United States: Third National Health and Nutrition Examination Survey, 1988 to 1994 Pediatrics 101 E8 9445518
Jastak S Wilkinson G 1984. The Wide Range Achievement Test–Revised: Administration Manual. Wilmington, DE:Jastak Associates, Inc.
Johnson DL Swank PR Baldwin CD McCormick D 1999 Adult smoking in the home environment and children’s IQ Psychol Rep 84 149 154 10203944
Jordaan ER Ehrlich RI Potter P 1999 Environmental tobacco smoke exposure in children: household and community determinants Arch Environ Health 54 319 327 10501147
Kemmeren JM van Poppel G Verhoef P Jarvis MJ 1994 Plasma cotinine: stability in smokers and validation of self-reported smoke exposure in nonsmokers Environ Res 66 235 243 8055845
Lanphear BP Dietrich K Auinger P Cox C 2000 Cognitive deficits associated with blood lead concentrations < 10 microg/dL in US children and adolescents Public Health Rep 115 521 529 11354334
Makin J Fried PA Watkinson B 1991 A comparison of active and passive smoking during pregnancy: long-term effects Neurotoxicol Teratol 13 5 12 2046627
Mannino D Moorman J Kingsley B Rose D Repace J 2001 Health effects related to environmental tobacco smoke exposure in children in the United States Arch Pediatr Adolesc Med 155 36 41 11177060
Martinez FD Antognoni G Macri F Bonci E Midulla F De Castro G Ronchetti R 1988 Parental smoking enhances bronchial responsiveness in nine-year-old children Am Rev Respir Dis 138 518 523 3202406
Martinez FD Cline M Burrows B 1992 Increased incidence of asthma in children of smoking mothers Pediatrics 89 21 26 1728015
Matt GE Hovell MF Zakarian JM Bernert JT Pirkle JL Hammond SK 2000 Measuring secondhand smoke exposure in babies: the reliability and validity of mother reports in a sample of low-income families Health Psychol 19 232 241 10868767
Matthews T 2001 Smoking during pregnancy in the 1990s Natl Vital Stat Rep 49 1 15
McMartin KI Platt MS Hackman R Klein J Smialek JE Vigorito R 2002 Lung tissue concentrations of nicotine in sudden infant death syndrome (SIDS) J Pediatr 140 205 209 11865272
Mitchell EA Ford RP Stewart AW Taylor BJ Becroft DM Thompson JM 1993 Smoking and the sudden infant death syndrome Pediatrics 91 893 896 8474808
National Center for Health Statistics 1994 Plan and operation of the Third National Health and Nutrition Examination Survey, 1988–1994 Vital Health Stat 1 1 416
Olds DL Henderson CR Jr Tatelbaum R 1994 Intellectual impairment in children of women who smoke cigarettes during pregnancy [published erratum Pediatrics 93:973] Pediatrics 93 221 227 8121734
Orlebeke JF Knol DL Verhulst FC 1999 Child behavior problems increased by maternal smoking during pregnancy Arch Environ Health 54 15 19 10025411
Picciotto MR Zoli M 2002 Nicotinic receptors in aging and dementia J Neurobiol 53 641 655 12436427
Pirkle JL Flegal KM Bernert JT Brody DJ Etzel RA Maurer KR 1996 Exposure of the US population to Environmental Tobacco Smoke: the Third National Health and Nutrition Examination Survey, 1988 to 1991 JAMA 275 1233 1240 8601954
Reijneveld SA Brugman E Hirasing RA 2000 Infantile colic: maternal smoking as potential risk factor Arch Dis Child 83 302 303 10999861
Rush D Callahan KR 1989 Exposure to passive cigarette smoking and child development. A critical review Ann NY Acad Sci 562 74 100 2662865
Rylander E Pershagen G Eriksson M Bermann G 1995 Parental smoking, urinary cotinine, and wheezing bronchitis in children Epidemiology 6 289 293 7619938
Schneider JS Huang FN Vemuri MC 2003 Effects of low-level lead exposure on cell survival and neurite length in primary mesencephalic cultures Neurotoxicol Teratol 25 555 559 12972068
Schoendorf KC Kiely JL 1992 Relationship of sudden infant death syndrome to maternal smoking during and after pregnancy [see comments] Pediatrics 90 905 908 1437432
Shah B Barnwell B Bieler G 1997. SUDAAN User’s Manual, Release 7.5. Research Triangle Park, NC:Research Triangle Institute.
Wakschlag LS Lahey BB Loeber R Green SM Gordon RA Leventhal BL 1997 Maternal smoking during pregnancy and the risk of conduct disorder in boys Arch Gen Psychiatry 54 670 676 9236551
Wasserman GA Liu X Pine DS Graziano JH 2001 Contribution of maternal smoking during pregnancy and lead exposure to early child behavior problems Neurotoxicol Teratol 23 13 21 11274872
Wechsler W 1991. Wechsler Intelligence Scale for Children–III. San Antonio, TX:Psychological Corporation.
Williams GM O’Callaghan M Najman JM Bor W Andersen MJ Richards DUC 1998 Maternal cigarette smoking and child psychiatric morbidity: a longitudinal study Pediatrics 102 E11 9651463
Wisborg K Kesmodel U Henriksen TB Olsen SF Secher NJ 2000 A prospective study of smoking during pregnancy and SIDS Arch Dis Child 83 203 206 10952633
|
15626655
|
PMC1253717
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2005 Jan 7; 113(1):98-103
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7210
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7241ehp0113-00010415626656Children's HealthArticlesA Noninvasive Isotopic Approach to Estimate the Bone Lead Contribution to Blood in Children: Implications for Assessing the Efficacy of Lead Abatement Gwiazda Roberto 1Campbell Carla 2Smith Donald 11Environmental Toxicology, University of California, Santa Cruz, California, USA2The Children’s Hospital of Philadelphia, Philadelphia, Pennsylvania, USAAddress correspondence to R. Gwiazda, ETOX, 1156 High St., University of California, Santa Cruz, CA 95064 USA. Telephone: (831) 459-3347. Fax: (831) 459-3524. E-mail:
[email protected] are very grateful to participating families and to S. Harper, who superbly coordinated all logistics.
This work was supported by the U.S. Department of Housing and Urban Development. The authors are solely responsible for the accuracy of the statements and interpretations contained in this publication, which do not necessarily reflect the views of the U.S. government.
The authors declare they have no competing financial interests.
1 2005 7 10 2004 113 1 104 110 7 5 2004 7 10 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Lead hazard control measures to reduce children’s exposure to household lead sources often result in only limited reductions in blood lead levels. This may be due to incomplete remediation of lead sources and/or to the remobilization of lead stores from bone, which may act as an endogenous lead source that buffers reductions in blood lead levels. Here we present a noninvasive isotopic approach to estimate the magnitude of the bone lead contribution to blood in children following household lead remediation. In this approach, lead isotopic ratios of a child’s blood and 5-day fecal samples are determined before and after a household intervention aimed at reducing the child’s lead intake. The bone lead contribution to blood is estimated from a system of mass balance equations of lead concentrations and isotopic compositions in blood at the different times of sample collection. The utility of this method is illustrated with three cases of children with blood lead levels in the range of 18–29 μg/dL. In all three cases, the release of lead from bone supported a substantial fraction of the measured blood lead level postintervention, up to 96% in one case. In general, the lead isotopic compositions of feces matched or were within the range of the lead isotopic compositions of the household dusts with lead loadings exceeding U.S. Environmental Protection Agency action levels. This isotopic agreement underscores the utility of lead isotopic measurements of feces to identify household sources of lead exposure. Results from this limited number of cases support the hypothesis that the release of bone lead into blood may substantially buffer the decrease in blood lead levels expected from the reduction in lead intake.
abatement efficacyblood leadbone leadfecal leadlead abatementlead hazardslead isotopeslead loadings
==== Body
Most (> 70%) of the body lead burden in children is contained within the skeleton (Barry 1981). Because lead is qualitatively a biologic analog to calcium, its uptake and release from the skeleton are partly controlled by processes affecting bone growth and turnover (Hu et al. 1998; O’Flaherty 1998). In adults, skeletal lead is contained within long-lived compartments of cortical [elimination half-life (t1/2) > 5–10 years] and trabecular (elimination t1/2 > 1 year) bone, with comparatively small amounts of lead in tissue compartments that rapidly exchange with extracellular fluid and plasma (Hu et al. 1998; Leggett 1993; O’Flaherty 1998; Rabinowitz et al. 1976). In children, however, the turnover rates of skeletal reservoirs of lead and the impact of bone lead releases on blood lead content are not well understood. In children exposed to lead hazards, the accumulation of lead in bone and other tissues is of serious concern because these body lead stores are believed to serve as internal sources of lead to blood during bone remodeling (Gulson et al. 1996, 1997b; Leggett 1993; Nordberg et al. 1991; O’Flaherty 1994). Moreover, mobilization of accumulated skeletal lead stores back into blood is suspected to be responsible for the apparent limited success of various lead hazard control measures to decrease blood lead levels in exposed children (Burgoon et al. 1995; Rust et al. 1999). These abatement efforts typically result in reductions of blood lead levels in exposed children of no more than 30% when evaluated within several months after intervention [U.S. Environmental Protection Agency (EPA) 1995].
The importance of bone lead storage and mobilization in controlling blood lead levels has been documented in adults (Rabinowitz et al. 1976; Smith et al. 1996). Increased bone resorption in winter months (Oliveira et al. 2002), during pregnancy and lactation (Gulson et al. 1997a; Lagerkvist et al. 1996; Manton et al. 2003; Rothenberg et al. 2001; Silbergeld 1991; Tellez-Rojo et al. 2002), under hyperthyroidism conditions (Goldman et al. 1994), or due to skeletal disease (Berlin et al. 1995) has been associated with elevated blood lead levels. In addition, experimental lead isotope studies in nonhuman primates have demonstrated lead releases from bone to blood (Inskip et al. 1996). The existence of a relationship between bone remodeling and blood lead content has been also hypothesized for children (Angle et al. 1995; Gulson et al. 1996; Gwiazda and Smith 2000; Hu et al. 1998; Manton et al. 2000; O’Flaherty 1994; Rust et al. 1999), though this link is difficult to document partly because of the challenges of determining bone lead burdens in pediatric populations (Hu et al. 1998).
Measurements of bone lead content in children could be used to establish empirical relationships between bone and blood lead levels in pediatric populations. However, this relationship would be affected by other factors such as current lead intake, age, and history of exposure that are thought to affect the nature of the bone lead–blood lead relationship. Nevertheless, because of the importance of bone lead in human lead toxicokinetics, the potential effect of bone turnover on blood lead content has been included in the structure of pharmacokinetic models of childhood lead poisoning. These include the Integrated Exposure and Uptake Biokinetic model (White et al. 1998), O’Flaherty’s (1998) physiologically based pharmacokinetic model, and Leggett’s (1993) biokinetic lead model. Validation of these models for bone lead release has been limited, however, because of the scarcity of suitable pediatric data for accurate ground-truthing and calibration.
Lead isotopic methods provide an alternative approach to estimate the impact of endogenous sources of lead on blood lead content (Gulson et al. 1997b; Smith et al. 1996). In its simplest form, this approach apportions the blood lead isotopic composition as a mixture of two end members: the lead isotopic composition of intake and the lead isotopic composition of the endogenous source(s). The critical challenge in applying this approach is the characterization of the isotopic composition of the end members contributing lead to blood (e.g., external sources and the skeleton). To this end, a variety of experimental designs have been used in adults. In these designs, the isotopic composition of the lead intake either was estimated from analysis of environmental samples (Gulson et al. 1995, 1996; Manton 1985; Smith et al. 1996) and from duplicate diets (Gulson et al. 1997a; Manton 1985; Rabinowitz et al. 1976) or was purposefully changed (Facchetti 1989; Rabinowitz et al. 1973, 1976, 1977). The lead isotopic composition of the endogenous skeletal source was estimated on the basis of the assumed historical exposure (Gulson et al. 1995, 1997b) or measured directly on bone samples (Manton 1985; Smith et al. 1996). In some cases the fraction of lead derived from the skeleton was calculated from simple proportionality (Gulson et al. 1995; Smith et al. 1996), whereas in others its computation required the use of mathematical models (Colombo and Fantechi 1983; Rabinowitz et al. 1973, 1976, 1977).
Studies by Gulson et al. (1996, 1997b), who used the lead isotopic approach to estimate the skeletal lead contribution to blood in children, took advantage of the fact that the studied children had lived at a younger age in locations with a presumably well-characterized environmental lead isotopic composition, which was different from that of their current exposure. The authors then assumed that the skeletal lead carried a homogeneous isotopic signature from the earlier exposure. Although their work provides supporting evidence for the contribution of bone lead to blood lead in children, their methodologic approach is limited to the special circumstances of a child moving to a very different location. In most cases, however, the lead isotopic composition of children’s skeletal tissue cannot be empirically ascertained, and therefore the apportionment of the blood lead isotopic composition between the skeletal and the exogenous end members is not possible. Isotopic measurements of shed deciduous lead in teeth could serve as proxy of the lead isotopic composition of bone, but this opportunistic sampling would be useful only for children ≥ 5 years of age. Similarly, it is often difficult to obtain a weighted average lead isotopic composition of lead intake, given the various possible sources and pathways of exposure (dust, soil, food, air) from which children absorb lead. Isotopic characterization of lead intake has been done from duplicate diets. However, this sampling method does not include all sources of lead exposure to the child, especially for younger children who may ingest high amounts of lead from environmental sources through increased hand-to-mouth activity.
Here we present a noninvasive isotopic approach to estimate the magnitude of the bone lead contribution to blood in children following household lead remediation. This approach does not require lead isotopic measurements of bone, nor does it assume the lead isotopic ratio of bone on the basis of the child’s lead exposure history. Instead, blood and feces are sampled for lead concentration and isotopic analyses before and after implementation of environmental lead hazard control measures to reduce the child’s lead exposure(s). Estimation of the bone lead contribution to blood using this method is illustrated with three cases of childhood lead poisoning. In addition, the sources of lead exposure to the child are identified from a comparison of the lead isotopic compositions of household sources and feces, using the latter as a surrogate measure of the magnitude and isotopic composition of lead intake.
Materials and Methods
Experimental approach.
The isotopic composition of blood is a function of the isotopic compositions and relative lead contributions of exogenous intake and endogenous sources. Here, we assume that the isotopic composition of feces reflects the isotopic composition of lead intake. However, the isotopic composition of bone is not known. To calculate this value and be able to solve the relative lead contributions from intake and from the skeleton to blood, we rely on an induced change in the magnitude and isotopic composition of lead intake through the elimination of identified household sources of lead exposure (i.e., household lead abatement intervention). The assumption in this approach is that by reducing the magnitude of the child’s lead intake, the relative contribution of lead to blood from the endogenous skeletal source increases and the lead isotopic composition of blood shifts toward the isotopic value of bone.
We applied a system of linear equations to calculate the endogenous lead contribution to blood, with lead content and isotopic composition of blood and feces before and after intervention as independent variables. More generally, this system of equations can be applied between any two time points with different blood lead levels, regardless of the cause and direction of change in blood lead content (increase or decrease).
We used the following mass balance equations for lead content and for lead isotopes at two different time points, t1 and t2, to describe the mixing of lead in blood:
where Pbblood is the concentration of lead in blood, in micrograms per deciliter. Pbin and Pbbone are the amounts of lead in blood from external intake and from bone, respectively, in micrograms per deciliter. (207Pb/206Pb)in is the isotopic ratio of lead in blood derived from external intake, and it is assumed to be identical to the isotopic composition of lead measured in feces, as follows:
It is also assumed that the lead isotopic composition of bone did not change between the two time points considered, as follows:
It is assumed that the amount of lead in blood from the external intake, Pbin, is proportional to the rate of lead intake. Here, the rate of lead excretion (Pbfeces, in micrograms lead per day) is used as a surrogate of the rate of lead intake, as follows:
where K is a biokinetic constant (in micrograms per deciliter/micrograms excreted per day) that relates the lead content of feces to the amount of lead in blood from external intake. This biokinetic constant K is different from the more familiar term biokinetic slope factor (BKSF), which refers to the increase in blood lead per unit of lead absorbed (instead of excreted) across the gastrointestinal (GI) tract (Bowers et al. 1994; Bowers and Cohen 1998; U.S. EPA 2003). This approach yields a solvable system of six equations with six unknowns, K, Pbint1, Pbint2, Pbbonet1, Pbbonet2, (207Pb/206Pb)bone, with no need for parameterization (e.g., use of independently obtained parameters that describe fractional lead absorption across the GI tract, rate of bone turnover, etc.).
Notably, this method can be applied to obtain the relative contributions of lead from the intake and the skeleton to blood only when the lead isotopic compositions of the external (intake) and internal (skeleton) sources are different. In practical terms, because the isotopic composition of the skeletal lead source typically cannot be known, this approach can be applied only if the difference between the blood and intake lead isotopic compositions is greater than the isotopic measurement error.
Subjects.
Children were recruited by the Children’s Hospital of Philadelphia from referrals by the Philadelphia Childhood Lead Poisoning Prevention Program. Inclusion criteria were that blood lead level was between 15 and 35 μg/dL, the child was < 6 years of age, the child spent most of his or her waking time within a single household environment, and the blood and fecal lead isotopic compositions were measurably different (to confirm the latter criterion, blood and fecal samples were analyzed within 2 weeks following recruitment). Four cases were recruited. Three boys, 14, 20, and 46 months of age, met the inclusion criteria and were retained in the study (Table 1). One case did not meet the latter criterion above and was excluded from follow-up. Informed written consent was obtained from all parents/guardians. All procedures used in the recruitment of subjects, including the administered questionnaire and the collection of biologic and environmental samples, received prior review and approval by the human subjects institutional review boards of the University of California at Santa Cruz and the Children’s Hospital in Philadelphia.
Sample collection.
Blood, 5-day complete fecal samples, and household environmental samples were collected at enrollment. Within 2 months, a state-certified lead abatement contractor conducted a thorough cleaning of the household environment, including high-efficiency particulate air (HEPA) vacuuming and wet washing of all horizontal surfaces with trisodium phosphate detergent. Blood and 5-day fecal samples were collected a second time (t2) at least 1 month after the house-hold cleaning. Finally, a third round of blood and 5-day fecal collections was performed at least 3 months after the second round of sample collection (Table 1).
Blood samples (3 mL) were collected into low-lead heparinized Vacutainer tubes (no. 367734; Becton-Dickinson, Franking Lakes, NJ) by the Children’s Hospital of Philadelphia. Parents collected daily fecal samples in diapers provided by the study (LUVS Ultra Leak Guards no. 4; Procter & Gamble, Cincinnati, OH) or in perforated urine collection “hats” (McKesson Medical Surgical, Richmond, VA) that had been prewashed with distilled water and air-dried in a filtered-air environment. Household samples of all deteriorated paints, floor dusts, and soils, if appropriate, were sampled by the Philadelphia Health Department following U.S. Department of Housing and Urban Development (HUD) guidelines (HUD 1995). All samples were shipped to the University of California at Santa Cruz for lead concentration and isotopic composition analyses, as described below.
Analytical techniques.
Processing of biologic samples was conducted under trace-metal–clean HEPA-filtered air (Class-100) conditions using clean techniques (Smith et al. 1992). Acids used in sample processing and analyses were quartz double distilled, water was ultrapure grade (18 MΩ.cm), and all sample-processing plasticware was acid cleaned (Flegal and Smith 1992).
Blood samples were processed in triplicate as described in Gwiazda and Smith (2000). Ultrapure water was added to fecal samples (at least two parts water to one part feces, wt/wt), and the mix was homogenized with a stainless steel blender. Duplicate aliquots (~2.5 g each) of the fecal homogenate were dried and digested overnight in 2–3 mL sub-boiling 16N HNO3. After evaporation to dryness, samples were reconstituted in 1N HNO3, and centrifuged at 15,000 × g. The supernatant was spiked with 209Bi for analysis in an inductively coupled plasma mass spectrometer (ICP-MS), as described below.
Paint (0.1–0.2 g) and soil (~1 g) samples were homogenized with mortar and pestle, weighed, and digested in trace-metal–grade 16N HNO3 for at least 12 hr. After evaporation to dryness, samples were reconstituted in 1N HNO3, filtered (Whatman filter paper no. 4; Fisher Scientific, Pittsburgh, PA), and spiked with 209Bi for analysis by ICP-MS. Dust wipes were digested in a similar fashion.
A double focusing magnetic sector ICP-MS (Finnigan Element, Thermo Electron Corporation, Bremen, Germany) was used for lead isotopic and concentration measurements using the method of Gwiazda et al. (1998), but with shorter scan times of 10 msec for each mass. 204Pb abundance was not measured. National Institute of Standards and Technology (NIST) standard reference material (SRM) 955b level 4 (lead in blood) was used to evaluate the precision of lead isotopic and accuracy of lead concentration measurements in blood. The measured lead concentration of the 955b blood SRM was 38.6 ± 1.3 μg/dL (2× SE, n = 5), in good agreement with the certified value of 39.4 μg/dL. The precision of the blood 207Pb/206Pb ratio measurements over the course of the study was 0.2% [2× relative standard deviation (RSD)], based on the analyses of NIST 955b blood SRM over 5 different days of analyses. The precision of blood 207Pb/206Pb and 208Pb/206Pb ratio measurements within an analytical run was 0.16 and 0.26% (2× RSD), respectively, based on triplicate analyses of the children’s blood samples at each single collection interval. The average difference in 207Pb/206Pb and 208Pb/206Pb ratios between homogenized feces duplicates was 0.11 and 0.16%, respectively (n = 39 pairs). Precision and accuracy of lead isotopic ratios of environmental samples were estimated from repeated measurements of NIST 981 (common lead isotopic standard reference material). The long-term precision of NIST 981 207Pb/206Pb and 208Pb/206Pb ratios was 0.13 and 0.10% (2× RSD, n = 5 different measurement days), and the accuracy was within 0.05% of the certified ratio values.
Diaper blank was estimated to be approximately 5.8 ng lead per diaper, based on the analyses of ultrapure water rinsed over the inner surface of new diapers (n = 12). Fecal sample contamination associated with homogenization was < 5 ng lead, based on total procedural homogenization blanks (n = 6) processed with each batch of feces. These lead blank values are three orders of magnitude less than the typical amount of lead found in feces in a diaper, indicating that fecal lead contamination associated with collection and processing was negligible.
Results
Relationships between lead isotopic ratios of environmental, feces, and blood samples.
In this study we were able to distinguish analytically the various household sources of environmental lead, because the overall range of 207Pb/206Pb ratios of environmental samples from all households (i.e., 4%) was approximately 20 times larger than the isotope ratio measurement error (< 0.2%) (Figure 1). In general, the lead isotopic compositions of feces from the first round of sampling (i.e., before household intervention) match (cases 1 and 2, Figure 1A,B) or are bracketed (case 3, Figure 1C) by the lead isotopic compositions of the household dusts with lead loadings exceeding U.S. EPA action levels that were collected in the same visit.
The lead content of feces of case 3 in the first visit indicates very variable daily lead intake (Figure 1C). The highest daily fecal lead content, 240 μg Pb, is up to 40 times higher than the average daily fecal lead content of approximately 6 μg Pb/day of the children in the other two cases. We calculated a lead content–weighted grand average fecal isotopic composition for each sampling round based on the lead content and isotopic composition of the daily fecal samples (Figure 2). These calculations indicate that the isotopic compositions of blood and average feces of case 3 (Figure 2C) from the first sampling round (t1) are in much closer proximity to each other than what is observed in the other two cases, consistent with a greater relative impact of recent lead exposures on blood lead levels.
In contrast to case 3, the lead intakes of cases 1 and 2 in the first round of sampling (t1) were low, as reflected in the lead content of feces (~ 6.5 and 5 μg/day, respectively) (Figure 1A,B). However, the blood lead levels in these two cases (20.3 and 29.3 μg/dL, respectively) are comparable with or higher than in case 3 (18.3 μg/dL). In addition, in both cases 1 and 2, blood from all sampling rounds contained higher 207Pb/206Pb ratios than the average feces (Figure 2A,B).
Blood lead levels declined between the first (t1) and second (t2) visits in all three cases, even though in cases 1 and 2 there was no significant change in the fecal lead content (Figure 2A,B). In these two cases the blood isotopic composition at the second visit (t2) moved toward the isotopic composition of feces (case 1) or remained unchanged (t2, case 2).
In contrast to this, in case 3 the fecal lead content decreased postintervention (t2) and the blood 207Pb/206Pb ratios shifted away from the isotopic composition of feces (Figure 2C). When the lead content of feces again increased at the final round of sampling (case 3, t3), the blood lead level also increased (from 12.9 to 16.6 μg/dL at t2 and t3, respectively), and its isotopic composition shifted back closer to the fecal lead 207Pb/206Pb ratio (Figure 2C). No significant change was observed in case 2 between t2 and t3.
Estimates of bone lead contribution to blood.
Estimates of the amount of lead in blood from bone at each collection time point are obtained by applying Equations 1–6 to blood and fecal lead concentrations and isotopic ratios of any two sampling rounds (i.e., t1 and t2, t1 and t3, t2 and t3). Thus, in cases 2 and 3, where three sampling rounds took place, it is possible to obtain two estimates of the bone lead contribution to blood for each collection time point. This is because each sampling round is used in two different pairs of time points in the calculations. For example, two estimates of bone lead contribution to blood were calculated for t2, one estimate based on the t1 and t2 sample collection pair, and the other based on the t2 and t3 sample collection pair (Table 2).
The estimated bone lead contribution to blood in the oldest child (46 months of age, case 2) is consistent throughout the three sampling rounds and amounts to > 90% of blood lead. In other words, uptake of lead from external sources in that child supported < 10% of the lead in blood throughout the 7.4 months encompassed by the sampling rounds. Because blood lead levels in that child ranged between approximately 25 and 29 μg/dL throughout the study, these results indicate that the chronically elevated blood lead levels may be attributed to the mobilization of substantial bone lead stores. In case 1, where only two sampling visits took place, the estimated bone lead contribution averaged approximately 65% but decreased slightly from the first visit (73%) to the second visit (58%), consistent with the reduction in blood lead levels (from 20.3 to 14.9 μg/dL) and with the absence of a reduction in fecal lead elimination (i.e., lead intake) over the time interval (Tables 1 and 2, Figure 2A).
In case 3, the amount of lead in blood from bone is more variable. For this case, the estimates of the bone lead contribution to blood on the basis of the two different sampling pairs are 36% at t1 (average of 19 and 53% calculated using the t1–t2 and t1–t3 collection times, respectively), 65% at t2 (average of 59 and 70% from pairs t1–t2 and t2–t3, respectively), and 40% at t3 (average of 33 and 48% from pairs t1–t3 and t2–t3, respectively). This variability in the estimates of bone lead contribution calculated using two different sampling pairs is produced by the relative size of the analytical measurement error compared with the isotopic differences between blood and feces from two collection time points. When isotopic differences between samples collected at different times are small, the measurement uncertainty in the isotopic values results in large uncertainties in the estimates of all parameters calculated from Equations 1–6.
The biokinetic factor K (Equations 5 and 6) relates the amount of lead in blood from external intake with the lead content of feces, that is, with the amount of lead ingested but not absorbed. If it is assumed that GI absorption of lead in infants and small children is on the order of 50% (Alexander et al. 1974; Ziegler et al. 1978), the value of K should be numerically equivalent to the more commonly used BKSF defined as the increase in blood lead per unit of lead absorbed across the GI tract (Bowers and Cohen 1998; Bowers et al. 1994; U.S. EPA 2003). Data from infants fed formula mixed with leaded water (Sherlock and Quinn 1986) suggest a BKSF for small children of 0.21–0.11 in the blood range of 13–30 μg/dL, if GI lead absorption is assumed to be 0.5. Calculated biokinetic factors (K) (Table 2) range from 0.83 to 0.12, although they are generally much more consistent for a given child. Comparison of biokinetic factors (K) across children, and even across studies, should be done with caution because this term is not normalized to body weight.
Discussion
The three case studies presented here serve to illustrate the application of this noninvasive isotopic approach to estimate the bone lead contribution to blood in lead-poisoned children. These results substantiate that in lead-exposed children reductions in blood lead levels post-intervention may be buffered by the release of significant amounts of lead from bone into blood and thus may not adequately reflect reductions in lead exposure from environmental sources. The endogenous source of this lead mobilized into blood is presumed to be the skeleton, because the skeleton contains most of the body lead burden. Thus, the ability of a household lead abatement intervention to produce considerable reductions in the blood lead level of a chronically lead exposed child may be substantially limited by the large contribution of bone lead to blood.
This is best demonstrated by case 2, the oldest child examined here (46 months of age at enrollment), whose fraction of lead in blood from bone was calculated to be > 90% throughout the study. Supporting this, the lead intake of this child was comparatively low (~ 6 μg/day fecal lead elimination) and constant throughout the three sampling visits, yet the blood lead level was very elevated and decreased only slightly over time (from 29.3 down to 25.2 μg/dL over 7 months). Thus, even if the lead intake had been completely eliminated by the household abatement intervention, the expected decrease in blood lead level would have been very small. This case, in particular, illustrates the limitations of assuming that blood lead levels are direct indicators of current environmental lead exposure and that lead hazard control measures would necessarily be efficacious in significantly reducing blood lead levels.
In cases 1 and 3, the estimated bone lead contribution to blood was calculated to be smaller than in case 2 (i.e., ~ 40–65% vs. > 90%) and, at least in case 3, more variable over time. The different estimated contributions of bone lead to blood lead over time in the three children studied here could be due to a number of factors, including differences in exposure history and levels of lead accumulated in bone. The child with the largest bone lead contribution to blood (case 2, > 90%) was the oldest of the three children and had a very low lead intake, based on fecal lead elimination. In this case, a larger store of bone lead accumulated over a prolonged period (i.e., years) of exposure to elevated environmental lead levels could have maintained elevated blood lead levels that only very slowly decreased over time once the exposures were controlled. Under this scenario, reduction of the elevated environmental exposures to the case 2 child may have occurred before the conduct of this study, consistent with his relatively low fecal lead content at enrollment. In the other two cases of younger children (~ 1.5 years old), the bone lead contribution to blood was smaller and more variable (at least in case 3), suggesting a smaller reservoir of lead in bone, possibly due to a shorter history of environmental exposure.
Historically, the efficacy of lead abatement practices for reducing childhood lead exposures has been evaluated based on reductions in blood lead levels as indicators of lead exposure/uptake (Aschengrau et al. 1994, 1998; CDC 1991; Charney et al. 1983; Farfel and Chisolm 1990; Hilts et al. 1995; Kimbrough et al. 1994). This approach does not sufficiently consider the very important contribution of accumulated bone lead stores in “buffering” reductions in blood lead levels postintervention. Although it may be more difficult to verify, a more accurate appraisal of the effectiveness of lead hazard control measures would be based on their success in reducing lead intake.
Fecal lead content measured over several days is one possible approach to estimating the overall magnitude of childhood lead intake. Fecal lead content should give an integrated measure of lead exposure/intake from all sources, dietary and environmental, inside and outside the home. In contrast, other approaches such as duplicate diet sampling may not sufficiently reflect total lead exposure/intake because duplicate diets do not reflect potentially important environmental sources of lead to children living in older housing or in the proximity of soils with high lead content. Similarly, hand wipes may provide an estimate of nondietary environmental lead exposure in some cases (Duggan et al. 1985), although they do not reliably reflect ingestion of environmental lead.
There are, however, limitations with the use of fecal lead content as a measure of lead intake. First, collection of complete fecal samples over multiple days may not be feasible in some cases. Second, variability among children in GI lead absorption should ideally be taken into consideration if fecal lead content were to be used as a direct surrogate of lead uptake and intake. Third, because excreted fecal lead reflects unabsorbed ingested lead in addition to lead eliminated via endogenous fecal (e.g., biliary) routes, variation in these physiologic processes from child to child may introduce variation not attributable to environmental lead exposure. Nonetheless, fecal lead content still may be the among the most accurate indicators of the amount and isotopic composition of lead the child is ingesting, and as a result, it may serve as a useful quantitative index of the extent of oral lead exposure from all sources (diet and environment).
Assumptions and limitations of this isotopic approach.
The mathematical approach used here to calculate the bone lead contribution to blood relies on a number of assumptions, including a) that the lead isotopic composition of feces reflects the lead isotopic composition of ingested lead that is incorporated into the circulation, and b) that the isotopic composition of the skeleton remains constant throughout the 3- to 6-month interval between consecutive sampling visits. Although prior studies have not systematically validated the first assumption, it is supported by a number of published observations. Studies where lead intake and excretion were measured in animals and humans showed that an increase in lead intake is quickly followed by an increase in fecal lead excretion (Barltrop and Killala 1967; Kehoe 1987; Ziegler et al. 1978). In addition, fecal lead excretions by children suffering elevated lead exposures have been shown to correlate with the degree of lead paint hazards in their household environment (Hammond et al. 1980). Perhaps most relevant to the present study, Rabinowitz (1987) showed that the lead isotopic compositions of leaded paints in the household environments of lead-poisoned children matched the isotopic compositions of the children’s bloods and their excreted feces. These latter observations are replicated in the three cases reported here where the lead isotopic compositions of feces matched or were within the range of the lead isotopic compositions of the household dusts with the highest lead loadings.
An additional factor related to the first assumption that is not included in the model but that may affect the utility of fecal lead content as a surrogate of lead intake is the elimination of lead into feces via endogenous (e.g., biliary) pathways. Biliary lead excretion has been shown to range between 40 and 85% of total body lead excretion in nonhuman primates (Cremin et al. 2001; O’Flaherty et al. 1996) and < 46% in adult humans (Rabinowitz et al. 1976), and it is estimated to be at least 50% in infants (Ziegler et al. 1978). Assuming that the lead isotopic composition of bile matches that of blood, the biliary elimination of endogenous lead into feces would shift the lead isotopic value of feces toward the isotopic value of blood, although the extent of this shift would depend on the amount (e.g., micrograms) of lead eliminated from this biliary route compared with the amount of lead in the feces (i.e., unabsorbed lead from oral intake). Consequently, the measured difference in lead isotopic composition between feces and blood would be smaller than the true isotopic difference between blood and the oral intake. Here, we conservatively chose to not include in the model a term for endogenous biliary lead excretion into feces because endogenous fecal lead excretion is unknowable for a particular child, and including this term in the model would introduce a large uncertainty in the calculation of the bone lead contribution to blood. Functionally, the impact of not including this variable in the model produces calculated bone lead contributions to blood that, if anything, are minimum values that could be larger for a particular child.
The second assumption of this model is that the isotopic composition of the skeleton remains constant throughout the sampling visits [i.e., the model assumes (207Pb/206Pb)bonet1 = (207Pb/206Pb)bonet2]. It is possible, however, that changes in the blood isotopic composition because of reductions in lead intake after intervention, for example, could produce small changes in the isotopic composition of metabolically active regions of bone that exchange lead with blood. Accordingly, the bone lead isotopic composition could change slightly toward that of blood, rather than remain constant throughout the study. If allowance is made in the model for a change in bone isotopic composition toward that of blood, as the magnitude of external sources of exposure changes, the estimated contribution of lead from bone to blood actually increases. Thus, the approach used here, which assumes that the bone lead isotopic composition does not change with time, yields a minimum calculated value for the contribution of bone lead to blood.
Conclusions
We present a noninvasive isotopic approach to estimate the bone lead contribution to blood in children following interventions to reduce environmental lead exposures. Illustration of this method using three cases of lead-poisoned children provides evidence that mobilized skeletal lead stores may contribute a significant fraction of lead to blood, up to 90% or more in one case presented here, which may substantially “buffer” reductions in blood lead levels after environmental lead remediation. Because the accumulated skeletal lead burden likely varies from child to child, depending partly on the child’s age and lead exposure history, it should be expected that blood lead levels would decrease at different rates postintervention, depending on the contributions of bone lead to blood in different children. This suggests that the efficacy of lead hazard remediation efforts should be evaluated over prolonged periods (i.e., ≥ 6–12 months) to allow adequate time for depletion of accumulated skeletal lead stores and a reduction in their absolute contribution to blood lead levels. Observations from this study also support the use of fecal lead content and isotopic composition as a proxy for the identification of sources of lead exposure.
Figure 1 Lead isotopic ratios of blood, feces, and environmental samples, and household dust lead loadings from the first visit (t1). The vertical bar below each dust isotopic composition symbol is the lead loading of that particular dust sample according to the right ordinate scale. Numbers adjacent to the feces symbols indicate the day of the 4–5 day sequential feces sample collection. (A) Case 1. Fecal lead content (μg): day 1, 7.0; day 2, 6.6; day 3, 2.9; day 4, 9.0. (B) Case 2. Fecal lead content (μg): day 1, 5.1; day 2, 6.0; day 3, 4.7; day 4, 1.9; day 5, 7.0. (C) Case 3. Fecal lead content (μg): day 1, 4.7; day 2, 41; day 3, 240; day 4, 7.3.
Figure 2 Lead content and isotopic composition of blood (circles) and feces (squares) from cases 1, 2, and 3 (A, B, and C, respectively). The visit number (1, 2, or 3) is shown on the symbols. The fecal lead isotopic composition shown is the lead content–weighted average of the lead isotopic compositions of the daily feces collected in the visit. The white rectangles on the x-axes are the ranges in calculated isotopic composition of lead in the skeleton.
Table 1 Age (months) and blood lead levels (BPb; μg/dL) of children at enrollment, household lead abatement, and subsequent sample collection visits.
Enrollment (t1)
2nd collection (t2)
3rd collection (t3)
Case Age BPb Abatement age Age BPb Age BPb
1 14 20.3 15.2 16.1 4.9 Withdrewa
2 46 29.3 47 49 25.4 53.4 25.2
3 20 18.3 22.1 27 12.9 36 16.6
a Child withdrew from the study before the third visit.
Table 2 Calculated fraction of lead in blood from bone, 207Pb/206Pb of bone, and biokinetic factor [in (μg/dL)/(μg/day)], from Equations 1–6.
Sampling round
Case t1 t2 t3
1
Fraction of lead in blood from bone (%) 73 58 NA
Bone lead isotopic composition 0.8610 0.8610
Biokinetic factor K (Equation 5) 0.83 0.83
2a
Fraction of lead in blood from bone (%) 91–92 91–96 92–96
Bone lead isotopic composition 0.8737–0.8750 0.8742–0.8750 0.8737–0.8742
Biokinetic factor K (Equation 5) 0.48–0.14 0.21–0.48 0.14–0.21
3a
Fraction of lead in blood from bone (%) 19–53 59–70 33–48
Bone lead isotopic composition 0.8474–0.8517 0.8505–0.8517 0.8474–0.8505
Biokinetic factor K (Equation 5) 0.12–0.21 0.15–0.21 0.12–0.15
NA, not applicable.
a In cases 2 and 3, two values can be calculated for each time point by pairing data from each sample collection time with data from either one of the other two collection times (see “Materials and Methods”). For example, for t1 Equations 1–6 can be applied in combination with t2 or in combination with t3.
==== Refs
References
Alexander FW Clayton BE Delves HT 1974 Mineral and trace-metal balances in children receiving normal and synthetic diets Q J Med 43 169 89 111 4822973
Angle CR Manton WI Stanek KL 1995 Stable isotope identification of lead sources in preschool children—the Omaha Study J Toxicol Clin Toxicol 33 6 657 662 8523488
Aschengrau A Beiser A Bellinger D Copenhafer D Weitzman M 1994 The impact of soil lead abatement on urban children’s blood lead levels: phase II results from the Boston Lead-in-Soil Demonstration Project Environ Res 67 2 125 148 7982389
Aschengrau A Hardy S Mackey P Pultinas D 1998 The impact of low technology lead hazard reduction activities among children with mildly elevated blood lead levels Environ Res 79 1 41 50 9756679
Barltrop D Killala NJ 1967 Faecal excretion of lead by children Lancet 2 7524 1017 1019 4168525
Barry PS 1981 Concentrations of lead in the tissues of children Br J Ind Med 38 1 61 71 7193476
Berlin K Gerhardsson L Borjesson J Lindh E Lundstrom N Schutz A 1995 Lead intoxication caused by skeletal disease Scand J Work Environ Health 21 4 296 300 8553006
Bowers TS Beck BD Karam HS 1994 Assessing the relationship between environmental lead concentrations and adult blood lead levels Risk Anal 14 2 183 189 8008927
Bowers TS Cohen JT 1998 Blood lead slope factor models for adults: comparisons of observations and predictions Environ Health Perspect 106 suppl 6 1569 1576 9860916
Burgoon DA Rust SW Schultz BD 1995. A summary of studies addressing the efficacy of lead abatement. In: Lead in Paint, Soil, and Dust: Health Risks, Exposure Studies, Control Measures, Measurement Methods, and Quality Assurance (Beard ME, Iske DA, eds). ASTM STP 1226. Philadelphia:American Society for Testing and Materials, 119–140.
CDC 1991. Preventing Lead Poisoning in Young Children. Atlanta, GA:Centers for Disease Control and Prevention.
Charney E Kessler B Farfel M Jackson D 1983 Childhood lead poisoning. A controlled trial of the effect of dust-control measures on blood lead levels N Engl J Med 309 18 1089 1093 6353234
Colombo A Fantechi R 1983 Isotopic Lead Experiment: A Dynamic Analysis of the Isotopic Lead Experiment Results. Report EUR 8760. Luxemburg:Commission of the European Communities Directorate-General, Scientific and Technical Information and Information Management.
Cremin JD Jr Luck ML Laughlin NK Smith DR 2001 Oral succimer decreases the gastrointestinal absorption of lead in juvenile monkeys Environ Health Perspect 109 6 613 619 11445516
Duggan MJ Inskip MJ Rundle SA Moorcroft JS 1985 Lead in playground dust and on the hands of schoolchildren Sci Total Environ 44 1 65 79 4023696
Facchetti S 1989 Lead in petrol—the isotopic lead experiment Accounts Chem Res 22 10 370 374
Farfel MR Chisolm JJ Jr 1990 Health and environmental outcomes of traditional and modified practices for abatement of residential lead-based paint Am J Public Health 80 10 1240 1245 2136329
Flegal AR Smith DR 1992 Current needs for increased accuracy and precision in measurements of low levels of lead in blood Environ Res 58 125 133 1511668
Goldman RH White R Kales SN Hu H 1994 Lead poisoning from mobilization of bone stores during thyrotoxicosis Am J Ind Med 25 3 417 424 8160659
Gulson BL Jameson CW Mahaffey KR Mizon KJ Korsch MJ Vimpani G 1997a Pregnancy increases mobilization of lead from maternal skeleton J Lab Clin Med 130 1 51 62 9242366
Gulson BL Mahaffey KR Mizon KJ Korsch MJ Cameron MA Vimpani G 1995 Contribution of tissue lead to blood lead in adult female subjects based on stable lead isotope methods [see comments] J Lab Clin Med 125 6 703 712 7769364
Gulson BL Mahaffey KR Vidal M Jameson CW Law AJ Mizon KJ 1997b Dietary lead intakes for mother/child pairs and relevance to pharmacokinetic models Environ Health Perspect 105 1334 1342 9405326
Gulson BL Mizon KJ Korsch MJ Howarth D Phillips A Hall J 1996 Impact on blood lead in children and adults following relocation from their source of exposure and contribution of skeletal tissue to blood lead Bull Environ Contam Toxicol 56 4 543 550 8645908
Gwiazda RH Smith DR 2000 Lead isotopes as a supplementary tool in the routine evaluation of household lead hazards Environ Health Perspect 108 1091 1097 11102302
Gwiazda RH Woolard D Smith D 1998 Improved lead isotope ratio measurements in environmental and biological samples with a double focussing magnetic sector inductively coupled plasma mass spectrometer (ICP-MS) J Anal At Spectrom 13 1233 1238
Hammond PB Clark CS Gartside PS Berger O Walker A Michael LW 1980 Fecal lead excretion in young children as related to sources of lead in their environments Int Arch Occup Environ Health 46 3 191 202 7450885
Hilts SR Hertzman C Marion SA 1995 A controlled trial of the effect of HEPA vacuuming on childhood lead exposure Can J Public Health 86 5 345 350 8556684
Hu H Rabinowitz M Smith D 1998 Bone lead as a biological marker in epidemiologic studies of chronic toxicity: conceptual paradigms Environ Health Perspect 106 1 8 9417769
HUD 1995. Guidelines for the Evaluation and Control of Lead-Based Paint Hazards in Housing. Washington, DC:U.S. Department of Housing and Urban Development, Office of Lead Hazard Control.
Inskip MJ Franklin CA Baccanale CL Manton WI O’Flaherty EJ Edwards CM 1996 Measurement of the flux of lead from bone to blood in a nonhuman primate (Macaca fascicularis ) by sequential administration of stable lead isotopes Fundam Appl Toxicol 33 2 235 245 8921342
Kehoe RA 1987 The ingestion of lead by healthy human subjects Food Chem Toxicol 25 6 439 453
Kimbrough RD LeVois M Webb DR 1994 Management of children with slightly elevated blood lead levels Pediatrics 93 2 188 191 8121729
Lagerkvist BJ Ekesrydh S Englyst V Nordberg GF Soderberg HA Wiklund DE 1996 Increased blood lead and decreased calcium levels during pregnancy: a prospective study of Swedish women living near a smelter Am J Public Health 86 9 1247 1252 8806376
Leggett RW 1993 An age-specific kinetic model of lead metabolism in humans Environ Health Perspect 101 598 616 8143593
Manton WI 1985 Total contribution of airborne lead to blood lead Br J Ind Med 42 3 168 172 3970881
Manton WI Angle CR Stanek KL Kuntzelman D Reese YR Kuehnemann TJ 2003 Release of lead from bone in pregnancy and lactation Environ Res 92 2 139 151 12854694
Manton WI Angle CR Stanek KL Reese YR Kuehnemann TJ 2000 Acquisition and retention of lead by young children Environ Res 82 1 60 80 10677147
Nordberg GF Mahaffey KR Fowler BA 1991 Introduction and summary. International workshop on lead in bone: implications for dosimetry and toxicology Environ Health Perspect 91 3 7 1674907
O’Flaherty EJ 1994 Physiologic changes during growth and development Environ Health Perspect 102 suppl 11 103 106 7737033
O’Flaherty EJ 1998 A physiologically based kinetic model for lead in children and adults Environ Health Perspect 106 suppl 6 1495 1503 9860908
O’Flaherty EJ Inskip MJ Yagminas AP Franklin CA 1996 Plasma and blood lead concentrations, lead absorption, and lead excretion in nonhuman primates Toxicol Appl Pharmacol 138 1 121 130 8658501
Oliveira S Aro A Sparrow D Hu H 2002 Season modifies the relationship between bone and blood lead levels: the Normative Aging Study Arch Environ Health 57 5 466 472 12641191
Rabinowitz M 1987 Stable isotope mass spectrometry in childhood lead poisoning Biol Trace Elem Res 12 223 229 24254605
Rabinowitz MB Wetherill GW Kopple JD 1973 Lead metabolism in the normal human: stable isotope studies Science 182 113 725 727 4752213
Rabinowitz MB Wetherill GW Kopple JD 1976 Kinetic analysis of lead metabolism in healthy humans J Clin Invest 58 2 260 270 783195
Rabinowitz MB Wetherill GW Kopple JD 1977 Magnitude of lead intake from respiration by normal man J Lab Clin Med 90 2 238 248 886210
Rothenberg SJ Kondrashov V Manalo M Manton WI Khan F Todd AC 2001 Seasonal variation in bone lead contribution to blood lead during pregnancy Environ Res 85 3 191 194 11237506
Rust SW Kumar P Burgoon DA Niemuth NA Schultz BD 1999 Influence of bone-lead stores on the observed effectiveness of lead hazard intervention Environ Res 81 3 175 184 10585013
Sherlock JC Quinn MJ 1986 Relationship between blood lead concentrations and dietary lead intake in infants: the Glasgow Duplicate Diet Study 1979–1980 Food Addit Contam 3 2 167 176 3709889
Silbergeld EK 1991 Lead in bone: implications for toxicology during pregnancy and lactation Environ Health Perspect 91 63 70 2040252
Smith DR Osterloh JD Flegal AR 1996 Use of endogenous, stable lead isotopes to determine release of lead from the skeleton Environ Health Perspect 104 60 66 8834863
Smith DR Osterloh JD Niemeyer S Flegal AR 1992 Stable isotope labelling of lead compartments in rats with ultralow lead concentrations Environ Res 57 190 207 1568440
Tellez-Rojo MM Hernandez-Avila M Gonzalez-Cossio T Romieu I Aro A Palazuelos E 2002 Impact of breast-feeding on the mobilization of lead from bone Am J Epidemiol 155 5 420 428 11867353
U.S. EPA 1995. Review of Studies Addressing Lead Abatement Effectiveness. EPA 747-R-95-006. Washington, DC:U.S. Environmental Protection Agency.
U.S. EPA 2003. Recommendations of the Technical Review Workgroup for Lead for an Approach to Assessing Risks Associated with Adult Exposures to Lead in Soil. EPA-540-R-03-001. Washington, DC:U.S. Environmental Protection Agency.
White PD Van Leeuwen P Davis BD Maddaloni M Hogan KA Marcus AH 1998 The conceptual structure of the integrated exposure uptake biokinetic model for lead in children Environ Health Perspect 106 suppl 6 1513 1530 9860910
Ziegler EE Edwards BB Jensen RL Mahaffey KR Fomon SJ 1978 Absorption and retention of lead by infants Pediatr Res 12 1 29 34 643372
|
15626656
|
PMC1253718
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan 7; 113(1):104-110
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7241
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7077ehp0113-00011115626657Children's HealthArticlesA Quantitative Look at Fluorosis, Fluoride Exposure, and Intake in Children Using a Health Risk Assessment Approach Erdal Serap 1Buchanan Susan N. 21Division of Environmental and Occupational Health Sciences, School of Public Health, and2Departments of Occupational Medicine and Family Medicine, College of Medicine, University of Illinois at Chicago, Chicago, Illinois, USAAddress correspondence to S. Erdal, Environmental and Occupational Health Sciences, School of Public Health, 2121 West Taylor St., Chicago, IL 60613 USA. Telephone (312) 996-5875. Fax: (312) 413-9898. E-mail:
[email protected] authors declare they have no competing financial interests.
1 2005 14 9 2004 113 1 111 117 8 3 2004 14 9 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. The prevalence of dental fluorosis in the United States has increased during the last 30 years. In this study, we used a mathematical model commonly employed by the U.S. Environmental Protection Agency to estimate average daily intake of fluoride via all applicable exposure pathways contributing to fluorosis risk for infants and children living in hypothetical fluoridated and non-fluoridated communities. We also estimated hazard quotients for each exposure pathway and hazard indices for exposure conditions representative of central tendency exposure (CTE) and reasonable maximum exposure (RME) conditions. The exposure pathways considered were uptake of fluoride via fluoridated drinking water, beverages, cow’s milk, foods, and fluoride supplements for both age groups. Additionally, consumption of infant formula for infants and inadvertent swallowing of toothpaste while brushing and incidental ingestion of soil for children were also considered. The cumulative daily fluoride intake in fluoridated areas was estimated as 0.20 and 0.11 mg/kg-day for RME and CTE scenarios, respectively, for infants. On the other hand, the RME and CTE estimates for children were 0.23 and 0.06 mg/kg-day, respectively. In areas where municipal water is not fluoridated, our RME and CTE estimates for cumulative daily average intake were, respectively, 0.11 and 0.08 mg/kg-day for infants and 0.21 and 0.06 mg/kg-day for children. Our theoretical estimates are in good agreement with measurement-based estimates reported in the literature. Although CTE estimates were within the optimum range for dental caries prevention, the RME estimates were above the upper tolerable intake limit. This suggests that some children may be at risk for fluorosis.
childrenexposurefluoridemulti-pathwayrisk
==== Body
Nearly two-thirds of the U.S. population receives drinking water from municipalities that add fluoride to their water systems to prevent dental caries [Centers for Disease Control and Prevention (CDC) 2002]. The CDC hails fluoridation of drinking water as one of the 10 great public health achievements of the 20th century (CDC 1999). The first Surgeon General’s report on oral health in the United States credits fluoridation for dramatically lowering caries rates. Several studies have shown caries reduction of up to 60% after fluoridation [U.S. Department of Health and Human Services (DHHS) 2000a].
Although the efficacy of drinking-water fluoridation is well accepted by the scientific community and policy makers, the benefits are not without consequence. Ingestion of fluoride during the formative years of a child’s enamel development can cause dental fluorosis—a condition marked by permanent, often pronounced staining of adult teeth. Reports of fluorosis prevalence in North American children range widely depending on public water fluoridation status (Clark 1994; Mascarenhas 2000; Riordan and Banks 1991; Tabari et al. 2000). In the National Survey of Dental Caries in U.S. school children (1986–1987), 22% of children examined had fluorosis (Brunelle 1989). In 1998, 69% of children 7–11 years of age examined in a suburban Boston pediatric practice were found to have fluorosis (Morgan et al. 1998). Children from a fluoridated community in North Carolina showed a prevalence of 78% with fluorosis (Lalumandier and Rozier 1995). In nonfluoridated communities, fluorosis prevalence reported in a number of studies conducted during 1990–2000 ranged from 3 to 45% (Clark 1994; Mascarenhas 2000; Riordan and Banks 1991; Tabari et al. 2000).
Several studies point to other sources of fluoride besides fluoridated drinking water (e.g., fluoride toothpaste, fluoride supplements, infant formula and beverages produced with fluoridated water, food grown in soil containing fluoride or irrigated with fluoridated water, and cow’s milk from livestock raised on fluoride-containing water and feed, and soil) that contribute to overall fluoride intake and therefore may contribute to dental fluorosis (Fomon et al. 2000; Jackson et al. 2002; Levy 1994; Levy et al. 2001; Pendrys and Stamm 1990). In this study, we evaluated total fluoride intake and fluorosis risk of infants and children using quantitative health risk assessment. Although several published studies in the past decade have measured daily intake rates of fluoride from various sources such as diet, toothpaste, and infant formula (Fomon et al. 2000; Jackson et al. 2002; Levy 1994; Levy et al. 2001; Pendrys and Stamm 1990), none has systematically considered cumulative fluoride intake from all significant sources combined. We performed a comparative analysis of fluoride intake in fluoridated and nonfluoridated communities by characterizing the exposures via all significant exposure pathways applicable for infants and children in two age groups: infants less than 1 year of age and children 3–5 years of age. The analysis was limited to formula-fed infants only.
Materials and Methods
We used the risk assessment paradigm developed by the National Academy of Sciences (1983), which is commonly used by federal environmental agencies in the United States to inform decisions regarding risk priorities, risk ranking, and health-based environmental standard development [U.S. Environmental Protection Agency (EPA) 1989, 1995]. This risk assessment model, in general, consists of the following four steps: hazard identification, dose–response assessment, exposure assessment, and risk characterization. We applied this four-step risk assessment paradigm to quantitatively estimate exposure-pathway–specific and cumulative daily average intake of fluoride by infants and children. The significance of dental fluorosis has been controversial at times, and there are differing perspectives by differing agencies and organizations charged with protecting the public health. Although the U.S. EPA considers fluorosis a cosmetic effect rather than an adverse health effect, the World Health Organization (WHO) treats fluorosis as an adverse health effect affecting millions of people around the world (WHO 2001, 2002). In this study, we estimated cumulative daily dose and health risk to determine the exposure pathways and conditions resulting in increased likelihood for dental fluorosis in children, with the vision that such information would be beneficial in identifying exposure pathways of concern and in managing risks for fluorosis. Therefore, application of a quantitative risk assessment model is appropriate for determining acceptability of risks associated with exposure to any chemical, whether or not that chemical has a specific adverse health effect.
Hazard identification.
Several health effects are associated with fluoride ingestion, ranging from nausea to neurotoxic effects to death (Mullins et al. 1998; Vogt et al. 1982). The effect of concern in our risk assessment is the most common effect of chronic ingestion of fluoride in the form of fluoride salts: dental fluorosis. Fluorosis occurs as permanent teeth are forming and is characterized by permanent hypomineralization. It appears initially as white streaks or mottling on the tooth enamel. With continued systemic exposure to fluoride, these streaks become white patches, progressing to brown stains and pitting. The exact age at which teeth are most vulnerable is somewhat controversial, with opinions ranging from the prenatal stage of permanent tooth formation to 3–6 years of age, when maximal mineralization occurs. It is generally accepted, however, that after 6–8 years of age, teeth are no longer susceptible to the adverse effects of fluoride.
Dose–response assessment.
The U.S. EPA publishes a database of toxicity values derived from dose–response relationships relating exposure (dose) to health effect for various chemicals found in the environment. This database, called the Integrated Risk Information System (IRIS; U.S. EPA 2003), provides the toxicity values [e.g., reference dose (RfD)] for individual non-carcinogenic chemicals. The RfD is an estimate of the daily exposure to children and adults that is likely to be without appreciable risk of deleterious effects during a lifetime, with uncertainty spanning perhaps an order of magnitude. The RfD published by the EPA for fluoride is 0.06 mg/kg-day and is based on the no observed adverse effects level (NOAEL) of 0.06 mg/kg-day and uncertainty and modifying factors of unity (U.S. EPA 2003). Uncertainty factors were not deemed necessary because NOAEL was derived from a chronic study focusing on the critical effect (dental fluorosis) in a sensitive population of humans (children). The scientific basis and rationale of the fluoride RfD (Burt 1992; Hodge 1950) can be found in IRIS and is beyond the scope of this article.
Exposure assessment.
The populations of interest, the pathways by which exposure may occur, and the magnitude, frequency, and duration of these potential exposures are identified in this step. The population of interest in this analysis is infants (< 1 year of age) and children (3–5 years of age). An estimated daily intake (EDI) is calculated for each exposure pathway using a number of exposure parameters using Equation 1 (U.S. EPA 1992):
where EDI is the estimated daily intake (milligrams per kilogram per day), C is the concentration in a specific medium (milligrams per liter or milligrams per kilogram), IR is the ingestion or intake rate (milligrams per day), EF is the exposure frequency (days per year), ED is the exposure duration (years), AF is the absorption factor (unitless), CF is the conversion factor (10−6 kg/mg), BW is the body weight (kilograms), and AT is the averaging time (days).
The exposure pathways considered are as follows: pathway A, ingestion of fluoridated public drinking water; B, ingestion of soft drinks and fruit juices (beverages); C, consumption of infant formula; D, ingestion of cow’s milk; E, consumption of foods; F, incidental ingestion of soil; G, ingestion of fluoride supplement tablets; and H, incidental ingestion of fluoride toothpaste. The exposure pathways A–E and G are included in the estimation of cumulative fluoride intake for infants. All exposure pathways except pathway C (infant formula) are included to estimate cumulative fluoride intake of children.
Using Equation 1, the EDI for each exposure pathway is calculated by identifying appropriate values for exposure parameters (e.g., concentration, ingestion rate, body weight, exposure frequency, exposure duration) for the two age groups. Two values for each exposure parameter are used in characterizing potential exposures: one value to represent an average or central tendency exposure (CTE) and another value for the high-end or reasonable maximum exposure (RME), which is intended to represent a plausible worst-case exposure (U.S. EPA 1989). The RME estimates are often used by the EPA when making regulatory decisions and recommendations regarding acceptability of health risk to humans.
Age-specific values used in the calculation for EDI (Equation 1) can be found in Table 1. We consulted the U.S. EPA (2002) for the estimation of average daily fluoride intake via all the exposure pathways except consumption of infant formula (pathway C), ingestion of fluoride supplements (pathway G), and incidental ingestion of toothpaste (pathway H). A more in-depth discussion about the rationale for exposure-pathway–specific exposure parameters shown in Table 1—specifically, fluoride concentrations in each exposure medium—is presented below. Exposure frequency was assumed to be 365 days per year. Exposure duration was 1 year for infants and 2 years for children. Exceptions to these for EF and ED variables in Equation 1 are also noted below. The AT is equal to ED times 365 days/year. We used average body weight of 8.4 kg for 2- to 12-month-old male and female infants, respectively, in the U.S. population, based on survey data from 1988 to 1994 (U.S. EPA 2002), as the body weight of infants. Using the same data source, we estimated the mean body weight for the 3- to 5-year-old group in a similar fashion at 17.2 kg. The estimation of EDI also requires information on absorption (or bioavailability) factor. Fluoride is readily absorbed from the gastrointestinal tract, with estimates of absorption ranging from 75 to 100% [Agency for Toxic Substances and Disease Registry (ATSDR) 2001; Ekstrand and Ehrnebo 1980]. In toothpaste, sodium fluoride is 100% available as fluoride ion (Alhaique et al. 1982), and studies show a linear relationship between amount of tooth-paste ingested and serum levels of fluoride (Ekstrand and Ehrnebo 1980). Therefore, the AF in Equation 1 is assumed to be unity.
Pathway A: ingestion of drinking water.
The U.S. Public Health Service sets optimal drinking water fluoride levels based on geographic temperature bands and corresponding water consumption rates (Lalumandier and Jones 1999). The recommended fluoride concentration in temperate zones is 1 ppm, or 1 mg/L. A recent study conducted by the U.S. Department of Agriculture (USDA) that measured fluoride content of nationally representative municipal water samples from 24 consolidated metropolitan statistical areas in the United States revealed that either water is fluoridated and contains approximately 1 mg/L of fluoride or it is not fluoridated with undetectable fluoride concentration (Miller-Ihli et al. 2003). The USDA study found that approximately 40% of the water samples were fluoridated with a mean concentration of 1.01 ± 0.15 mg/L. We assumed that the water in non-fluoridated areas does not contain any fluoride.
The use of bottled water as the primary source of drinking water has increased in the United States. The American Dental Association (ADA) recently called for labeling of fluoride concentrations on bottled water because of increased use of bottled water not only as a drinking water source but also in preparation of infant formulas and various foods. Bartels et al. (2000) examined fluoride concentrations of five commercially available bottled water products. The results indicated that although there were significant differences in fluoride concentrations among different brands and between different batches from the same brand, all products had fluoride concentrations lower than the ADA-accepted standard for optimally fluoridated water (i.e., 0.7–1.2 mg/L dependent on the average maximum daily air temperature of an area). Because widespread use of bottled water is a recent phenomenon, there are limited data to ascertain how bottled water intake is affecting children’s teeth. Our intake/risk estimates for infants and children consuming non-fluoridated tap water would most likely be equivalent to intake/risk estimates of those consuming bottled water as their drinking water source because most bottled water in the United States is currently not fluoridated. However, this may change in the future because of pressure from consumer groups and federal/state regulatory agencies.
Pathway B: ingestion of soft drinks and fruit juices.
The ingestion of soft drinks and commercially prepared fruit juices has more than doubled in the last 25 years (Levy 1994). Because these beverages are usually prepared with fluoridated water, they can be a significant source of fluoride. Pang et al. (1992) reported the fluoride content of sodas, juices, punches, tea, and Gatorade purchased in North Carolina. Fluoride levels were highly variable, ranging from < 0.1 to 6.7 mg/L. We used the weighted average of these reported concentrations (0.76 mg/L) in calculating the EDI for this pathway.
Pathway C: consumption of infant formula.
Infant formula processed with fluoridated water may be a significant source of fluoride in infants. In 1979, because of the concern about fluoride intake in infants, formula manufacturers voluntarily agreed to lower the concentration of fluoride in their products (Fomon et al. 2000; Levy 1994). However, fluoridated water used to reconstitute or dilute powdered or concentrated preparations remains a concern. An average concentration of 0.65 mg/kg fluoride is used in the EDI calculation. This concentration was derived based on a survey of fluoride concentrations in ready-to-use formula (mean, 0.23 mg/kg fluoride), concentrated liquid (mean, 0.6 mg/kg fluoride), and powdered concentrate (1.13 mg/kg fluoride) sold in retail stores in the United States (ATSDR 2001; Dabeka and McKenzie 1987). The intake rate of infant formula was estimated from feeding recommendations by Behrman and Vaughn (2000).
Pathway D: ingestion of cow’s milk.
Cows ingesting fluoridated water or feed processed with fluoridated water produce milk containing fluoride. The mean fluoride concentration of 0.041 mg/kg (range, 0.007–0.086 mg/kg) reported in a Canadian study (Dabeka and McKenzie 1987) that surveyed fluoride concentrations in 68 samples of milk sold in retail stores across Canadian provinces was used in this analysis.
Human breast milk contains very low levels of fluoride (0.004 mg/L in nonfluoridated and 0.01 mg/L in fluoridated areas) even when intake by the mother is high (Fomon et al. 2000; Levy 1994). Moreover, the percentage of exclusively breast-fed infants at 6 months of age in the United States was only 22% in 1995 (Ryan 1997). For these reasons, only formula-fed infants are included in this analysis. Exclusively breast-fed infants will have a much lower average daily fluoride intake for the duration of the breast-feeding period than will formula-fed infants.
Pathway E: consumption of food.
Dabeka and McKenzie (1995) determined fluoride concentrations in individual food items and food composites in various categories (milk and dairy products, meat and poultry, soups, bakery goods and cereals, vegetables, fruits and fruit juices, fats and oils, sugar and candies, beverages, and other miscellaneous items) purchased in Winnipeg, Canada. Food categories with the highest mean fluoride levels were fish (2.118 mg/kg), soups (0.606 mg/kg), and beverages (1.148 mg/kg). The mean fluoride concentration in all samples, including milk, various beverages and fruit juices, and tap water, was 0.325 mg/kg, ranging from 0.011 to 4.970 mg/kg. Using these data, we estimated the mean fluoride concentration of 0.262 and 0.29 mg/kg fluoride in foods potentially consumed by infants and children, respectively. This estimate does not include milk, beverages and fruit juices, and tap water because these are treated separately in our analysis. For infants, certain food items were excluded from their diet (e.g., cold cuts, lunch meat, cured meats, honey), and fluoride exposure due to food consumption was limited to 8 months, starting at 4 months of age.
Pathway F: incidental ingestion of soil.
Children inadvertently ingest soil through normal hand-to-mouth behavior. Industrial sites, hazardous waste sites containing fluoride, and soil contaminated with phosphate-containing fertilizers may have higher levels of fluoride. We used the mean fluoride concentration in soils and other surface materials in the United States (430 mg/kg; range, 10–37,000 mg/kg) (ATSDR 2001) in the calculation of the EDI for the incidental soil ingestion pathway. Because children < 1 year old are not ambulatory, the average daily fluoride intake for this pathway is calculated for children 3–5 years of age only.
Pathway G: ingestion of fluoride supplements.
Ingestion of fluoride supplements can be a major exposure pathway for some children. These supplements are prescribed to infants and children in areas that lack fluoridated public water supplies. Although several studies indicate that supplements are often prescribed inappropriately to children in fluoridated areas (Lalumandier and Rozier 1995; Pendrys and Katz 1989), we assumed that only children living in nonfluoridated areas receive supplementation. The ADA, the American Academy of Pediatric Dentistry, and the American Academy of Pediatrics recommend supplemental fluoride intake of 0.25 and 0.5 mg/day, for children 6 months to 3 years of age and children 3–6 years of age respectively, in areas with nonfluoridated water (CDC 2001). After the recommended dosing schedule for infants, exposure was limited to 6 months for infants < 1 year, starting at 6 months of age.
Pathway H: incidental ingestion of tooth-paste.
Because > 90% of toothpaste sold in North America is fluoridated, many children are exposed to fluoride through incidental ingestion of toothpaste. Toothpastes specifically flavored for children have been linked with use of larger quantities of toothpaste, increasing the importance of this pathway (Levy 1994). The recommended concentration for fluoride ion in the United States is generally 1,000 mg/kg (ATSDR 2001; CDC 2001). The CTE and RME ingestion rates of toothpaste used to estimate EDI were the average (0.26 g toothpaste per brushing) and 90th percentile (0.77 g toothpaste per brushing) compiled from 11 studies (CDC 2001; Levy 1993, 1994). We assumed a brushing frequency of once daily for the CTE and three times daily for the RME. This pathway was excluded from the estimation of cumulative fluoride intake for infants (< 1 years of age) because several studies show that many in this age group do not have their teeth brushed (Levy et al. 1997; Tabari et al. 2000).
The EDI representing CTE and RME scenarios are calculated for each exposure pathway discussed above using Equation 1. Cumulative EDI of fluoride is estimated by adding EDI values for infants and children living in fluoridated and nonfluoridated areas using Equations 2–5. In nonfluoridated areas, fluoride concentration in drinking water was assumed to be zero; thus, intake through ingestion of drinking water was not considered. On the other hand, it was assumed that no intake via ingestion of fluoride supplements would occur in fluoridated areas.
For infants living in fluoridated areas:
For children 3–5 years of age living in fluoridated areas:
For infants living in nonfluoridated areas:
For children 3–5 years of age living in nonfluoridated areas:
Risk characterization.
The hazard quotient (HQ), as an estimate of the RME and CTE health risks associated with fluoride exposure via each exposure pathway, is estimated by integrating exposure and toxicity information. The sum of the HQs, the hazard index (HI), is then calculated by dividing cumulative dose (EDI) by the safe dose (RfD) using Equation 6, which represents the total fluoride intake risk:
Results
Numerical results of the CTE and RME EDI estimates for each pathway and for each age group are shown in Table 2. Figure 1 depicts the RME EDI estimates for infants and children. For infants, although drinking water (52%) and infant formula (39%) are the two most significant sources contributing to cumulative daily fluoride intake in fluoridated areas, infant formula (71%), fluoride supplements (13.4%), and food (12.9%) are the sources of importance in nonfluoridated areas. For children, toothpaste (57%), drinking water (22%), and food (9%) in fluoridated areas and tooth-paste (63%), fluoride supplements (14%), and food (10%) in nonfluoridated areas contribute significantly to the cumulative daily intake under the RME conditions.
Tables 3 and 4 show the HQ and HI values estimated for infants and children for each exposure scenario. Table 4 also documents the estimates of cumulative EDI applicable to each exposure group living in fluoridated or nonfluoridated communities. All of the HI values are around unity for all CTE estimates, slightly elevated for infants living in fluoridated areas. On the other hand, all HI estimates for the RME scenario are greater than unity, indicating that cumulative daily fluoride intake is greater than the safe dose level established by the EPA for fluoride. Therefore, there may be a segment of both populations who are at risk of developing fluorosis due to exposure to fluoride via exposure pathways studied in this analysis, under the specified RME conditions. Figure 2 illustrates the HI estimates for each exposure group in relation to the acceptable standard of unity for HI. It is interesting to note that all exposure-pathway–specific HQ values are less than or around unity for infants and children under CME conditions, as shown in Table 3. However, fluoridated drinking water ingestion and consumption of infant formula for infants and incidental ingestion of toothpaste by children are associated with HQ values slightly greater than unity under the RME conditions, which result in HI estimates greater than unity.
The cumulative daily fluoride intake in fluoridated areas was estimated at 0.20 and 0.11 mg/kg-day for RME and CTE scenarios, respectively, for infants. On the other hand, the RME and CTE estimates for children were 0.23 and 0.06 mg/kg-day, respectively (Table 4). In areas where municipal water is not fluoridated, our RME and CTE estimates for cumulative daily average intake were, respectively, 0.11 and 0.08 mg/kg-day for infants and 0.21 and 0.06 mg/kg-day for children. For infants, cumulative fluoride intake is all due to dietary sources in fluoridated areas. In non-fluoridated areas, dietary intake constitutes about 87% (0.1 mg/kg-day) and 90% (0.07 mg/kg-day) of the cumulative intake for infants and about 18% (0.04 mg/kg-day) and 43% (0.02 mg/kg-day) of the cumulative daily intake for children under RME and CTE scenarios, respectively. In fluoridated areas, dietary intake constituted 38% (0.09 mg/kg-day) and 73% (0.05 mg/kg-day) of the cumulative intake for children for RME and CTE scenarios, respectively. These results demonstrate that total fluoride exposure is due mainly to dietary sources for infants; however, non-dietary sources (e.g., fluoride supplements, toothpaste) gain importance for children’s exposure to fluoride. The average optimum dietary fluoride intake by children living in fluoridated communities is found to be close to 0.05 mg/kg-day (range, 0.02–0.1 mg/kg-day; Institute of Medicine 1999). The Institute of Medicine recently established a tolerable upper intake level of 0.1 mg/kg-day for infants, toddlers, and children ≤8 years of age, based on the lowest observed adverse effect level for moderate fluorosis, using dietary fluoride intake data (Institute of Medicine 1999). All of our dietary intake estimates fall within the range of 0.02–0.1 mg/kg-day, except for infants living in fluoridated areas under the RME scenario, primarily due to ingestion of water. Levy et al. (2001) also found that for children < 12 months of age, drinking water was a primary source of fluoride intake.
Discussion
Several studies published in the literature have estimated total daily fluoride intakes from dietary sources and toothpaste ingestion. Pendrys and Stamm (1990) estimated fluoride intake from diet (water and beverages), supplements, and toothpaste to be 0.07 (range, 0.04–0.2) and 0.08 (range, 0.05–0.21) mg/kg-day for children 2 years of age from fluoridated and nonfluoridated communities, respectively. These EDI estimates are similar to our estimates for 3- to 5-year-old children, with the mean of 0.06 mg/kg-day in both fluoridated and non-fluoridated water areas. It is interesting to note that the high-end estimates reach approximately 0.2 mg/kg-day in both analyses. Levy et al. (2001) estimated daily fluoride intake from water (including beverages), toothpaste, and fluoride supplements from birth to 36 months of age as part of a longitudinal study in Iowa. The estimated mean intakes were 0.06 mg/kg for the 3- to 12-month-old group and 0.043 mg/kg-day for the 20- to 36-month-old group. The 90th percentile values were 0.12 and 0.08 mg/kg-day for infants (3–12 months of age) and 3-year-old children, respectively. On the other hand, the maximum fluoride intake estimates were significantly higher, amounting to 0.2 mg/kg-day for 3-year-old children and 0.9 mg/kg-day for infants. We estimated average intake levels of 0.05 and 0.06 mg/kg-day for < 1- and 3- to 5-year-old age groups in our analysis for combined fluoride sources from water, beverage, fluoride supplement, and toothpaste, which agree with the estimates of Levy et al. (2001). Our RME EDI estimates for these four exposure pathways were 0.12 and 0.23 mg/kg-day for infants and children, respectively. Although the infant estimate agrees with the reported 90th percentile value, our RME for children is higher (close to maximum), potentially because, although we consider older children, Levy et al. (2001) limits the maximum age studied to 3 years. In addition, Levy et al. (2001) did not include intake of prepackaged beverages such as fruit juice and soda, and the amount of toothpaste used and proportion ingested was estimated by parents, both of which may have led to underestimation of fluoride intake. Jackson et al. (2002) recently estimated average daily dietary intake of fluoride from food (including milk) and beverages using a food questionnaire and USDA intake rates for 3- to 5-year-old children living in fluoridated and nonfluoridated towns in Indiana. The children from the fluoridated town had an average fluoride daily intake of 0.033 mg/kg-day and a maximum intake of 0.062 mg/kg-day. On the other hand, children from nonfluoridated communities had an average of 0.028 mg/kg-day and a maximum intake of 0.058 mg/kg-day. Our EDI estimates for these pathways (milk, food, beverages) for the 3- to 5-year-old exposure group are slightly lower, with 0.04 and 0.02 mg/kg-day for RME and CTE scenarios, respectively. This may be because our estimates for fluoride intake through milk, beverages, and food do not differentiate whether these sources come from fluoridated or nonfluoridated areas.
Prevention of dental caries, as established by numerous epidemiologic studies, has been such a dramatic public health achievement that the U.S. Public Health Service has set a goal of increasing the percentage of the U.S. population being served by a fluoridated supply to 75%, in its Healthy People 2010 initiative (U.S. DHHS 2000b). However, the findings of this health risk assessment study support concerns that a segment of the infant and child population in the United States may be exposed to amounts of fluoride greater than the optimum level for caries prevention. We found that when only dietary exposure pathways are considered, the EDI varies from 0.02 to 0.1 mg/kg-day in nonfluoridated communities, which is within the optimum range (Institute of Medicine 1999). However, in fluoridated communities, this range was 0.05–0.2 mg/kg-day, with drinking water and infant formula being the primary contributors. When nondietary sources were also considered, the cumulative EDI values significantly increased for children, whereas there was a negligible difference between the dietary exposure and cumulative exposure for infants. For the 3- to 5-year-old age group, the use of fluoride supplements and, especially, inadvertent ingestion of toothpaste containing fluoride significantly increased the total fluoride intake by 2- to 6-fold under the RME scenario. However, drinking water, food, fluoride supplements, and toothpaste contributed in similar percentages (21–27%) to the cumulative EDI under the CTE scenario for children living in fluoridated communities.
Analysis of uncertainty is an essential component of risk assessment. In this study, we used a single point value for each of the exposure parameters. However, fluoride concentrations in drinking water, beverages and fruit juices, and various food items are known to vary greatly (Jackson et al. 2002). Studies measuring fluoride concentration in beverages do not track products to their source to verify whether they were produced with fluoridated water (Heilman et al. 1999; Jackson et al. 2002; Levy 1994; Pang et al. 1992). A child consuming only beverages prepared with non-fluoridated water would have a lower fluoride intake. Children brushing more or less often obviously increase or decrease their risk of swallowing toothpaste. Children using mouth rinses and gels and specially flavored tooth-paste may especially be increasing their fluoride intake. Because of the availability of scant data on intake rates of bottled water, this source was not considered. The increased reliance on bottled water as the primary drinking source among the U.S. population may change the dynamics of fluoride intake among the children, especially given the fact that many bottled water products do not contain any fluoride. That is why it is paramount to continuously track the prevalence of dental caries and fluorosis at specific life stages to determine trends and to apportion the total intake into each source. Tea leaves contain high levels of fluoride, and brewed tea concentrations can range from 1 to 6 mg/L (Institute of Medicine 1999; Pang et al. 1992). Children growing up in ethnic communities with frequent tea consumption may have increased high intake of fluoride (Cao et al. 1997; Jin et al. 2000). An epidemiologic investigation carried out in Mexico showed that boiling water doubled fluoride concentrations found in nonboiled water (Grimaldo et al. 1995). Thus, food or infant formula prepared with boiled water may result in increased fluoride intake through diet. The uncertainty associated with concentrations of fluoride in drinking water, drinking water ingestion rate, consumption rates of beverages, cow’s milk, food, and fluoride supplement dosage can be classified as relatively low because these estimates emanate from national-scale studies conducted by the U.S. EPA and USDA. The uncertainty for the rest of the exposure parameters fall into “high” or “medium to high” categories. Fluoride concentrations in various exposure media (e.g., beverages, cow’s milk, infant formula, food, soil) and incidental toothpaste ingestion rate are especially uncertain. Therefore, the uncertainty in the overall intake and risk estimates can be described as “medium” at best, most likely as “medium to high.”
The HI, which considers all exposure pathways applicable for a given exposure group, was greater than unity in all cases under the RME conditions and was within acceptable ranges in all cases except for infants living in fluoridated areas under the CTE conditions. Therefore, it is likely that some infants and children receive fluoride levels in excess of those “likely to be without appreciable deleterious effects” (U.S. EPA 2003) and are at risk for fluorosis. The findings of this study confirm the importance of considering all potentially applicable exposure pathways in estimating cumulative daily fluoride dose for scientifically sound decision making in fluorosis risk management. Although the EDI associated with the ingestion of drinking water pathway (RME: 0.05 mg/kg-day, children; 0.1 mg/kg-day, infants; CTE: 0.02 mg/kg-day, children; 0.04 mg/kg-day, infants) does not exceed the optimum fluoride range in fluoridated areas by itself, the cumulative intake exceeds the optimum range when other pathways are considered. Therefore, one approach could be implementation of measures to reduce fluoride intake from sources other than water in communities where tap water is fluoridated. The risk management for fluorosis in these communities could focus on preparation of infant formula for infants and ingestion of toothpaste for children. This finding emphasizes the significance of educating parents and child-care specialists about fluorosis risk by public health practitioners, physicians, and dentists. The fluorosis risk can easily be reduced by supervising children while brushing and by preparing infant formula with nonfluoridated water or purchase of infant formula constituted without fluoride. A significant role in fluorosis risk management is also assumed by the public health, medical, and dental professionals by accurately diagnosing fluoride needs of children by inquiring about all sources that are associated with fluoride exposure on a case-by-case basis and making informed and educated decisions about fluoride supplement prescription unique to each child.
On the other hand, a significant finding of our analysis is that, for both age groups living in nonfluoridated areas, although under the CTE scenario the cumulative intake is within the optimum range (0.06 mg/kg-day for children, 0.08 mg/day for infants), under the RME scenario the cumulative intake estimates are higher (0.21 mg/kg-day for children, 0.11 mg/kg-day for infants), exceeding the optimum range. This raises questions about the continued need for fluoridation in the U.S. municipal water supply to protect against the risk of fluorosis. However, given the uncertainties inherent in this analysis, it is not possible to be conclusive. Further research with carefully designed epidemiologic studies with enough statistical power and strong exposure assessment component is essential and warranted to answer critical questions about the necessity of fluoridation in the presence of changes in dietary behavior of children and multiple sources of fluoride currently contributing total intake. Cost–benefit analysis for fluoride should be a component of such studies. In addition, future studies should lead to collection of detailed exposure data for each exposure pathway so that more robust probabilistic risk assessment techniques, as opposed to point estimates of intake/risk presented here, can be applied to obtain distribution of fluoride intake/risk among children with quantitative measures of uncertainty.
Figure 1 RME daily intake estimates for each exposure pathway.
Figure 2 HI estimates for each exposure scenario.
Table 1 Summary of exposure parameters used in the calculation of estimated daily fluoride intake.
Exposure pathway Fluoride concentration CTE intake ratea RME intake rate
A. Drinking waterb 1 mg/L < 1 year old: 0.34 L/day < 1 year old: 0.88 L/day
1–10 years old: 0.4 L/day (U.S. EPA 2002) 1–10 years old: 0.9 L/day (U.S. EPA 2002)
B. Beveragesc 0.76 mg/L (Pang et al. 1992) < 1 year old: 19 g/day < 1 year old: 23.75 g/day
3–5 years old: 269 g/day (U.S. EPA 2002) 3–5 years old: 336.25 g/day (U.S. EPA 2002)
C. Infant formula 0.65 mg/kg (ATSDR 2001) 198 mL/feeding, 4.4 feedings/day (Behrman and Vaughn 2000) 214 mL/feeding, 4.8 feedings/day (U.S. EPA 2002Behrman and Vaughn 2000)
D. Cow’s milkc 0.041 mg/kg (Dabeka and McKenzie 1987) < 1 year old: 61 g/day < 1 year old: 76.25 g/day
3–5 years old: 335 g/day (U.S. EPA 2002) 3–5 years old: 418.75 g/day (U.S. EPA 2002)
E. Foodb < 1 year old: 0.262 mg/kg < 1 year old: 223.6 g/day < 1 year old: 612.7 g/day
3–5 years old: 0.290 mg/kg (Dabeka and McKenzie 1995) 3–5 years old: 691.9 g/day (U.S. EPA 2002) 3–5 years old: 1,312.5 g/day (U.S. EPA 2002)
F. Soild 430 mg/kg (ATSDR 2001) 0.1 g/day (U.S. EPA 2002) 0.4 g/day (U.S. EPA 2002)
G. Fluoride supplements 6 months to 10 years of age: 0.25 mg/day NaF 6 months to 3 years old: 0.25 mg/day NaF
3–6 years old: 0.5 mg/day NaF (CDC 2001) 3–6 years old: 0.5 mg/day NaF (CDC 2001)
H. Toothpaste 1,000 mg/kg (ATSDR 2001) 3–5 years old: 0.26 g/brushing (Levy 1993) 3–5 years old: 0.77 g/brushing (Levy 1993)
1 brushing/day 3 brushings/day
a Recommended mean intake rate as a combined estimate for males and females was used in all cases in the CTE scenario.
b For drinking water and food consumption, 90th percentile of recommended intake rate was used in the RME scenario.
c For consumption of beverages and cow’s milk, 25% more consumption than the mean was assumed in the estimation of RME daily intake.
d For incidental ingestion of soil by children, upper percentile ingestion rate was used in the RME scenario.
Table 2 EDI (mg/kg-day) estimates for CTE and RME exposure scenarios.
CTE
RME
Exposure pathway < 1 year old 3–5 years old < 1 year old 3–5 years old
A. Fluoridated drinking water 0.04 0.023 0.10 0.052
B. Beverages 0.0017 0.012 0.021 0.015
C. Infant formula 0.067 NA 0.079 NA
D. Cow’s milk 0.0003 0.0008 0.00037 0.001
E. Food 0.0052 0.012 0.014 0.022
F. Soil NA 0.0025 NA 0.01
G. Fluoride supplements 0.0074 0.014 0.015 0.029
H. Toothpaste NA 0.015 NA 0.13
NA, exposure pathways assumed to be not applicable.
Table 3 The CTE and RME HQ estimates for individual exposure pathways.
CTE
RME
Exposure pathway < 1 year old 3–5 years old < 1 year old 3–5 years old
A. Fluoridated drinking water 0.7 0.4 1.7 0.9
B. Beverages 0.03 0.2 0.04 0.2
C. Infant formula 1.1 NA 1.3 NA
D. Cow’s milk 0.005 0.01 0.006 0.02
E. Food 0.09 0.2 0.2 0.4
F. Soil NA 0.04 NA 0.2
G. Fluoride supplements 0.1 0.2 0.2 0.5
H. Toothpaste NA 0.2 NA 2.2
NA, exposure pathways assumed to be not applicable.
Table 4 HIs and cumulative EDIs (mg/kg-day) for exposure scenarios of concern.
HI
Cumulative EDI
Exposure scenario CTE RME CTE RME
Fluoridated area
< 1 year old 1.9 3.3 0.11 0.20
3–5 years old 1.1 3.9 0.06 0.23
Nonfluoridated area
< 1 year old 1.4 1.8 0.08 0.11
3–5 years old 0.9 3.5 0.06 0.21
==== Refs
References
Alhaique F Santucci E Guadagnini G de Marchi F 1982 Is fluoride in dentifrices available? Boll Chim Farm 121 573 578 7183326
ATSDR 2001. Toxicological Profile for Fluorides, Hydrogen Fluoride, and Fluorine. Draft for Public Comment. Atlanta, GA:Agency for Toxic Substances and Disease Registry.
Bartels D Haney K Khajotia SS 2000 Fluoride concentration in bottled water J Okla Dent Assoc 91 1 18 22 11314109
Behrman RE Vaughan VC eds. 2000. Nelson Textbook of Pediatrics. 16th ed. Philadelphia:W.B. Saunders.
Brunelle JA 1989 The prevalence of dental fluorosis in U.S. children, 1987 [Abstract] J Dent Res 68 special issue 995
Burt BA 1992 The changing patterns of systemic fluoride intake J Dent Res 71 special issue 1228 1237 1607439
Cao J Zhao Y Liu J 1997 Brick tea consumption as the cause of dental fluorosis among children from Mongol, Kazak, and Yugu populations in China [Abstract] Food Chem Toxicol 35 827 9350228
CDC (Centers for Disease Control and Prevention) 1999 Ten great public health achievements—United States, 1900–1999 MMWR Morb Mortal Wkly Rep 48 241 243 10220250
CDC (Centers for Disease Control and Prevention) 2001 Recommendations for using fluoride to prevent and control dental caries in the United States MMWR Morb Mortal Wkly Rep 50 1 42 11215787
CDC (Centers for Disease Control and Prevention) 2002 Populations receiving optimally fluoridated public drinking water—United States, 2000 MMWR Morb Mortal Wkly Rep 51 144 147 11905481
Clark DC 1994 Trends in prevalence of dental fluorosis in North America Community Dent Oral Epidemiol 22 148 152 8070241
Dabeka RW McKenzie AD 1987 Lead, cadmium, and fluoride levels in market milk and infant formulas in Canada J Assoc Anal Chem 70 754 757
Dabeka RW McKenzie AD 1995 Survey of lead, cadmium, fluoride, nickel, and cobalt in food composites and estimation of dietary intakes of these elements by Canadians in 1986–1988 J AOAC Int 78 897 909 7580328
Ekstrand J Ehrnebo M 1980 Absorption of fluoride from fluoride dentifrices Caries Res 14 96 102 6927971
Fomon SJ Ekstrand J Ziegler EE 2000 Fluoride intake and prevalence of dental fluorosis: trends in fluoride intake with special attention to infants J Public Health Dent 60 131 139 11109209
Grimaldo M Borja-Aburto VH Ramírez AL Ponce M Rosas M Diaz-Barriga F 1995 Endemic fluorosis in San Luis Potosi, Mexico. I. Identification of risk factors associated with human exposure to fluoride Environ Res 68 25 30 7729383
Heilman JR Kiritsy MC Levy SM Wefel JS 1999 Assessing fluoride levels of carbonated soft drinks J Am Dent Assoc 130 1593 1599 10573939
Hodge HC 1950 The concentration of fluorides in drinking water to give the point of minimum caries with maximum safety J Am Dent Assoc 40 436 449
Institute of Medicine 1999. Dietary Reference Intakes for Calcium, Magnesium, Vitamin D, and Fluoride. Washington, DC:National Academy Press.
Jackson RD Brizendine EJ Kelly DA Hinesley R Stookey GK Dunipace AJ 2002 The fluoride content of foods and beverages from negligibly and optimally fluoridated communities Community Dent Oral Epidemiol 30 382 391 12236830
Jin C Yan Z Juanwei L Ruodeng X Sangbu D 2000 Environmental fluoride content in Tibet [Abstract] Environ Res 83 333 10944077
Lalumandier JA Jones JL 1999 Fluoride concentrations in drinking water J Am Water Works Assoc 91 42 51
Lalumandier JA Rozier RG 1995 The prevalence and risk factors of fluorosis among patients in a pediatric dental practice Pediatr Dent 17 19 25 7899097
Levy S 1993 A review of fluoride intake from fluoride dentifrice J Dent Child 60 115 124
Levy SM 1994 Review of fluoride exposures and ingestion Community Dent Oral Epidemiol 22 173 180 8070245
Levy SM Kiritsy C Slager SL Warren JJ Kohout FJ 1997 Patterns of fluoride dentifrice use among infants Pediatr Dent 19 50 55 9048414
Levy SM Warren JJ Davis CS Kirchner HL Kanellis MJ Wefel JS 2001 Patterns of fluoride intake from birth to 36 months J Public Health Dent 61 70 77 11474917
Mascarenhas AK 2000 Risk factors for dental fluorosis: a review of the recent literature Pediatr Dent 22 269 277 10969430
Miller-Ihli NJ Pehrsson PR Cutrifelli RL Holden JM 2003 Fluoride content of municipal water in the United States: what percentage is fluoridated? J Food Comp Anal 16 621 628
Morgan L Allres D Tavares M Bellinger D Needleman H 1998 Investigation of the possible associations between fluorosis, fluoride exposure, and childhood behavior problems Pediatr Dent 20 4 244 252 9783294
Mullins M Warden C Barnum D 1998 Pediatric death and fluoride-containing wheel cleaner [Letter] Ann Emer Med 31 523 525
National Academy of Sciences 1983. Risk Assessment in Federal Government Managing the Process. Washington, DC:National Academy Press.
Pang DTY Phillips CL Bawden JW 1992 Fluoride intake from beverage consumption in a sample of North Carolina children J Dent Res 71 1382 1388 1629454
Pendrys DG Katz RV 1989 Risk of enamel fluorosis associated with fluoride supplementation, infant formula, and fluoride dentifrice use Am J Epidemiol 130 1199 1208 2589311
Pendrys DG Stamm JW 1990 Relationship of total fluoride intake to beneficial effects and enamel fluorosis J Dent Res 69 special issue 529 538 2179311
Riordan PJ Banks JA 1991 Dental fluorosis and fluoride exposure in western Australia J Dent Res 70 1022 1028 2066481
Ryan AS 1997 The resurgence of breastfeeding in the United States Pediatrics 99 e12 9099787
Tabari ED Ellwood R Rugg-Gunn AJ Evans DJ Davies RM 2000 Dental fluorosis in permanent incisor teeth in relation to water fluoridation, social deprivation and tooth-paste use in infancy Br Dent J 189 216 220 11036750
U.S. DHHS 2000a. Oral Health in America: A Report of the Surgeon General. Rockville, MD:National Institute of Dental and Craniofacial Research, National Institutes of Health, U.S. Department of Health and Human Services.
U.S. DHHS 2000b. Healthy People 2010—Understanding and Improving Health. 2nd ed. Washington, DC:U.S. Department of Health and Human Services.
U.S. EPA 1989. Risk Assessment Guidance for Superfund, Vol. 1: Human Health Evaluation Manual (Part A). EPA/540/1-890002. Washington, DC:U.S. Environmental Protection Agency, Office of Emergency Response.
U.S. EPA 1992 Guidelines for exposure assessment Fed Reg 57 22887 22938
U.S. EPA 1995. Guidance for Risk Characterization at the U.S. Environmental Protection Agency. Washington, DC:U.S. Environmental Protection Agency, Science Policy Council.
U.S. EPA 2002. Child Specific Exposure Factors Handbook. Risk Assessment Guidance for Superfund, Vol 1: Human Health Evaluation Manual (Part A). EPA/540/1-890002. Washington, DC:U.S. Environmental Protection Agency, Office of Emergency Response.
U.S. EPA 2003. Integrated Risk Information System. Cincinnati, OH:U.S. Environmental Protection Agency, Environmental Criteria and Assessment Office. Available: http://www.epa.gov/iris [accessed 22 October 2003].
Vogt RL Witherell L LaRue D Klaucke DN 1982 Acute fluoride poisoning associated with an on-site fluoridator in a Vermont elementary school Am J Public Health 72 1168 1171 7114344
WHO 2001. Water-Related Diseases. Fluorosis: The Disease and How It Affects People. Geneva:World Health Organization. Available: http://www.who.int/water_sanitation_health/diseases/fluorosis/en/[accessed 8 December 2004].
WHO 2002. World Water Day 2001: Oral Health. Geneva:World Health Organization. Available: http://www.who.int/entity/water_sanitation_health/en/oralhealth.htm [accessed 8 December 2004].
|
15626657
|
PMC1253719
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan 14; 113(1):111-117
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7077
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0001415631951PerspectivesEditorialGuest Editorial: Noise and Health Babisch Wolfgang Federal Environmental Agency, Berlin, Germany, E-mail:
[email protected] Babisch is a senior research officer at the German Federal Environmental Agency. His research focus is on noise epidemiology, particularly the auditory and nonauditory health effects of noise. He is a member of the International Commission on Biological Effects of Noise.
1 2005 113 1 A14 A15 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Noise affects everybody in everyday life—at home, at leisure, during sleep, when traveling, and at work. However, human organisms are not prepared to shut off the noise. Hearing is a permanent process using cortical and subcortical structures to filter and interpret acoustical information; the analysis of acoustical signals is essential for human survival and communication. Noise is detrimental to health in several respects, for example, hearing impairment, sleep disturbance, cardiovascular effects, psychophysiologic effects, psychiatric symptoms, and fetal development (Stansfeld et al. 2000). Furthermore, noise has widespread psychosocial effects including noise annoyance, reduced performance, and increased aggressive behavior [American Academy of Pediatrics 1997; World Health Organization (WHO) 2001].
Noise causes acute mechanical damage to hair cells of the cochlea in the inner ear when the short-term sound intensity or peak impulse noise levels are very high {LAF (A-weighted sound pressure level) > 120 dB; LCpk (C-weighted peak sound pressure level) > 135 A-weighted decibels [dB(A)]}. In the long run, average sound pressure levels (LAeq) of > 85 dB(A) are likely to cause significant hearing loss due to metabolic exhaustion [International Organization for Standardization (ISO) 1990]. This is not only relevant in occupational settings but also with respect to leisure activities, including firecrackers, toy pistols, and other noisy toys; loud music in discotheques, concerts, and when listening via headphones; and noisy machines and tools (Maassen et al. 2001). Particularly, children and adolescents are affected (Bistrup et al. 2001). The WHO and the U.S. Environmental Protection Agency consider a daily average sound exposure equivalent to LAeq = 70 dB(A) to be safe for the ear (WHO 2000). The large numbers of young people with hearing impairments should serve as a warning. “Noise hygiene” can be improved, particularly through education at school.
Even ear-safe sound levels can cause nonauditory health effects if they chronically interfere with recreational activities such as sleep and relaxation, if they disturb communication and speech intelligibility, or if they interfere with mental tasks that require a high degree of attention and concentration (Evans and Lepore 1993). The signal–noise ratio (in terms of signal processing) should be at least 10 dB(A) to ensure undisturbed communication. High levels of classroom noise have been shown to affect cognitive performance (Bistrup et al. 2001). Reading and memory have been reported to be impaired in schoolchildren who were exposed to high levels of aircraft noise (Hygge et al. 2002). Some studies have shown higher stress hormone levels and higher mean blood pressure readings in children exposed to high levels of community noise (Babisch 2000; Passchier-Vermeer 2000).
During sleep, electrophysiologic awakening reactions can be detected in an electroencephalogram for event-related maximum noise levels above LAF = 40–45 dB(A) in the bedroom (e.g., aircraft overflights). Recent studies suggest even lower thresholds. The long-term somatic consequences of such arousals are still a matter of discussion and research (WHO Regional Office for Europe 2004). Sleep deprivation, however, is associated with an increased risk of accidents and injuries. Cardiovascular responses found during sleep were independent of sleep disturbance. A subject may sleep during relatively high noise levels but still show autonomic responses.
Among other nonauditory health end points, short-term changes in circulation (including blood pressure, heart rate, cardiac output, and vasoconstriction) as well as in levels of stress hormones (including epinephrine, norepinephrine, and corticosteroids) have been studied in experimental settings for many years (Babisch 2003; Berglund and Lindvall 1995). From this, the hypothesis emerged that persistent noise stress increases the risk of cardiovascular disorders including high blood pressure and ischemic heart disease. Classical biologic risk factors have been shown to be elevated in subjects who were exposed to high levels of traffic noise. Nowadays the biological plausibility of the association is established (Babisch 2002). Its rationale is the general stress concept:
Sound/noise is a psychosocial stressor that activates the sympathetic and endocrine systems.
Acute noise effects do not occur only at high sound levels in occupational settings, but also at relatively low environmental sound levels when, more importantly, certain activities such as concentration, relaxation, or sleep are disturbed.
The following questions need to be answered:
Do these changes observed in the laboratory habituate, or do they persist under chronic noise exposure?
If they habituate, what are the physiologic costs; if they persist, what are the long-term health effects?
There is no longer any need to prove the noise hypothesis as such. Decision making and risk management rely on quantitative risk assessment, but not all biologically notifiable effects are of clinical relevance. The results of epidemiologic noise studies suggest an increase in cardiovascular risk with increasing noise exposure (e.g., Babisch 2000). Unfortunately, most of the individual studies that have been carried out lack statistical power. Over the years the quality of studies has improved, and many potential confounding factors have been considered. Some expert groups have rated the evidence of an association as sufficient (overview by Babisch 2002; Passchier-Vermeer 2003). Transportation noise from road and air traffic is the predominant sound source in our communities; outdoor sound levels for day–evening–night (Lden) > 65–70 dB(A) were found to be associated with odds ratios of 1.2–1.8 in exposed subjects compared with unexposed subjects [< 55–60 dB(A)] (Babisch 2000). Because large parts of the population are exposed to such noise levels [European Environmental Agency (EEA) 2004], noise policy can have a significant impact on public health (Kempen et al. 2002; Neus and Boikat 2000). For noise levels below an Lden of 55 dB(A), no major annoyance reactions or adverse health effects are to be expected.
Studies use magnitude of effect, dose–response relationship, biological plausibility, and consistency of findings among studies as issues in epidemiologic reasoning. Environmental and health policy must determine acceptable noise standards that consider the whole spectrum from subjective well-being to somatic health. This means that limit values may vary depending on the severity of outcomes. Future noise research should focus on source-specific differences in risk characterization, combined effects, differences between objective (sound level) and subjective (annoyance) exposure on health, sensitive/vulnerable groups, sensitive periods of the day, coping styles, and other effect-modifying factors.
==== Refs
References
American Academy of Pediatrics. 1997 Noise: a hazard for the fetus and newborn. Committee on Environmental Health Pediatrics 100 724 727 9836852
Babisch W 2000 Traffic noise and cardiovascular disease: epidemiological review and synthesis Noise Health 2 8 9 32 12689458
Babisch W 2002 The noise/stress concept, risk assessment and research needs Noise Health 4 16 1 11 12537836
Babisch W 2003 Stress hormones in the research on cardiovascular effects of noise Noise Health 5 18 1 11 12631430
Berglund B Lindvall T 1995. Community Noise. Archives of the Center for Sensory Research Vol 2, No. 1. Stockholm:Center for Sensory Research.
Bistrup ML Hygge S Keiding L Passchier-Vermeer W 2001. Health Effects of Noise on Children and Perception of Risk of Noise. Copenhagen:National Institute of Public Health.
EEA Traffic Noise: Exposure and Annoyance. Copenhagen:European Environmental Agency. Available: http://themes.eea.eu.int/Sectors_and_activities/transport/indicators/consequences/noise_exposure/Noise_TERM_2001.doc.pdf [accessed 9 June 2004].
Evans G Lepore SJ 1993 Nonauditory effects of noise on children: a critical review Child Environ 10 1 31 51
Hygge S Evans GW Bullinger M 2002 A prospective study of some effects of aircraft noise on cognitive performance in schoolchildren Psychol Sci 13 469 474 12219816
ISO 1990. Acoustics: Determination of Occupational Noise Exposure and Estimation of Noise-Induced Hearing Impairment. ISO 1999. 2nd ed. Geneva:International Organization for Standardization.
Maassen M Babisch W Bachmann KD Ising H Lehnert G Plath P 2001 Ear damage caused by leisure noise Noise Health 4 13 1 16 12678931
Neus H Boikat U 2000 Evaluation of traffic noise-related cardiovascular risk Noise Health 2 7 65 77 12689473
Passchier-Vermeer W 2000. Noise and Health of Children. TNO report PG/VGZ/2000.042. Leiden:Netherlands Organization for Applied Scientific Research (TNO).
Passchier-Vermeer W 2003 Relationship between environmental noise and health J Aviation Environ Res 7 suppl 35 44
Stansfeld S Haines M Brown B 2000 Noise and health in the urban environment Rev Environ Health 15 1–2 43 82 10939085
van Kempen EEMM Kruize H Boshuizen HC Ameling CB Staatsen BAM; de Hollander AEM 2002 The association between noise exposure and blood pressure and ischemic heart disease: a meta-analysis Environ Health Perspect 110 307 317 11882483
WHO 2000. Guidelines for Community Noise. Geneva:World Health Organization. Available: http://www.who.int/docstore/peh/noise/guidelines2.html [accessed 18 October 2004].
WHO 2001. Occupational and Community Noise. Fact Sheet No 258. Geneva:World Health Organization. Available: http://www.who.int/inf-fs/en/fact258.html [accessed 10 January 2003].
WHO Regional Office for Europe 2004. Noise and Health Home. Bonn, Germany:WHO European Centre for Environment and Health. Available: http://www.euro.who.int/ Noise [accessed 18 October 2004].
|
15631951
|
PMC1253720
|
CC0
|
2021-01-04 23:40:55
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A14-A15
|
utf-8
|
Environ Health Perspect
| 2,005 |
10.1289/ehp.113-a14
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0001715626638PerspectivesCorrespondenceTCDD and Puberty in Girls Wolff Mary S. Britton Julie A. Russo Jose Mount Sinai School of Medicine, New York, New York, E-mail:
[email protected] Chase Cancer Center, Philadelphia, PennsylvaniaThe authors declare they have no competing financial interests.
1 2005 113 1 A17 A17 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
We would like to comment on the article by Warner et al. (2004), in which the authors reported no significant associations between age at menarche and exposure to 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), an extremely potent antiestrogenic xenobiotic. The exposure of girls to TCDD at Seveso, Italy, resulted in very high serum TCDD levels (> 100 pg/g lipid), 10–100 times levels usually seen today. Warner et al. noted that the literature is mixed regarding the agonist/ antagonist effects in humans of persistent exposures of this type. First, polybrominated biphenyl exposures have been associated with earlier menarche in girls, whereas experimental models show delayed puberty, a discordance that may be due to timing of exposure (Blanck et al. 2000). Second, as Warner et al. (2004) noted, the experimental data show that TCDD and other estrogen antagonists delay vaginal opening (VO) and disrupt cyclicity in rodents treated pre-natally (Gray et al. 1997; Levy et al. 1995). However, hormonal activity depends on both timing and level of dose, such that phytoestrogens, for example, may be estrogenic—hastening VO—at high doses given after birth (Lamartiniere et al. 1995; Whitten et al. 1995).
Epidemiologic data regarding hormonally dependent female cancer are equivocal, such that there have been suggestions of a protective (i.e., antiestrogenic) effect of TCDD for breast and uterine cancer in TCDD-exposed women from Seveso (Bertazzi et al. 2001), whereas a carcinogenic effect has been observed in cohorts exposed for longer times (Manz et al. 1991; Warner et al. 2002). The findings of Warner et al. (2004), albeit not statistically significant, suggest earlier menarche with higher TCDD level among women who were younger than 8 years of age at the time of exposure [hazard ratio, 1.08 for 10-fold increase in TCDD levels; 95% confidence interval (CI), 0.89–1.30) but not among all women regardless of age. The study population appears to have the usual patterns of risk for menarche as indicated by associations that occur in the expected directions [e.g., for Seveso zone, body mass index (BMI), physical activity, alcohol intake]. Also, TCDD levels were higher among younger girls (median, 205 ppt) than in all girls (median, 140 ppt), an effect that may reflect lower BMI among younger girls and dilution of body burden by greater body size in older girls, but also a significantly higher target-organ dose.
Warner et al. (2004) examined associations in premenarcheal girls who were a younger subset (0–8 years of age) during the exposure window in 1976. This age stratum should capture any strong underlying associations among girls exposed early in life. However, it is known that pubertal transition occurs around 5–7 years of age and that age at menarche is strongly correlated with age at first signs of development (de Ridder et al. 1992; Nicolson and Hanley 1953). Therefore, hormonal exposures before 5 years of age might alter the milestones of female development, including menarche, either more potently or in a different direction than peripubertal exposures. Therefore, the youngest girls in this population (Warner et al. 2004) may have been more susceptible to hormonal effects of environmental toxicants. Recognizing the limitation of small numbers available for further age stratification, it would be interesting to know whether risk of earlier (or later) puberty was raised among girls exposed at earlier ages, such as 0–4 years.
==== Refs
References
Bertazzi PA Consonni D Bachetti S Rubagotti M Baccarelli A Zocchetti C 2001 Health effects of dioxin exposure: a 20-year mortality study Am J Epidemiol 153 1031 1044 11390319
Blanck HM Marcus M Tolbert PE Rubin C Henderson AK Hertzberg VS 2000 Age at menarche and tanner stage in girls exposed in utero and postnatally to poly-brominated biphenyl Epidemiology 11 641 647 11055623
de Ridder CM Thijssen JH Bruning PF Van den Brande JL Zonderland ML Erich WB 1992 Body fat mass, body fat distribution, and pubertal development: a longitudinal study of physical and hormonal sexual maturation of girls J Clin Endocrinol Metab 75 442 446 1639945
Gray LE Wolf C Mann P Ostby JS 1997 In utero exposure to low doses of 2,3,7,8-tetrachlorodibenzo-p -dioxin alters reproductive development of female Long Evans hooded rat offspring Toxicol Appl Pharmacol 146 237 244 9344891
Lamartiniere CA Moore JB Brown NM Thompson R Hardin MJ Barnes S 1995 Genistein suppresses mammary cancer in rats Carcinogenesis 16 2833 2840 7586206
Levy JR Faber KA Ayyash L Hughes CL Jr 1995 The effect of prenatal exposure to the phytoestrogen genistein on sexual differentiation in rats Proc Soc Exp Biol Med 208 60 66 7892297
Manz A Berger J Dwyer JH Flesch-Janys D Nagel S Waltsgott H 1991 Cancer mortality among workers in chemical plant contaminated with dioxin Lancet 338 959 964 1681339
Nicolson AB Hanley C 1953 Indices of physiological maturity: derivation and interrelationships Child Dev 24 3 38 13082600
Warner M Eskenazi B Mocarelli P Gerthoux PM Samuels S Needham L 2002 Serum dioxin concentrations and breast cancer risk in the Seveso Women’s Health Study Environ Health Perspect 110 625 628 12117637
Warner M Samuels S Mocarelli P Gerthoux PM Needham L Patterson DG Jr 2004 Serum dioxin concentrations and age at menarche Environ Health Perspect 112 1289 1292 15345341
Whitten PL Lewis C Russell E Naftolin F 1995 Phytoestrogen influences on the development of behavior and gonado-tropin function Proc Soc Exp Biol Med 208 82 86 7892301
|
15626638
|
PMC1253721
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A17
|
utf-8
|
Environ Health Perspect
| 2,005 |
10.1289/ehp.113-a17
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0002415631956EnvironewsForumChemical Exposures: The Ugly Side of Beauty Products Barrett Julia R. 1 2005 113 1 A24 A24 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
In recent decades reproductive and developmental problems have become more prevalent—for example, data from the Centers for Disease Control and Prevention (CDC) show that male reproductive problems, including undescended testicles and hypospadias, doubled between 1970 and 1993. Environmental chemicals are strongly suspected to be contributing factors. Several recent reports highlight the presence of low-level concentrations of potential reproductive or developmental toxicants, particularly phthalates, in cosmetics and personal care products. A key question is whether these exposures are significant enough to cause harm.
In June 2004, Environment California issued Growing Up Toxic: Chemical Exposures and Increases in Developmental Diseases, which details chemicals found in consumer products and their potential health impacts. Other reports released around the same time by the Environmental Working Group (Skin Deep: A Safety Assessment of Ingredients in Personal Care Products) and Friends of the Earth (Shop Till You Drop? Survey of High Street Retailers on Risky Chemicals in Products 2003–2004) support Environment California’s publication.
According to these three reports, makeup, shampoo, skin lotion, nail polish, and other personal care products contain chemical ingredients that lack safety data. Moreover, some of these chemicals have been linked in animal studies to male genital birth defects, decreased sperm counts, and altered pregnancy outcomes. There is no definitive evidence for the same effects in humans, but widespread exposure, primarily to phthalates, has been shown to occur.
Phthalates, as key components in plastics, appear in many consumer products. The main phthalates in cosmetics and personal care products are dibutyl phthalate in nail polish, diethyl phthalate in perfumes and lotions, and dimethyl phthalate in hair spray. Often, their presence is not noted on labels.
“The concerns that are focused around this particular chemical [class] have arisen from a series of tests and studies that have been released recently that point to significant potential health concerns,” says Sujatha Jahagirdar, an environmental advocate with Environment California. For example, a population study conducted by the CDC and published in the March 2004 issue of EHP demonstrated that 97% of 2,540 individuals tested had been exposed to one or more phthalates. Another preliminary study conducted at the Harvard School of Public Health and published in the July 2003 issue of EHP showed a correlation between urinary phthalate metabolite concentrations and DNA damage in human sperm. However, exposure sources in this study were unknown.
The personal care industry remains confident about phthalate safety, however. The Cosmetic Ingredient Review panel, an independent research group sponsored by the Cosmetic, Toiletry, and Fragrance Association, published a detailed literature review in February 2003 that unequivocally states that current use of phthalates in cosmetics and personal care products is safe. Marian Stanley, manager of the Phthalate Esters Panel of the American Chemistry Council, says, “Some of these concerns [from environmental groups] are based on high-dose animal testing. The exposure that we really see in people—and we have the CDC numbers to back that up—is remarkably low. To us, why bother getting rid of a highly useful product when there should be no concern?”
Therein lies the controversy—environmental groups view the CDC data as evidence of widespread exposure, whereas industry groups view it as evidence of low-level exposure that falls well below amounts shown to cause problems in animal studies. The environmental groups respond that although it may be low-level exposure, it is chronic low-level exposure. Says Elizabeth Sword, executive director of the nonprofit Children’s Health Environmental Coalition: “In my view there is sufficient evidence to pique my concern, not only as a parent but as the executive director of this organization, to circulate this information directly to parents in a way that they can then make the healthiest decisions.”
However, consumers cannot make such judgments without knowing the ingredients contained in the products they use. “There are industry trade secrets and formulations that for industry reasons are kept from the consumer,” says Sword. “This prevents the consumer from making fully informed decisions.”
Environment California and the other environmental organizations hope to change that through consumer education and policy reform at the state and federal levels. “Environment California is pushing for a commonsense chemical policy that requires chemical manufacturers to test . . . their chemicals before they are released into the market and also provide the public with the tools that it needs to protect itself from potential dangerous impacts,” says Jahagirdar. “Labeling is an extremely important and ethical thing for manufacturers to be doing.”
“I think a lot of this comes down to an individual’s acceptance of risk,” says Sword. “[Each person’s] personal risk tolerance is different. I think what we as a society need to feel confident about is that adults will at least make better decisions if you give them a way to do so, particularly when the health of a child may be at risk from making a bad decision.”
Starting too young? Concern is mounting over the effects of long-term exposures to chemicals—such as phthalates—found in cosmetics and personal care products.
|
15631956
|
PMC1253722
|
CC0
|
2021-01-04 23:40:55
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A24
|
utf-8
|
Environ Health Perspect
| 2,005 |
10.1289/ehp.113-a24
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0002615643724EnvironewsForumInternational Health: North Korean Catastrophe Tenenbaum David J. 1 2005 113 1 A26 A26 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
When the Democratic People’s Republic of Korea (DPR Korea, or North Korea as it is still commonly known) makes headlines, it usually concerns the country’s nuclear ambitions. But recently the environment made the news, when the United Nations Environment Programme (UNEP) issued its DPR Korea: State of the Environment 2003 report, which describes environmental conditions in the secretive Asian country. The report paints a grim picture of a mountainous, heavily forested country facing serious environmental challenges.
The report, which is available online at http://www.rrcap.unep.org/reports/soe/dprksoe.cfm, was produced by officials from 20 North Korean government and academic agencies with advice from experts at UNEP and funding from the United Nations Development Programme. In a 27 August 2004 press release announcing the first-ever nationwide report on conditions in North Korea, UNEP acknowledged “a paucity of research and data on which to base reliable environmental assessments.”
The nation is mired in a morass of intertwined environmental problems. The report says North Korea’s population is projected to grow from 23 million in 2004 to 29 million in 2020. Coal warms most houses and powers most industry. It is a major cause of severe air pollution, yet according to the report, the national goal is to quintuple coal consumption by 2020. As it is, the amount of firewood cut to meet the demand for fuel jumped from 3.0 million cubic meters per year in 1990 to 7.2 million cubic meters in 1996, causing serious deforestation.
“Soil erosion has in large part been caused by the cutting down of trees on hillsides and common land,” says Paul French, author of the 2004 book North Korea: The Paranoid Peninsula. “This was done to make way for extra private plots where people could grow food during the famine [which began in the late 1990s]. . . . The local people had little choice as this was an extreme survival strategy in the face of the famine and government callousness and inability to provide food.”
The government turned a blind eye, says French, and people managed to get some extra food. However, the rains, when they came, simply washed off the hillsides—because most of the nation’s forests are on slopes steeper than 20 degrees, deforestation causes erosion and flooding in the watershed. In 1995, floods cost North Korea US$15 billion in damages, and soil erosion nationwide the next year was estimated at 15 tons per hectare.
Although numerous sewage treatment plants have been built in North Korea, many households in small towns and rural areas still discharge untreated sewage into surface waters. The UNEP report attributed severe stream pollution to a “decrease in investment in environmental protection and abnormal operation of waste-water/sewage treatment plants.”
In the Taedong River, which flows through the capital, Pyongyang, the effects of these inputs are compounded by the construction of a barrier at the sea to block incoming floodwaters and by low river volume. Both of these factors have reduced the river’s natural purification capacity, concentrating contaminants near waste-water discharge points. Today, the Taedong exceeds government environmental standards and continues to deteriorate.
The report cites a number of government efforts to plant trees and conserve water, indicating that officials are aware of declining environmental conditions. However, the report avoided mention of the unique political/economic context for North Korea’s environmental conditions. Ruth Greenspan Bell, who studies Asian environmental matters for the nonprofit research group Resources for the Future, says she would assume the situation in North Korea to be the same as that in countries such as the Soviet bloc before 1989 and China today—“that environmental protection, if it exists, lacks any independent role and gets subsumed to production and full-employment goals.”
The entry for North Korea in the 2004 CIA World Fact Book notes that this nation, “one of the world’s most centrally planned and isolated economies,” faces desperate economic conditions. The industrial infrastructure “is nearly beyond repair as a result of years of underinvestment and spare parts shortages,” and industrial output has been declining for years. The Central Intelligence Agency estimates that massive military spending supports an army of 1 million.
Bell raises a second question about the data used in the report. “It is often important to take data from societies like North Korea—in which independent data gatherers and assessors don’t exist—with a grain of salt,” she says. “Too often people feel compelled to tell authorities what they want to hear.” Still, noted UNEP director Klaus Töpfer at the report’s launch, “By bringing together the available environmental information and identifying priority issues, the report will help strengthen monitoring and assessment, policy setting, action planning, and resourcing in DPR Korea.”
A glimpse inside. A dearth of data exists in the public realm on the environmental problems facing North Korea, but a new report from the United Nations Environment Programme leaves little doubt that severe pollution problems are affecting the country and its people.
|
15643724
|
PMC1253723
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A26
|
utf-8
|
Environ Health Perspect
| 2,005 |
10.1289/ehp.113-a26
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a00027EnvironewsForumEHPnet: Noise Pollution Clearinghouse Dooley Erin E. 1 2005 113 1 A27 A27 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Not all sound is bad, but too much of the wrong sounds harm your health. What many people don’t know is that everyday items such as lawn mowers and kitchen blenders can emit noise at hazardous levels. More than 30 million Americans work at al job where they are exposed to hazardous sound levels on a regular basis. One-third of Americans with some degree of hearing loss can attribute that loss to sound exposure. And the evidence is building to point toward other noise-related health effects. The Noise Pollution Clearinghouse (NPC) is one group whose mission is to foster awareness of noise-related issues. On the NPC’s website, located at http://www.nonoise.org/, visitors can find many different resources to learn about what noise pollution is and how it can be fought.
The NPC has four ongoing campaigns: Quiet Classrooms, Quiet Lawns, Quiet Lakes, and Silencing Car Alarms. The Quiet Classrooms portion of the site offers tips to students, teachers, and others on how to make the learning environment as quiet as possible, while the Quiet Lawns page rates 40 different lawn mowers in terms of noisiness. The Quiet Lakes page features information on the noise caused by sport watercraft and what the NPC is doing to fight this noise source. The Silencing Car Alarms portion of the site tells why the NPC thinks car alarms should be outlawed and lists quieter alternatives for keeping cars safe from thieves.
For the layperson, the NPC has assembled an online library of almost 50 articles, reports, and seminal documents from a variety of sources. Within this section is a dictionary of noise terms, a primer on environmental noise, and more technical documents from national and international experts. A separate library contains noise-related documents just from the U.S. Environmental Protection Agency. This page also links to the full text of the Noise Control Act and federal regulations from the Office of Noise Abatement and Control, as well as to Noise Effects Handbook: A Desk Reference to Health and Welfare Effects of Noise. This 10-chapter textbook was written by the Office of Noise Abatement and Control to address effects ranging from fetal impacts to how loss of hearing affects speech and other activities.
Starting once more from the homepage, the Hearing Loss and Occupational Noise Library includes documents from the Occupational Health and Safety Administration, the National Institute for Occupational Safety and Health, and the Mining Safety and Health Administration. Located here are criteria, guides, and standards for protecting workers’ hearing, plus a bibliography of 2,500 references on hearing and ear protection, among other topics. The NPC also is building an online noise law library with federal, state, local, and European noise-related laws and regulations as well as proposed regulations.
For people who want to put their knowledge to work, the NPC Resource Library page has links for activists, educational resources, upcoming noise conferences and meetings, and potential funding sources. The NPC also provides pages on its website for local noise organizations that could not otherwise afford to host their own sites.
|
0
|
PMC1253724
|
CC0
|
2021-01-04 23:40:55
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A27
|
utf-8
|
Environ Health Perspect
| 2,005 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0002815643721EnvironewsNIEHS NewsEnvironmental Knights of the Roundtable: Stirring the Pot in Environmental Health Hood Ernie 1 2005 113 1 A28 A31 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
The Roundtable on Environmental Health Sciences, Research, and Medicine can be thought of as a think tank—a neutral, nonofficial setting where scientists, government officials, academics, industry representatives, and members of advocacy groups can gather to consider and discuss new scientific findings and emerging issues in environmental health. The roundtable, based at the Institute of Medicine (IOM) in Washington, D.C., is purposefully deliberative in nature. Its 34 members do not recommend specific actions or provide formal advice.
Despite that policy, the group has become highly influential in helping to shape the research agenda for fields in its purview. It has also helped what some observers felt was a disparate, fractured discipline to define itself more clearly and more broadly. By articulating a more holistic approach to environmental health, incorporating the natural, social, and built environments, the roundtable seeks to expand the dialogue, encouraging collaborations and partnerships among stakeholders. By identifying potential approaches to deal with new challenges, the group seeks to enhance the effectiveness of environmental health research and medicine in improving and protecting public health. “We try to find approaches toward making a contribution that would be unique to a body like the roundtable,” says NIEHS deputy director and roundtable member Samuel Wilson.
Roundtable workshops are designed to educate participants so that they can make informed decisions in their own arenas, whether they come from federal or state agencies, industry, or academia. The regional meetings are intended not only to provide information about regional environmental issues and concerns, but also to serve as outreach mechanisms, allowing local stakeholders to learn about new approaches while interacting with each other in the neutral roundtable setting.
Roundtable co-chair Lynn Goldman, a professor of environmental health sciences at the Johns Hopkins Bloomberg School of Public Health, finds the group’s many forms of interaction to be exciting and valuable. “Suddenly there’s an ‘a-ha’ in the room, where connections and collaborations are forming that weren’t there, and it’s out of that kind of stirring the pot that something like the roundtable can produce enormous benefits,” she says.
Roundup in Houston
The roundtable has instituted a series of regional meetings across the nation. With its inherent neutrality, the roundtable seeks to facilitate dialogue among often-contentious groups in these regional meetings. “So often, these are individuals who only see each other in an adversarial setting,” says Goldman. “So it’s got to be healthy for people to be brought together in a setting where they can listen to each other, where they’re not directly at odds, where they’re not litigating each other, where they’re not fighting about what’s going to be in a regulation.”
Following on successful regional meetings in Pitts-burgh and Atlanta, the roundtable began 2004 with a January 23 conference in Houston. Like the two previous venues, the city and its surrounding region present a unique environmental situation, and a community atmosphere that the roundtable felt would be conducive to its message. “I often say Houston is ground zero for the interplay between many economic and environmental issues,” says Myron Harrison, senior health advisor for ExxonMobil Corporation and a roundtable member. “Houston has very real challenges. It’s a very business-oriented, high-growth, internationally oriented city. It won’t be able to achieve the growth and stature that is envisioned if it is difficult to attract new business and highly educated employees. Accomplishing this is in part dependent upon solving a broad set of air, land, and water issues.”
Goldman elaborates: “[Houston is] a place where there’s a very sharp interface between the human imprint on the land and the natural environment, a natural environment that’s fairly fragile. On top of that, there is a tremendous diversity in that community, with enormous issues of environmental empowerment, environmental justice, and social equality. All of that came to the fore in the workshop.”
Jane Laping, executive director of the local environmental group Mothers for Clean Air, was pleased that the roundtable chose to come to Houston. “It’s nice to finally be recognized,” she says. “We’re the fourth largest U.S. city, we’ve got the largest petrochemical complex here, we’ve got the worst ozone in the country for the fourth year now—it’s pretty bad. We really need some help.”
The one-day Houston workshop featured presentations on the many pressing environmental health issues in the region, including air pollution, water quality and flooding problems, urban sprawl, and obesity, as well as material on potential solutions such as sustainable growth, green buildings, and the importance of partnerships. “No one group, no one sector, no one set of stakeholders is going to solve anything by themselves,” says Harrison. “It only happens when you get these partnerships. . . . And we showed some good examples of partnerships at the Houston meeting.”
Wilson agrees that the Houston conference was successful in that regard. “There have been some significant follow-up activities that look very positive,” he says. “The scientists have become involved with the civic planners, also the environmental groups have made contact with the academics much more effectively as a result of the meeting. And it seems that the whole community down there is working on this topic in a much more tangible, enthusiastic, and robust way than it had before.”
The roundtable also held a regional meeting in Iowa in November 2004 (after this article’s press time) to examine the state of health and the environment in rural areas of the state.
Emerging Issues: Nanotechnology
With the rapid development of nanotechnology, the roundtable felt the time was right to examine the potential environmental health issues involved with the expected proliferation of nanomaterials into virtually every aspect of commerce in the coming decades. By encouraging increased attention and research on the possible health and environmental pitfalls presented by nanomaterials, the roundtable hopes to contribute to the growing efforts among many stakeholders to maximize the enormous anticipated benefits of the technology by discovering and minimizing its associated risks.
The workshop, Technology and Environmental Health: Implications of Nanotechnology was convened in Washington, D.C., on 27 May 2004. Although many nanotechnology conferences have been held recently, Goldman says this one was different, thanks to the nature of the roundtable’s proceedings: “We were able to provide a neutral ground for discussion, and be able to hear from science leaders who are right at the cutting edge of doing toxicological assessments, leaders of industry who are right at the cutting edge of developing products, social science and policy experts who’ve been looking at the issue, and the people who are leading the nanotech efforts in the government.”
Presentations covered the gamut of issues related to nanotechnology, from potential applications in medicine and environmental remediation to potential health risks, along with discussions about societal implications and the importance of public perception to the technology’s ability to deliver on its promises. Ultimately, the meeting served as a forum for consideration of research needs in the area, to ensure that environmental health questions are answered before it’s too late to prevent negative impacts.
Says Christine Coussens, program officer of the IOM Board of Health Sciences Policy and study director of the roundtable: “The real purpose was to find out what’s missing in terms of a research agenda as the technology is developing.”
Goldman feels that the mix of attendees and the timing of the meeting were both fortuitous: “There’s a small group of experts in nanotechnology, and a number of them were on the agenda, but I think they had a different audience than they usually have, an audience that was very, very important in terms of bringing together the leadership from the federal health agencies. I was very pleased . . . that the meeting was able to be influential at a time that’s very critical.”
A Meeting of the Minds on Disasters
On 22 June 2004, the roundtable held Public Health Risks of Disasters: Building Capacity to Respond, its first workshop in collaboration with another IOM group, the Disasters Roundtable. The conference was staged with the intent of integrating expertise and ideas from the two disciplines as well as increasing the role of public and environmental health considerations in disaster response. “The idea actually came from an internal request at the National Academies,” says Coussens. “The Disasters Roundtable hadn’t been spending a lot of their time talking about health and health risks associated with disasters. They knew a lot about disasters—infrastructure, communications, and other facets—and we knew a lot about health, and so we were asked to put together a workshop agenda that would look at some of the cross-cutting issues, trying to integrate between the two disciplines.”
Presenters at the meeting included emergency preparedness officials from the Department of Homeland Security and the Department of Health and Human Services, along with the director of the Centers for Disease Control and Prevention, public health and disasters experts from academia, and emergency management officials from both large and smaller metropolitan areas. With both natural and terrorism-related disasters seemingly inevitable, workshop participants stressed the need for enhanced collaboration and coordination among all those involved in disaster preparedness and response. They also advocated expanding preparation, mitigation, and response efforts to include hospitals, health care professionals, nongovernmental organizations, mass media, private businesses, academia, and the engineering and scientific communities. Many presentations explored the impacts of disasters on public health, including topics such as rapid assessment of health effects during disasters, infrastructure loss as a public health risk, and health effects of terrorism.
Roundtable member Jack Azar, who is vice president of environment, health, and safety at Xerox Corporation, was particularly anxious that the private sector be included in more multidisciplinary, integrated preparedness and response planning. “I was the only person from industry who spoke,” he says, “and what I asked was for industry to be included in the kinds of discussions that go on in emergency preparedness situations normally between government and nongovernment organizations [such as the Red Cross] only. One hundred million people are usually in the workplace when these things happen, so businesses really need to be brought into it as well.”
According to Goldman, the conference succeeded in increasing communication between the two fields. “I think this kind of meeting enriches the tools you have in your toolbox for doing things like assessing and managing risk, and hopefully helps to identify areas where more research, more information would be valuable for protection of the population. There’s more to it than screening your bags at the airport.”
Spanning the Globe
With the next roundtable workshop, Global Environmental Health in the 21st Century: From Government Regulation to Corporate Social Responsibility, held 13–14 October 2004 in Washington, D.C., the group turned its attention to globalization as a potential driver of environmental health. Many companies in the United States are actually multinational, and they’re governed under a number of different countries’ regulations, says Coussens. One major question for the symposium was how this impacts environmental health in the United States and globally.
The initial thrust of the workshop was the concept of environmental management systems, the organized programs by which companies ensure adherence to high standards of environmental stewardship. For many companies, the concept is embodied in certification by the International Organization for Standardization under ISO 14001, an environmental management system that has been adopted around the world. But there is controversy over the effectiveness of such standardized approaches. “It’s not clear how environmental management systems impact or help to minimize the impact on environmental health,” says Azar. “There hasn’t really been any work trying to look scientifically at the impacts, what the benefits have been of [companies] getting ISO 14001–certified.”
Environmental regulation was another major theme. Several industry representatives pointed out the challenges brought about by the increasing global diversity of regulatory approaches. “Twenty years ago, the United States had [environmental regulation] to itself,” says Harrison. “It set the regulations, and then everyone copied them. That’s no longer the case. . . . These days, the leading edge of regulation is in the European Union [EU]. The EU is much more aggressive.”
Industry is increasingly seeing what could be characterized as a globalization of environmental regulation, as multinational companies respond to requirements imposed by different countries. “What’s happening is you’re getting different regulatory regimes created,” explains Harrison, “but for these companies that operate all around the world, you can’t be developing one product for one country and one product for another country—they have to do it all the same.” This will be a fertile area for future research, as scientists investigate the impact of such globalization on environmental health.
Many companies are now moving beyond regulatory compliance to embrace a concept called corporate social responsibility, and the potential impact of that trend was very much on the workshop’s agenda. Today, says Harrison, companies are faced not just with health and safety expectations, nor just with environmental expectations, but also with a long list of what are called social indicators, which include biodiversity, fair labor practices, and human rights. “The corporate social responsibility agenda is driving every bit as much activity—and maybe more in some places and some companies—than is regulation,” he says.
Azar concurs: “Everybody understands we’ve got to go well beyond compliance to a more sustainable concept. But it can be defined in many different ways. It’s going to take a different form whether you’re a chemical company, an electronics company, an appliance company, or an automobile company.” The workshop included presentations from both advocates and skeptics of voluntary corporate responsibility measures. The workshop, says Coussens, also raised awareness of the transparency that is needed to ensure corporate social responsibility. “It’s got to be more than some kind of marketing gimmick,” she says. “It has to provide real, useful data.”
Wilson anticipates this workshop will have long-term ramifications for the field of environmental health. “Integrating industrial practices into environmental health more so that there’s a much better communication pathway between the two groups is very important, and I think there’s a lot of downstream work to do on that,” he says.
The roundtable had an ambitious agenda in 2004, and the future looks to be equally challenging. As the scope of the roundtable expands, it is likely that its influence upon the field of environmental health will continue to grow, as will its success in providing a unique forum for consideration of the many complicated issues it faces.
Texas town meeting. The roundtable met in Houston to examine the region’s environmental health issues.
Balancing buckyballs. A workshop on nanotechnology looked at both the potential benefits and the potential dangers to health.
Chance favors the prepared. A workshop on disasters brought new perspectives to the thinking on preparedness and response planning.
Industrial evolution. The move from government regulation to corporate social responsibility was debated at a recent roundtable workshop.
|
15643721
|
PMC1253725
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A28-A31
|
utf-8
|
Environ Health Perspect
| 2,005 |
10.1289/ehp.113-a28
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a00031EnvironewsNIEHS NewsHeadliners: Neurological Disease: Neural Protein May Stop the Progression of Alzheimer Disease Phelps Jerry 1 2005 113 1 A31 A31 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Stein TD, Anders NJ, DeCarli C, Chan SL, Mattson MP, Johnson JA. 2004. Neutralization of transthyretin reverses the neuroprotective effects of secreted amyloid precursor protein (APP) in APPSW mice resulting in tau phosphorylation and loss of hippocampal neurons: support for the amyloid hypothesis. J Neurosci 24:7707–7717.
As many as 4.5 million Americans suffer from Alzheimer disease (AD), which usually begins after age 60, and the risk of developing the disease goes up with age. About 5% of men and women aged 65–74 have AD, and nearly half of those aged 85 and older have the disease.
AD is characterized by the presence of protein plaques and tangles of fibers in brain tissue. The disease may in fact be caused by the abnormal processing of the so-called amyloid precursor protein and the accumulation of the protein β-amyloid. Other brain abnormalities in people with AD include nerve cell death in specific areas that are vital to memory and other mental abilities, as well as lower levels of certain neurotransmitters. A recent study by NIEHS grantee Jeffrey Johnson of the University of Wisconsin–Madison has identified a protein known as transthyretin that blocks the effects of β-amyloid.
In working with a transgenic mouse containing defective human genes associated with early-onset AD, Johnson and colleagues noticed that although these mice had high levels of β-amyloid, they did not exhibit any neurodegenerative symptoms. Further investigations led the team to discover that these mice also were producing high levels of transthyretin. When the mice were given antibodies that prevented transthyretin from interacting with the β-amyloid protein, the mice showed typical brain cell death. In vitro studies of human brain cells treated with transthyretin and β-amyloid showed minimal amounts of cell death, confirming the results seen in the mice.
These studies show that transthyretin may block the progression of AD by inhibiting the effects of β-amyloid. This discovery suggests that it may be possible to develop a drug that increases the production of transthyretin and thus protects people at risk for AD, such as those with a genetic predisposition. The findings may also improve the chances of detecting potential environmental factors in the development of AD by allowing scientists to identify agents that upset the balance between transthyretin and β-amyloid proteins.
|
0
|
PMC1253726
|
CC0
|
2021-01-04 23:40:55
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A31
|
utf-8
|
Environ Health Perspect
| 2,005 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0003215643722EnvironewsNIEHS NewsEnvironmental Roots of Asthma Mead M. Nathaniel 1 2005 113 1 A32 A33 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
From 1980 to 1999, the number of U.S. doctor’s office visits for asthma jumped from about 6 million to nearly 12 million, according to data from the Centers for Disease Control and Prevention, and the World Health Organization estimates cases worldwide at 100–150 million. Epidemiologic studies have linked the disease to a plethora of modern lifestyle factors, but the traditional focus has been on heredity and a few identifiable triggers such as animal dander, fungi, ozone, and pollens. At an October 2004 symposium titled Environmental Influences on the Induction and Incidence of Asthma, cosponsored by the NIEHS and the U.S. Environmental Protection Agency, presenters reviewed the scientific evidence for a wider expanse of predisposing factors, including environmental tobacco smoke (ETS) exposure, obesity, dietary fat intake, oxidative stress, and in utero xenobiotic exposures. The emerging array of dynamic interactions between genes, allergens, and pollutants all point to a complex profile of susceptibility and to new possibilities for public health intervention.
Acquiring a Healthy Tolerance
The critical interactions between genetic susceptibility and environmental exposures in the induction of asthma are likely to be heavily influenced by the developmental phase at which the exposures occur. For example, it has long been suspected that decreased exposure to microbes during early life may be contributing to the rise in asthma incidence. Of pivotal interest, from a developmental perspective, is how, why, and when some people acquire immunological tolerance to common allergens, while others go on to develop asthma.
“The programming of this tolerance begins during prenatal and postnatal development,” said Harald Renz, a research scientist at Germany’s Marburg University. In studies of traditional farm environments in Switzerland, Austria, and Germany, Renz’s team consistently found an inverse relationship between asthma rates and maternal blood levels of the bacterial endotoxin lipopolysaccharide (LPS), which is a marker for exposure to gram-negative bacteria common in farmyards. “Infants born to mothers who maintained their daily farm work during pregnancy were almost completely protected from asthma,” he said. “Animal studies using LPS during gestation have confirmed these findings: the offspring are largely protected against the development of allergic inflammation and respiratory hyperresponsiveness.”
Other investigators urged caution against overly simplistic perspectives on the protective impact of early-life exposures to microbes. “The focus on microbial exposure is only one piece of a much larger picture,” said Peter Sly, a lung specialist at the Telethon Institute for Child Health Research in Perth, Australia. “Throughout early life, the immune system takes maturational cues from the environment in the form of microbial stimulation, bowel flora, mother’s milk, and dietary factors. At the same time, the infant is exposed to allergens in the diet and environment. If the allergen exposure coincides with those normal maturational cues, then you’re less likely to develop allergic sensitization and asthma.”
An Eye on Inflammation
In western societies, however, said Sly, maturational cues are often missing due to factors such as more sanitary living conditions and use of antibiotics. Problems arise, moreover, when the fetus or infant is exposed to airborne pollutants such as ETS and diesel exhaust particles (DEP), which can cause airway inflammation and may enhance allergic sensitization and drive disease expression. Increased protection against asthma therefore stems from a confluence of early-life microbial exposure, normal immune maturation, and low exposure to airway irritants or inflammatory factors.
The concept of synergy was a repeated theme at the symposium. One prominent example was the interaction between ragweed pollens and DEP, which have received increasing attention as culprits in the rising incidence of asthma. “Many studies have found that DEP enhances airway responsiveness in asthmatics,” said clinical immunologist Andre Nel of the University of California Medical School in Los Angeles. “We also know that DEP has an adjuvant effect on the Th2 cytokine responses [specific immune responses that increase allergic tendencies] to ragweed pollens, causing an allergen-specific IgE response in humans and thus greater susceptibility to asthma.”
Nel has studied the quinones, nitrogen oxides, and other pro-oxidative chemicals in DEP. These chemicals tend to increase oxidative stress and stimulate inflammatory pathways that, in turn, pave the way for asthma. Conversely, thiol antioxidants have been shown to interfere with the effects of DEP. Research is now needed to determine whether antioxidant treatment may be beneficial for children living along roadways with increased traffic density, where asthma prevalence tends to be higher.
Maritta S. Jaakkola, a senior scientist at the Institute of Occupational Medicine of England’s University of Birmingham, reported on several studies showing a strong relationship between the extent of smoke exposure and asthma. Jaakkola’s research has shown that prenatal, infant, childhood, and adult exposures can all predispose individuals to asthma. In a study in Finland, 8% of asthma cases that started in adulthood were attributable to ETS exposure within the preceding year. “Exposures to ETS in prenatal life, early childhood, and adulthood can all raise the risk of asthma,” said Jaakkola. “For adults, even quite recent exposures can make a difference.”
Different groups of mechanisms seem to be involved: ETS may promote chronic respiratory infections in early life, contributing indirectly to asthma risk. In contrast, ETS-related irritants that inflame the airways may play a stronger role in adult cases of asthma. Obese adults might also be at greater risk, given data presented by Stephanie Shore of the Harvard School of Public Health showing increased inflammatory cytokine levels and airway hyperresponsiveness in these individuals.
Additional discussions focused on the identification of inflammatory markers that can serve as potential indicators of asthma risk. Karin Yeatts, a researcher at the University of North Carolina Center for Environmental Medicine, Asthma, and Lung Biology, spearheaded a study on the effects of different particle sizes and their impact on inflammatory markers in adult asthma patients. Preliminary results indicate that a subgroup of the asthmatic adults had increased levels of inflammatory markers in their lungs in response to increases in ambient concentrations of particles smaller than 2.5 microns. “The levels of particulate matter triggering the upper airway responses were actually lower than those specified by the current national regulations,” said Yeatts. “This suggests that a subgroup of asthmatic adults who show this diverse spectrum of inflammatory cytokines in their blood may be at greater risk where the rest of the population would be relatively safe.”
The symposium yielded a number of suggestions for public health interventions to lower asthma incidence. Among the proposed strategies were “healthy home” design and building remediation to minimize humidity and improve indoor air quality; changes in infection control to curb rising asthma rates in the elderly; increased education on maternal smoking as a preventable risk factor; more green belts in urban areas as pollution buffers; stricter sanctions on emissions from automobiles and diesel engines, mandating diesel particle traps; a large-scale shift away from fossil fuel use; greater efforts to reduce exposures to known sensitizers in the workplace (including a ban on smoking at work); and better public health communication to all high-risk groups.
The public health challenge of asthma will call for a confluence of scientific and policy directives. “Ultimately, in tackling the problem of factors associated with asthma incidence, we are facing a new challenge to understand the complexity in host–environment interactions as well as the practical issues in developing social policy,” said presenter Kevin B. Weiss, a professor of medicine at Northwestern University. “The challenge is great, but the potential for public health impact is even greater.”
Cats and clouds. Animal dander and secondhand tobacco smoke were just two environmental triggers of asthma discussed at a recent meeting cosponsored by the NIEHS and the EPA.
|
15643722
|
PMC1253727
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A32-A33
|
utf-8
|
Environ Health Perspect
| 2,005 |
10.1289/ehp.113-a32
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a00033EnvironewsNIEHS NewsBeyond the Bench: Building Blocks of Learning Fitzgerald Amy 1 2005 113 1 A33 A33 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Playing with blocks has long been a favorite pastime of children and one that parents often encourage as a means of developing reasoning, spatial acuity, and other skills. A program developed by the Community Outreach and Education Program (COEP) of the Massachusetts Institute of Technology (MIT) Center for Environmental Health Studies turns this childhood pastime into an effective method for teaching students about DNA and cellular processes by building models out of LEGO blocks.
Now a commercial product, the LEGO Life Science kits contain different-colored blocks representing the basic structural elements of DNA. So far, the kit series includes models of DNA, chromosomes, and photosynthesis. The kits were developed by Lexington public school teacher Kathleen Vandiver to bring the form and function of the double helix alive for middle-school students. Vandiver later joined the staff of the MIT COEP and has worked with the program to design a learning activity for students based on the kits called “The Shape of Life: From Helix to Chromosome.”
The activity begins with students identifying LEGOs that represent molecules of sugar, phosphates, and nucleotide bases. Using these pieces, they construct their own twisting model of the DNA ladder, with careful attention to base pairing. A brief overview of DNA replication follows, using the LEGO DNA structure as a simulation aid. Students then have individual exploration time to answer questions and investigate variations of their DNA model. Teachers may also add a mutation lesson.
Next, the students learn how DNA’s complex sequence is replicated prior to mitosis, and the lesson scales up to the LEGO Chromosomes kit to model the process of mitosis. The activity concludes with the study of structural components of chromosomes, including a discussion of genes and traits. With the Chromosomes kit, students can build a LEGO fish as a model to demonstrate how genes can be expressed in a living creature. The fish has only 3 chromosome pairs, rather than a human’s 23 pairs, so it’s easier to understand the relationship between genes and traits. Chromosomes, cell membranes, and spindle fibers are modeled in LEGOs as the students move through the stages of interphase, prophase, metaphase, anaphase, and telophase.
The kits can be used to teach many levels of students. Although originally designed for middle schoolers, they can be reassembled into a more advanced version for use at the college level. Several introductory biology classes at MIT have used the sets. Says Vandiver, “It is important to realize that many people need to be taught the basics in order to understand the issues in environmental health.” And what could be more basic—or fun—than playing with blocks?
The LEGO Life Science kits are available for purchase at http://www.legoeducationstore.com/.
Constructive thinking. COEP researcher Luke Higgins (second from left) helps students build a DNA double helix from LEGOs.
|
0
|
PMC1253728
|
CC0
|
2021-01-04 23:40:55
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A33
|
utf-8
|
Environ Health Perspect
| 2,005 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0003415631958EnvironewsFocusDecibel Hell: The Effects of Living in a Noisy World Chepesiuk Ron 1 2005 113 1 A34 A41 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
It’s not difficult for a person to encounter sound at levels that can cause adverse health effects. During a single day, people living in a typical urban environment can experience a wide range of sounds in many locations, including shopping malls, schools, the workplace, recreational centers, and the home. Even once-quiet locales have become polluted with noise. In fact, it’s difficult today to escape sound completely. In its 1999 Guidelines for Community Noise, the World Health Organization (WHO) declared, “Worldwide, noise-induced hearing impairment is the most prevalent irreversible occupational hazard, and it is estimated that 120 million people worldwide have disabling hearing difficulties.” Growing evidence also points to many other health effects of too much volume.
The growing noise pollution problem has many different causes. Booming population growth and the loss of rural land to urban sprawl both play a role. Other causes include the lack of adequate anti-noise regulations in many parts of the world; the electronic nature of our age, which encourages many noisy gadgets; the rising number of vehicles on the roads; and busier airports. The U.S. Environmental Protection Agency (EPA) has long identified transportation—passenger vehicles, trains, buses, motorcycles, medium and heavy trucks, and aircraft—as one of the most pervasive outdoor noise sources, estimating in its 1981 Noise Effects Handbook that more than 100 million people in the United States are exposed to noise sources from traffic near their homes.
Some experts define noise simply as “unwanted sound,” but what can be unwanted for one person can be pleasant or even essential sound to to another—consider boom boxes, car stereos, drag races, and lawn mowers in this context. Sound intensity is measured in decibels (dB); the unit A-weighted dB (dBA) is used to indicate how humans hear a given sound. Zero dBA is considered the point at which a person begins to hear sound. A soft whisper at 3 feet equals 30 dBA, a busy freeway at 50 feet is around 80 dBA, and a chain saw can reach 110 dBA or more at operating distance. Brief exposure to sound levels exceeding 120 dBA without hearing protection may even cause physical pain.
Mark Stephenson, a Cincinnati, Ohio–based senior research audiologist at the National Institute for Occupational Safety and Health (NIOSH), says his agency’s definition of hazardous noise is sound that exceeds the time-weighted average of 85 dBA, meaning the average noise exposure measured over a typical eight-hour work day. Other measures and definitions are used for other purposes. For example, “sound exposure level” accounts for variations in sound from moment to moment, while “equivalent sound level” determines the value of a steady sound with the same dBA sound energy as that contained in a time-varying sound.
Growing Volume
In the United States, about 30 million workers are exposed to hazardous sound levels on the job, according to NIOSH. Industries having a high number of workers exposed to loud sounds include construction, agriculture, mining, manufacturing, utilities, transportation, and the military.
Noise in U.S. industry is an extremely difficult problem to monitor, acknowledges Craig Moulton, a senior industrial hygienist for the Occupational Safety and Health Administration (OSHA). “Still,” he says, “OSHA does require that any employer with workers overexposed to noise provide protection for those employees against the harmful effects of noise. Additionally, employers must implement a continuing, effective hearing conservation program as outlined in OSHA’s Noise Standard.”
Meanwhile, there is no evidence to suggest things have gotten any quieter for residents since the EPA published its 1981 handbook. “For many people in the United States, noise has drastically affected the quality of their lives,” says Arline L. Bronzaft, chair of the Noise Committee of the New York City Council of the Environment and a psychologist who has done pioneering research on the effects of noise on children’s reading ability. “My daughter lives near La Guardia airport in New York City, and she can’t open a window or enjoy her backyard in the summer because of the airplane noise.”
Indeed, the term secondhand noise is increasingly used to describe noise that is experienced by people who did not produce it. Anti-noise activists say its effect on people is similar to that of secondhand smoke. “Secondhand noise is really a civil rights issue,” says Les Blomberg, executive director of the Noise Pollution Clearinghouse, an anti-noise advocacy group based in Montpelier, Vermont. “Like secondhand smoke, it’s put into the environment without people’s consent and then has effects on them that they don’t have any control over.”
Secondhand noise can also have a negative effect in the workplace. “Workers in the construction trades get exposure to noise not just from what they are doing but also from what is going on around them,” says Rick Neitzel, director of communications for the National Hearing Conservation Association. “Electricians, for example, have a reputation as being a member of a quiet trade, but if they work all day next to a laborer who is using a jackhammer, it’s going to have a harmful effect.”
Even disregarding other people’s noise, there are any number of household tools and appliances that can produce harmful sound levels in the comfort of one’s own home. According to the fact sheet “Noise in the Home” produced by the League for the Hard of Hearing, dishwashers, vacuum cleaners, and hair dryers can all reach or exceed 90 dBA.
Our modern industrialized society has spawned ubiquitous entertainment and sports industries with their boom boxes, “personal stereos” (Gap Kids now even offers a jacket with a built-in radio and speakers conveniently attached right in the hood), surround-sound movie theaters, loud TV commercials, and even louder commercials at sports stadiums crammed full of thousands of noisy fans. In drag racing, a growing international sport, a German team of audio engineers set an earsplitting record of 177 dB–sound pressure level in 2002. Popular “boom cars” equipped with powerful stereo systems that are usually played with the volume and bass turned up abnormally high and the car windows rolled down can hit 140–150 dBA. Listening to music at a level of 150 dBA would be like standing next to a Boeing 747 airplane with its engines at full throttle, according to statistics provided by Noise Free America, an anti-noise advocacy group.
Even the countryside is not immune to the impact of noise pollution. According to the New York Center for Agricultural Medicine and Health in Cooperstown, a staggering 75% of farmworkers have some kind of hearing problem, largely the result of long-term exposure to loud equipment.
The United States is not the only country where noise pollution is affecting the quality of life. In Japan, for instance, noise pollution caused by public loudspeaker messages and other forms of city noise have forced many Tokyo citizens to wear earplugs as they go about their daily lives. In Europe, about 65% of the population is exposed to ambient sound at levels above 55 dBA, while about 17% is exposed to levels above 65 dBA, according to the European Environment Agency.
“The noisy problems associated with air travel are concentrated in communities around airports, whereas motorways or high-speed trains—traveling, for instance, from north to south Europe—have the potential to disturb thousands of people living along the route day after day,” says Ken Hume, a principal lecturer in human physiology at the Manchester Metropolitan University in England.
Noise is indeed everywhere, and experts expect no decrease in noise levels, given the powerful impact of technology on modern life. “In the past three decades, we have built noisier and noisier devices that are not subject to any regulations,” Blomberg says. “Think about it. The car alarm is a seventies invention, as is the leaf blower. The stereo sound systems we have in our cars are much louder than the sound system the Beatles used for their concerts in the sixties. All they had back then were three-hundred-amp speakers.”
Scary Sound Effects
Numerous scientific studies over the years have confirmed that exposure to certain levels of sound can damage hearing. Prolonged exposure can actually change the structure of the hair cells in the inner ear, resulting in hearing loss. It can also cause tinnitus, a ringing, roaring, buzzing, or clicking in the ears. The American Tinnitus Association estimates that 12 million Americans suffer from this condition, with at least 1 million experiencing it to the extent that it interferes with their daily activities.
NIOSH studies from the mid to late 1990s show that 90% of coal miners have hearing impairment by age 52—compared to 9% of the general population—and 70% of male metal/nonmetal miners will experience hearing impairment by age 60 (Stephenson notes that from adolescence onward, females tend to have better hearing than males). Neitzel says nearly half of all construction workers have some degree of hearing loss. “NIOSH research also reveals that by age twenty-five, the average carpenter’s hearing is equivalent to an otherwise healthy fifty-year-old male who hasn’t been exposed to noise,” he says.
“Noise has an insidious effect in that the more exposure a person has to noise, the more the hearing loss will continue to grow,” says Josara Wallber, disabilities services liaison for the National Technical Institute for the Deaf in Rochester, New York. “Hearing loss is irreversible. Once hearing is lost, it’s lost forever.”
William Luxford, medical director of the House Ear Clinic of St. Vincent Medical Center in Los Angeles, points out one piece of good news: “It’s true that continuous noise exposure will lead to the continuation of hearing loss, but as soon as the exposure is stopped, the hearing loss stops. So a change in environment can improve a person’s hearing health.”
For many young people, changing their environment and their behavior would be a wise and healthy move. That’s because audiologists are fitting more and more of them with hearing aids, says Rachel Cruz, a research associate at the House Ear Clinic. She says audiologists are blaming this disturbing development on youth’s penchant for listening to loud music, especially with the use of headphones.
Research is catching up with this anecdotal evidence. In the July 2001 issue of Pediatrics, researchers from the Centers for Disease Control and Prevention reported that, based on audiometric testing of 5,249 children as part of the Third National Health and Nutrition Examination Survey, an estimated 12.5% of American children have noise-induced hearing threshold shifts—or dulled hearing—in one or both ears. Most children with noise-induced hearing threshold shifts have only limited hearing damage, but continued exposure to excessive noise can lead to difficulties with high-frequency sound discrimination. The report listed stereos, music concerts, toys (such as toy telephones and certain rattles), lawn mowers, and fireworks as producing potentially harmful sounds.
For the baby boom generation, on the other hand, a change of environment may be too late. “Many baby boomers began losing their hearing when the amplification of popular music came into vogue in the nineteen sixties,” says Cruz. “We are starting to see that a lot of musicians and audio engineers who have been involved with popular music for a long time are having hearing problems.” Cruz is gathering data for a research study to examine how these professionals’ occupational sound exposures affect their hearing over a span of years.
Beyond the Ears
The effects of sound don’t stop with the ears. Nonauditory effects of noise exposure are those effects that don’t cause hearing loss but still can be measured, such as elevated blood pressure, loss of sleep, increased heart rate, cardiovascular constriction, labored breathing, and changes in brain chemistry. According to the WHO Guidelines for Community Noise, “these health effects, in turn, can lead to social handicap, reduced productivity, decreased performance in learning, absenteeism in the workplace and school, increased drug use, and accidents.”
The nonauditory effects of noise were noted as early as 1930 in a study published by E.L. Smith and D.L. Laird in volume 2 of the Journal of the Acoustical Society of America. The results showed that exposure to noise caused stomach contractions in healthy human beings. Reports on noise’s nonauditory effects published since that pioneering study have been both contradictory and controversial in some areas.
Data pertaining to whether noise can increase the risk of damage to the fetus is a case in point. A study published by L.D. Edmonds, P.M. Layde, and J.D. Erickson in the July–August 1979 issue of the Archives of Environmental Health found no significant data suggesting an effect of noise on fetal development in pregnant women who lived near airports. But in the October 1997 issue of Pediatrics, the Committee on Environmental Health of the American Academy of Pediatrics published a policy statement based on a review of research on the potential health effects of noise on the fetus and the newborn. The committee concluded that excessive noise exposure in utero may result in high-frequency hearing loss in newborns and further that excessive sound levels in neonatal intensive care units may disrupt the natural growth and development of premature infants. It recommended that noise-induced health effects on fetuses and newborns are clinical and public health concerns that merit further study.
Studies have revealed that as children grow they are exposed to sounds that can threaten their health and cause learning problems. For instance, in the September 1997 issue of Environment and Behavior, Cornell University environmental psychologists Gary Evans and Lorraine Maxwell reported that the constant roar of jet aircraft could cause higher blood pressure, boosted stress levels, and other effects with potential life-long ramifications among children living in areas under the flight paths of airport.
Other human and animal studies also have linked noise exposure to chronic changes in blood pressure and heart rate. For example, in the July–August 2002 issue of the Archives of Environmental Health, a team of government and university researchers concluded that exposure to sound “acts as a stressor—activating physiological mechanisms that over time can produce adverse health effects. Although all the effects and mechanisms are not elucidated, noise may elevate systolic blood pressure, diastolic blood pressure, and heart rate, thus producing both acute and chronic health effects.”
Noise has also been shown to affect learning ability. In 1975 Bronzaft collaborated on a study of children in a school near an elevated train track that showed how exposure to noise can affect children’s reading ability. Half of the students in the study were in classrooms facing the train track and the other half were in classrooms in the school’s quieter back section. The findings, published in the December 1975 issue of Environment and Behavior, were that students on the quieter side performed better on reading tests, and by sixth grade they were a full grade point ahead of the students in the noisier classrooms.
Bronzaft and the school principal persuaded the school board to have acoustical tile installed in the classrooms adjacent to the tracks. The Transit Authority also treated the tracks near the school to make them less noisy. A follow-up study published in the September 1981 issue of the Journal of Environmental Psychology found that children’s reading scores improved after these interventions were put in place. “After we did the study, more than twenty-five other studies were done examining the effect of noise on children’s learning ability,” Bronzaft says. “They have all found the same thing to be true: noise can affect children’s learning.”
The EPA reported in the Noise Effects Handbook that surveys taken in communities significantly affected by noise indicated that interruption of sleep was the underlying cause of many people’s complaints. Research has shown that unwanted sound is most annoying at the times when people expect to rest or sleep, that it can interrupt or delay sleep, and that it can have subtle effects on sleep, such as causing shifts from deeper to lighter sleep stages. “The research is pretty solid that noise can prevent people from getting a good night’s sleep,” Hume says. “I believe that sleep deprivation can have negative health effects when it becomes a chronic problem.”
Fighting for Quiet
Worldwide, airports have become a flash point for community frustration over noise pollution. In September 2002, officials at the Frankfurt am Main Airport in Germany received 56,330 noise-related complaints, a 30% increase over the same month in 2001. The same year, residents living near a rural airport outside London, England, were submitting 100 petitions daily, objecting to proposals for three new runways at the site.
In March 2003, representatives from eight neighborhoods in Portland, Oregon, showed up for a city council hearing convened to discuss dozens of expansion projects for Portland International Airport. The airport was already a busy one: in 2002 it handled 12.2 million passengers and about 29,000 containers of air cargo. “The impacts are tremendous on the neighborhoods under the flight paths,” testified one neighborhood representative, Jean Ridings. “People move in and move [right back] out. It’s becoming a disaster.” In response, the airport has initiated a multiyear, multimillion-dollar effort to study the sound impact of the airport, which locals hope will lead to a plan to reduce airport noise.
Noise Free America is seeking to file a class-action lawsuit against the makers of boom car equipment. Ted Rueter, Noise Free America’s director and an assistant professor of political science at DePauw University in Greencastle, Indiana, says one group member has written a legal brief on the topic and has approached several public-interest law firms seeking representation, with no takers so far. Rueter says Noise Free America will continue to pursue the suit.
A lot of money is being made from disturbing the peace, charges Mark Huber, communications director for Noise Free America. “By using paid lobbyists in Washington, D.C., and in state legislatures, the automobile and entertainment industries are quietly removing obstacles protecting the public against noise,” Huber says. “Try to get a noise control law passed through a state legislature and see what happens. We tried to get a boom car law enacted in the Virginia General Legislature, but right here in Richmond there are at least fifty car clubs, all of which are politically active. So our legislation disappeared.”
Stephen McDonald, vice president of government affairs for the Washington, D.C.–based Specialty Equipment Market Association (SEMA), denies that any powerful lobby exists and is working against the best interests of society. SEMA represents manufacturers, distributors, retailers, and installers of specialty automotive equipment, including boom car equipment. “Our prime focus is representing the interests of businesses that sell exhaust systems,” McDonald says. “But that doesn’t mean we want the products to increase noise to a level where it becomes objectionable. We do need to strike a balance, though, between what is acceptable for a neighborhood and what’s fair to people who want to customize their cars.”
Anti-noise activists say that Europe and several countries in Asia are more advanced than the United States in terms of combating noise. “Population pressure has prompted Europe to move more quickly on the noise issue than the United States has,” Hume says. In the European Union, countries with cities of at least 250,000 people are creating noise maps of those cities to help leaders determine noise pollution policies. Paris has already prepared its first noise maps. The map data, which must be finished by 2007, will be fed into computer models that will help test the sound impact of street designs or new buildings before construction begins.
In the United States, the Noise Control Act of 1972 empowered the EPA to determine noise limits to protect the public health and welfare, and to establish a noise control office. Congress did establish the Office of Noise Abatement and Control (ONAC), as well as federal standards for business, industries, and communities, and it did begin researching the effects of sound exposures. In 1982, however, the Reagan administration defunded the office. “We are no longer doing research on noise,” says Kenneth Feith, an EPA senior scientist and policy advisor. “We just don’t have the money or staff to do it.”
Activists believe that closing the ONAC has had a tremendous negative effect at the state and local level. “The U.S. has long since given up its lead in regulating noise, and because of that there has been no consistency in implementing local noise regulations,” Huber says. The Noise Control Act, though still on the books, is essentially toothless.
In the mid-1990s, people in the borough of Queens, New York, who lived under the flight paths of La Guardia Airport, took their concerns about noise to Representative Nina Lowey (D–NY). “I could see that noise is a serious public health issue, and so I decided to do something about it,” Lowey says. In 1997 the congresswoman introduced legislation that’s become known as the Quiet Communities Act (HR 536), which provided for the refunding of the ONAC and for $21 million to be spent annually on noise reduction. Among other measures, the money would be used to carry out a national noise assessment program to identify trends in noise exposure and response, develop and disseminate information and public education materials on the health effects of noise, and establish regional technical assistance centers, which would use the resources of universities and private organizations to assist state and local noise control programs.
“More and more communities are being affected by airports, trains, and railways,” Lowey says. “We need a national office to coordinate policy. That’s common sense to me. The federal government has to play a larger role on the noise issue. Otherwise, we will continue to lag behind other parts of the world in combating noise.” While Lowey remains optimistic that the legislation will eventually pass, other sources doubt that it will happen, noting that the proposed legislation has been introduced and rejected several times.
Activists in other countries say they too want the United States to play a more leading role on the noise issue. “Re-establishing the ONAC would be a huge move in the right direction,” says Hans Schmid, the Vancouver, Canada–based president of the Right to Quiet Society. “That will show that the United States is serious about the noise issue. If the United States leads, other countries, especially Canada, will follow.”
But as in other areas of environmental health, merely having a more powerful government agency in place that can set more regulations is not the ultimate answer, according to other experts. Regulations provide an important foundation, Stephenson says, but better education of workers, consumers, businesses, and citizens is critical. “We’ve found that in some factories as many as one-third of the workers who have significant hearing loss don’t wear hearing protectors, even though the factory has a comprehensive hearing conservation program in place,” he says.
Bronzaft stresses that governments worldwide need to increase funding for noise research and do a better job coordinating their noise pollution efforts so they can establish health and environmental policies based on solid scientific research. “Governments have a responsibility to protect their citizens by curbing noise pollution,” she says.
Feith agrees. “The EPA had a successful educational program in the nineteen seventies in which we went to schools and educated students about noise,” he says. “When students took the message home, they helped increase the sensitivity to the noise issue. We need more programs like that to educate the public about noise.”
In the meantime, some facilities are doing what they can to help themselves to a quieter environment. Although peace and quiet are essential prerequisites for a healing environment, a Mayo Clinic study published in the February 2004 issue of the American Journal of Nursing showed that peak noise levels during the clinic’s morning shift change rivaled the excruciating sound of a jackhammer. The study further showed that a few simple changes—for example, holding staff reports at shift change in an enclosed room (rather than at the nurses’ station) and replacing roll-type paper towel dispensers with quieter models—reduced peak noise levels at shift change by 80%.
Similarly, the din of overhead pagers, which can reach 80 dBA, inspired the developers of the Woodwinds Health Campus in Woodbury, Minnesota, to build the facility with a staff location sensor and badge system, among other sound-friendly features. Staff can be located in just about any area of the Woodwinds campus without being paged. “We have developed an innovative approach to reducing noise in our hospital while fostering a healing environment,” says Cindy Bultena, executive lead of healing and clinical coordination for Woodwinds. “Our change sounds simple enough, but it’s a very radical one for hospitals.”
By delivering their patients and staff from decibel hell, facilities like Woodwinds and the Mayo Clinic have scored one small victory in the ongoing battle against noise pollution. Their initiative, moreover, shows that given the pervasiveness and harmful effects of noise, governments, communities, and organizations worldwide will need to be creative and aggressive in addressing what will certainly continue to be one of the 21st century’s most important environmental health issues.
On the increase. Our technological society encourages the propagation of noisy devices, and children are being exposed earlier than ever to an abundance of electronic noise.
On the street. Booming bass is quickly becoming the sound-track of urban life.
On the job. Occupational noise is pervasive throughout many industries and may cause serious damage despite regulations to protect workers’ hearing.
On the go. Transportation sound is perhaps the largest contributor to urban noise pollution.
On the way up. Problems from airplane and airport noise are increasing as more and more flights take off over residential areas.
On the mend? Hospitals can be some of the noisiest public locations, but some health care facilities are actively fighting noise in the interest of better patient care.
Counting Decibels
Device/Situation dBA*
Grand Canyon at night, no birds, no wind 10
Quiet room 28–33
Computer 37–45
Floor fan 38–70
Refrigerator 40–43
Normal conversation 40
Forced-air heating system 42–52
Radio playing in background 45–50
Clothes washer 47–78
Dishwasher 54–85
Bathroom exhaust fan 54–55
Microwave oven 55–59
Normal conversation 55–65
Laser printer 58–65
Hair dryer 59–90
Window fan on “high” setting 60–66
Alarm clock 60–80
Vacuum cleaner 62–85
Push reel mower 63–72
Sewing machine 64–74
Telephone 66–75
Food disposal 67–93
Inside car with windows closed, traveling at 30 miles per hour 68–73
Handheld electronic game 68–76
Inside car with windows open, traveling at 30 miles per hour 72–76
Electric shaver 75
Air popcorn popper 78–85
Electric lawn edger 81
Electric can opener 81–83
Gasoline-powered push lawn mower 87–92
Average motorcycle 90
Air compressor 90–93
Weed trimmer 94–96
Leaf blower 95–105
Circular saw 100–104
Maximum output of stereo 100–120
Chain saw 110
Average snowmobile 120
Average fire crackers 140
Average rock concert 140
* Measurements are approximate and may vary by source.
Sources: National Institute on Deafness and Other Communication Disorders, Environmental Protection Agency, Noise Pollution Clearinghouse.
|
15631958
|
PMC1253729
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A34-A41
|
utf-8
|
Environ Health Perspect
| 2,005 |
10.1289/ehp.113-a34
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0004215631959EnvironewsSpheres of InfluenceNoise that Annoys: Regulating Unwanted Sound Schmidt Charles W. 1 2005 113 1 A42 A44 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Anyone who lives in Bensenville, Illinois, knows about the “Bensenville pause.” According to long-time resident Pat Johnson, it goes like this: As the roar of a jetliner departing from nearby O’Hare International Airport becomes a blasting shriek, the residents of this small town stop talking and wait. Conversations pick up as the plane goes by, but they soon pause again; planes fly over Bensenville every three to four minutes. “Sometimes, it’s hard to fall asleep,” Johnson says. “You do, but then you wake up again. The noise interrupts churches and classrooms. There are times you can’t even talk on the phone.”
The case of Bensenville may be extreme, but it’s not unusual. Today, millions of Americans suffer from noise pollution caused by planes, road traffic, car alarms, boom boxes, stereos, and many other volume-enhanced contraptions, some of them earsplitting by design. Until recently, for example, Sony Corporation marketed amplifiers and speakers with a “Disturb The Peace” advertising campaign that boasted of “new ways to offend.” Les Blomberg, who directs the nonprofit Noise Pollution Clearinghouse, refers to unwanted noise as aural litter or audible trash —“That is how people experience community noise: as someone else’s garbage thrown into their space,” he says.
In many developed countries, such as some member nations of the European Union, governments have stepped in to protect citizens from this aural assault with regulations that set maximum sound levels for construction equipment, vehicles, and airplanes. Switzerland has gone so far as to prohibit aircraft departures between 11:30 p.m. and 5:00 a.m., except in unusual and unforeseen cases. Yet Americans seeking relief from noise pollution are remarkably powerless.
A Regulatory Void
Years ago, the Environmental Protection Agency (EPA) had federal regulatory authority over noise pollution. Working through the agency’s Office of Noise Abatement and Control (ONAC), EPA staff developed model noise codes that were provided to local municipalities upon request. With assistance from the EPA, these model codes were then customized to address local noise pollution sources and concerns. The EPA also had enforcement authority over the Noise Control Act of 1972, a national law designed to protect Americans from “noise that jeopardizes their health or welfare.”
ONAC was preparing to establish federal noise standards for transportation sources and construction machinery when its funding was abruptly cut off in 1981 by the incoming Reagan administration. With one stroke, the administration crippled the Noise Control Act and left the country without a coherent national noise policy. Reagan’s view was that noise was better managed by states and local communities. However, Blomberg says, with ONAC’s closure came cuts for federal assistance in this area. Without federal dollars, more local efforts to fight noise pollution were forced to compete forstate funding—often unsuccessfully.
Meanwhile, efforts to draft national noise standards for transportation sources—which at the time were cited by the EPA as the greatest source of residential exposure to noise pollution—were stopped in their tracks and have not been revived. Since ONAC’s closure, federal oversight of transportation noise has been filled by agencies whose core mandates are often at odds with noise control.
The Federal Aviation Administration (FAA), for instance, has the authority to determine where and how airport noise should be managed. But according to Peter Kirsch, an attorney with the Denver, Colorado–based firm Kaplan Kirsch & Rockwell who has represented plaintiffs in noise litigation, this responsibility conflicts with one of the FAA’s main purposes, which is to promote the growth of the aviation industry. Likewise, the Federal Highway Administration has primary authority over traffic noise—yet this agency’s core mission is to build, maintain, and upgrade the nation’s road system.
Consequently, communities that suffer from noise pollution are often thwarted by officials from the FAA and other agencies. Even efforts by individual airports to become more noise-friendly are usually rebuffed by FAA officials—particularly if the solutions involve flight restrictions that could impede commerce, Kirsch says. “Airports usually have to fight the feds to achieve some environmental gains,” he says. “It’s a backwards approach to environmental protection, and it creates a permanent animosity among the FAA, local communities, and airport operators.”
A Health Problem?
Why has noise pollution—the bane of existence for so many people—been given such short shrift by the federal government? One reason is the disagreement over its inherent health risks.
Some researchers, for instance Birgitta Berglund, a professor of psychology at Stockholm University in Sweden and editor of the World Health Organization’s 1999 Guidelines for Community Noise, suggest unwanted sound exposure can cause hearing loss, fatigue, loss of balance, nausea, reduced sex drive, headaches, and mental disorders. Others link noise pollution with susceptibility to colds, changes in blood pressure, and heart disease.
But establishing causal links between sounds and health risks is challenging, if not impossible, says Sanford Fidell, a noise expert and a principal of Fidell Associates, a Woodland Hills, California–based consulting firm for airports, communities, and government agencies. Unlike drugs or chemicals, noise pollution leaves no residue in the body, he says. Therefore, it’s difficult to measure its cumulative effects or to distinguish noise impacts from other, similar stressors. Humans are clearly irritated by noise, but their reactions to it are tempered by personality and other idiosyncratic factors.
“One thing that’s certain is that there’s a causal link between sleep disturbance and noise,” says Eric Zwerling, director of the Rutgers University Noise Technical Assistance Center. “And there’s no question that sleep disturbance results in a loss of productivity and efficiency and a greater potential for accidents.” Zwerling says his views are backed by evidence provided by the EPA in its seminal 1974 guidance known most commonly as the “levels document.”
The Airport Controversy
The FAA regulates noise according to a value called the day–night average sound level, abbreviated as DNL. Based on its interpretation of the scientific literature, the Federal Interagency Committee on Aviation Noise (FICAN) noted in a 1992 report titled Federal Agency Review of Selected Airport Noise Analysis Issues that 12.3% of residents are “highly annoyed” once noise reaches an average of 65 decibels (dB). The DNL 65 dB is now an established regulatory trigger for FAA-funded noise remediation efforts. In a standard practice, officials will designate a DNL 65 dB “contour zone” around an airport, within which residents may qualify for home buy-outs or structural soundproofing, the latter being the FAA’s preferred remedial option to mitigate noise impacts.
Many experts are critical not only of the DNL metric and the 65-dB threshold, which they view as economically motivated with little basis in science, but also of FICAN itself, which has heavy representation from the aviation industry. “You could say FICAN is the fox guarding the henhouse,” says Kirsch. He adds that the DNL 65 dB threshold is problematic because it represents flight noise averaged over a typical 24-hour period. Thus, the value doesn’t reflect much louder short-term noise events, nor does it reflect the frequency of noise events among a given population.
Caught between the regulators and the science are communities like Bensenville, which increasingly turn to the courts in search of relief. Cases like these can drag on for many years. For instance, Bensen-ville’s activists—many of them housewives and mothers—have fought O’Hare over noise, among other issues, for more than three decades.
For its part, the FAA claims to have lessened the impact of aircraft noise by requiring quieter “Stage III” engines on planes that weigh 75,000 pounds or more. The requirement for Stage III engines on larger aircraft was imposed by the Airport Noise and Capacity Act (ANCA) of 1990, which also created a mechanism for airports to follow if they wanted to restrict the remaining older, louder Stage I or II planes weighing less than 75,000 pounds. A spokesperson with the FAA Office of Public Affairs says that in 1975, with 250 million people flying a year, there were 7 million people affected by aircraft noise. Today, 700 million people fly each year, but the FAA estimates 600,000 people are affected by noise (although Blomberg says most experts outside the FAA think this number is far too low).
The validity of the FAA’s numbers has no bearing on flight frequency, which has increased 40% since 1990, according to the U.S. Bureau of Transportation Statistics. And flight frequency is among the problems most often cited by those who suffer from aircraft noise. Moreover, under ANCA, Stage III engines are not required for planes that weigh less than 75,000 pounds, which include corporate jets and other aircraft whose use is steadily rising. Kirsch is now involved in a pivotal case in Naples, Florida, where in 2001 the local airport successfully used the ANCA procedures to ban the loud Stage I and II planes that are lighter than the law’s weight limit. Ever since, Kirsch has fought a protracted legal battle with the industry and the FAA, which is struggling to overturn the ban and reintroduce the louder aircraft against the desires of both the community and the airport itself.
A Local Choice
Transportation aside, much of the annoying racket assaulting residential eardrums comes under the purview of local ordinances. Commercial and industrial noise sources, loud music, barking dogs, early-morning lawn mowers, and unmuffled motorcycles could all be regulated if local governments so chose. The challenge is to overcome local opposition, prepare the necessary regulations, and then educate law enforcement and residential communities about their existence.
Zwerling and his staff at the Rutgers University Noise Technical Assistance Center write customized noise codes for local jurisdictions and train designated municipal officials on ways to monitor and enforce them. “It’s unbelievably gratifying,” he says.
But Zwerling concedes that transportation sources are not so easily addressed, when local regulation is prevented by federal preemption. Unlike local governments, who have no vested interest in the operation of thumping subwoofers or the First Amendment rights of a Led Zeppelin–obsessed teenager, the federal agencies that regulate transportation noise makers must by necessity be concerned with those constituents’ economic well-being.
“When it comes to noise, I think it’s important to have some distance from those who regulate and those who are regulated,” Zwerling says. “The feds need to either get all the way into regulating noise or they need to get all the way out so the locals can do it. That way, a powerful agency like the California Air Resources Board could start setting noise standards for the state. Pretty soon, other states like New York or New Jersey would follow suit. You need a state with enough power to set some influential standards.”
|
15631959
|
PMC1253730
|
CC0
|
2021-01-04 23:40:55
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A42-A44
|
utf-8
|
Environ Health Perspect
| 2,005 |
10.1289/ehp.113-a42
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0004615631960EnvironewsInnovationsClamoring for Quiet: New Ways to Mitigate Noise Manuel John 1 2005 113 1 A46 A49 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
On a typical day in an American suburb, the steady whoosh of traffic on a nearby freeway drowns out the rustling of leaves in the wind. From across the street comes the nagging whine of a leaf blower, accompanied every few minutes by the deeper roar of a jet taking off from the airport. The cacophony of noise in the modern world is annoying to many and literally enough to make some people sick. Fortunately, new technologies are emerging to combat noise pollution.
Quieter Airports Take Off
Sound levels are typically measured in decibels (dB). Humans hear sound within a limited frequency range, which is reflected in a value known as A-weighted dB, or dBA. According to community noise guidelines published in 1999 by the World Health Organization, for a good night’s sleep background sound levels should not exceed 30 dBA. In outdoor living areas, sounds above 50 dBA are annoying to humans. The Occupational Safety and Health Administration (OSHA) requires employers to provide workers with hearing protection if they are exposed to an 8-hour time-weighted average of 85 dBA or more. For those living or working near flight paths of major airports, the noise of aircraft taking off and landing can exceed 100 dBA.
Seven years after the passage of the National Environmental Policy Act of 1969, the Federal Aviation Administration (FAA) adopted the Aviation Noise Abatement Policy (ANAP), which among other things, sought to reduce aircraft noise at the source—the aircraft itself. Under ANAP, airlines have retired or replaced noisier aircraft in three stages. But while aircraft are now significantly quieter than they were a few decades ago, many airports have added new runways and increased the number of takeoffs and landings. And urban sprawl has resulted in more people living around airports than ever before. The result is continued public pressure to reduce aircraft noise.
The National Aeronautics and Space Administration (NASA) is spearheading research in reducing aircraft noise through its Quiet Aircraft Technology program. The FAA standard for aircraft noise is the EPNdB (or effective perceived noise dB—a measure that is weighted to reflect the particular range of sounds generated by aircraft). NASA aims to develop the technology to reduce commercial aircraft noise by 10 EPNdB by 2007 and another 10 EPNdB by 2019.
“Our goal is to provide the technology to contain all annoying aircraft noise within the airport boundary,” says Dennis Huff, chief of the Acoustics Branch at NASA’s Glenn Research Center in Cleveland, Ohio. “It will be up to regulations and the marketplace to decide when the technology is used before the noise reduction benefit is realized.”
Jet engine noise comes predominately from two sources. An approaching jet creates a high-pitched whine as the fan pulls air into the engine. As the jet passes by, a low-pitched rumble is created by exhaust leaving the engine.
Working with the major aircraft engine manufacturers, NASA has been able to reduce the former sound by designing engines with larger fans. Larger fan blades turn at a slower tip speed, which reduces both noise and fuel consumption. The turbo fan engines introduced in the 1970s are much quieter than the turbo jet engines they replaced, and engines being designed today are quieter still.
Different approaches are being used to reduce the noise produced by exhaust leaving the engine. Researchers have found that notching chevrons into the rim of the nozzle allows hot engine air to mix more thoroughly with the cooler ambient air. This decreases turbulence and reduces engine noise. Chevrons have been used so far on aircraft flown by America West and USAir. New engines with larger fans also slow exhaust air speed, for even more noise reduction.
On the Road to Quieter Highways
Freeways are a ubiquitous source of noise pollution in urban America. Currently, barrier walls and earthen berms are the primary noise mitigation strategies, cutting the sound that reaches nearby homes by 10–15 dBA. However, these structures are expensive to build (often $1–2 million per mile) and to maintain (graffiti is a major problem). In addition, because sound waves have a tendency to bend over and around objects and to spread out with distance, barrier walls are only effective in reducing sound at distances of less than 400 meters from the roadway.
One of the more promising approaches to reducing road noise involves the use of rubberized asphalt pavement. In the late 1990s, the state of Arizona resurfaced a portion of Interstate 17 through central Phoenix using an asphalt rubber friction course (ARFC) overlay. Though the Arizona Department of Transportation (ADOT) had used this mix simply to extend the life of the concrete base, the public was more enthusiastic about how quiet it made the road.
Studies in Europe and Arizona have shown that resurfacing with ARFC can achieve noise level reductions of 3–5 dBA when compared to traditional asphalt dense-graded surfaces, and 6–12 dBA compared to concrete surfaces. As a tire passes over pavement, it causes a change in air pressure between the tire and the pavement, which generates sound. ARFC has many air pockets that dampen the air pressure gradient and thus reduce sound. In addition, the ARFC surface provides a smoother ride than concrete because it is laid in a continuous manner with minimal joints and a smaller aggregate (rock) mixed in.
In 2002, the Maricopa (Arizona) Association of Governments, the Phoenix area Metropolitan Planning Organization, and ADOT launched the $34 million Quiet Pavement Pilot Program, which so far has resurfaced more than 100 miles of highway with ARFC, says ADOT communications specialist Allison Saxe. ADOT is working with the Federal Highway Administration to collect sound measurements before and after the resurfacing to determine ARFC’s noise-reducing properties over time. So far the new pavement has yielded an average reduction of 4 dBA. Currently, the use of alternative pavement surfaces to achieve noise reduction is not eligible for federal funds unless the state can provide data proving the noise-reduction properties of the material and makes a commitment to repave or erect sound barriers if noise reduction diminishes over time.
Constructing Quieter Buildings
Manufacturers of building components are also making exciting advances in the field of noise reduction. Traditionally, architects and builders have used two methods to reduce sound transmission through walls, floors, and ceilings. The first is to install materials with air pockets (e.g., insulation) that trap sound waves; the second is to increase wall thickness. These approaches may work for new construction, but they are difficult and costly to implement in existing buildings, where walls must be gutted and rebuilt. Recently, Quiet Solution, a California-based manufacturer of soundproofing materials, introduced a product line that can easily be added to new or existing walls to achieve remarkable reductions in sound transmission.
Quiet Solution’s breakthrough product line of drywalls, caulks, tiles, and other materials employs a viscoelastic polymer that converts sound waves to harmless heat. The polymer kills vibration and is more effective with successive layers applied. The ability of building materials to reduce sound transmission is typically classified according to “sound transmission class,” or STC. Typical interior wall construction using wood studs sheathed in drywall has an STC rating of 30–34. By adding a 5/8”-thick sheet of Quiet Solution drywall to both sides of an existing wall, the STC rating jumps to 56, which translates into an 86% perceived sound reduction. In new construction, it is possible to obtain an STC rating of 70 using two layers of wood studs and a layer of Quiet Solution drywall on each side.
Marc Porat, chairman and founder of Quiet Solution, explains what this might mean in today’s home environment. “A typical home theater produces sounds as loud as a hundred decibels. A room built with standard-construction walls adjacent to the home theater would have sound levels of about seventy decibels, which is far too loud for conversation. However, with a wall built to an STC of sixty, the adjacent room would have sound levels of forty decibels, about as quiet as a library.”
Active Noise Control
Another noise reduction technology that is making significant inroads in certain sectors employs the concept of “active noise control” (ANC). In its simplest form, ANC involves producing a sound field that is the mirror image of the offending sound. In essence, active noise cancels out the disturbance, with the net result that the sound is significantly reduced. A sensor such as a microphone, accelerometer, or other device picks up the annoying sound and relays the signal to an electronic controller, which drives an actuator (an electromagnetic speaker or vibration generator) to generate the opposing sound.
ANC works best for controlling narrow-bandwidth, low-frequency sounds, such as air traveling through a duct. The technology is enjoying widespread use in the industrial sector for silencing the noise of large industrial fans, compressors, and generators.
“There are half a dozen companies around the world installing active noise control technologies in industry,” says Rich Silcox, assistant head of NASA’s Structural Acoustics Branch at Langley Research Center. “Most of these devices have to be tailored to specific applications. There are not a lot of off-the-shelf products.”
One consumer product that does employ ANC is headphones available through specialty mail-order catalogues and retailers such as Brookstone and Bose. ANC headphones typically cost several hundred dollars. They are used extensively by pilots and airport workers, but are becoming increasingly popular with the public to ensure quiet airplane rides and work environments.
A related approach to noise control is called active structural–acoustic control (ASAC). In this system, the actuators are vibration sources such as shakers or piezoceramic patches, which use an electric current to introduce an additional vibration that is out of phase with the vibration of the surface they are attached to. These actuators can modify how a structure vibrates, thereby altering the way it radiates sound. This type of system is used in helicopters, for example, to counter noise generated by the rotor and gear box. Some turboprop aircraft employ a combination of ANC and ASAC devices to counter the sound and vibration generated by the propellers.
Mowing Down Noise
One of the most pervasive sources of noise pollution in suburban neighborhoods is lawn equipment. The Noise Pollution Clearinghouse (NPC), a nonprofit agency providing access to a variety of materials on controlling noise pollution, has chosen lawn equipment as one of its primary focuses.
“The average life of the lawn mowers and weed trimmers in the United States today is about seven years,” says NPC executive director Les Blomberg. “By 2011 most of today’s stock will be in the recycle heap. There is a tremendous opportunity to reshape our neighborhood soundscapes by reshaping the lawn and garden marketplace.”
According to data provided by the NPC’s annual “Quiet Lawns” report, which rates various brands of lawn mowers on noisiness, a typical two-stroke gas-powered lawn mower subjects the operator to 85–90 dBA and should be operated only while wearing hearing protection. The latest (2004 model year) gas mowers employ four-stroke engines producing as little as 82 dBA. Electric-powered lawn mowers are quieter still, with the best model emitting only 68 dBA and not requiring the use of hearing protection. For small, evenly contoured lawns, consumers may want to purchase an old-fashioned reel lawn mower, used by golf courses because of their better cut. Some models produce as little as 63 dBA.
The NPC will be adding ratings for weed trimmers and chain saws to its annual report. “Our motto is ‘good neighbors keep their noise to themselves,’” Blomberg says.
Seeking Silence
As awareness is raised about the effects of noise on human health and well-being, public demand for controlling that noise will increase. In the not-too-distant future, technologies for developing machines that generate excessive sound may also incorporate the technology to suppress it. For societies seeking to cope with sensory overload, devices and innovations to reduce the sounds of modern life—and thus noise pollution—are good news indeed.
Just plane brilliant? Chevron nozzles (above) reduce the sound of exiting jet engine exhaust.
Asphalt for a better sleep. Rubber-augmented pavement cuts down on road noise in Phoenix, Arizona.
Caulk for quieter walls. New drywall and caulk are engineered to muffle building noise.
Sounding out quiet. New head phones use active noise control to counter unwanted sounds.
Cutting with cords. Electric lawn mowers can produce sound levels as low as 68 dBA.
==== Refs
Suggested Reading
Cowan J 1994. The Handbook of Environmental Acoustics. New York, NY: John Wiley & Sons.
Federal Highway Administration 1992. Highway Traffic Noise. Washington, D.C.: Federal Highway Administration, U.S. Department of Transportation. Available: http://www.fhwa.dot.gov/environment/htnoise.htm [accessed 6 December 2004].
Miyara F 1997. Guidelines for an Urban Noise Ordinance. Rosario, Argentina: Acoustics and Electroacoustics Laboratory, Universidad Nacional de Rosario. Available: http://www.nonoise.org/resource/activist/ord/ordguide.htm [accessed 6 December 2004].
Noise Pollution Clearinghouse Quiet lawns: creating the “perfect” landscape without polluting the soundscape. In: The Quiet Zone. Summer 2004:1–6. Available: http://www.nonoise.org/library/qz6/qz_summer2004.pdf [accessed 6 December 2004].
Shafer RM 1998. The Book of Noise. Indian River, Ontario: Arcana Editions.
|
15631960
|
PMC1253731
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A46-A49
|
utf-8
|
Environ Health Perspect
| 2,005 |
10.1289/ehp.113-a46
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a00051EnvironewsScience SelectionsAsbestos and Autoimmunity: More Bad News from Libby? Renner Rebecca 1 2005 113 1 A51 A51 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Autoimmune diseases such as rheumatoid arthritis, multiple sclerosis, and systemic lupus erythematosus seem to be the product of a complex and poorly understood interaction between environmental exposures and genetic predisposition. Autoantibodies may be markers of subclinical disease, so epidemiological studies that look for autoantibodies in populations exposed to likely environmental triggers offer one possible way to better understand this gene–environment interaction. To study whether asbestos could be such an environmental trigger, Jean Pfau and colleagues at the University of Montana in Missoula went to the nearby town of Libby, where they found evidence that asbestos exposure may indeed induce autoimmunity [EHP 113:25–30].
Asbestos exposure in Libby stems from the mining of vermiculite, which is used for insulation and fireproofing. The vermiculite, mined extensively from the 1920s to 1990, was laced with toxic amphibole asbestos, and the mining operations released asbestos into the air and contaminated the mine, processing sites, and many of the buildings and properties in town. Homes also became polluted through the use of vermiculite for insulation and garden fill, according to U.S. Environmental Protection Agency investigations. Virtually the entire town was designated a Super-fund National Priorities List site in October 2002.
The decades of occupational and environmental exposure to amphibole asbestos in Libby have been linked to a high incidence of asbestos-related diseases including fibrosis, pleural plaques, and cancer. Anecdotal evidence suggests there may also be a link in Libby between asbestos exposure and autoimmunity. In a 2000–2001 screening of 7,307 Libby area residents by the Agency for Toxic Substances and Disease Registry, 6.7% reported having been diagnosed with an autoimmune disease. Pfau and colleagues note that figure typically should be less than 1%.
In the current study, the researchers sampled the blood of 50 middle-aged men and women from Libby and 50 matched controls from Missoula, where there is no known asbestos exposure. The samples were analyzed for antinuclear antibodies (ANAs) using a commercially available indirect immunofluorescence test. ANAs are a class of autoantibody often found in the blood of people whose immune systems may be predisposed to cause inflammation against their own body tissues. The researchers also looked for correlations between length of asbestos exposure, presence of asbestos-related disease, and ANA levels among the Libby subjects.
They found that ANAs occurred 28.6% more frequently in the Libby samples than in those from Missoula. This finding is consistent with the results of a limited number of other studies of populations exposed to asbestos. In addition, individuals who had been exposed to asbestos for more than five years tended to have higher concentrations of ANAs than those with less exposure. Of the people from Libby, 12 had no lung abnormalities, but the rest had asbestos-related lung problems; those with more severe lung problems also had higher concentrations of autoantibodies.
Based on the correlation between asbestos-related disease and ANA levels, the results suggest that asbestos is an agent of systemic autoimmunity and that autoimmune responses may play a role in the progression of asbestos-related diseases, according to the authors. Pfau and colleagues intend to continue their studies of actual autoimmune diseases among the Libby population.
Libby, Libby, Libby. The saga continues for the residents of Libby, Montana, as new research suggests that amphibole asbestos exposure may induce autoimmunity.
|
0
|
PMC1253732
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A51
|
utf-8
|
Environ Health Perspect
| 2,005 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a00053AnnouncementsNIEHS Extramural UpdateAsthma and Air Pollution: What’s Happening in NIEHS Extramural Research Tinkle Sally S. [email protected] 2005 113 1 A53 A53 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Asthma is a chronic inflammatory disease with symptoms including reversible airway constriction, chest tightness, cough, and wheezing. The incidence of asthma is increasing and accounts for nearly 500,000 hospitalizations, 2 million emergency department visits, and 5,000 deaths annually in the United States. Asthma develops most commonly in children, although recent data suggest an increase in new cases among adults and the elderly.
An individual’s risk for developing asthma is defined by a complex interaction of environmental exposures and hereditary factors. Risk factors include atopy or a predisposition to a Th2 immune response, diminished childhood microbe exposure, age at time of critical exposure, obesity, urbanization, and low socioeconomic status. In addition, numerous epidemiological studies have linked air pollution to exacerbation of acute asthma, increased use of asthma medication, increased school and work absence, and increased hospitalization. The NIEHS, recognizing these links and the persistence and continuing increase in air pollution globally, supports numerous research investigations that may provide keys to improved prevention and clinical management of asthma.
Toxicological research has characterized several components of air pollution, including particulate matter (PM), gaseous elements such as ozone, microbial products including endotoxin, heavy metals, and indoor and outdoor allergens such as house dust mite allergen and ragweed. Current NIEHS-sponsored extramural research targets pulmonary injury and dysfunction consequent to these exposures.
For example, researchers are examining the cellular and molecular pathways involved in oxidative stress induced by organic and metal-containing PM. Oxidative stress is a component of the inflammatory response and of airway hyperreactivity and asthma exacerbation. Other investigators are determining the cellular mechanisms though which diesel exhaust particles act as an adjuvant for common environmental allergens and contribute to the increased incidence of allergies and allergic asthma. Several laboratories are exploring outcomes of ozone exposure including neutrophilic inflammation, cytokine production, and impaired pulmonary function, while others are testing the impact of perinatal ozone exposure, in combination with house dust mite exposure, on lung maturation and childhood asthma.
Genetics research focuses on candidate genes whose expression is altered by environmental exposures that contribute to asthma development. Current studies are investigating known polymorphisms in the pulmonary surfactant proteins important to host defense and in the Th2 cytokines, such as IL-13, that drive the asthma response. Genomics studies are also in progress to identify new asthma susceptibility genes and polymorphic markers of disease.
On 18–19 October 2004, the NIEHS and the U.S. Environmental Protection Agency cosponsored the workshop Environmental Influences on the Induction and Incidence of Asthma. Participants reviewed the current scientific evidence on factors that contribute to the induction and increased incidence of asthma, and small interdisciplinary discussion groups identified research questions critical to improved understanding of the induction of asthma and clinical management. The workshop’s conclusions highlighted the need to identify the critical windows of perinatal lung development and to understand how environmental exposures during these developmental windows leads to asthma. [For more on this workshop, see “Environmental Roots of Asthma,” p. A32–A33 this issue.]
|
0
|
PMC1253733
|
CC0
|
2021-01-04 23:40:53
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A53
|
utf-8
|
Environ Health Perspect
| 2,005 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a00054AnnouncementsFellowships, Grants, & AwardsFellowships, Grants, & Awards 1 2005 113 1 A54 A55 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Metals in Medicine
The objective of this program announcement (PA) is to encourage research that bridges the areas of inorganic chemistry and medicine in continuation of PA-01-071. The National Institute of General Medical Science (NIGMS) is joined in this announcement by the NIEHS and the NIH Office of Dietary Supplements (ODS).
The mechanisms by which organisms control transition metal ions and the roles of these metals in cellular regulation and signaling in health and disease are of principal interest. The interactions of synthetic inorganic complexes with living systems and their components are an additional area of interest. These areas are linked by the need to involve researchers having a deep understanding of inorganic chemistry in medically relevant research. Much of the work is expected to involve collaborations including chemists, biologists, and medical researchers. The results will be relevant to understanding the mechanisms of metal handling by biological systems and the basic cellular roles underlying the nutritional requirement for essential metals. It is expected that this research will also contribute to the identification of new targets for drug discovery, diagnostics, and future therapeutic approaches involving metal complexes, although drug development, per se, is not a focus of the program.
A higher-order problem presents itself in understanding how the genome-encoded components and the other molecules are constituted in networks of interacting molecules with particular distributions in time and space. Advances in imaging techniques and analytic methods are beginning to yield copious quantitative and spatial data on specific molecules in biological systems. Knowledge of the network and changes in its components over time, and the local rules by which the individual components distribute material and information, will substantially advance our knowledge.
Studies of metalloenzyme structure and function, mechanisms of action, and inhibition are currently well supported and produce results that are utilized in the design of new diagnostic and therapeutic products. Additional stimulation of this area is not needed. In contrast, work in other areas of bioinorganic chemistry lags behind its potential application to human health. These areas include 1) mechanisms of metal metabolism as well as the roles of metals in regulation of cell function and cell–cell interaction, and 2) basic research toward diagnostic and therapeutic applications of metal complexes and of metal chelators and toward exploiting the unique properties of metals for therapeutic applications. The emphasis of this announcement is on the ions, complexes, and organometallic compounds of the transition metals known as lanthanides and actinides, post-transition metals, and metalloid elements.
Metal Metabolism and Regulation.
Metal metabolism is emerging as an exciting area of cell biology and a potential area for therapeutic intervention. Normal metal metabolism appears to maintain free metal ion concentrations at a very low level and to deliver metals very selectively to their sites of action, while maintaining tight control over their reactivity. Aberrant metal metabolism contributes to pathological conditions such as Menkes’ disease, Wilson’s disease, and hemochromatosis. Intercepting normal metalation reactions may be a way to control metalloprotein activity. Metals may also be associated with the pathology of protein aggregates such as those formed by prions and in Alzheimer’s disease. Metals have also emerged as important sensors and transducers of information with roles in regulation and neurotransmission.
Areas of interest include 1) improved metal ion sensors to study cellular metal ion concentrations and localization; 2) reagents suitable to manipulate those concentrations; 3) identification and characterization of the macromolecular players and vesicular compartments involved in metal ion homeostasis and metal trafficking; 4) elucidation of the roles of metals in cell regulation, signal transduction, and cell–cell signaling; 5) identification and understanding of mRNAs and metal-, oxygen-, and redox-responsive transcriptional and translational regulators, and their potential as therapeutic targets; 6) elucidation of the mechanistic roles of essential trace elements for which metabolic functions are not yet clearly established; 7) analytical tools that accurately monitor biologically important pools, storage pools, and the chemical speciation of metals; 8) biomarkers of exposure and mechanisms of metal toxicity; 9) biomarkers for variable susceptibility to metal toxicity in the human population; and 10) chelation chemistry that can serve as the foundation for therapies to ameliorate aberrant metal accumulations and the effects of toxic exposures.
Interactions of Metal Complexes with Living Systems.
The therapeutic application of metal complexes is an underdeveloped area of research. Basic principles to guide the development of metallopharmaceuticals are lacking. Metal-containing agents may offer unique therapeutic opportunities. However, significant obstacles, including potential metal accumulations and toxicities, require further research before the promise of medicinal inorganic chemistry can be realized.
Metal complexes may be useful as research probes of biological function, as intermediary lead compounds in the development of non–metal-containing therapeutics, and as potential diagnostic and therapeutic agents. Opportunities exist to exploit the unique properties of metal complexes, (e.g., hydrolytic and redox activity, Lewis acidity, electrophilicity, valency, geometry, magnetic, spectroscopic, radiochemical properties) to measure and/or alter cellular functions. The actions of these compounds may provide insights that are different from those that can be achieved through other chemical, biochemical, or genetic manipulations. Similarly, the actions of metal complexes in whole living organisms are expected to differ in general from the actions of non–metal-containing agents and may offer unique research, diagnostic, or therapeutic opportunities. Principles are needed for the design of safe metal-containing therapeutics.
Another goal of this program is to utilize the power of inorganic chemistry to provide new knowledge of and new approaches for intervention in biological systems. Still another goal is to improve understanding of the reactions of metal complexes in living systems to improve the specificity of these interactions and gain control over the potential toxicity of synthetic metal complexes. The long-term goal is to establish the basic principles of an inorganic medicinal chemistry that will allow for rational design and screening of potential metallopharmaceuticals in the future.
Areas of interest include 1) reactions of metal complexes with cellular constituents (e.g., DNA, RNA, proteins, lipids, carbohydrates, redox substrates, signaling molecules); 2) reactions of metal complexes within the cellular milieu and in vivo; 3) uptake of metal complexes into cells and delivery to specific cellular compartments; 4) interactions of metal complexes with specific enzymes and receptors; 5) mechanisms by which synthetic metal complexes recruit cell cycle, signal transduction, and other metabolic pathways to alter cell functions; and 6) structure–activity relationships for ligand design to control metal complex activity and stability in vitro and in vivo.
The NIH Metals in Medicine meeting report includes a list of specific research opportunities and challenges. This list is intended to be illustrative, not exhaustive. Investigator-initiated ideas are welcome on any subject that will contribute to the objectives listed in this PA.
Research encouraged by this announcement may utilize any appropriate experimental organisms or model systems. For some problems, interesting discoveries may be found in microorganisms from unusual environments and atypical experimental organisms. For other problems, yeast, common invertebrate and vertebrate model organisms, and human cell/tissue cultures may be appropriate. Investigators considering human clinical trials are strongly encouraged to contact the program staff.
This funding opportunity will use the regular research (R01), exploratory research (R21), and program project (P01) award mechanisms. For a description of the R21 grant mechanism see http://grants.nih.gov/grants/funding/r21.htm. For descriptions of the P01 grant mechanism see http://www.nigms.nih.gov/funding/grntmech.html#b (NIGMS) and http://www.niehs.nih.gov/dert/programs/p01.htm (NIEHS).
This funding opportunity uses just-in-time concepts. It also uses the modular as well as the nonmodular budget formats (see http://grants.nih.gov/grants/funding/modular/modular.htm). Specifically, if you are submitting an application with direct costs in each year of $250,000 or less, use the modular budget format described in the PHS 398 application instructions, available at http://grants1.nih.gov/grants/funding/phs398/phs398.html in an interactive format. Otherwise, follow the instructions for nonmodular research grant applications. For further assistance, contact GrantsInfo at 301-435-0714 (telecommunications for the hearing impaired: TTY 301-451-0088) or by e-mail: [email protected].
Applications must be prepared using the PHS 398 application instructions and forms (rev. 5/2001). Applications must have a Dun & Bradstreet (D&B) Data Universal Numbering System number as the universal identifier when applying for federal grants or cooperative agreements. This number can be obtained by calling 1-866-705-5711 or online at http://www.dnb.com/us/. The D&B number should be entered on line 11 of the face page of the PHS 398 form. Applications must be submitted on or before the receipt date described at http://grants.nih.gov/grants/funding/submissionschedule.htm. The complete version of this PA is available at http://grants.nih.gov/grants/guide/pa-files/PA-05-001.html.
Contact: Peter C. Preusch, Division of Pharmacology, Physiology, and Biological Chemistry, NIGMS, Bldg 45, Rm 2AS.43C, MSC 6200, Bethesda, MD 20892-6200 USA, 301-594-5938, fax: 301-480-2802, e-mail: [email protected]; Claudia Thompson, NIEHS, DERT/OPD/CEMBB, MD EC-21, PO Box 12233, Research Triangle Park, NC 27709 USA, 919-541-4638, fax: 919-541-4606, e-mail: [email protected]; Becky Costello, ODS, NIH, Bldg 31, Rm 1B25, MSC 2086, Bethesda, MD 20892-2086 USA, 301-435-2920, fax: 301-480-1845, e-mail: [email protected]. Reference: PA No. PA-05-001
NIGMS National Centers for Systems Biology
The National Institute of General Medical Sciences (NIGMS) currently supports the analysis of complex biological systems through investigator-initiated research project grants. The resources needed to conduct the multifaceted, multidisciplinary projects that may be required to achieve significant advances in these complex areas may be beyond the scope of the typical R01 or P01 grant. Therefore, this request for applications (RFA) presents an opportunity for applicants to assemble large teams of investigators from diverse disciplines that may not be possible with other funding mechanisms.
The biomedical sciences have undergone a fundamental shift in the conceptual and technical approaches that can be applied to certain problems of profound importance. These problems center on understanding the behavior of biological systems whose function is the product of spatial and temporal ordering of myriad interacting components. Modeling approaches are being used to understand the orderly development of biological pattern in organisms such as Drosophila and Caenorhabditis elegans, and at the clinical level, new approaches are being explored to understand the integrated activity of tissues and organs.
Part of the impetus for systems-scale approaches rests on advances in acquiring data of the necessary quality and quantity to permit computational modeling. Among the most striking examples are the availability of complete DNA sequences for hundreds of organisms, including humans, and the availability of high-throughput instrumentation for analyses of gene function such as gene expression microarrays and proteomics technologies. These advances have made it feasible to generate a truly comprehensive parts list for any organism and to track changes over time. Ultimately, it should be possible to enumerate all the informational units of the genomes (protein coding genes, non–protein coding genes, regulatory regions), their processed forms, and their dynamic presence in cells.
Rapid advances in large-scale data collection and analysis have given scientists a global yet detailed view of cellular processes, instead of focusing on individual molecules or a small number of interacting molecules. Unprecedented opportunities have emerged that may open the door to uncover hidden rules governing the ensemble of biomolecules working concertedly to perform certain functions in the cell. In the meantime, substantial challenges in information integration, interpretation, and representation have arisen. In order to move beyond the phase of cataloguing the parts list and truly transform data into knowledge, and knowledge into principles, iterative cycles of data collection and model generation and validation will be necessary.
A higher-order problem presents itself in understanding how the genome-encoded components and the other molecules (metabolites, ions, water, etc.) are constituted in networks of interacting molecules with particular distributions in time and space. Advances in imaging techniques and analytic methods are beginning to yield copious quantitative and spatial data on specific molecules in biological systems. Knowledge of the network and changes in its components over time, and the local rules by which the individual components distribute material and information, will substantially advance our knowledge.
At the organism level, phenotype must take into account the relationships and interactions of biological and environmental variables. Basic biological systems—including gene sequences, structures, and pathways that direct metabolism and development—vary within individuals, among individuals, among populations, and among species. Advances in complex systems-level understanding must ultimately include models that account for these variations.
Medical, biotechnological, and other uses of biological information increasingly depend on our ability to understand the principles and dynamics that explain the behavior of the system as a whole. Whether the goal is to understand the consequences of disease or injury, identify particular molecular targets for drug interventions, or modify the metabolism of microorganisms to produce medicines, the challenge is predictability. Predicting how the system of interest will respond to an intervention is a computational problem. For biological systems, this challenge is daunting.
Parallel to scientific challenges are organizational and educational challenges. At the institutional level, building cohesive multidisciplinary research teams by integrating expertise across traditional disciplinary boundaries is not a simple undertaking. Beyond institutions, excessive overlap and redundancy in project selection and tool development exists in the research communities that could be reduced by promoting communications, collaborations, and technology and data sharing. The emergence of new science demands an adequate workforce of new scientists. Training for the future leaders of systems biology research who are knowledgeable and skilled in both experimental and computational subjects is timely. Good mechanisms and plans to address these challenges are significant tasks of the centers.
High priority will be given to projects that integrate multi-investigator, multidisciplinary approaches with a high degree of interplay between computational and experimental approaches. Innovation is critical for both research project design and infrastructure design with a mission of serving communities beyond the participating investigators, institutions, and collaborators. A variety of organizational models are possible; it is not the intent of this RFA to prescribe any particular one.
The NIGMS awarded two centers under this program in 2002 (http://www.nigms.nih.gov/news/releases/complex_centers.html), two centers in 2003 (http://www.nigms.nih.gov/news/releases/complex_centers-2003.html), and one center in 2004 (http://www.nigms.nih.gov/news/releases/quantitative_bio_center.html). Potential applicants should become familiar with the research focuses of the existing centers. Research conducted by the future centers should complement and enhance projects already funded.
Some groups interested in the subject of this RFA might find the P01 mechanism more suited to the scale of their efforts; they should consult the prior announcement at http://grants.nih.gov/grants/guide/pa-files/PA-98-077.html.
The NIGMS intends to support systems biology research for the areas that are central to its mission of supporting basic biomedical research, and that focus on developing new computational approaches to biomedical complexity. Research areas that historically have been computationally based (e.g., molecular structure and modeling) are excluded as a focus of this center program. Research focusing on disease processes and their specific organ systems is not eligible. NIGMS mission areas include, but are not limited to, the following: 1) signaling networks and the regulatory dynamics of cellular processes such as cell cycle control, transient complex formation, organelle biogenesis, and intercellular communications; 2) supramolecular machines, such as the replisome, spliceosome, and molecular motor assemblies in cell division and motility; 3) pattern formation and developmental processes in model systems (e.g., Drosophila, C. elegans, etc.); 4) metabolic networks and the control of the flux of substrates, intermediates, and products in cell physiology; 5) organ system networks involved in multiorgan failure in shock, trauma, and burn injury; and 6) genetic architecture of biological complexity related to inherited variation and environmental fluctuations.
The NIGMS National Centers for Systems Biology will be expected to provide national leadership in systems biology research and training. To do so, they will be expected to support training and outreach activities that will ensure the flow of information and expertise both into and out of the centers. Centers should have plans to bring the most advanced technologies developed at other laboratories to the centers and to disseminate expertise and knowledge to a wider community through collaborations, visiting investigatorships, fellowships, center websites, workshops, symposia, summer courses/internships, and/or other means. To maximize the impact, centers should conduct training at multiple levels appropriate to their institutions. Incorporation of developmental research projects led by junior and new investigators into the center research and development plans is strongly encouraged. Over a period of time, centers should evolve into integrated research, training, and knowledge exchange headquarters of scientific communities that will be the engines for coordinated scientific discoveries. The centers should also have plans for outreach to undergraduate institutions, including minority-serving institutions. Information on relevant minority-serving institutions may be obtained by consultation with staff of the NIGMS Division of Minority Opportunities in Research (http://www.nigms.nih.gov/about_nigms/more.html).
In addition to research and training contributions, successful centers will provide their home institutions with the means to implement organizational and professional changes that will make systems biology research an attractive career option for both established and entry-level investigators.
This funding opportunity will use the NIH P50 Research Center Grant award mechanism. As an applicant, you will be solely responsible for planning, directing, and executing the proposed project. This RFA is a one-time solicitation and may be reannounced in the future. The earliest expected award date is in December 2005. Applications that were submitted in response to previous RFAs of this program but unfunded may be revised and resubmitted for this RFA.
The NIGMS intends to commit up to $7 million in fiscal year 2006 to fund one to three new P50 center grants in response to this RFA. An applicant may request a project period of up to five years and a budget for direct costs of up to $2 million per year, exclusive of subproject fiscal and administrative costs (see http://grants.nih.gov/grants/guide/notice-files/NOT-OD-04-040.html).
The PHS 398 application instructions are available at http://grants.nih.gov/grants/funding/phs398/phs398.html in an interactive format. For further assistance, contact GrantsInfo by calling 301-435-0714 or e-mailing [email protected].
Applications must be prepared using the PHS 398 application instructions and forms (rev. 5/2001). Applications must have a Dun & Bradstreet (D&B) Data Universal Numbering System number as the universal identifier when applying for federal grants or cooperative agreements. This number can be obtained by calling 1-866-705-5711 or online at http://www.dnb.com/us/. The D&B number should be entered on line 11 of the face page of the PHS 398 form.
Letters of intent must be received by 25 January 2005, with 25 February 2005 the deadline for applications. The complete version of this announcement is available online at http://grants.nih.gov/grants/guide/rfa-files/RFA-GM-05-010.html#PartI.
Contact: James J. Anderson, Center for Bioinformatics and Computational Biology, NIGMS, 45 Center Dr, Rm 2As.25A, MSC 6200, Bethesda, MD 20892-6200 USA, 301-594-0943, fax: 301-480-2228, e-mail: [email protected]; Jiayin (Jerry) Li, Center for Bioinformatics and Computational Biology, NIGMS, 45 Center Dr, Rm 2As.19F, MSC 6200, Bethesda, MD 20892-6200 USA, 301-594-0682, fax: 301-480-2004, e-mail: [email protected]. Reference: RFA No. RFA-GM-03-009
|
0
|
PMC1253734
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A54-A55
|
utf-8
|
Environ Health Perspect
| 2,005 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0016a15631953PerspectivesCorrespondenceComments on “Recent Developments in Low-Level Lead Exposure and Intellectual Impairment in Children” Jusko Todd A. Department of Epidemiology, University of Washington, Seattle, Washington, E-mail:
[email protected] Richard L. Division of Nutritional Sciences, Cornell University, Ithaca, New YorkHenderson Charles R. Jr.Department of Human Development Cornell University, Ithaca, New YorkLanphear Bruce P. Cincinnati Children’s Hospital, Medical Center, Cincinnati, OhioBruce P. Lanphear has acted as an expert witness for several plaintiffs in lead cases, but he has not received financial remuneration; instead, any payment has been donated directly to the Cincinnati Children’s Hospital Medical Center. The other authors declare they have no competing financial interests.
1 2005 113 1 A16 A16 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
We commend Koller et al. (2004) for their thoughtful and detailed review of recent research on childhood lead exposure and intellectual development, and we take this opportunity to clarify and respond to several of their questions regarding our study of children with blood lead concentrations <10 μg/dL) (Canfield et al. 2003).
The children in our cohort were recruited between 24 and 30 months of age, and all had participated in a prior randomized dust control trial (Lanphear et al. 1999). In that trial, dust and blood lead concentrations were assessed at 6, 12, 18, and 24 months of age as part of an evaluation of whether dust control measures reduced children’s blood lead concentrations. Koller et al. (2004) raised several questions related to whether children’s participation in the prior study affected the results we reported (Canfield et al. 2003). Specifically, their concerns related to confounding, where an imbalance in the distribution of intervention/control participants across levels of blood lead and IQ could bias the association between blood lead concentrations and IQ.
Our statistical model was developed a priori and included covariates that were established predictors of children’s intelligence (Canfield et al. 2003). Because home visitation by a dust control team (intervention) seemed unlikely to increase children’s IQ and because children who participated in the intervention actually had slightly lower IQ scores at 3 and 5 years of age compared with controls, intervention status was not considered a plausible confounder. To demonstrate that participation in the dust control trial did not introduce any bias of consequence and to illustrate our basis for excluding intervention status from our published models, in this letter we summarize results for a semiparametric spline model, which is identical to the one we reported previously (Canfield et al. 2003) except for the inclusion of intervention status as a potential confounding factor. The estimated decline in IQ as blood lead concentration increases from 1 to 10 μg/dL is 6.8 points when controlling for intervention status. This estimate is not meaningfully different from the 7.4-point decline we reported previously (Canfield et al. 2003). Furthermore, the shape of the dose–response function is preserved, with a steeper slope at lower blood lead concentrations. Estimates of the predicted decline in IQ from parametric models with linear and quadratic terms for blood lead also differ by < 10% from the reported results (Canfield et al. 2003) when intervention status is included in the model.
Additionally, Koller et al. (2004) suggested that the Stanford-Binet IV Test of Intelligence (SBIV) may not have provided the most accurate estimate of IQ for our cohort because of the relative weighting of verbal and nonverbal skills that are assessed and because of problems with the standard method of dealing with zero-scored subtests. Koller et al. (2004) suggested that the Wechsler Primary and Preschool Scales of Intelligence (WPPSI) would have yielded a more reliable and valid measure of intelligence. We first note that despite many attractive features of the WPPSI (and especially of the WPPSI-Revised, which we considered using), the SBIV has features that we believe made it a superior test for our particular cohort. Most importantly, the SBIV can be administered to 2-year-olds, whereas the youngest age for the WPPSI-R is 3 years. Because our sample was predominantly composed of families with lower parental education and income, we preferred the test with the lower floor.
With respect to how zero-scored subtests are handled, we indeed followed the standard scoring procedure for the SBIV, which states that a zero score “should not be included in the determination of the related Area Score or of the Composite Score” (Delaney and Hopkins 1987). Because this scoring method was used in the standardization of the instrument, a different approach would yield scores with unknown psycho-metric properties and thereby compromise interpretation of the results.
Nevertheless, any particular scoring method has its weaknesses, and we agree that it would be useful to know whether our results change markedly by incorporating information about zero scores. We therefore added as a time-varying covariate in our mixed models the number of subtests on which each child scored zero. In the semi-parametric spline model, the estimated decline in IQ as blood lead concentration increased from 1 to 10 μg/dL was 6.3 points. Estimates from parametric models with linear and quadratic terms for blood lead differed by < 5% from the results we reported previously (Canfield et al. 2003). Thus, the incorporation of information about zero-scored subtests did not change our results markedly.
Potential sources of confounding and misclassification need to be carefully considered in the design and analysis phase of any study, observational or otherwise, and in the interpretation of results. The detailed attention given to these issues by Koller et al. (2004) has allowed us the opportunity to provide additional information about our methods and results and thereby address these methodologic issues.
==== Refs
References
Canfield RL Henderson CR Jr Cory-Slechta DA Cox C Jusko TA Lanphear BP 2003 Intellectual impairment in children with blood lead concentrations below 10 microg per deciliter N Engl J Med 348 1517 1526 12700371
Delaney DA Hopkins TF 1987. The Stanford-Binet Intelligence Scale: Fourth Edition Examiner’s Handbook. Chicago:The Riverside Publishing Company.
Koller K Brown T Spurgeon A Levy L 2004 Recent developments in low-level lead exposure and intellectual impairment in children Environ Health Perspect 112 987 994 15198918
Lanphear BP Howard C Eberly S Auinger P Kolassa J Weitzman M 1999 Primary prevention of childhood lead exposure: a randomized trial of dust control Pediatrics 103 772 777 10103301
|
15631953
|
PMC1253735
|
CC0
|
2021-01-04 23:41:49
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A16a
|
utf-8
|
Environ Health Perspect
| 2,005 |
10.1289/ehp.113-1253736
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0016b15631953PerspectivesCorrespondenceLow-Level Lead Exposure and Intellectual Impairment in Children: Koller et al. Respond Koller Karin Levy Len Brown Terry MRC Institute for Environment & Health, University of Leicester, Leicester, United Kingdom, E-mail:
[email protected] Anne Institute of Occupational Health, University of Birmingham, Birmingham, United KingdomThe authors declare they have no competing financial interests.
1 2005 113 1 A16 A17 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
We are grateful to Jusko et al. for addressing two concerns raised in our review (Koller et al. 2004) relating to confounding and their use of the Stanford-Binet test in their original report (Canfield et al. 2003). They provide valuable additional analysis of their data, which further support their original findings.
Of relevance to the area of confounding is a recent publication by Mink et al. (2004) in which the effects of different combinations of confounders on multivariate analyses of neurobehavior and neurotoxic exposure were studied. Taking maternal intelligence, home environment, and socioeconomic status as the three most important confounders in this field, Mink et al. urged caution in associating small differences in IQ score in the range of 3–10 points with the effects of environmental exposure; they also made a strong case for a priori consideration and planning for all potential confounders in epidemiological studies. As Jusko et al. explain, this is indeed the method they used in their original analyses (Canfield et al. 2003).
We feel that the weight of evidence across a number of studies has come down in support of an effect of low-level lead exposure on children’s intellectual and neurobehavioral function; as stressed by Bellinger (2004), this evidence is supported by studies on experimental animals in which confounding is largely irrelevant.
==== Refs
References
Bellinger DC 2004 Assessing environmental neurotoxicant exposures and child neurobehavior: confounded by confounding? Epidemiology 15 383 384 15232396
Canfield RL Henderson CR Jr Cory-Slechta DA Cox C Jusko TA Lanphear BP 2003 Intellectual impairment in children with blood lead concentrations below 10 microg per deciliter N Engl J Med 248 1517 1526 12700371
Koller K Brown T Spurgeon A Levy L 2004 Recent developments in low-level lead exposure and intellectual impairment in children Environ Health Perspect 112 987 994 15198918
Mink PJ Goodman M Barraj LM Imrey H Kelsh MA Yager J 2004 Evaluation of uncontrolled confounding in studies of environmental exposures and neurobehavioral testing in children Epidemiology 15 385 393 15232397
|
0
|
PMC1253736
|
CC0
|
2021-01-04 23:40:55
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A16b-A17
|
utf-8
|
Environ Health Perspect
| 2,005 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0018a15631954PerspectivesCorrespondenceTCDD and Puberty: Warner and Eskenazi Respond Warner Marcella Eskenazi Brenda School of Public Health, University of California-Berkeley, Berkeley, California, E-mail:
[email protected] authors declare they have no competing financial interests.
1 2005 113 1 A18 A18 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
As Wolff et al. note, in data from the Seveso Women’s Health Study (SWHS) we found no change in age of onset of menarche associated with TCDD exposure in all women in the cohort or in women exposed before 8 years of age (Warner et al. 2004). However, Wolff et al. comment that hormonal exposures before 5 years of age might be the more relevant time period, given that the pubertal transition occurs around 5–7 years of age. Recognizing that our data may be limited by small numbers, Wolff et al. are interested in knowing whether risk of earlier (or later) puberty was seen among girls who were exposed before 5 years of age.
Of the 282 women in the SWHS cohort who were premenarcheal at the time of the explosion on 10 July 1976, 84 women were <5 years of age. The mean age of menarche reported for the 84 women was 12.6 ± 1.5 years, and the median lipid-adjusted serum TCDD level was 233 ppt (range, 3.6–56,000 ppt). In Cox proportional hazards models, when log10TCDD was entered as the exposure variable, the hazard ratio associated with a 10-fold increase in TCDD was 1.2 [95% confidence interval, 0.98–1.6; p for trend = 0.07]. That is, the risk of early menarche was increased with the presence of a 10-fold increase in serum TCDD level (e.g., from 10 to 100 ppt), but not significantly. The data were too sparse in the lower exposure groups to perform categorical analyses. The observed increase was limited to the subset of women who were < 5 years of age at exposure, as the effect was diminished when we considered including older ages (< 6 years, < 7 years).
In summary, the sample size is too small to state with certainty, but it seems that the women who received higher exposure and were < 5 years of age at the time of the explosion may have been at somewhat increased risk for earlier menarche. As we stated in our article (Warner et al. 2004), the women in this study experienced significant TCDD exposure during the postnatal but prepubertal developmental period. Given that animal evidence suggests in utero exposure can affect onset of puberty, continued follow-up of the offspring of the SWHS cohort is important.
==== Refs
Reference
Warner M Samuels S Mocarelli P Gerthou PM Needham L Patterson DG Jr 2004 Serum dioxin concentrations and age at menarche Environ Health Perspect 112 1289 1292 15345341
|
0
|
PMC1253737
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A18a
|
utf-8
|
Environ Health Perspect
| 2,005 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0018b15631954PerspectivesErrataErrata 1 2005 113 1 A18 A18 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Because the study “Threshold of Trichloroethylene Contamination in Maternal Drinking Waters Affecting Fetal Heart Development in the Rat” (Johnson et al. 2003) was a long-term and continuous study, the authors compiled the data from controls of several treatment groups. The control “sets” were statistically analyzed comparing the data to each other before being combined. The authors opine that the control values were statistically consistent across and throughout all the treatment groups. Using the control data in a cumulative manner increased the generalizability of the data, which purports to demonstrate the background rate and variability around rate estimates. The larger sample size somewhat increased statistical power without the inappropriate use of further valuable animal resources.
Table 1 presents the date ranges of experimental treatment and the coinciding control treatments. Each treatment exposure had a corresponding control group. Also, because of the more detailed information on competing financial interests now included in EHP’s Instructions to Authors, the authors now report that S.J. Goldberg served as an expert witness for a plaintiff in a judicial hearing in 1997. As previously stated in a prior letter to the editor (Johnson et al. 2004), at all times throughout this research, the authors were free to design, conduct, interpret, and publish the research without compromise by any controlling sponsor as a condition of review or publication.
In “Environmental Health Disparities: A Framework Integrating Psychosocial and Environmental Concepts” by Gee et al. [
Environ Health Perspect 112:1645–1653 (2004)], the title of Figure 1 should be “Stress–exposure disease framework for environmental health disparities.”
Table 1 Control versus TCE treatment groups and dates of exposure.
Control
TCE
Fetuses/mothersa Dates Dose Fetuses/mothers Dates
135/15 14 Jun 1989–10 Oct 1992 1,100 ppm 105/9 29 Jun 1989–12 Mar 1990
155/13 11 Dec 1992–20 Oct 1993a 1.5 ppm 181/13 29 Dec 1989–26 Dec 1990
62/6 15 Apr 1994–23 May 1994a
120/10 6 Jul 1994–7 Jul 1995 2.5 ppb 144/12 6 Jun 1995–13 Jun 1995
134/11 18 Jul 1995–6 Oct 1995 250 ppb 110/9 5 Jul 1995–21 Jul 1995
aThe total number of control rat fetuses/mothers was 606/55.
bOther studies that coincided with these control groups were carried out during December 1989–June 1995 [e.g., metabolites that were reported in other articles (Johnson et al. 1998a, 1998b).
==== Refs
References
Johnson PD Dawson BV Goldberg SJ 1998a Cardiac teratogenicity of trichloroethylene metabolites J Am Coll Cardiol 32 2 540 545 9708489
Johnson PD Dawson BV Goldberg SJ 1998b A review: trichloroethylene metabolites: potential cardiac teratogens Environ Health Perspect 106 suppl 4 995 999 9703484
Johnson PD Dawson BV Goldberg SJ Mays MZ 2004 Trichloroethylene: Johnson et al.’s Response [Letter] Environ Health Perspect 112 A608 A609
Johnson PD Goldberg SJ Mays MZ Dawson BV 2003 Threshold of trichloroethylene contamination in maternal drinking waters affecting fetal heart development in the rat Environ Health Perspect 111 289 292 12611656
|
0
|
PMC1253738
|
CC0
|
2021-01-05 12:09:11
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A18b
|
utf-8
|
Environ Health Perspect
| 2,005 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0018c15631954PerspectivesCorrespondenceComment on “Breast Milk: An Optimal Food” Cattaneo Adriano Unit for Health Services Research and International Health, Child Health Institute, Trieste, Italy, E-mail:
[email protected] Maryse Initiativ Liewensufank, Itzig, Luxemburg, E-mail:
[email protected] authors declare they have no competing financial interests.
Editor’s note: In accordance with journal policy, Pronczuk et al. were asked whether they wanted to respond to this letter, but they chose not to do so.
1 2005 113 1 A18 A19 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
In their editorial “Breast Milk: An Optimal Food,” Pronczuk et al. (2004) stated that “in most cases, mothers can and should be reassured that breast milk is by far the best food to give to their babies,” despite the evidence that “a myriad of potential chemical contaminants … can be detected in breast milk,” mainly because a) levels of environmental contaminants, as determined by subsequent surveys, continue to decrease; b) exposure through breast milk may be less important than exposure in utero; and c) there is little evidence that exposure through breast milk is associated with damage.
We believe that there is probably a fourth good reason in support of their recommendation. There is in fact some evidence that breast-feeding may counteract some of the negative effects of exposure to environmental contaminants in utero.
For example, Boersma and Lanting (2000) showed that at 6 years of age cognitive development is affected by prenatal exposure to polychlorinated biphenyls (PCBs) and dioxins. Breast-fed children, however, when compared to formula-fed children, had an advantage in terms of quality of movements, fluency, and cognitive development tests at 18 and 42 months of age and at 6 years of age, despite a higher PCB exposure from breast milk.
Ribas-Fito et al. (2003), studying a birth cohort of 92 mother–infant pairs highly exposed to organochlorine compounds, found that prenatal exposure was associated with a delay in mental and psychomotor development at 13 months of age and that long-term breast-feeding counterbalanced this damage because it was associated with better performance on both the mental and motor scales compared to short-term or no breast-feeding.
Vreugdenhil et al. (2004) found that children who were breast-fed for at least 16 weeks did not show the delays in development of the central nervous system that are present in children breast-fed for 6–16 weeks or formula-fed, despite a similar prenatal exposure to PCBs.
This evidence is not conclusive (scientific evidence rarely is), but we believe that it should not be omitted in an article on environmental contaminants and breast-feeding.
==== Refs
References
Boersma ER Lanting CI 2000 Environmental exposure to poly-chlorinated biphenyls (PCBs) and dioxins. Consequences for longterm neurological and cognitive development of the child lactation Adv Exp Med Biol 478 271 287 11065080
Pronczuk J Moy G Vallenas C 2004 Breast milk: an optimal food [Editorial] Environ Health Perspect 112 A722 A723 15345351
Ribas-Fito N Cardo E Sala M Eulalia dM Mazon C Verdu A 2003 Breastfeeding, exposure to organochlorine compounds, and neurodevelopment in infants Pediatrics 111 e580 e585 12728113
Vreugdenhil HJ Van Zanten GA Brocaar MP Mulder PG Weisglas-Kuperus N 2004 Prenatal exposure to poly-chlorinated biphenyls and breastfeeding: opposing effects on auditory P300 latencies in 9-year-old Dutch children Dev Med Child Neurol 46 398 405 15174531
|
15631954
|
PMC1253739
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A18c-A19
|
utf-8
|
Environ Health Perspect
| 2,005 |
10.1289/ehp.113-1253739
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0025a15643720EnvironewsForumInnovative Technologies: Reverse Osmosis Moves Forward Potera Carol 1 2005 113 1 A25 A25 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
As drought and growing populations cause water supplies to dwindle in areas around the world, reclaimed wastewater offers a possible solution. Indeed, some communities in California already use reclaimed wastewater to irrigate crops, water golf courses, and augment freshwater aquifers to block saltwater intrusion. Critics are concerned about the potential health hazards of the pharmaceuticals, hormones, and other contaminants that even treated wastewater has been shown to contain. But recent research reveals that the process of reverse osmosis may remove some of these contaminants.
As described in the 12 March 2004 issue of the Journal of Chromatography A, Joel Pedersen, an environmental chemist at the University of Wisconsin–Madison, and his colleagues used gas chromatography–mass spectrometry to look for 19 compounds in effluent samples collected from reclaimed wastewater plants in California. They found detectable concentrations for 13, including food preservatives, painkillers, oral contraceptive hormones, and prescription medications. However, at the 228th American Chemical Society meeting held in Philadelphia in August 2004, Pedersen further reported that gas chromatography confirmed all 13 compounds to have been eliminated at two pilot plants testing reverse osmosis for contaminant removal.
Nonetheless, Pedersen cautions that it’s too early to recommend that all reclaimed wastewater facilities employ reverse osmosis. “This is a case where the analytical chemistry is ahead of the toxicology,” he says.
“Little is known about the toxicity of trace concentrations of these compounds,” agrees Shane Snyder, project manager of research and development at the Southern Nevada Water Authority (SNWA) in Las Vegas. Snyder has monitored the flow of treated wastewater effluent into nearby Lake Mead since 1997. He says fish in Las Vegas Bay are the healthiest in all of Lake Mead because they thrive on nutrients in the effluent. Snyder and colleagues at the U.S. Fish and Wildlife Service are writing a paper on this topic.
Often used to remove salts, reverse osmosis requires electricity to pump water through semipermeable membranes. “A lot of work is involved to perform reverse osmosis correctly,” says Pedersen. “Large-scale reverse osmosis may not be economically feasible in some areas.” Salts, contaminants, and biofilms can clog the pores of membranes, raising maintenance costs.
Still other costs can make the process prohibitively expensive for inland cities in particular. Reverse osmosis generates brine. While coastal California wastewater facilities dump brine into the ocean, inland facilities must heat the brine to evaporate the water, then dispose of the dry salt in a landfill. “The cost of brine disposal is often more expensive than the cost of reverse osmosis itself,” says Snyder. About 30% of treated water ends up as brine during reverse osmosis. That water loss “is not acceptable when you live in the desert,” Snyder says. By comparison, standard treatment results in less than 1% water loss, according Snyder.
Moreover, “reverse osmosis membranes are not infallible,” says Snyder. For instance, the carcinogen N-nitrosodimethylamine, a disinfectant by-product of wastewater treatment, breaches reverse osmosis membranes. However, dangerous compounds may be removed with less expensive treatments than reverse osmosis. For example, advanced oxidation methods can destroy N-nitrosodimethylamine.
But it’s too soon to count reverse osmosis out just yet. Newer models require less pressure to pump water through. “More efficient membranes will lower the energy costs of reverse osmosis,” Snyder predicts, “and likely make the process more cost-effective.”
One step back, two steps forward. New advances in reverse osmosis may mean cleaner—and healthier—reclaimed wastewater.
|
15643720
|
PMC1253740
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A25a
|
utf-8
|
Environ Health Perspect
| 2,005 |
10.1289/ehp.113-a25a
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0025b15643720EnvironewsForumThe Beat Dooley Erin E. 1 2005 113 1 A25 A27 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Smoky Horror Picture Show?
At the American Medical Association’s 2004 annual meeting, the group’s policy-making House of Delegates adopted a resolution urging the film industry to give an “R” rating to movies with scenes of characters smoking. The goal of the resolution is to reduce the amount of smoking seen in movies, and to limit those scenes to movies seen only by adults. Speaking before the assemblage, Stephen Hansen, coordinator of the association’s Tobacco Control Coalition, cited several recent studies showing that the number of smoking scenes onscreen is up from an average of 5 scenes per hour in the 1950s to 11 today. Other studies suggest that film depictions of smoking may correlate with the onset of smoking in youth.
EU Bans Phthalates in Toys
In September 2004 the European Competitiveness Council voted to ban three phthalates from all products intended for children and to prohibit the use of three others specifically in toys and other items intended to be chewed or sucked by very young children. These chemicals, which are used to soften vinyl plastic, have been linked with reproductive and liver effects, and are known to leach from products that contain them. More than 900 tons of phthalates are produced each year.
Once the measure has been adopted formally by the council it will be sent to the European Parliament for a second reading. The European Commission will be charged with overseeing the implementation of the ban.
Roaming Foam May Find a Home
The polystyrene foam that helps boat docks stay afloat can break off in large chunks, littering the lakescape and posing a boating hazard. Foam is traditionally very hard to recycle because it is wet and oily, and often contains metal screws and other items that can damage recycling machines. Now the Missouri-based company BioSpan Technologies has developed a solvent that dissolves the wet, dirty chunks at a ratio of more than 3 cubic yards of foam per gallon of solvent. The dissolved blend is then mixed with recycled asphalt to patch potholes. Other products made with the blend are used to preserve cement, wood, and metal.
Coco Locomotion
Coconuts are the latest plant to be tapped for bio-based fuels. In October 2004, a unit of the Philippine National Oil Company opened the first cocodiesel plant. The plant is meant to show Filipino farmers how the technology can benefit them and their communities. Coconut oil and methanol are the major raw materials used to produce a biodiesel that burns cleaner than regular diesel without the need for engine modifications. The fuel costs about 8¢ less per kilometer to use, and the process also yields glycerine, which can be used to make soap. Some Filipino government vehicles are already using a 1% blend of cocodiesel as part of a presidential drive to reduce vehicular pollution.
Targeting Mosquitoes Online
Ever wonder whether those swarming mosquitoes in your backyard are carrying West Nile virus or some other disease? Researchers at Texas A&M University are developing a web-based real-time system that researchers and the public will be able to use to see where disease-carrying vectors have been spotted. The Mosquito Spatial Information Management System will map disease occurrence, epidemiology, and control procedures. Jim Olson, an entomologist on the team, said the system is just a small part of a larger multiagency project to determine the level of mosquito resistance to pesticides. This information will help pest management officials choose the most appropriate mosquito control measures for any given locality.
Mozambique Phases Out Leaded Gas
In August 2004 Mozambique announced its intention to ban the importation of leaded gasoline by the end of the year. The decision followed government approval of an action plan by the Leaded Gasoline Phase-out Task Force, a multiagency group working to facilitate the replacement of leaded gas with safer options, and to educate the public on the health and societal benefits of doing so. The task force plans to completely phase out the use of leaded gasoline in the country by mid-2005.
Most lead exposure is to airborne lead and lead in dust and soil. Excessive lead exposure is associated with cognitive impairment, stunted growth, and permanent brain damage and mental retardation. Lead has been found in vegetables grown in urban African gardens at levels higher than U.S. EPA allowable limits.
|
0
|
PMC1253741
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A25b-A27
|
utf-8
|
Environ Health Perspect
| 2,005 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0050aEnvironewsScience SelectionsA Whiff of Danger: Synthetic Musks May Encourage Toxic Bioaccumulation Washam Cynthia 1 2005 113 1 A50 A50 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
A class of widely used fragrances that are considered nontoxic may pose a hidden threat to human health by enhancing the effects of compounds that are toxic—a paradox discovered by Stanford University researchers Till Luckenbach and David Epel in a recent study of synthetic musk compounds [EHP 113:17–24]. The duo, based at Stanford’s Hopkins Marine Station, found that musks inhibited natural defenses against toxicants in California mussels, and that the effect remained long after exposure. Their findings raise a red flag for human health because musk compounds concentrate in fats (including breast milk) and endure in human tissue long after exposure.
People typically are exposed to musks transdermally, through soap, cosmetics, and clothes washed with scented detergents. Musks also are inhaled, through cologne sprays. Every year, some 8,000 metric tons of the inexpensive synthetic fragrances are produced worldwide.
The discovery of musk compounds in human fat a decade ago prompted Japan and Germany to ban some musk compounds. German researchers who measured human body burdens found musks in the fat of all their subjects and concluded that humans are constantly exposed to these highly stable compounds. The United States and other countries, though, allowed continued use of the fragrances because they were considered safe; a battery of routine toxicology screens have shown musk compounds to be nontoxic.
Epel and Luckenbach speculated that musks enhance the effects of toxicants by confounding cellular defense systems. Cells naturally resist toxicants through multidrug/multixenobiotic resistance (MDR/MXR) efflux transporters, proteins that keep foreign chemicals from entering cells. Epel and Luckenbach built on earlier findings reported in the September 1997 issue of EHP Supplements that man-made fat-soluble chemicals could inhibit MDR/MXR efflux transporters. Because musks are fat-soluble, they suspected synthethic musk compounds of having this effect.
The researchers chose mussel gill tissue for their study because its efflux transporters are particularly active. They incubated the tissue for 90 minutes in a solution containing musk compounds and the fluorescent dye rhodamine B. The dye reflects efflux transporter activity; finding rhodamine B in the tissue would indicate the transporters were failing.
Immediately after incubation, Epel and Luckenbach found rhodamine B uptake to be 38–84% higher in tissue treated with musk compounds than in controls. They were surprised to find, 24 hours later, that rhodamine uptake was still 30–74% higher in tissue exposed to musks. Efflux transport remained compromised 48 hours after exposure in tissue treated with certain commonly used compounds: musk xylene, musk ketone, Galaxolide, and Celestolide. Only tissue exposed to the compounds Traseolide and Tonalide recovered before 48 hours postexposure.
Epel and Luckenbach believe their study is the first to demonstrate long-term inhibition of the MDR/MXR system by synthetic musks. They warn that musk compounds, and possibly other chemicals as well, might similarly compromise the MDR/MXR system in humans. Evidence for this theory comes from the effectiveness of chemosensitizing drugs, which inhibit efflux transporters much as musk compounds do. Chemosensitizers are now being tested in clinical trials to prevent tumor cells from resisting harsh chemotherapeutics.
Luckenbach and Epel conclude that it is important to determine whether musks and other chemicals cause similar effects in humans. If so, they write, the result could be unanticipated accumulation of toxicants that would confound safety predictions of seemingly harmless chemicals.
The science of scents. New data on musks show the compounds may inhibit cellular defenses against chemicals and bioaccumulate, with potentially hazardous results.
|
0
|
PMC1253742
|
CC0
|
2021-01-04 23:40:55
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A50a
|
utf-8
|
Environ Health Perspect
| 2,005 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0050bEnvironewsScience SelectionsETS and Learning: Children’s Exposure Linked to Cognitive Effects Holzman David C. 1 2005 113 1 A50 A51 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
Previous studies have linked exposure to environmental tobacco smoke (ETS) with lower performance on tests of intelligence, reasoning ability, and language development, as well as higher risk for grade retention, suggesting that such exposure may cause cognitive deficits. Other adverse effects linked with ETS exposure include middle ear infections, colic, sudden infant death syndrome, and exacerbation of asthma. New findings now show that even extremely low-level exposure to ETS may be neurotoxic, according to a team led by Kimberly Yolton of the University of Cincinnati College of Medicine and Cincinnati Children’s Hospital Medical Center [EHP 113:98–103]. In fact, although a dose–response relationship held for all exposures, the greatest deficits proportionally speaking occurred when overall exposure was low, a phenomenon also noted in lead exposure.
The current study is notable for being the largest of its type, including 4,399 children aged 6–16 years who participated in the Third National Health and Nutrition Examination Survey (NHANES III), conducted from 1988 to 1994. It is also the first to rely solely on a biological marker of exposure—serum cotinine—rather than on data from interviews or questionnaires. “Reports of ETS exposure are complicated by poor recall, an inattention to crucial details such as adjustment for the amount of tobacco exposure, the child’s proximity to the smoker, room ventilation, and other factors that may compromise the validity of exposure measures,” the authors write. Furthermore, people tend to underreport smoking, which is increasingly being seen as a socially undesirable behavior.
While participating in NHANES III, children provided blood samples and took the reading and math subtests of the Wide Range Achievement Test–Revised and the block design and digit span subtests of the Wechsler Intelligence Scale for Children–III (the former Wechsler subtest measures visual construction abilities, and the latter, short-term and working memory). For the current analyses, children were excluded from the sample if they had reported using tobacco products within five days of cognitive testing and blood collection, or if their serum cotinine concentration indicated they probably were active smokers.
Yolton and colleagues measured serum cotinine concentrations in the samples and correlated the data with the children’s test scores. The results showed that children exposed to ETS had mildly to moderately depressed scores on tests of math, reading, and visuospatial skills as compared to children who lacked such exposures, but no deficits in memory. “The range of decrement in scores is very roughly equivalent to the loss of two to five IQ points at varying levels of exposure,” says Yolton. The authors estimate that more than 21.9 million U.S. children are at risk for ETS-related reading deficits.
The study is limited by NHANES III’s lack of measures of parental cognitive abilities and quality of home environment. Also, it is unclear whether the serum cotinine levels, taken just once for each subject, represented chronic or acute levels. However, other studies have shown serum cotinine concentrations to be stable in both smokers and nonsmokers. And although more research is needed to confirm these findings, the authors say this analysis adds to the evidence supporting policy to further reduce childhood exposure to ETS.
|
0
|
PMC1253743
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A50b-A51
|
utf-8
|
Environ Health Perspect
| 2,005 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0068aAnnouncementsBook ReviewDiamond: A Struggle for Environmental Justice in Louisiana’s Chemical Corridor VanderMeer Dan Dan VanderMeer was among the senior management staff at the Centers for Disease Control and Prevention that created its Center for Environmental Health. In 1984 he received the U.S. Public Health Service highest civilian award for helping establish the federal Agency for Toxic Substances and Disease Registry. He was the Department of Health and Human Services’ principal representative in the response to the national disaster at Love Canal where he coordinated health studies and recommendations in support of the eventual relocation and restoration of a major portion of the community.1 2005 113 1 A68 A68 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
By Steve Lerner
Cambridge, MA:MIT Press, 2004. 296 pp. ISBN: 0-262-12273-1, $27.95 cloth
Amazon.com lists over a dozen volumes on environmental justice, but only a few recent writings about disproportionately higher exposures to toxic and hazardous substances in low-income communities and people of color. Now there is another.
Lerner and others writing on this topic make it clear that “environmental justice” is an oxymoron. As a rule, those who live and work where chemicals and radioactive materials are produced are poor. Likewise, wastes from homes, industries, and weapons manufacture are deposited in poor communities. Environmental injustice is perhaps a better descriptor.
Accusations of environmental racism are not uncommon among those living in affected communities and their advocates. This was true in Diamond, a small, exclusively African-American neighborhood in the town of Norco, a few miles upriver from New Orleans. Norco was named for the New Orleans Refining Company built on plantation land. Over time, the oil business expanded to produce fuels, solvents, and other petroleum-based substances. Royal Dutch Shell and its successor, the Motiva-Equilon Alliance, have owned the business in recent decades. Lerner details this history, describing how complex social, racial, and economic factors combined to deny African-American residents many potential benefits of the growth of the oil industry. He lays out the conditions that led them to believe passionately that their health and well-being were at severe risk from exposures to pollution released from the refinery.
A major explosion occurred in a unit in the Shell refinery early morning on 4 May 1988. Seven workers died and 48 people were injured, some of whom were community residents. Over 4,000 people were temporarily evacuated. Lerner suggests that this was a tipping point for the Diamond community. The event lurked in the background as data describing leaks of pollutants into the surrounding areas were reported by Shell in the 1990s in response to new federal rules. Leadership in the community evolved. Margie Richardson, a local teacher, formed Concerned Citizens of Norco. Environmental justice advocates gravitated to Norco to support the citizens. And eventually Shell agreed to buy out the neighborhood. The book provides a deep level of detail on these people and the process.
The epic struggles in the 1970s and 1980s among residents, industry, and government to find a satisfactory resolution to community exposures to hazardous substances all seem to have a curiously common set of characters: the key local community activist(s) who emerge(s) from obscurity to a position of leadership; a core of nonresident advocates who bolster these community leaders; a representative who speaks for the industry but cannot commit the fiscal resources for putting things right; local, state, and federal environmental and health agency representatives who can help define the problem but are powerless to change the fundamental conditions in the community; expert consultants retained by the community, government, and industry—few of whom agree and none of whom are trusted by a majority; attorneys representing citizens or industry; and, finally, the media reporting on key events and observers (usually academics) who write papers and books about the process.
These were all present in Diamond. Lerner identifies with citizens and advocates who demanded relocation. Unlike white residents of Norco, the African-American community perceived unacceptably high risks and insignificant benefits. Although they lived with the same environmental contaminants, white residents believed that the oil economy strengthened their economic, educational, and social infrastructure. They did not support their African-American neighbors’ demands to have their houses purchased by the oil industry, and they did not relocate. Lerner notes that the unity of purpose in the Diamond neighborhood eventually resulted in a buyout and exodus from a foul and potentially dangerous toxic chemical environment. This success also disbanded an African-American community with roots spanning three centuries and ended the de facto segregation of Norco.
|
0
|
PMC1253744
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A68a
|
utf-8
|
Environ Health Perspect
| 2,005 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences ehp0113-a0068bAnnouncementsNew BooksNew Books 1 2005 113 1 A68 A68 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright.
==== Body
A History of Epidemiologic Methods and Concepts
Alfredo Morabia, ed.
New York:Springer-Verlag, 2004. 405 pp. ISBN: 3-7643-6818-7, $119
Agriculture and the Nitrogen Cycle: Assessing the Impacts of Fertilizer Use on Food Production and the Environment
Arvin R. Mosier, Keith Syers, John R. Freney, eds.
Washington, DC:Island Press, 2004. 374 pp. ISBN: 1-55963-710-2, $40
Carbon Dioxide Utilization for Global Sustainability
Sang-Eon Park, Jong-San Chang, Kyu-Wan Lee, eds.
Burlington, MA:Elsevier, 2004. 625 pp. ISBN: 0-444-51600-X, $253
Cell Surface Receptors: A Short Course on Theory and Methods
Lee E. Limbird
New York:Springer-Verlag, 2004. 218 pp. ISBN: 0-387-23069-6, $85
Corporate Environmentalism and Public Policy
Thomas P. Lyon, John W. Maxwell
Cambridge:Cambridge University Press, 2004. 306 pp. ISBN: 0-521-81947-4, $85
Electronic Scientific, Technical, and Medical Journal Publishing and Its Implications: Report of a Symposium
Committee on Electronic Scientific, Technical, and Medical Journal Publishing, The National Academies
Washington, DC:National Academies Press, 2004. 122 pp. ISBN: 0-309-09161-6, $28.25
G Protein Coupled Receptor-Protein Interactions
Susan R. George, Brian F. O’Dowd, David R. Sibley, eds.
Hoboken, NJ:John Wiley & Sons, 2004. 320 pp. ISBN: 0-471-23546-6, $149
Global Carbon Cycle Integrating Humans, Climate, and the Natural World
Christopher B. Field, Michael R. Raupach, eds.
Washington, DC:Island Press, 2004. 568 pp. ISBN: 1-55963-527-4, $45
How Cancer Works
Lauren Sompayrac
Sudbury, MA:Jones and Bartlettt Publishers, 2004. 110 pp. ISBN: 0-7637-1821-1, $26.95
Make Your Mark in Science: Creativity, Presenting, Publishing, and Patents, A Guide for Young Scientists
Claus Ascheron, Angela Kickuth
Hoboken, NJ:John Wiley & Sons, 2004. 256 pp. ISBN: 0-471-65733-6, $29.95
Novel Compounds From Natural Products in the New Millennium: Potential and Challenges
Benny K-H Tan, Boon-Huat Bay, Yi-Zhun Zhu
River Edge, NJ:World Scientific, 2004. 336 pp. ISBN: 981-256-113-7, $65
Petit Point: A Candid Portrait on the Aberrations of Science
Pierre-Gilles de Gennes
River Edge, NJ:World Scientific, 2004. 80 pp. ISBN: 981-256-011-4, $14
Rachel Carson: A Biography
Arlene R. Quaratiello
Westport, CT:Greenwood, 2004. 168 pp. ISBN: 0-313-32388-7, $29.95
Science and Technology in the National Interest: Ensuring the Best Presidential and Federal Advisory Committee Science and Technology Appointments
Committee on Ensuring the Best Presidential and Federal Advisory Committee Science and Technology Appointments
Washington, DC:National Academies Press, 2004. 224 pp. ISBN: 0-309-09512-3, $50.50
Setting Priorities for Large Research Facility Projects Supported by the National Science Foundation
Committee on Setting Priorities for NSF-Sponsored Large Research Facility Projects, National Research Council
Washington, DC:National Academies Press, 2004. 236 pp. ISBN: 0-309-09084-9, $41.50
The Genetic Code and the Origin of Life
Lluis Ribas de Pouplana, Godfrey Maurice, eds.
New York:Springer-Verlag, 2004. 270 pp. ISBN: 0-306-47843-9, $145
Teen Guides to Environmental Science
John Mongillo, Peter Mongillo
Westport, CT:Greenwood, 2004.
Five Volumes, ISBN: 0-313-32183-3, $249.95
|
0
|
PMC1253745
|
CC0
|
2021-01-04 23:40:54
|
no
|
Environ Health Perspect. 2005 Jan; 113(1):A68b
|
utf-8
|
Environ Health Perspect
| 2,005 |
nan
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7450ehp0113-00024315743709ResearchCommentaryCan Lessons from Public Health Disease Surveillance Be Applied to Environmental Public Health Tracking? Ritz Beate 1Tager Ira 2Balmes John 31Department of Epidemiology, University of California, Los Angeles, California, USA2Division of Epidemiology, and3Division of Environmental Health Sciences, School of Public Health, University of California, Berkeley, California, USAAddress correspondence to B. Ritz, Department of Epidemiology, University of California at Los Angeles, 650 Charles Young Dr., Room 73-320 CHS, Los Angeles, CA 90095 USA. Telephone: (310) 206-7458. Fax: (310) 206-6039. E-mail:
[email protected] thank J. Mann for her comments and all members of the Center for Excellence in Environmental Public Health Tracking for their involvement in discussions of some of the issues presented here.
This work was partially funded by a Centers for Disease Control and Prevention grant for a Center of Excellence for Environmental Public Health Tracking at the University of California at Los Angeles, University of California at Berkeley, and University of California at San Francisco, grant U50/CCU922409-03.
The authors declare they have no competing financial interests.
3 2005 2 12 2004 113 3 243 249 27 7 2004 2 12 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Disease surveillance has a century-long tradition in public health, and environmental data have been collected at a national level by the U.S. Environmental Protection Agency for several decades. Recently, the Centers for Disease Control and Prevention announced an initiative to develop a national environmental public health tracking (EPHT) network with “linkage” of existing environmental and chronic disease data as a central goal. On the basis of experience with long-established disease surveillance systems, in this article we suggest how a system capable of linking routinely collected disease and exposure data should be developed, but caution that formal linkage of data is not the only approach required for an effective EPHT program. The primary operational goal of EPHT has to be the “treatment” of the environment to prevent and/or reduce exposures and minimize population risk for developing chronic diseases. Chronic, multifactorial diseases do not lend themselves to data-driven evaluations of intervention strategies, time trends, exposure patterns, or identification of at-risk populations based only on routinely collected surveillance data. Thus, EPHT should be synonymous with a dynamic process requiring regular system updates to a) incorporate new technologies to improve population-level exposure and disease assessment, b) allow public dissemination of new data that become available, c) allow the policy community to address new and emerging exposures and disease “threads,” and d) evaluate the effectiveness of EPHT over some appropriate time interval. It will be necessary to weigh the benefits of surveillance against its costs, but the major challenge will be to maintain support for this important new system.
environmental healthevaluationinterventionregistriessurveillance
==== Body
The Centers for Disease Control and Prevention (CDC) describes its own mission as serving “as the national focus for developing and applying disease prevention and control, environmental health, and health promotion and education activities designed to improve the health of the people of the United States” (CDC 2005). Recently, the CDC, for the first time, funded state and larger metropolitan health departments and three academic centers to begin to develop a national environmental public health tracking (EPHT) network. The CDC vision for the EPHT program is to improve protection of communities from adverse health effects through the integration of public health and environmental information systems. To implement this vision, the goal is to develop a national tracking (i.e., surveillance) network that links chronic disease and environmental data sources.
Surveillance has a long tradition in public health for both the descriptive epidemiology of diseases and the provision of insights into disease causation and disease control. It can be taken as axiomatic that, ultimately, all surveillance systems aim at disease control. Generally, surveillance refers to the continuous, routine collection of data related to health or exposures of populations over the long term, and the associated analysis, interpretation, and dissemination of the results. Surveillance data collected by government agencies such as the CDC and the U.S. Environmental Protection Agency (EPA) provide important archives that permit continued reinterpretation and health research. To date, however, the data systems established and used for surveillance focus either on diseases/syndromes or on media (e.g., ambient air pollutants, toxic agents) without formal linkage between systems. In this article, we focus our analyses mainly on properties and lessons learned from disease surveillance systems. We also provide arguments that effective surveillance does not always require formal linkage of exposure and health outcome data; indeed, there are problems inherent in surveillance of environmentally related diseases when based on formal linkage of routinely collected data.
Established Surveillance Systems—History, Goals, and Properties
Surveillance for various specific diseases and toxic agents has become an established feature of public health systems in developed countries. The systems include sophisticated registries and monitoring networks that collect data through several different techniques.
The oldest systems that allowed monitoring of population health trends are vital statistic records established in Europe in the 1700s. In England and Wales, death records had a prominent place as demographic barometers for the health of communities and citizens throughout the 19th century. Variations in mortality rates from diseases such as cholera, dysentery, or workplace-related death (e.g., due to mining accidents) suggested socioeconomic, work-related, and environmental causes. This information was employed to justify a public health campaign not only to improve population health in England but also to measure the success of interventions [e.g., the construction of sewer systems (Mooney 1997)]. A distinguishing property of these early surveillance systems was a focus on acute causes of death for which there were either close temporal and/or spatial proximity between a perceived exposure and the outcome sufficient to establish causality (Koch, in press); or they allowed broad ecological comparisons of mortality rates between communities before and after public health interventions were implemented.
Vital statistics data (deaths, birth numbers, and outcomes) still provide a major source of surveillance data to monitor and to compare general trends in population health, to identify subgroups at risk, and to assess the effectiveness of intervention and treatment programs. Moreover, developed nations have invested in the establishment of many registry systems to collect more detailed morbidity data that provide surveillance for acute and chronic infectious diseases, occupational injuries and deaths, cancers, and birth defects. Unfortunately, in the United States none of the health outcomes surveillance databases are linked specifically, in either space or time, with relevant exposure databases.
Below we describe the function, motivation, and attributes that make these systems successful.
Surveillance for infectious and other acute diseases.
Infectious disease surveillance is the paradigm for the surveillance of diseases that, aside from some exceptions (e.g., syphilis, tuberculosis, and AIDS), are characterized by acute onset and rapid resolution. The descriptive data provided by surveillance systems for these types of diseases provide the basis for the monitoring of the effects of interventions (e.g., standardized treatment, public education campaigns) and temporal and spatial trends that reflect changes in population behavior and attitudes, demography, provision of health services related to sexually transmitted diseases, and loss of efficacy of standard treatment regimens. The detection of “outbreaks” of disease [e.g., resurgence of syphilis in populations of homosexual males (D’Souza et al. 2003)] is an integral part of these systems. The timely collection, organization, analysis, and dissemination of these data facilitate prompt responses by public health systems to changes in disease occurrence for which immediate intervention appears warranted. The CDC’s critical role in the control of infectious diseases depends, to a large extent, on data from these surveillance systems. For these efforts to succeed, highly specific and rapid methods for recognition and unambiguous diagnosis of diseases, coupled with effective and acceptable intervention strategies, must be available. Many acute infectious diseases fulfill these requirements. Continued technological advances can be expected to improve still further the diagnostic speed for other infectious diseases that require longer diagnostic confirmation periods, such as tuberculosis and AIDS. Intervention strategies to stop outbreaks are varied and include a) treatment of the infected individual, which results in both the recovery of the affected individual and the protection of susceptible individuals in the population from transmission, and b) if no treatment is available, quarantine of the infected individual until remission and immunization of susceptible individuals—that is, by prevention of transmission of the infectious agent and disease through the removal of susceptible individuals or carriers. Surveillance of diseases for which we routinely immunize continues for the purpose of identification of gaps in immunity in a population.
Infectious diseases of more insidious onset and/or tendency to relapse and remit over long periods of time (e.g., tuberculosis, HIV infection, malaria, Helicobacter pylori) pose problems for surveillance and characterize many of the chronic diseases that would be the target for environmental health tracking. Although the specific pathogens can be identified with relative ease, the diseases can present slowly over long periods, such that the connection between the primary exposure sources is lost or difficult to trace with specificity. Treatment usually is long and burdensome, and methods for primary prevention may be difficult or impossible to implement (in terms of cost, acceptability, and need for persistence). For example, to control malaria, one has to prevent transmission of the disease (vector control and behavior change) rather than control the disease after transmission has occurred. Because responses for these programs do not curb the occurrence of proximal cases, the success of these interventions will often not be apparent until after a lengthy period during which no new cases are observed. In fact, in cases where there are long delays between the implementation of an intervention and the reduction in disease incidence or morbidity, it may be difficult to quantitate precisely (or even accurately) the extent to which the intervention altered the outcome of the disease.
To complicate matters further, there are a number of infectious agents that, to date, elude our diagnostic and surveillance tools. Many viruses and bacteria cause nonspecific syndromes or symptom complexes that include most diarrheal and respiratory symptoms. The situation whereby similar syndromes are caused by many different infectious agents bears a striking similarity with the situation of environmental exposure to chemical agents because many different agents or mixtures can produce a similar syndrome. New infectious agents (and, by analogy, chemical exposures) that produce these nonspecific syndromes may elude detection for long periods or until such time as a unique syndrome has been successfully related to an agent/exposure (e.g., Escherichia coli O157:H7c and hemolytic uremic syndrome). Although surveillance systems to monitor entire populations for these ubiquitous disease syndromes or symptoms that generally do not result in chronic illness or death have not been a priority in the past, the importance of “syndromic surveillance” has now been recognized (CDC 2004). Only when there is a small susceptible group that suffers severe symptoms or deaths do these syndromes start to draw public attention and require a response and investment in pathogen identification and disease prevention efforts (e.g., the West Nile virus outbreak; most infected individuals show minor symptoms of respiratory illness, but some infections in the elderly cause death). In general, for infectious diseases and syndromes for which we lack diagnostic and/or immunization-based prevention tools as a society, we opt for broad-based strategies to prevent exposure and intervene on potential media (e.g., prevention of contamination of water or food by microorganisms), instead of implementation of large disease- or syndrome-based surveillance.
Acute poisoning from metals or chemicals has similar attributes to infectious diseases, such as specific and acute symptom complexes that can be identified via biological tests. In the case of lead poisoning, state and federal agencies implemented a combination of preventive measures (removing lead from paint and gasoline) and surveillance for high levels of exposure that are likely in susceptible groups (e.g., in California for young low-income children with health insurance from Medi-Cal). However, there is one fundamental difference compared with the treatment of an infectious disease: Only lead removal from the environment, not the medical treatment of an individual, will reduce the risk to others in contaminated environments. Thus, the intervention that follows the identification of a poisoning case through surveillance will have to be broader and include remedial activities that remove the sources of poisoning. In fact, as we discuss below, the primary operational goal of environmental health tracking is the “treatment” of the environment in such a manner as to reduce population risk. Although a substantial part of the effort to control infectious diseases would also fall under this rubric, it is important to recognize that the individual medical treatment and prevention aspects of infectious disease surveillance are less relevant for many of the noninfectious health outcomes that will be considered for inclusion as part of environmental health tracking (e.g., asthma, many cancers).
Surveillance for chronic diseases.
Similar to infectious and other acute disease surveillance, surveillance for chronic diseases has been implemented largely for diseases that are dreaded because of their consequences (disability and death). We define a chronic disease/syndrome as one that can have acute or insidious onset and whose symptoms and/or physiological abnormalities persist over long periods of time (years to lifelong, but they can remit with or without recurrence, e.g., asthma).
Another criterion that applies to both types of diseases for which surveillance systems exist is that they are identifiable by clinical and/or pathological examination with a high degree of specificity; that is, measurement tools are available and cost-effective and allow for unambiguous diagnosis. However, although early disease detection and intervention might be favorable and increase survival for some chronic diseases (e.g., carcinoma of the cervix, colon cancer, breast cancer), for many, neither screening tools nor universally effective treatments are available (e.g., lung cancer, many cancers of the gastrointestinal tract). Furthermore, because many chronic diseases generally are irreversible without some intervention, treatment interventions will not remove the cause of the disease in the same way as an antibiotic may eliminate bacteria and, at the same time, prevent transmission of the infection to others. However, in contrast to the specificity of metal chelation therapy in the case of lead poisoning, treatment for a chronic disease such as asthma is likely to be effective independent of the cause of the disease; for example, inhaled steroid treatment reduces inflammation and symptoms regardless of the nature of the trigger (molds, viruses, or air pollution) causing attacks.
Cancer surveillance has been described by CDC as an essential tool to a) assess patterns in the occurrence of cancer and detect important trends within populations, b) assess the impact of cancer prevention programs, and c) allow the rational allocation of limited resources for cancer (CDC 2004). Some of the attributes that favor certain infectious diseases for surveillance activities clearly overlap with those of certain cancers; that is, for some cancer types, effective strategies exist for reduction of mortality from cancer, and strategies for prevention of new cases may exist that include changes in behavioral and environmental factors.
Interestingly, another stated goal of cancer surveillance is the “wise allocation of limited resources including setting priorities for allocating health resources,” which depends partly on the “availability of complete, timely, and high-quality cancer data” (CDC 2004). For those cancers for which the etiology is unclear and/or complex and/or for which satisfactory early screening tools and/or treatments are lacking, surveillance data represent an important research tool for ascertainment of disease etiology (host and environmental factors) and definition of disease natural history (progress of disease over time). For those cancers for which screening is new (e.g., recommendations for colonoscopy for colon cancer) or for which the groups that derive maximum benefit are still controversial (e.g., mammography), surveillance can provide important data on the effectiveness of screening. However, if there are long lag periods between the introduction of a screening procedure and improved survival for a specific cancer, it may be difficult to quantitate the population benefit. If a new environmental exposure or some human behavior intervenes during this time interval and changes the incidence and/or the natural history of a given cancer or group of cancers, the efficacy of a screening program may be underestimated at best or considered nonexistent at worst. These issues clearly are relevant for any environmental health tracking system that focuses on chronic health problems. These issues are summarized in Table 1.
The same caveat for new screening tools also applies to the evaluation of preventive interventions. Because of the long latency between initiation and diagnosis of most cancers, the effectiveness of preventive interventions, such as the success of smoking cessation programs, will not become apparent until years or even decades after implementation. Thus, intervention evaluation efforts must operate on a different time scale from those for many acute infectious diseases. Furthermore, cancers, like most chronic diseases, have multi-factorial etiologies such that several risk factors operate through different or similar pathways that lead to the same outcome: For example, lung cancer can be caused by smoking and by exposure to asbestos, and subjects exposed to both agents may differ in risk from those exposed to either one of these carcinogens (Liddell 2001). However, surveillance of cancer trends over time that aims to document the success of an intervention could be misleading if the reduction of one of the carcinogens in a population (e.g., the prevalence of asbestos exposure) is accompanied by an increase in prevalence in another risk factor for the disease (e.g., smoking). Whether or not these two exposures would affect the same individuals in a population would not matter, because we are only monitoring trends in overall population rates.
Although cancer surveillance through registries enables a vast amount of etiologic research that contributes to the identification of cancer risk and preventive factors, this research is not part of the monitoring/surveillance effort per se but requires separately funded scientific studies, some of which will make use of surveillance data as a primary or major resource. These studies are necessary to identify the cancer-initiating events that generally precede disease diagnosis by years or decades and to estimate individual level exposures and take latency and susceptibility into account. Etiologic factors that contribute to cancers are not identifiable through disease surveillance except in those rare cases where a carcinogenic agent can be identified by a biological or chemical marker in the affected tissue(s) long after the initiation of cancer. One example is the human papilloma virus, which can be identified at higher rates in the tissue of women diagnosed with cervical cancer than among nonaffected controls (Salmeron et al. 2003). However in such cases, to permit causal inferences, a registry also would need to obtain samples from unaffected population controls, a task outside the scope of any registry. This reasoning extends also to cancer cluster investigations; that is, only when an etiology is already established and highly specific (e.g., for vinyl chloride and angiosarcoma or asbestos and mesothelioma, but not asbestos and lung cancer) can a cluster suggest the cause of the disease and be used to help guide intervention and prevention efforts (removal of asbestos). Therefore, careful consideration must be given to the expenditure of resources to investigate such occurrences.
Environmental Health Tracking
Use of existing surveillance systems for linkage purposes.
We have listed the goals and requirements for an EPHT system in Table 2. Generally, such a system can take advantage of already existing, active, passive, or sentinel surveillance systems, if the requirements for linkage are fulfilled (see “System requirements,” Table 2) or if they can be used as a starting point from which additional data that pertain to environmental exposures or the diseases of interest can be obtained. These systems have different functions, costs, and utility for public health and environmental tracking. Active surveillance systems have the advantage of relatively complete ascertainment and standardized collection of data over time but are very resource intensive and usually focused only on one type of disease or exposure. Passive systems are cheaper to maintain but are potentially subject to biased, incomplete reporting. Reports of unusual events (e.g., space–time clusters of disease, uncommon exposures such as a toxic spill) do not meet the formal requirements for surveillance noted above. However, the systems through which these reports appear (e.g., Morbidity and Mortality Weekly Report) do provide the temporal continuity and standardization of presentation that satisfy the requirements for surveillance. Reports of unusual events may provide the initial stimulus for the identification of important ongoing, environmental health risks but should avoid the pitfalls of chronic disease (cancer) cluster investigations. Most important, all existing surveillance systems, once they fulfill the requirements for linkage, can serve descriptive functions and allow the conduct of ecologic analyses in the broadest sense—that is, population exposures and outcomes for population inference. On the other hand, etiologic questions may be answerable only if additional resources become available to a) provide for collection of additional data for assessment of exposure and other disease risk factors (e.g., those that act as confounders or effect modifiers) at the individual level (e.g., pesticide or air pollution exposures at homes and workplaces of subjects of interest, smoking and diet information, genetic susceptibility factors, access to health care); b) collect data in control subjects (e.g., nondiseased subjects as controls for cancers) or collect data for diseases for which routine monitoring systems are not in place (e.g., asthma); and c) conduct additional data analysis not provided for within the routine monitoring systems. Furthermore, certain etiologic questions may be answered best through other types of study design that do not rely on disease monitoring in a geographically based population but either follow cohorts of individuals over a long time [e.g., Nurses’ Health Study (Hunter et al. 1990; Laden et al. 2001) cohort] and/or store biological samples for a large number of individuals [e.g., the National Health and Nutrition Examination Survey (NHANES) (Chapman et al. 2003)], or target special highly exposed groups within a population [e.g., the Agricultural Health Study for pesticide exposures (Alavanja et al. 2003)] or vulnerable subgroups of a population (children for asthma, elderly for Alzheimer or Parkinson disease). Table 3 lists the advantages and disadvantages of different systems to evaluate environmental health questions and references examples from the literature for the use of such systems.
Criteria for the expansion/contractions of an existing surveillance system.
The design of an EPHT and surveillance system cannot be static. There always will be a need to expand the “core” of the system or to provide ad hoc elements to address specific issues whether these relate to what data the system collect or which populations it needs to cover. The criteria for expansion (and contraction) cannot be specified a priori; however, what can be specified is a process to keep the system dynamic and relevant. Table 4 summarizes some suggested questions that should be addressed. Most important are recognition of the need for continued re-evaluation and the existence of a base of fiscal resources to make adjustments when such are deemed necessary.
A parallel issue relates to the ability of a tracking system to recognize the potential for some new environmental exposure to cause health effects before adequate human health data are available. The solution to this problem is the inclusion of a mechanism for ongoing, continuing reviews of the relevant toxicology and exposure literature. The regular preparation of position papers by expert panels should serve as the first step in the decision-making process that is identified by item 1 in Table 4. The findings of these position papers should be subjected to a second-level review to assess the logistical and cost–benefit implications of the inclusion of new exposures into the tracking system.
Conclusions and Recommendations
Initiation of linkage between existing disease and exposure surveillance systems for EPHT is very desirable and feasible. We have identified what we believe to be the important pitfalls that should be avoided for such linkage activities. The goals, purposes, and limitations of any proposed linkage must be discussed and stated clearly. In addition, currently available data resources and surveillance systems will need to be evaluated critically first to decide whether they fit the criteria for a successful linkage or might need to be updated and expanded to make linkage possible and useful.
Identification of many important relations between environmental factors and heath outcomes requires individual-level data that are not routinely collected by any surveillance system; thus, these can be addressed adequately only with targeted research. In contrast, data linkages performed in a surveillance context typically will not be able to address key factors at the level of the individual. Data linkage efforts may be able to detect some relations but would also be expected to miss others that could, however, be established in well-designed epidemiological studies. The distinction between data linkages in the surveillance context and targeted research is an important one, and the EPHT program must avoid the expectation that simple linkage approaches in the surveillance context can substitute for sound epidemiological research.
Design of surveillance approaches requires a balance between demands for more extensive and higher quality data and the feasibility of collecting such data. For environmental agent–disease relationships that are already well established, formal linkage of data may not be the most efficient use of resources. For example, exposure to lead has been clearly associated with decreased cognitive development in children. Use of data linkage projects to assess this relationship at the community level might be problematic because of our potential inability to detect subtle but important effects that require large cohorts of children and very sophisticated test procedures, and resources might be better devoted to identifying and addressing determinants of exposure. Furthermore, tracking of exposures to environmental agents without linkage to health outcomes can spawn effective interventions, such as efforts to reduce the use of polybrominated diphenyl ethers after these compounds were detected in increasing concentration over time in human breast milk.
Concerns about the implications of data linkage are particularly important in a policy context. A community-level association between exposure to an environmental hazard and an adverse health outcome need not be demonstrated before intervention is initiated if the relationship has been appropriately established in the scientific literature. For example, not every community needs to show a relationship between consumption of local fish contaminated with mercury and elevated blood mercury levels before taking action to warn the population that excessive local fish consumption should be avoided. Moreover, as we discussed above, for chronic diseases of multifactorial etiology, it will be difficult to demonstrate relationships between reductions in releases or concentrations of environmental agents and disease outcomes. The U.S. EPA is beginning to emphasize “accountability”—that is, demonstrations that reductions in health outcomes result from policy activities that reduce levels of hazardous agents in the environment. Although it is laudable to show such relationships where they can be demonstrated, the converse view that such relationships must be demonstrated before a policy intervention can be initiated is not supported.
Because chronic, multifactorial diseases do not lend themselves to data-driven, quick, and convenient evaluations of intervention strategies, time trends, exposure identification, or the identification of at-risk populations based on linkage and surveillance only, we propose that, first and foremost, EPHT should be synonymous with a dynamic process that requires regular system updates to a) incorporate new technologies to improve exposure and disease assessment at the population level, b) allow public dissemination of new data that become available, c) allow the public health and environmental policy communities to address new and emerging “threads” (for both exposures and health outcomes), and d) evaluate its effectiveness over some appropriate time interval. A challenge will be to maintain consistent support and funding for important routine public health systems that may seem less exciting than the public outrage producing “toxins or diseases of the week.” This is particularly true at times of economic downturns, in response to short-term public and political pressures. Although the risks attributable to environmental factors might be small in a relative sense, they can result in a large disease burden in absolute numbers because of the ubiquitous nature of certain exposures, the possible synergy of these factors with other risk factors, and the increased vulnerability of certain subpopulations. Thus, risk assessments based on any single surveillance system are likely to provide downwardly biased estimates of risk for a specific environmental hazard, because of the difficulty related to the identification of the effects of exposures to multiple environmental hazards whose composition may change over time and for which it is nearly impossible to construct accurate exposure histories even at an ecological level. Nonetheless, in some cases, surveillance may be the only practical method to obtain sufficient data to carry out a preliminary assessment of risk (contingent on adequate quality data).
By their nature, many chronic diseases are irreversible to a large extent (if at all) even after the exposure is removed. Therefore, treatment interventions directed at individuals will not remove the cause of the disease or the possible source of disease for others in the community. Thus, the primary operational goal of environmental health tracking has to be the “treatment” of the environment in such a manner as to reduce population risk. It will be important and necessary to evaluate and weigh the benefits of surveillance against its costs. In addition, we have pointed out that some strategies to evaluate the effectiveness of interventions can be severely flawed if they do not address the complexity of disease causation. On the other hand, prevention might be our only rationale option, even if multifactorial diseases do not lend themselves to surveillance data-driven evaluations of intervention strategies.
Table 1 Challenges for chronic disease surveillance relevant to EPHT.
Characteristics of the disease
Onset can be insidious
Exact time of onset not known and often not subject to estimation, which complicate temporal characteristics of exposure
Often long latency between onset of exposure and clinical manifestation of disease
Heterogeneous mix of phenotypic components (e.g., asthma: allergic, nonallergic, cough variant types)
May have multiple natural histories and differ in antecedent exposure profiles (risk factors for onset or recurrence)
Genetic heterogeneity may not be reflected in phenotype (e.g., young-onset breast cancers with and without BRCA1 and BRCA2 mutations)
Multiple etiologies; some pathways may not involve the same putative risk factors (e.g., young-onset Parkinson disease caused by MPTP exposure or by Parkin mutations)
Characteristics of exposure
Often involves complex mixtures that can change over time
Relevant parameters often not easily defined
Timing of onset
Cumulative dose versus critical time of exposure
Threshold versus no threshold
Effect modification by other exposures
Direct measurement often not available
Reliance on imperfect surrogates
MPTP, 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine.
Table 2 Goals and requirements for an EPHT system.
Surveillance goals Requirements for health data Requirements for exposure data System requirements
Descriptive (ecologic) Chronic diseases Long-term exposure assessment Minimum set of variables for linkage is available (e.g., residential/work address and geocoded exposure location)
Temporal Specificity of diagnosis Broad spatial coverage that captures medium-scale spatial heterogeneity and should “match” health spatial units as closely as possible Clear documentation of all variable of changes in format and/or content
Spatial Standardization of diagnostic algorithms over time and procedures to convert from one standard to another (e.g., ICD-9 to ICD-10) Long historical record keeping and acceptable procedures to convert old to new measurement techniques or metrics Continued linkage of health and exposure data
Moderately short time delays between diagnosis and “registration” (e.g., example within 6 months) Develop criteria for selection of exposures such as known or suspected health impacts and/or regulatory requirements Continued dissemination of results to agencies and public
Agreed upon spatial reference (e.g., residence at diagnosis) Identification of “sentinel” substances where possible Ongoing administrative, legal, and fiscal support for linkage and dissemination activities
Acute diseases (e.g., poisonings) Collect data on
Specificity of diagnosis Broad categories of sources
Standardization of diagnostic algorithms over time and procedures to convert from one standard to another (e.g., ICD-9 to ICD-10) Broad classes of relevant “components”
Short time delay between identification and registration (e.g., days to weeks)
Agreed upon spatial reference (e.g., residence at diagnosis)
Etiologic Chronic and acute diseases and clusters Requirements in addition to those mentioned above Requirements in addition to those mentioned above
Chronic Specificity and standardization (as needed for descriptive purposes) Near real-time or real-time access to quality-assured data for acute disease and cluster evaluation Ability to acquire QA/QC and release data consistent with time requirements
Acute Time of registration and spatial reference (as above) Ability to estimate individual exposure for acute, cluster and chronic disease, or refined spatial and temporal data for acute disease and cluster evaluation Ability to support special monitoring projects
Clusters (spatial and temporal) Expanded data on risk factors Data sufficient for spatial and temporal (acute and cumulative) exposure modeling over time for chronic disease Fiscal and staff support for ongoing modeling
Access to noncases for risk factors and exposure Specific source apportionment in terms of sources and components for acute disease and cluster evaluation Fiscal support for selected, existing registries and special studies
Abbreviations: ICD, International Classification of Diseases, 9th and 10th Revisions (WHO 1978, 1993); QA/QC, quality assurance/quality control.
Table 3 Advantages and disadvantages of various systems for the examination of environmental health questions.
Registries Advantages Disadvantages Selected examples/references
Disease registries
Death or birth certificates Standardized continuous collection of data for the total population in a geographic area
Collects causes of deaths, birth weight, and gestational age in a standardized manner
Allows examination of differences in space and time that includes trends for causes of deaths and birth outcomes
Relatively cheap and well established Outcome data are relatively limited in breadth (i.e., to fatal diseases and few birth outcomes)
Relatively little quality control over data collection
No exposure data
Automatic link to exposure data possible through address (at birth or deaths)
For extensive individual level exposure assessment, subjects (or proxies) need to be contacted (additional research funding necessary)
Potential ethical and legal concerns related to automatic data linkage Ritz et al. 2000
Wilhelm and Ritz 2003
Disease registries (reportable infectious diseases, cancer, end-stage renal disease, and birth defect registries; hospital discharge data; health maintenance organization data) Standardized continuous collection of data for the total or subgroups of a population in a geographic area
Allows examination of differences in space and time that includes trends for these diseases
High-data quality for registries established in accordance with specified (national) standards (e.g., surveillance epidemiology and end results cancer registry standards) Laws necessary that mandate reporting and registration
Continuous and extensive financial support necessary
Often registers only one specific type of disease
No exposure data available
Automatic link to exposure data possible through address at diagnosis (additional research funding necessary)
Potential ethical and legal concerns related to automatic data linkage Ritz et al. 2002
Reynolds et al. 2003
Shaw et al. 1999
Mann et al. 2002
Exposure/hazard registries
Ecological exposure registries/databases (air and water pollution, pesticides, industrial emissions inventories) Standardized continuous collection of exposure data for the total population in a geographic area
Allows examination of differences in space and time that includes trends for these exposures
High-data quality for these registries based upon certain specified (national) standards
Allows for population-level exposure estimates either directly or through model Laws necessary that mandate reporting and registration
Continuous and extensive financial support necessary
Usually registers only one specific type or group of exposures in a single medium (e.g., air, water)
Exposure data are collected at the ecological not at the individual level
No disease information without additional linkage to geographic identifiers (e.g., addresses)
For disease outcome, linkage subjects (or proxies) may need to be contacted (additional research funding necessary) Ritz and Yu 1999
Mortimer et al. 2002
Individual-level exposure registries (biomonitoring, e.g., NHANES) Collects specific exposure data for a group of select individuals suspected to be exposed at high levels, or for a regional or national random sample of the population
Allows examination of exposure differences in space and time that includes trends for exposures if collected repeatedly or continuously
Individual-level exposure measurements available
Specific exposures of relatively high data quality Very expensive
Usually only one type of specific exposure collected
Usually no disease data collected simultaneously or prospectively (needs addition research funding)
If samples are collected for specific research purposes only, subjects need to consent to new analyses
Groups that are willing to contribute urine, blood, etc., may not be representative of the larger population Murphy et al. 1983
MacIntosh et al. 1996
Ruckart et al. 2004
Surveys
Cross-sectional or repeated surveys (NHANES, ISAAC, MONICA, CHIS) Collect data on one or more diseases and exposures simultaneously for a representative regional, national, or international sample using standardized methods
Allows examination of differences in space and time including trends for exposures and diseases if collected repeatedly
Individual-level exposure and disease measures available
High-data quality
Subjects need to be contacted and participate only once One time or repeated high financial investment necessary; costs depend on data collection protocol, sample size, length of observation period, etc.
Cross-sectional data for exposure and disease may cause problems of temporal ambiguity and survivor bias
Disease outcome measures often rely on self-report only
Research subjects have to be willing to participate, thus may not be representative of the general population Keil et al. 1996
Hirsch et al. 1999
Ramadour et al. 2000
Peters et al. 2001
Chapman et al. 2003
Longitudinal cohorts (Framingham study, Nurses’ Health Study, California Teachers Study, Agricultural Health Study) Collect one or more diseases and exposures over time
Longitudinal data for exposure and disease avoid problems of temporal ambiguity
Investigation of outcomes beyond those of original interest often can be undertaken
Individual-level exposure estimates available
High-data quality Extremely high financial investment necessary over extended periods; costs depend on data collection protocol, sample size, length of observation period, etc.
A cohort is by definition a restricted group of individuals that may or may not be representative of a population of specific interest (e.g., those highly exposed to an environmental agent or those within a susceptible age or ethnicity)
Research subjects have to be willing to participate repeatedly over extended periods of time and have to be traceable
The study protocol dictates exactly for which disease and exposures information will be collected, unless biological samples can be stored for later analyses (which may have legal implications for consent) Hunter et al. 1990
Garland et al. 1995
Feskanich et al. 1998
Laden et al. 1999, 2001
Alavanja et al. 2003
Abbreviations: CHIS, California Health Interview Survey; ISAAC, International Study of Asthma and Allergies in Childhood; MONICA, Monitoring of Trends and Determinants in Cardiovascular Diseases.
Table 4 Issues for expansion and contraction of an EPHT system.
Have scientific data provided compelling new evidence of disease–exposure associations or evidence that previously suspected associations are not causal?
Are there new technologies (biomarkers, molecular dosimeters) that indicate the need to updated data collection procedures?
Have there been changes in nosology that require new case definitions?
Are there new sources of ongoing data collection (routine public health, research cohorts) that offer cost-efficient opportunities to expand surveillance activities?
Have there been changes to sources of exposure data that either improve their quality or render them no longer suitable for routine surveillance?
Is there public concern about an environmental health issue for which surveillance is the most efficient mechanism to acquire preliminary data?
Is there widespread use of a new substance/chemical with the potential for exposing a large population or biopersistence of a substance (e.g., phthalates)?
==== Refs
References
Alavanja MC Samanic C Dosemeci M Lubin J Tarone R Lynch CF 2003 Use of agricultural pesticides and prostate cancer risk in the Agricultural Health Study cohort Am J Epidemiol 157 9 800 914 12727674
Chapman RS Hadden WC Perlin SA 2003 Influences of asthma and household environment on lung function in children and adolescents: the Third National Health and Nutrition Examination Survey Am J Epidemiol 158 2 175 189 12851231
CDC 2004. National Program of Cancer Registries: The Foundation for Cancer Prevention and Control. Atlanta, GA:National Center for Chronic Disease Prevention and Health Promotion, Centers for Disease Control and Prevention. Available: http://www.cdc.gov/cancer/npcr/about2004.htm [accessed 21 November 2004].
CDC 2005. About CDC. Atlanta, GA:Centers for Disease Control and Prevention. Available: http://www.cdc.gov/aboutcdc.htm [accessed 22 January 2005].
D’Souza G Lee JH Paffel JM 2003 Outbreak of syphilis among men who have sex with men in Houston, Texas Sex Transm Dis 30 12 872 873 14646631
Feskanich D Owusu W Hunter DJ Willett W Ascherio A Spiegelman D 1998 Use of toenail fluoride levels as an indicator for the risk of hip and forearm fractures in women Epidemiology 9 4 412 416 9647905
Garland M Morris JS Stampfer MJ Colditz GA Spate VL Baskett CK 1995 Prospective study of toenail selenium levels and cancer among women J Natl Cancer Inst 87 7 497 505 7707436
Hirsch T Weiland SK von Mutius E Safeca AF Gräfe H Csaplovics E 1999 Inner city air pollution and respiratory health and atopy in children Eur Resp J 14 3 669 677
Hunter DJ Morris JS Stampfer MJ Colditz GA Speizer FE Willett WC 1990 A prospective study of selenium status and breast cancer risk JAMA 264 9 1128 1131 2384937
Keil U Weiland SK Duhme H Chambless L 1996 The International Study of Asthma and Allergies in Childhood (ISAAC): objectives and methods; results from German ISAAC centres concerning traffic density and wheezing and allergic rhinitis Toxicol Lett 86 2–3 99 103 8711784
Koch T In press. The map as intent: variations on the theme of John Snow. Cartographica.
Laden F Hankinson SE Wolff MS Colditz GA Willett WC Speizer FE 2001 Plasma organochlorine levels and the risk of breast cancer: an extended follow-up in the Nurses’ Health Study Int J Cancer 91 4 568 574 11251983
Laden F Neas LM Spiegelman D Hankinson SE Willett WC Ireland K 1999 Predictors of plasma concentrations of DDE and PCBs in a group of U.S. women Environ Health Perspect 107 75 81 9872720
Liddell FDK 2001 The interaction of asbestos and smoking in lung cancer Ann Occup Hyg 45 341 356 11418084
MacIntosh DL Spengler JD Ozkaynak H Tsai L Ryan PB 1996 Dietary exposures to selected metals and pesticides Environ Health Perspect 104 202 209 8820589
Mann JK Tager IB Lurmann F Segal M Quesenberry CP Jr Lugg MM 2002 Air pollution and hospital admissions for ischemic heart disease in persons with congestive heart failure or arrhythmia Environ Health Perspect 110 1247 1252 12460805
Mooney G 1997 Professionalization in public health and the measurement of sanitary progress in nineteenth-century England and Wales Soc Hist Med 10 1 53 78 11619192
Mortimer KM Neas LM Dockery DW Redline S Tager IB 2002 The effect of air pollution on inner-city children with asthma Eur Respir J 19 4 699 705 11999000
Murphy RS Kutz FW Strassman SC 1983 Selected pesticide residues or metabolites in blood and urine specimens from a general population survey Environ Health Perspect 48 81 86 6825639
Peters A Frohlich M Doring A Immervoll T Wichmann HE Hutchinson WL 2001 Particulate air pollution is associated with an acute phase response in men; results from the MONICA-Augsburg Study Eur Heart J 22 14 1198 1204 11440492
Ramadour M Burel C Lanteaume A Vervloet D Charpin D Brisse F 2000 Prevalence of asthma and rhinitis in relation to long-term exposure to gaseous air pollutants Allergy 55 12 1163 1169 11117274
Reynolds P Von Behren J Gunier RB Goldberg DE Hertz A Harnly ME 2003 Childhood cancer and agricultural pesticide use: an ecologic study in California Environ Health Perspect 110 319 324 11882484
Ritz B Yu F 1999 The effect of ambient carbon monoxide on low birth weight among children born in Southern California between 1989 and 1993 Environ Health Perspect 107 17 25 9872713
Ritz B Yu F Chapa G Fruin S 2000 Effect of air pollution on preterm birth among children born in Southern California between 1989 and 1993 Epidemiology 11 502 511 10955401
Ritz B Yu F Chapa G Fruin S Shaw G Harris J 2002 Ambient air pollution and birth defects Am J Epidemiol 155 17 25 11772780
Rothman K 1986. Modern Epidemiology. Boston:Little Brown & Co.
Rothman K 1990 A sobering start for the cluster busters’ conference. Keynote presentation Am J Epidemiol 132 suppl 1 S6 S13 2356837
Ruckart PZ Kakolewski K Bove FJ Kaye WE 2004 Long-term neurobehavioral health effects of methyl parathion exposure in children in Mississippi and Ohio Environ Health Perspect 112 46 51 14698930
Salmeron J Lazcano-Ponce E Lorincz A Hernandez M Hernandez P Leyva A 2003 Comparison of HPV-based assays with Papanicolaou smears for cervical cancer screening in Morelos State, Mexico Cancer Causes Control 14 6 505 512 12948281
Shaw GM Wasserman CR O’Malley CD Nelson V Jackson RJ 1999 Maternal pesticide exposure from multiple sources and selected congenital anomalies Epidemiology 10 1 60 66 9888281
WHO 1978. International Classification of Diseases, 9th Revision. Geneva:World Health Organization.
WHO 1993. International Classification of Diseases, 10th Revision. Geneva:World Health Organization.
Wilhelm M Ritz B 2003 Residential proximity to traffic and adverse birth outcomes in Los Angeles County, California, 1994–1996 Environ Health Perspect 111 207 116 12573907
|
15743709
|
PMC1253746
|
CC0
|
2021-01-04 23:40:58
|
no
|
Environ Health Perspect. 2005 Mar 2; 113(3):243-249
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7450
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7519ehp0113-00025015743710ResearchArticlesUrinary Trivalent Methylated Arsenic Species in a Population Chronically Exposed to Inorganic Arsenic Valenzuela Olga L. 1Borja-Aburto Victor H. 2Garcia-Vargas Gonzalo G. 3Cruz-Gonzalez Martha B. 4Garcia-Montalvo Eliud A. 1Calderon-Aranda Emma S. 1Del Razo Luz M. 11Seccion de Toxicología, Cinvestav-IPN, México DF, México2Salud en el Trabajo, Instituto Mexicano del Seguro Social, México DF, México3Facultad de Medicina, Universidad Juárez del Estado de Durango, Gómez Palacio, Durango, México4Servicios de Salud del Estado de Hidalgo, Pachuca, MéxicoAddress correspondence to L.M. Del Razo, Sección de Toxicología, Cinvestav-IPN, P.O. Box 14-740, Avenida Instituto Politécnico Nacional #2508, Colonia Zacatenco, CP 07300 México DF, México. Telephone: 52-55-5061-3307. Fax: 52-55-5747-7111. E-mail:
[email protected] greatly appreciate the help of Coordinación de Investigación, Servicios de Salud de Hidalgo, and personnel from Centro de Salud de la Jurisdicción de Zimapan for coordinating the fieldwork. We thank D.J. Thomas (U.S. Environmental Protection Agency) for provision of custom-synthesized methylated trivalent arsenicals.
This study was supported by the Mexican Council for Science and Technology (Conacyt 38471-M).
The authors declare they have no competing financial interests.
3 2005 22 11 2004 113 3 250 254 23 8 2004 22 11 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Chronic exposure to inorganic arsenic (iAs) has been associated with increased risk of various forms of cancer and of noncancerous diseases. Metabolic conversions of iAs that yield highly toxic and genotoxic methylarsonite (MAsIII) and dimethylarsinite (DMAsIII) may play a significant role in determining the extent and character of toxic and cancer-promoting effects of iAs exposure. In this study we examined the relationship between urinary profiles of MAsIII and DMAsIII and skin lesion markers of iAs toxicity in individuals exposed to iAs in drinking water. The study subjects were recruited among the residents of an endemic region of central Mexico. Drinking-water reservoirs in this region are heavily contaminated with iAs. Previous studies carried out in the local populations have found an increased incidence of pathologies, primarily skin lesions, that are characteristic of arseniasis. The goal of this study was to investigate the urinary profiles for the trivalent and pentavalent As metabolites in both high- and low-iAs–exposed subjects. Notably, methylated trivalent arsenicals were detected in 98% of analyzed urine samples. On average, the major metabolite, DMAsIII, represented 49% of total urinary As, followed by DMAsV (23.7%), iAsV (8.6%), iAsIII (8.5%), MAsIII (7.4%), and MAsV (2.8%). More important, the average MAsIII concentration was significantly higher in the urine of exposed individuals with skin lesions compared with those who drank iAs-contaminated water but had no skin lesions. These data suggest that urinary levels of MAsIII, the most toxic species among identified metabolites of iAs, may serve as an indicator to identify individuals with increased susceptibility to toxic and cancer-promoting effects of arseniasis.
arsenicarsenic skin lesionsarsenic speciationhyperkeratosishyperpigmentationhypopigmentationmetabolismmethylationtrivalent arsenictrivalent methylarsenic speciesurine metabolites
==== Body
Arsenic is a ubiquitous element found in several forms in foods and environmental media such as soil, air, and water; the predominant form in drinking water is inorganic As (iAs), which is both highly toxic and readily bioavailable. iAs is a recognized carcinogen in humans [National Research Council (NRC) 2001]. Chronic ingestion of iAs-contaminated drinking water is therefore considered the major pathway behind the risk to human health. It has been estimated that 200 million people worldwide are at risk from health effects associated with high concentrations of As in their drinking water (NRC 2001). Several other regions in the world are exposed to levels above the maximum permissible limit recommended by the World Health Organization (WHO 1993).
In humans, the chronic ingestion of iAs (> 500 μg/day As) has been associated with cardiovascular, nervous, hepatic, and renal alterations and diabetes mellitus as well as cancer of the skin, bladder, lung, liver, and prostate [Agency for Toxic Substances and Disease Registry (ATSDR) 2000]. Characteristic features of arseniasis include skin manifestations, such as hyperpigmentation, hypopigmentation, and hyperkeratosis on the palms and soles, and skin cancer at later stages (Cebrian et al. 1983; Schwartz 1997; Tseng et al. 1968).
In humans, the mechanism by which iAs exerts its toxic effects is very complex because its metabolism involves at least five metabolites that can exert toxic effects. The scheme for the stepwise conversion of arsenite (iAsIII) into mono-, di-, and trimethylated products is as follows:
Briefly, the metabolic process is carried out in two processes: a) the reactions of reduction that convert the pentavalent species to trivalency, and b) reactions of oxidative methylations where iAs is converted to mono-, di-, and trimethyl arsenic forms (MAs, DMAs, and TMAsO, respectively). Thus, both pentavalent methylarsenic (MAsV) and trivalent methylarsenic (MAsIII) forms are intermediates or products of this pathway (Lin et al. 2002; Thomas et al. 2004).
Using S-adenosylmethionine as a methyl group donor, As methyltransferase (Cyt19, EC 2.1.1.138) has been shown to catalyze reactions, reduction and oxidative methylation, in rodents and humans (Waters et al. 2004). Other studies have shown the capacity of two mammalian proteins to reduce iAsV, glutathione S-transferase omega (GST Ω, EC 2.5.1.18) (Zakharyan et al. 2001) and the purine nucleoside phosphorylase (PNP, EC 2.4.2.1) (Nemeti et al. 2003; Radabaugh et al. 2002).
Urinary As is generally regarded as the most reliable indicator of recent exposure to iAs and is used as the main biomarker of exposure (Mushak and Crocetti 1995). In addition, the urinary profiles of iAs metabolites have frequently been used in epidemiologic studies to assess the capacity of exposed individuals to methylate iAs. During almost 20 years, the methylation of iAs has been generally evaluated using urinary measurement of iAs (III + V), MAs (III + V), and DMAs (III + V) in people exposed to As. Nevertheless, the differentiation of the trivalent intermediaries of As metabolism is important because the trivalent methylated arsenicals, MAsIII and DMAsIII, are more potent than either iAsIII or iAsV in cytotoxicity (Styblo et al. 2000), genotoxicity (Mass et al. 2001; Nesnow et al. 2002), and inhibition of enzymes with antioxidative functions (Lin et al. 2001; Styblo et al. 1997). Therefore, the formation of MAsIII and DMAsIII in the methylation pathway for iAs may play a significant role in the induction of toxic effects associated with exposures to iAs.
The goal of this study was to assess the urinary pattern of As methylation, including trivalent methylated metabolites, in an As-endemic population using freshly collected samples analyzed as soon as possible to avoid the oxidation of MAsIII and DMAsIII, even at temperatures < 0°C (Del Razo et al. 2001; Gong et al. 2001). Additionally, we compared the pattern of urinary trivalent methylated metabolites between persons with and without skin lesions associated with arsenicism in an endemic Mexican area.
Materials and Methods
Site selection.
Study subjects were residents of Zimapan in the state of Hidalgo, an area located in the central part of Mexico, approximately 220 km from Mexico City. It has been a mining district since the 16th century. By 1810 there were 40 smelters operating in and around Zimapan (Garcia and Querol 1991). There have been no active smelters in Zimapan since the 1940s; however, tailing piles from the flotation process have accumulated in Zimapan for > 60 years. Tailings are sediments resulting from settling of ore’s wastes. Some rocks from the Zimapan Valley with higher than world average iAs concentrations for the rock type (2,550–21,400 mg/kg) were found in all the tailings (Mendez and Armienta 2003). Most of the current exposure occurs outside the Zimapan basin, but old tailings near the edge of the town are still an iAs pollution source. Two major pathways contaminate ground-water with iAs: a) iAs dissolved from ore and other minerals in the mining district can be transported through fractures in the limestone (mainly arsenopyrite) to water sources, and b) rainwater leaches through surrounding mine tailing piles (Armienta et al. 1997a). The National Water Commission of Mexico found high iAs concentrations in many of the wells in 1992. Water samples collected from springs and drilled wells (~ 180 m total depth) presented levels between 21 and 1,100 μg As/L (Comisión Nacional del Agua 1992).
In 1999, the municipality closed one of the wells connected to the municipal water system that contained the highest iAs concentration (1,100 μg/L). This action reduced the average iAs concentration in the municipal water from 580 to 350 μg/L. However, > 40% of the valley residents in this area are not connected to this municipal supply and rely on local springs and norias (bucket-wheel wells) for their potable water, and some of these sources are still heavily polluted with iAs.
Subject selection.
We conducted a cross-sectional study with 104 participants who lived in areas where their drinking water normally contained iAs, 76 Zimapan residents exposed to ≥ 50 μg/L iAs and 28 individuals exposed to ≤ 10 μg/L iAs (controls), in accordance with the regulations of the Ethical Committee of the Faculty of Medicine, Juarez University of Durango. Subjects were recruited through door-to-door contact. They had to be at least 15 years of age and live in the town for the previous 2 years. Before enrollment in the study, each participant read and signed an informed consent form. Subjects were interviewed by trained interviewers regarding general characteristics with emphasis in personal habits, history and habits of water consumption, smoking habits, and medical, occupational, and residential histories. They underwent physical examination looking for typical dermatologic signs of arseniasis. These signs of arseniasis were evaluated by medical health care physicians, who were blind to time and level of exposure for each subject at the time of physical examination. The physicians have been evaluating dermatologic signs of arseniasis in Mexico for about 10 years. Participants were asked to exclude seafood from their diets for the preceding 4 days. Individuals who had received drugs with well-defined organ toxicity within the past 4 months or were suffering chronic alcoholism were excluded. Each family’s drinking water was analyzed for total As (TAs) concentration. The final decision on study eligibility was based on the measurement of TAs concentration in the household water source, and approximately 50% of the iAs-high exposed group presented with at least one skin sign of arseniasis, such as hypo/hyperpigmentation, palmoplantar hyperkeratosis, and ulcerative lesions as described by Yeh (1973).
Exposure assessment.
We estimated the total liters of drinking water consumed per day by each subject on the basis of subjects’ statements. Daily estimates of As consumption were calculated as the product of the number of liters consumed per day and the As concentration in the subject’s drinking water source. Cumulative exposure to iAs or time-weighted iAs exposure (TWE) was calculated using the duration of exposure, the number of liters consumed per day, and the historical As concentration reported by the Mexican National Water Commission from 1992 to the present time (Garcia-Vargas et al. 1994).
Chemicals.
Arsenic acid disodium salt (Na2HAsVO4) and sodium m-arsenite (NaAsIIIO2), both > 99% pure, were obtained from Sigma Chemical Co. (St. Louis, MO, USA). Methylarsonic acid (MAsV) disodium salt [CH3AsVO(ONa)2; 99% pure] was obtained from Ventron (Danvers, MA, USA), and dimethylarsinic acid [DMAsV; as (CH3)2AsVO(OH); 98% pure] was obtained from Strem (Newburyport, MA, USA). The trivalent methylated arsenicals methyloxoarsine (MAsIIIO; CH3AsIIIO) and iododimethylarsine of DMAsIII [DMAsIIII; (CH3)2AsIIII] were synthesized by W.R. Cullen (University of British Columbia, Vancouver, British Columbia, Canada) using previously described methods (Cullen et al. 1984; Styblo et al. 1997). Identity and purity of the synthesized arsenicals were confirmed using 1H nuclear magnetic resonance, mass spectrometry, and hydride generation–atomic absorption spectrophotometry (HG-AAS) as previously described (Hughes et al. 2000). In aqueous solutions, MAsIIIO and DMAsIIII are presumed to form MAsIII and DMAsIII, respectively. Working standards of these arsenicals that contained 1 μg/mL As were prepared daily from stock solutions. Sodium borohydride (NaBH4) was obtained from EM Science (Gibbstown, NJ, USA). Tris hydrochloride was purchased from J.T. Baker (Phillipsburg, NJ, USA). Creatinine kits were purchased from Randox (San Diego CA, USA). All other chemicals used were at least analytical grade. Standard reference material (SRM) water (SRM 1463c) and urine [SRM 2670; National Institute of Standards and Technology (NIST), Gaithersburg, MD, USA] were used for quality control of TAs in water and urine analysis, respectively.
Drinking-water collection and processing.
Tap water samples were collected in the homes of potential subject families using acid-washed containers transported to the site of the study by the investigators. We collected a total of 91 water samples from 80 households (more than one sample was obtained from each household if participants used different sources of water to drink and cook). Water samples were stored at −20°C until subsequent assay. Water samples were transported to the Cinvestav-IPN laboratories in Mexico City for TAs analysis. TAs was determined by HG-AAS using a PerkinElmer 3100 spectrometer (PerkinElmer, Norwalk, CT, USA), equipped with a FIAS-200 flow injection atomic spectroscopy system as reported previously (Del Razo et al. 1990). All measurements were made using an As electrodeless discharge lamp. SRM 1463c was used for quality control of TAs in water analysis. The certified TAs concentration in SRM 1463c is 82.1 ± 1.2 μg/L. Replicate analyses of this SRM using the method described above gave concentrations of 82.7 ± 1.7 μg/L, which is in good agreement with the certified value.
Urine collection and processing.
After clinical exploration, all participants were scheduled for urine sample collection each third day over 3 weeks in groups of 10–12 individuals each time. Subjects were seen between 0700 and 0800 hr at the local health center, where urine spot samples were collected with a minimum of contamination in 250-mL polypropylene containers that we provided. Urine samples were immediately frozen in dry ice. To prevent oxidation of unstable trivalent methylated arsenicals, frozen urine samples were immediately transported to Cinvestav-IPN laboratory and analyzed within 6 hr after collection.
A pH-specific HG-AAS has been optimized to permit simultaneous analysis of all known metabolites of iAs, including iAsIII, iAsV, MAsIII, MAsV, DMAsIII, and DMAsV in urine (Del Razo et al. 2001). This method is based on a pH-specific generation of hydrides from tri- and pentavalent iAs, MAs, and DMAs with subsequent chromatography and determination of As contents in HG-AAS. The HG-AAS apparatus was based on the design of Crecelius et al. (1986). For hydride generation at ≤ pH 2, 1 mL sample urine, 5 mL deionized water, and 1 mL 6 M hydrochloric acid (HCl) were placed into the reaction vessel. This mixture had a final pH of 1–2. For hydride generation at pH 6, 1 mL sample urine, 5 mL deionized water, 1 mL 2.5 M Tris-HCl, and 0.06 M NaOH buffer, pH 6, were placed into the reaction vessel. This mixture had a final pH of approximately 6. At either pH, thorough mixing of the contents of the reaction vessel was followed by injection into the reaction vessel of 1 mL of a 4% solution of NaBH4 in 0.02 M NaOH. Cold-trapped arsines were released from the U-tube by its removal from the liquid nitrogen and application of heat, for separation of the later arsines for a gradient of temperature.
We used SRM 2670 to validate analysis of TAs; SRM 2670 consists of two bottles of urine—one containing an elevated concentration of As and one containing a normal concentration. The certified TAs concentration in the elevated urine is 480 ± 100 μg/L. As in normal urine is not certified; however, the NIST provides a reference value of 60 μg/L. Replicate analyses of these SRMs using the method described above give concentrations of 507 ± 17 μg/L and 64 ± 5 μg/L, respectively, which are in good agreement with the certified and reference values. The TAs concentration in urine samples reported in this article is the sum of the concentrations of iAsIII, iAsV, MAsIII, MAsV, DMAsIII, and DMAsV.
Creatinine in urine.
Urinary creatinine was measured by the Jaffe reaction using a Randox commercial kit. Arsenical species concentrations in urine were corrected for creatinine concentration as an indication of urine dilution.
Statistical methods.
Data analysis was carried out using Stata 8.0 statistical software (Stata Corp., College Station, TX, USA). Arsenical values were transformed to a log scale in order to calculate means and range, to perform statistical comparisons between groups, and to evaluate potential confounding factors. We used Mann-Whitney tests to compare urinary As metabolites among exposed groups with and without lesions. Potential confounding risk factors evaluated included age, sex, sunlight exposure, and TWE.
Results
Eighty families with a total of 104 participants completed the sampling protocol (Table 1). Because of the lack of good job opportunities in this area, most of the young men emigrate out of the country; in consequence, most of the subjects (90%) were female. The concentration of TAs in home drinking water of study participants ranged from 1 to 1,054 μg/L. In 24 homes (30%), the subjects drank bottled water in addition to municipal water.
Urine samples from both controls and individuals chronically exposed to high iAs by consumption of drinking water containing this metalloid were analyzed to determine the concentrations of iAsIII, MAsIII, and DMAsIII. Arsenical values were adjusted by creatinine concentration. Urinary creatinine measurements ranged from 105 to 3,230 mg/L, with an average of 595 mg/L. Average urinary concentrations of trivalent and pentavalent As species in the total study group are shown in Table 2. Methylated trivalent arsenicals were detected in 98% of analyzed urine samples. In addition, trivalent arsenicals (iAsIII + MAsIII + DMAsIII) were the predominant species in urine samples (65%). On average, the major metabolite, DMAsIII, represented 49% of total urinary As, followed by DMAsV (23.7%), iAsV (8.6%), iAsIII (8.5%), MAsIII (7.4%), and MAsV (2.8%).
Cutaneous signs of arsenicism were observed in 55 individuals from the group exposed to ≥ 50 μg/L As in drinking water. The type and proportion of cutaneous signs observed in participants of this study are shown in Table 3. Hyperkeratosis in the palm or sole was the most frequent skin sign of arsenicism (56.6%).
Table 4 summarizes the average arsenical concentrations according to the level of As exposure and the presence of skin lesions. Interestingly, in the high-As-exposure group, subjects presenting cutaneous signs had significant increases in the concentration of MAsIII. In addition, the average of relative proportion of urinary MAsIII was marginally higher in exposed individuals with skin lesions compared with those who drank iAs-contaminated water but had no skin lesions (Table 5).
The conditional logistic regression model was based on 76 subjects exposed to ≥ 50 μg/L As in drinking water; this model was adjusted by age, sex, and TWE. The risk of occurrence of arseniasis related to both absolute and relative quantity of MAsIII was significant (p < 0.008 and < 0.004, respectively). The odds ratios (OR) for the subjects having hyperkeratosis plantar was estimated to be 1.06 [95% confidence interval (CI), 1.03–1.19] for concentration of MAsIII and 1.22 (95% CI, 1.07–1.44) for relative proportion of MAsIII. Even though DMAsIII was the main species found in urine, neither its concentration nor its relative proportion was associated with the risk of As skin lesions (data not shown).
Another variable, independent of iAs metabolites, that was significantly associated with the presence of hyperkeratosis plantar (p = 0.003) in the group who drank water containing As > 50 μg/L was the lifetime iAs exposure, estimated as TWE (OR = 1.20; 95% CI, 1.06–1.35).
Discussion
MAsIII and DMAsIII in urine.
The analysis of urinary trivalent methylated metabolites of iAs using freshly collected urine samples, within 6 hr of collection to reduce differences in handling among samples and to minimize the extent of oxidation of trivalent arsenicals before analysis, allowed detection of the presence of MAsIII and DMAsIII in 98% of the urine collected, even in urine samples from subjects with low As exposure (≤ 10 μg/L in drinking water; Table 4). The optimization of As speciation techniques has only recently permitted analysis of oxidation states of As in methylated metabolites. Initial studies using the optimized techniques detected small amounts of MAsIII and/or DMAsIII in urine from residents exposed to iAs in drinking water in several geographical regions, including Romania (Aposhian et al. 2000), Inner Mongolia (Le et al. 2000), Mexico (Del Razo et al. 2001), and West Bengal (Mandal et al. 2001). However, most of these studies analyzed urine samples that were stored for an extended time after collection. Because MAsIII and DMAsIII are rapidly oxidized even at temperatures < 0°C (Del Razo et al. 2001; Gong et al. 2001), these studies probably underestimated the concentrations of these metabolites. In contrast, analyses of freshly collected urine samples in this study showed that methylated trivalent arsenicals (MAsIII and DMAsIII) are in fact prevalent urinary metabolites of iAs (Table 2). DMAsIII also was detected only when fresh void urine was collected from DMAsV-fed rats (Cohen et al. 2002). Csanaky and Gregus (2002) reported that intravenously injected iAs was excreted mainly as MAsIII, and Suzuki et al. (2001) reported that this excreted MAsIII was conjugated by glutathione [MAsIII(GS)2] in rat bile.
Urinary detection of methylated and dimethylated arsenicals containing As in both oxidation states indicates that metabolism of As involves changes in the oxidation state of As during methylation. It is likely that interactions of trivalent iAs metabolites with proteins and other cellular constituents are responsible for retention and toxic effects of As in tissues of animals and humans exposed to iAs. A study with a population chronically exposed to iAs from drinking water indicated that methylated arsenicals are also retained in tissues (Aposhian et al 1997, 2000). These As-exposed individuals were treated with an As chelator, 2,3-dimercaptopropane-1-sulfonic acid (DMPS), which resulted in a massive release of MAs, including MAsIII, in urine, suggesting that DMPS mobilized tissue depots of iAs.
Skin lesions and trivalent methylated metabolites of iAs.
Skin keratosis and changes in skin pigmentation are two hallmark signs of arseniasis. Many residents of the Zimapan area had skin lesions related to iAs exposure (Armienta et al. 1997b) (Table 3). According to the historical values of As in drinking water, most of the families who participated in this study were exposed to extremely high As concentrations at least from 1992 to 1999. After this time, the level of concentration of As in water has been decreased because the municipality closed one of the wells connected to the municipal water system that contained the highest iAs concentration (1,100 μg/L). In addition, several residents previously drank bottled water with normal values of As instead of drinking water from the municipal system. This fact can explain the great prevalence of dermatoxicity, despite the moderate concentration of arsenicals in urine observed in the present study (Table 4).
We also assessed the profile of iAs metabolites on dermatoxicity (Table 3). Previous studies in other regions, such as the Lagunera Region in Mexico (Del Razo et al. 1997) and Taiwan (Yu et al. 2000), showed that subjects with arseniasis were more likely to have a higher concentration of MAs in urine than were exposed individuals who had did not have arseniasis; at that time, the speciated arsenical concentrations in urine were made without mentioning their oxidation state. Recent advent of techniques for speciation of As has helped establish the speciation of As according to oxidation states.
Importantly, trivalent methylated metabolites, especially DMAsIII, were not stable in human urine and oxidized quickly to yield pentavalent MAsV and DMAsV (Del Razo et al. 2001). As noted above, these samples were analyzed within 6 hr of collection to reduce differences among samples in handling and to minimize the extent of oxidation of AsIII before analysis.
Interestingly, in our study the iAs-exposed individuals bearing skin signs of arsenicism had significantly higher urinary relative proportions and concentrations of MAsIII. These data suggest that a high output of MAsIII in urine may predict increased susceptibility to arseniasis.
MAsIII and DMAsIII have been reported to be highly toxic in mammalian cells (Styblo et al. 2000, 2002) and genotoxic (Mass et al. 2001; Nesnow et al. 2002). The reason for the high toxicity of methylated trivalent arsenicals has not been adequately explained, except that methylated trivalent arsenicals exert genotoxicity via reactive oxygen species (Nesnow et al. 2002). Although the comparative toxicity of MAsIII(GS)2 was about nine times higher than that of iAsIII, the accumulation rate of MAsIII(GS)2 was 40 times higher than that of iAsIII. These results suggest that MAsIII(GS)2 was more toxic than iAsIII, at least in part due to the more efficient accumulation of As in cells (Hirano et al. 2004). Moreover, Vega et al. (2001) showed that normal human epidermal keratinocytes exposed to low doses (0.001–0.01 μM) of MAsIII stimulated expression of certain proinflammatory cytokines and growth factors that are critical to maintaining homeostasis and barrier integrity in the skin, suggesting that the overexpression of these products can lead the skin pathologic processes.
Another possible mechanism for higher toxicity of trivalent arsenicals compared with the corresponding pentavalent forms is that trivalent species have a higher affinity for thiol compounds (Shiobara et al. 2001).
In light of these observations, biomethylation of iAs, a process yielding toxic trivalent methylated metabolites, appears to be a mechanism of activation of As as a toxin and possibly as a carcinogen. Because of the adverse biologic effects of these metabolites, the analysis of urinary MAsIII may serve as an effective tool for the evaluation of health risks associated with exposure to iAs.
There were no significant associations between other confounding risk factors, such as duration of sunlight, and skin lesions (data not shown).
Another important factor associated with the presence of As skin lesions was the lifetime exposure of As evaluated as TWE. Table 1 shows the significant difference between this variable between exposed As subjects, demonstrating that the magnitude of exposure is directly related to the presence of skin lesions. In other words, the basic principle of dose–response relationship was fulfilled for the presence of As skin lesions.
The major limitations of this study are the small sample population and the fact that most of the participants were female. Previous reports have indicated that age, dose, pregnancy, and sex are among factors that affect the urinary profiles of iAs metabolites (Del Razo et al. 1997; Hughes et al. 2000; Yu et al. 2000). Results obtained in this study may not generalize to males or to the entire population.
This study provides novel data on the pattern of trivalent and pentavalent metabolites of iAs clearance in fresh urine from a population exposed to iAs in drinking water. Unlike other studies, in which urine samples were stored for several weeks before analysis, this study shows that MAsIII and DMAsIII in urine are predominant As species compared with their corresponding pentavalent arsenicals.
MAsIII, the most potent toxicant in the entire metabolic pathway of iAs, could be mainly responsible for the toxic and carcinogenic effects of iAs exposure, and its detection and quantification in human populations can assist in risk assessment and could be the cause of As carcinogenesis. Our findings support the view that the extent and character of adverse effects associated with iAs exposures are at least in part determined by the rate of the formation and by the composition of iAs metabolites.
Further research in other populations with arseniasis is needed to confirm the potential relationship between the concentrations of MAsIII in biologic samples from human populations and the little-understood etiology of hyperkeratosis, skin hypo- or hyperpigmentation, and cancer that can result from chronic iAs exposure.
Table 1 Demographics of the study population.
Low iAs exposure
High iAs exposure
Characteristics Control Without skin lesions With skin lesions
No. of subjects 28 21 55
Sexa
Male 2 (7.1) 1 (4.8) 7 (14.6)
Female 26 (92.9) 20 (95.2) 48 (85.4)
Age (years) 35 (18–50) 35 (21–49) 35 (15–51)
Sunlight exposure (hours) 2.3 (0–8) 2.2 (0–8) 2.8 (0–9)
TAs concentration in drinking water (μg/L) 1.6 (1–6) 117 (50–1,504) 115 (50–658)
Duration of iAs exposure (years)b 26 (4–50) 21 (4–49) 26 (4–51)
TWE (mg) 0.01 (0.01–0.06) 5.8 (0.02–16.3) 9.3 (0.23–26.9)*
Values are mean (range) except where noted.
a Values are mean (%).
b Duration of well water consumption.
* Statistically significant difference (p < 0.05) between the exposed individuals with and without skin lesions.
Table 2 Concentration and relative proportion of As species in residents of the Zimapan area (n = 104).
iAs metabolite in urine Concentration (μg/g creatinine) Relative proportion (%)
iAsV 5.84 (1–65.5) 8.6
iAsIII 4.46 (0.1–172.3) 8.5
MAsV 1.45 (0.1–28.3) 2.8
MAsIII 4.93 (0.1–101.9) 7.4
DMAsV 14.56 (1–710) 23.7
DMAsIII 30.75 (0.1–506.3) 49
TAs 84.85 (9.1–1398.1) 100
Concentration of metabolites of As in urine are reported as geometric mean (range).
Table 3 Distribution of skin lesion in iAs-exposed subjects (n = 76).
Frequency [no. (%)]
Skin lesion With lesion w/o lesion
Hypopigmentation 36 (47.4) 40 (52.6)
Hyperpigmentation 29 (38.2) 47 (61.8)
Hypo-/hyperpigmentation 9 (11.8) 67 (88.2)
Hyperkeratosis on the palms 33 (43.4) 43 (56.6)
Hyperkeratosis on the soles 30 (39.5) 46 (60.5)
Hyperkeratosis on the palms or soles 43 (56.6) 33 (43.4)
Keratosis on the trunk 17 (22.4) 59 (77.6)
Cutaneous horns 4 (5.3) 72 (94.7)
Bowen’s disease 1 (1.3) 75 (98.7)
Squamous cell carcinoma 1 (1.3) 75 (98.7)
w/o, without. Frequency was calculated for 76 subjects exposed to ≥ 50 μg/L As in drinking water.
Table 4 Urinary pattern of iAs species in humans exposed to As through drinking water in the Zimapan area, according to level exposition and the presence of As skin lesions (n = 104).
Metabolite concentration of iAs in urine (μg/g creatinine)
As species Control (n = 28) Exposed, without lesions (n = 21) Exposed, with lesions (n = 55)
IAsV 3.6 (1.0–10.5) 6.1 (2.0–37.2) 8.2 (2.4–65.5)
IAsIII 1.6 (0.1–9.7) 6.9 (1.5–101.6) 6.3 (0.3–172.3)
MAsV 0.6 (0.1–5.5) 1.8 (0.3–16.6) 2.0 (0.1–28.3)
MAsIII 2.2 (0.4–9.6) 4.8 (0.1–24.9) 7.5 (0.2–101.9)*
DMAsV 7.4 (1.8–38.5) 15.9 (1.0–226.5) 19.8 (1.0–710.1)
DMAsIII 7.9 (0.1–65.4) 48.1 (2.2–206) 51.9 (1.4–506.3)
TAs 33.3 (9.1–106) 116 (61.2–371.7) 121.2 (51.9–1,398)
Values shown are geometric mean (range).
* Statistically significant difference (p < 0.05) between the exposed individuals with and without skin lesions (by Mann-Whitney test).
Table 5 Comparison of mean percentage of As species in urine among As-exposed subjects with and without skin lesions.
Percent As-exposed subjects
As species Without lesions (n = 21) With lesions (n = 55)
iAsV 6.5 7.9
iAsIII 10.9 8.0
MAsV 3.5 2.3
MAsIII 5.9 7.7*
DMAsV 21.5 23.1
DMAsIII 51.7 51.0
* Statistically marginal difference (p = 0.072) between the exposed individuals with and without skin lesions (by Mann-Whitney test).
==== Refs
References
Aposhian HV Arroyo A Cebrian ME Del Razo LM Hurlbut KM Dart RC 1997 DMPS-arsenic challenge test. I. Increased urinary excretion of monomethylarsonic acid in humans given dimercaptopropane sulfonate J Pharmacol Exp Ther 282 192 200 9223554
Aposhian HV Gurzau ES Le XC Gurzau A Healy SM Lu X 2000 Occurrence of monomethylarsonous acid in urine of humans exposed to inorganic arsenic Chem Res Toxicol 13 693 697 10956055
Armienta MA Rodriguez R Aguayo A Ceniceros N Villaseñor G Cruz O 1997a Arsenic contamination of groundwater at Zimapan, Mexico Hydrogeol J 5 39 46
Armienta MA Rodriguez R Cruz O 1997b Arsenic content in hair of people exposed to natural arsenic polluted ground-water at Zimapan, Mexico Bull Environ Contam Toxicol 59 583 589 9307423
ATSDR 2000. Toxicological Profile for Arsenic. Atlanta, GA:Agency for Toxic Substances and Disease Registry.
Cebrian ME Albores A Aguilar M Blakely E 1983 Chronic arsenic poisoning in the north of Mexico Hum Toxicol 2 121 233 6840787
Cohen SM Arnold LL Uzvolgyi E Cano M St John M Yamamoto S 2002 Possible role of dimethylarsinous acid in dimethylarsinic acid-induced urothelial toxicity and regeneration in the rat Chem Res Toxicol 15 1150 1157 12230408
Comisión Nacional del Agua (National Water Commission) 1992. Estudio de Prospección Geohidrológica y Exploración Geofísica en la Zona de Tecozautla-Vizarro, Estado de Hidalgo y Queretaro. IGAMSA, Tomo 1. Informe Técnico. México DF:Comisión Nacional del Agua.
Crecelius EA Bloom NS Cowan CE Jenne EA 1986. Speciation of Selenium and Arsenic in Natural Waters and Sediments: Vol 2. Arsenic Speciation. Final Report for Electric Power Research, Palo Alto, CA. Richland, WA:Battelle Pacific Northwest Laboratories.
Csanaky I Gregus Z 2002 Species variations in the biliary and urinary excretion of arsenate, arsenite and their metabolites Comp Biochem Physiol C Toxicol Pharmacol 131 355 365 11912060
Cullen WR McBride BC Reglinski J 1984 The reaction of methylarsenicals with thiols: some biological implications J Inorg Biochem 21 179 194
Del Razo LM Arellano MA Cebrian MA 1990 The oxidation states of arsenic in well water from chronic arsenicism area of northern Mexico Environ Poll 64 143 153
Del Razo LM Garcia-Vargas GG Vargas H Albores A Gonsebatt ME Montero R 1997 Altered profile of urinary arsenic metabolites in adults with chronic arsenicism. A pilot study Arch Toxicol 71 211 217 9101036
Del Razo LM Styblo M Cullen WR Thomas DJ 2001 Determination of trivalent methylated arsenicals in biological matrices Toxicol Appl Pharmacol 174 282 293 11485389
Garcia GG Querol FS 1991. Description of some deposits in the Zimapan district, Hidalgo. In: Economic Geology, Mexico (Salas GP, ed). Boulder, CO:Geological Society of America, 295–313.
Garcia-Vargas GG Del Razo LM Cebrian ME Albores A Ostrosky-Wegman P Montero R 1994 Altered urinary porphyrin excretion in a human population chronically exposed to arsenic in Mexico Hum Exp Toxicol 13 839 847 7718303
Gong Z Lu X Cullen WR Le XC 2001 Unstable trivalent arsenic metabolites, monomethylarsonous acid and dimethylarsinous acid J Anal At Spectrom 6 1409 1413
Hirano S Kobayashi Y Cui X Kanno S Hayakawa T Shraim A 2004 The accumulation and toxicity of methylated arsenicals in endothelial cells: important roles of thiol compounds Toxicol Appl Pharmacol 198 458 467 15276427
Hughes MF Del Razo LM Kenyon EM 2000 Dose-dependent effects on tissue distribution and metabolism of dimethylarsinic acid in the mouse after intravenous administration Toxicology 143 155 166 10755702
Le XC Ma M Cullen WR Aposhian HV Lu X Zheng B 2000 Determination of monomethylarsonous acid, a key arsenic methylation intermediate, in human urine Environ Health Perspect 108 1015 1018 11102289
Lin S Del Razo LM Styblo M Wang C Cullen W Thomas DJ 2001 Arsenicals inhibit thioredoxin reductase in cultured rat hepatocytes Chem Res Toxiciol 14 305 311
Lin S Shi Q Nix FB Styblo M Beck MA Herbin-Davis KM 2002 A novel S -adenosyl-l -methionine: arsenic(III) methyltransferase from rat liver cytosol J Biol Chem 277 10795 10803 11790780
Mandal BK Ogra Y Suzuki KT 2001 Identification of dimethylarsinous and monomethylarsonous acids in human urine of the arsenic-affected areas in West Bengal, India Chem Res Toxicol 14 371 378 11304125
Mass MJ Tennant A Roop BC Cullen WR Styblo M Thomas DJ 2001 Methylated trivalent arsenic species are genotoxic Chem Res Toxicol 14 355 361 11304123
Mendez M Armienta MA 2003 Arsenic phase distribution in Zimapan mine tailings, Mexico Geofis Int 42 131 140
Mushak P Crocetti AF 1995 Risk and revisionism in arsenic cancer risk assessment Environ Health Perspect 103 684 689 7588479
Nemeti B Csanaky I Gregus Z 2003 Arsenate reduction in human erythrocytes and rats—testing the role of purine nucleoside phosphorylase Toxicol Sci 74 22 31 12730608
Nesnow S Roop BC Lambert G Kadiiska M Mason RP Cullen WR 2002 DNA damage induced by methylated trivalent arsenicals is mediated by reactive oxygen species Chem Res Toxicol 5 1627 1634 12482246
NRC (National Research Council) 2001. Arsenic in Drinking Water. Washington, DC:National Academy Press.
Radabaugh TR Sampayo-Reyes A Zakharyan RA Aposhian HV 2002 Arsenate reductase II. Purine nucleoside phosphorylase in the presence of dihydrolipoic acid is a route for reduction of arsenate to arsenite in mammalian systems Chem Res Toxicol 15 692 698 12018991
Schwartz RA 1997 Arsenic and the skin Int J Dermatol 36 241 250 9169318
Shiobara Y Ogra Y Suzuki KT 2001 Animal species difference in the uptake of dimethylarsinous acid (DMA(III)) by red blood cells Chem Res Toxicol 14 1446 1452 11599937
Styblo M Del Razo LM Vega L Germolec DR LeCluyse EL Hamilton GA 2000 Comparative toxicity of trivalent and pentavalent inorganic and methylated arsenicals in rat and human cells Arch Toxicol 74 289 299 11005674
Styblo M Drobna Z Jaspers I Lin S Thomas DJ 2002 The role of biomethylation in toxicity and carcinogenicity of arsenic: a research update Environ Health Perspect 110 767 771 12426129
Styblo M Serves SV Cullen WR Thomas DJ 1997 Comparative inhibition of yeast glutathione reductase by arsenicals and arsenothiols Chem Res Toxicol 10 27 33 9074799
Suzuki KT Tomita T Ogra Y Ohmichi M 2001 Glutathione-conjugated arsenics in the potential hepato-enteric circulation in rats Chem Res Toxicol 14 1604 1611 11743743
Thomas DJ Waters SB Styblo M 2004 Elucidating the pathway for arsenic methylation Toxicol Appl Pharmacol 198 319 326 15276411
Tseng WP Chu HM How SW Fong JM Lin CS Yeh S 1968 Prevalence of skin cancer in an endemic area of chronic arsenicism in Taiwan J Natl Cancer Inst 40 453 463 5644201
Vega L Styblo M Patterson R Cullen W Wang C Germolec D 2001 Differential effects of trivalent and pentavalent arsenicals on cell proliferation and cytokine secretion in normal human epidermal keratinocytes Toxicol Appl Pharmacol 172 225 232 11312651
Waters SB Devesa V Del Razo LM Styblo M Thomas DJ 2004 Endogenous reductants support the catalytic function of recombinant rat cyt19, an arsenic methyltransferase Chem Res Toxicol 17 404 409 15025511
WHO 1993. Guidelines for Drinking Water Quality: Recommendations. Vol 1. 2nd ed. Geneva:World Health Organization.
Yeh S 1973 Skin cancer in chronic arsenicism Human Pathol 4 469 485 4750817
Yu RC Hsu KH Chen CJ Froines JR 2000 Arsenic methylation capacity and skin cancer Cancer Epidemiol Biomarkers Prev 9 1259 1262 11097236
Zakharyan RA Sampayo-Reyes A Healy SM Tsaprailis G Board PG Liebler DC 2001 Human monomethylarsonic acid (MMA(V)) reductase is a member of the glutathione-S -transferase superfamily Chem Res Toxicol 14 1051 1057 11511179
|
15743710
|
PMC1253747
|
CC0
|
2021-01-04 23:40:57
|
no
|
Environ Health Perspect. 2005 Mar 22; 113(3):250-254
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7519
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7384ehp0113-00025515743711ResearchArticlesOccupational Exposure to Crystalline Silica Dust in the United States, 1988–2003 Yassin Abdiaziz 1Yebesi Francis 2Tingle Rex 11Directorate of Evaluation and Analysis, Office of Evaluations and Audit Analysis, and2Directorate of Cooperative and State Programs, Office of Outreach Services and Alliances, Occupational Safety and Health Administration, U.S. Department of Labor, Washington, DC, USAAddress correspondence to A.S. Yassin, Directorate of Evaluations and Analysis, Office of Evaluations and Audit Analysis, Occupational Safety and Health Administration, U.S. Department of Labor, 200 Constitution Ave. NW, Room N3641, Washington, DC 20210 USA. Telephone: (202) 693-2042. Fax: (202) 693-1641. E-mail:
[email protected] opinions expressed in this article do not necessarily represent those of the Occupational Safety and Health Administration.
The authors declare they have no competing financial interests.
3 2005 6 12 2004 113 3 255 260 2 7 2004 6 12 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. The purposes of this study were a) to summarize measurements of airborne (respirable) crystalline silica dust exposure levels among U.S. workers, b) to provide an update of the 1990 Stewart and Rice report on airborne silica exposure levels in high-risk industries and occupations with data for the time period 1988–2003, c) to estimate the number of workers potentially exposed to silica in industries that the Occupational Safety and Health Administration (OSHA) inspected for high exposure levels, and d) to conduct time trend analyses on airborne silica dust exposure levels for time-weighted average (TWA) measurements. Compliance inspection data that were taken from the OSHA Integrated Management Information System (IMIS) for 1988–2003 (n = 7,209) were used to measure the airborne crystalline silica dust exposure levels among U.S. workers. A second-order autoregressive model was applied to assess the change in the mean silica exposure measurements over time. The overall geometric mean of silica exposure levels for 8-hr personal TWA samples collected during programmed inspections was 0.077 mg/m3, well above the applicable American Conference of Governmental Industrial Hygienists threshold limit value of 0.05 mg/m3. Surgical appliances supplies industry [Standard Industrial Classification (SIC) 3842] had the lowest geometric mean silica exposure level of 0.017 mg/m3, compared with the highest level, 0.166 mg/m3, for the metal valves and pipe fitting industry (SIC 3494), for an 8-hr TWA measurement. Although a downward trend in the airborne silica exposure levels was observed during 1988–2003, the results showed that 3.6% of the sampled workers were exposed above the OSHA-calculated permissible exposure limit.
crystalline silica dustindustriesoccupationsOSHA IMISsilica exposure
==== Body
Silica is a mineral compound made up of one silicon atom and two oxygen atoms (SiO2). It has a melting point of 1,600°C and is a colorless, odorless, and noncombustible solid [American Conference of Governmental Industrial Hygienists (ACGIH) 2001]. Crystalline silica is formed when silica molecules are lined up in order and in crystal form. It is an abundant mineral in rock, sand, and soil. Quartz is a term often used to refer to crystalline silica dust.
Crystalline silica has been used in many industries such as blast furnaces, cement manufacturing, glass and concrete mixing product manufacture, ceramics, clay, glass and china pottery, electronic, foundry, sand-blasting and manufacturing abrasives, and many construction activities (Altindag et al. 2003; Flanagan et al. 2003; Irwin 2003; Rappaport et al. 2003). It is used as an abrasive agent in many industrial applications. Occupations having a high potential for exposure to crystalline silica dust (respirable quartz) are metal, coal, and nonmetal (except fuels) mining; foundry, stone clay, and glass production work; and agricultural, chemical production, highway repair, and tuck-pointing work [Akbar-Khanzadeh and Brillhart 2002; Occupational Safety and Health Administration (OSHA) 2004; Rappaport et al. 2003].
Silica dust is an inhalation hazard. Workers may be at risk of silicosis from exposure to silica dust when high-velocity impact shatters the sand into smaller, respirable (< 0.5 to 5.0 μm in diameter) dust particles. Silicosis is a disease where scar tissue forms in the lungs and reduces the ability to extract oxygen from the air. Symptoms of silicosis can be acute, accelerated, or chronic. Acute silicosis may develop within weeks and up to 5 years after breathing large amounts of crystalline silica. Accelerated silicosis may develop shortly after exposure to high concentrations of respirable crystalline silica, whereas chronic silicosis occurs after ≥10 years of exposure to relatively low concentrations of crystalline silica [American Thoracic Society 1997; National Institute for Occupational Safety and Health (NIOSH) 2002]. Many workers in a wider range of industries are exposed to silica, usually in the form of respirable quartz (OSHA 2001, 2003).
OSHA has estimated that more than 2 million workers are exposed to crystalline silica dust in the general, maritime, and construction industries (OSHA 2003). More than 100,000 workers have high-risk exposure to airborne silica dust through construction and mining operations (Akbar-Khanzadeh and Brillhart 2002; NIOSH 1991). There were an estimated 3,600–7,300 newly recognized silicosis cases per year in the United States from 1987 to 1996 (Rosenman et al. 2003). Between 1990 and 1996, 200–300 deaths per year are known to have occurred where silicosis was identified as a contributing cause on death certificates (Akbar-Khanzadeh and Brillhart 2002; OSHA 2003).
The International Agency for Research on Cancer (IARC 1987, 1997) classified crystalline silica as a known human carcinogen. Exposure to crystalline silica has been associated with an increased risk of developing lung cancer (Engholm and Englund 1995; Knutsson et al. 2000; Hughes et al. 2001; Lynge et al. 1986; Robinson et al. 1995; Stern et al. 1995). Previous studies also documented an association between airborne silica exposure and other health problems, including chronic obstructive pulmonary disease, rheumatoid arthritis, scleroderma, Sjogern’s syndrome, lupus, and renal disease (Goldsmith 1997; Hnizdo and Vallyathan 2003; Kane 1997; Parks et al. 2002).
The current OSHA permissible exposure limit (PEL) for crystalline silica is based on a particle counting formula recommended by the ACGIH in the 1970s (ACGIH 1980; OSHA 1989, 1993). In 1986, the ACGIH revised the threshold limit value (TLV) of 0.1 mg/m3 for respirable quartz (ACGIH 1986). Currently, the NIOSH (1998) and the ACGIH (2001) both recommend an occupational exposure limit of 0.05 mg/m3 for respirable crystalline silica. OSHA recognized the need to revise the PEL to reflect current sampling and analytical methods, and the agency determined to address the significant risk of silicosis and other serious diseases associated with silica through a special emphasis program (SEP) on silicosis (Dear 1996; Jeffress 1998; OSHA 2003).
The purposes of this study were a) to summarize measurements of airborne (respirable) crystalline silica dust exposure levels among U.S. workers, b) to provide an update of the Stewart and Rice (1990) report on the airborne silica exposure levels in high-risk industries and occupations with data for the time period 1988–2003, c) to estimate the number of workers potentially exposed to silica in industries that OSHA inspected for high exposure levels, and d) to conduct time trend analyses on silica dust exposure levels for time-weighted average (TWA) measurements.
Materials and Methods
Data sources.
The OSHA Integrated Management Information System (IMIS) database was used for the analysis of the airborne concentration of crystalline silica exposure (OSHA IMIS 2003). The OSHA IMIS database contained personal sample measurements of silica exposure (n = 11,036) collected during 3,732 OSHA inspections conducted between 1988 and 2003. Of the 11,036 samples, 203 duplicate measures of personal samples were excluded because the number of personal silica samples exceeded the total number of workers who were sampled. A total of 3,188 samples with missing values and 436 area and bulk samples were excluded from the analysis. The remaining 7,209 personal samples collected during 2,512 OSHA inspections were used in this analysis.
Analytic methods.
The analytic framework used in this study is based on Stewart and Rice’s (1990) method for grouping industries with the highest geometric means and those with the lowest geometric means, where five or more samples were available. We selected a sample size of five arbitrarily as the minimum number required for obtaining stable and reliable descriptive statistics. Personal samples of silica exposure measurements were stratified into two groups by type of inspections to explore if estimates of silica samples were biased in any direction: a) all 2,512 inspections and b) 948 programmed inspections. Two separate estimation analyses were conducted. First, we analyzed all personal samples (n = 7,209) of silica exposure measurements collected during OSHA inspections to determine whether estimates of silica samples collected during complaint, referral, monitoring, follow-up, and fatality inspections were highly biased toward the upper end. Second, we analyzed only personal samples (n = 2,868) randomly collected during programmed inspections. In this later analysis, samples collected during complaint, referral, monitoring, follow-up, and fatality inspections were excluded.
In this article, the term “exposure” is defined as the concentration of airborne occupational crystalline silica dust measured in the workers’ personal breathing work environment. In this study we focused on the analysis of personal samples of silica exposure levels measured as an 8-hr TWA measurement among workers in various industries and occupations, and silica levels are expressed as milligrams per cubic meter.
The term “industry” is defined as a group of establishments that primarily engaged in the same kind of economic activity, regardless of their types of ownership. Industries were coded using four-digit Standard Industrial Classification (SIC; Office of Management and Budget 1987) codes. The term “occupation” is defined as a collection of jobs or types of work requiring similar skills, responsibilities, educational requirements, training, licensure and credentials, and the like, found within various industries. To update silica exposure levels among workers with different job titles, the high-risk industries of “stonework masonry” (SIC 1741) and “gray iron foundry” (SIC 3321) with exposure levels above ACGIH TLV of 0.05 mg/m3 were selected (Dear 1996). Using 1997 county business patterns (U.S. Census Bureau 1997) and reports to OSHA inspectors by the facility (OSHA IMIS 2003), the percentage and number of workers potentially exposed to crystalline silica by selected industries were estimated.
Airborne silica measurement.
Personal samples of airborne respirable silica particles were collected using OSHA method ID-142 for quartz in workplace atmosphere using a personal sampling pump and a cyclone assembly (OSHA 1996). Using this method, a respirable sample was collected by drawing air at approximately 1.7 L/min through a 10-mm nylon Dorr-Oliver cyclone attached to a 37-mm diameter polyvinyl chloride filter cassette with a 5-μm pore size (part no. 625413, Mine Safety Appliances, Pittsburgh, PA; or cat. no. P-503700, Omega Specialty Instrument Co., Chelmsford, MA). The cyclone assembly and sampling pump were placed on an employee to collect samples of tiny respirable silica particles from the air in the breathing zone of the employee during an 8-hr work shift. Samples were properly packaged and shipped to the OSHA Salt Lake Technical Center (OSHA 1996). The sample particulates were dissolved in tetrahydrofuran and analyzed by using X-ray diffraction. The qualitative limit of detection for quartz is 5 μg. Further laboratory details are available in OSHA (1996).
Statistical analyses.
Statistical analyses were conducted using SAS software (SAS Institute, Inc. 1999). First, we conducted a univariate analysis to examine the distribution of the airborne silica exposure levels. We used natural-log transformation of airborne silica exposure levels because silica levels had a positively skewed distribution. In addition to arithmetic mean and median, geometric mean of airborne silica levels and geometric standard deviation (GSD) were calculated for each industry over the period of 1988–2003. Second, the prevalence of elevated crystalline silica exposure levels for 8-hr TWA measurements among workers in high-risk industries and occupations was estimated. Third, a non-parametric regression was applied to make multiple comparisons of silica exposure levels among different major industries, and the null hypothesis of equal variances among different categories of industries and for significant differences in mean exposure levels among industries was tested using F-test statistics. Fourth, mixed autoregressive and moving average model [ARMA (1,1)] regression analyses were conducted to evaluate time trends in the silica exposure levels. Finally, a second-order autoregressive error model was created to regress exposure levels on time with errors from one period to be related to errors from the previous two periods. A finding of p ≤ 0.05 was considered statistically significant.
The covariates examined for association with higher airborne silica levels were industry, inspections, and year. Industries were grouped into four categories based on the four-digit SIC codes: construction (1521–1799), manufacturing (2011–3299, 3411–3999), metal (3312–3399), and service combined with all other industries including wholesale and retail trade and finance, insurance and real estate, and transportation, communication, and utility (4011–9721) (Office of Management and Budget 1987). Because mining and agricultural industries were not addressed in the OSHA IMIS data, both industries were excluded from this analysis. Dummy variables were used to adjust the significant effect of various industry groups.
Results
Prevalence of elevated airborne crystalline silica in occupations and industries.
In the construction industry, “stonework masonry” (SIC 1741) that primarily engages in masonry work, stone cutting, bricklaying, and the like, has been one of the high-risk industries where overexposure to silica exists. Within occupations, the prevalence of elevated airborne silica exposure levels ≥ 0.10 mg/m3 among workers with the job title “masonry worker” in the stonework masonry industry was twice as high (6.9%) as the prevalence among workers with the job title “bricklayer” in the same industry (3.1%).
The prevalence of elevated airborne crystalline silica exposure levels ≥ 0.50 mg/m3 was 0.5% (n = 36) for all sampled workers (Figure 1). The proportion of workers with elevated airborne silica exposure levels ≥ 0.10 mg/m3 was 29.9% (n = 2,106). Within industries, workers in the metal industry had a prevalence of elevated airborne silica exposure levels ≥ 0.05 mg/m3 (35.6%), 2.9 times higher than the prevalence among workers in the construction industry (12.4%).
Airborne crystalline silica dust levels.
Table 1 presents arithmetic mean, geometric mean, standard deviations, and median of 8-hr TWA exposure measurements by industries with the highest and lowest airborne silica exposure. Geometric mean (GSD) airborne silica exposure levels were between 0.017 mg/m3 (GSD, 0.931 mg/m3; surgical appliances supplies industry, SIC 3842) and 0.166 mg/m3 (GSD, 0.943 mg/m3; metal valves and pipe fitting industry, SIC 3494). The geometric mean and GSD airborne silica exposure levels by industries and type of inspections are shown in Table 2. The overall geometric mean of silica exposure levels for samples collected during programmed inspections was 0.077 mg/m3. The geometric mean of samples collected under all inspections combined was higher in eight industries, whereas the geometric mean from programmed inspections was higher in two industries (Table 2).
Table 3 presents the airborne silica exposure levels by occupations in the “gray iron foundry” industry (SIC 3321). Gray iron foundry is the industry that primarily engages in manufacturing gray and ductile iron castings, including cast iron pressure and soil pipes and fittings. Workers with the job title “spruer” had the highest geometric mean airborne silica exposure levels (0.154 mg/m3), followed by workers with the job title “hunter operator” (0.093 mg/m3), those with the job title “charger” (0.091 mg/m3), and workers with the job title “core maker” (0.078 mg/m3).
The airborne silica exposure levels by occupations in the “stonework masonry” industry (SIC 1741) are shown in Table 4. The overall geometric mean of silica exposure levels for workers in this industry was 0.065 mg/m3. The geometric mean silica exposure levels were highest in those workers with the job title “helper” (0.099 mg/m3), followed by those with the job title “stone cutter” (0.070 mg/m3), those with the job title “bricklayer” and “laborer” (0.067 mg/m3), and workers with the job title “masonry worker” (0.065 mg/m3).
There were an estimated 119,381 workers potentially exposed to crystalline silica in 18 selected industries (Table 5). An estimated 25,027 workers were potentially exposed to airborne silica exposure in the automotive repair paint shop (SIC 7532) compared with 114 workers in the metal valves and pipe fitting industry (SIC 3494). Workers potentially exposed to silica exposure in stonework masonry (SIC 1741), plastering drywall work (SIC 1742), and tile, marble, and mosaic work (SIC 1743) were estimated at 44,989 employees. Workers in the testing laboratories services (SIC 8734) were estimated at 18,497 potentially exposed to airborne silica exposure.
The nonparametric regression showed the mean square error (MS) in airborne silica exposure between industries (MSbi = 0.048) and within industries (MSwi = 0.014), with F (3, 7,205) = 3.28 (p = 0.02). In this analysis we rejected the null hypothesis of no significant differences in the mean exposure levels between industries. We attempted to fit a mixed autoregressive and moving average model, ARMA (1,1), to the silica exposure data. A chi-squared value of 12.6 (p = 0.01) showed that we could not reject the hypothesis that the residuals are correlated. Thus, ARMA (1,1) was not an adequate model for silica exposure data. A final second-order autoregressive error model showed that a decline in the airborne silica exposure levels of 10.0% was observed per year between 1988 and 2003, but it was not statistically significant (p = 0.18, R2 = 0.0398). Within industries, the autroregressive error model AR(2) predicted that the construction industry has significantly lower airborne silica exposure levels (p = 0.10) during this time period. The findings also predicted that manufacturing industries have higher silica exposure levels than the metal industries, but it was not statistically significant at p ≤ 0.05. The estimated autocorrelation coefficients ρ1 and ρ2 were −0.153 and −0.082, respectively, with an estimated variance of error term of 0.014. The results showed that the negative effect of an OSHA inspection on the airborne silica exposure levels was estimated at β = −0.007, with p = 0.0319.
Discussion
Our findings suggest that geometric mean crystalline silica exposure levels have declined in some high-risk construction industries during 1988–2003. A comparison of our results with silica exposure levels found in a previous study by Stewart and Rice (1990) revealed a significant decline over the years. The geometric mean airborne silica exposure level in the general contractor industry (SIC 1541) was almost 6.2 times higher, at 0.354 mg/m3 (Stewart and Rice 1990), in 1979–1987 compared with 0.057 mg/m3 in 1988–2003. The geometric mean airborne silica exposure levels in the bridge tunnel construction industry (SIC 1622) were 5.5 times higher, at 0.383 mg/m3, in 1979–1987 compared with 0.069 mg/m3 in 1988–2003. The stonework masonry industry (SIC 1741) had geometric mean airborne silica exposure levels 9.8 times higher, at 0.619 mg/m3, in 1979–1987 than its level, 0.063 mg/m3, in 1988–2003. The significant decline of airborne silica observed in the construction industry could be explained by the implementation of advanced health and safety programs, effective engineering controls, work practice controls, and personal protective equipment (Flanagan et al. 2003; Flynn and Susi 2003).
Silica exposure levels among workers in the gray iron industry (SIC 3321) were significantly lower in 1988–2003 than in 1979–1987. Our results also showed that silica exposure levels for workers with the job title “furnace operators” declined by 53.5% of what they were in 1979–1987, from 0.142 mg/m3 (Stewart and Rice 1990) to 0.066 mg/m3. Geometric mean airborne silica exposure levels for workers with the job title “grinder” went down by 28.6%, from 0.105 mg/m3 to 0.075 mg/m3. Furthermore, silica exposure levels for workers with the job title “reline cupola” decreased more than 5.7 times, from 0.384 mg/m3 in 1979–1987 (Stewart and Rice 1990) to 0.067 mg/m3 in 1988–2003. Geometric mean silica exposure levels for workers with the job title “cleaning department” declined by 50.8%, from 0.122 mg/m3 to 0.060 mg/m3, whereas exposure levels for workers with the job title “sorter” decreased from 0.127 mg/m3 (Stewart and Rice 1990) to 0.067 mg/m3.
The recent decline of airborne silica exposure levels in the gray iron foundry could be attributed to many potential factors, in addition to OSHA’s enforcement as part of its SEP for workplace exposure to silica (Jeffress 1998). Because of the OSHA inspections and enforcement actions, most foundry industries were required to take action to reduce the overexposure and comply with OSHA’s standard PEL (Irwin 2003). The OSHA PEL was defined by a formula that included the percentage respirable silica (OSHA 2001). Assuming that the dust is 100% crystalline silica, the OSHA PEL is computed at 0.1 mg/m3. Using the OSHA-calculated PEL of 0.436 mg/m3 as the criterion, 3.6% of the sampled workers were overexposed to airborne silica exposure, whereas using the ACGIH TLV of 0.05 mg/m3 as the criterion, 85.5% of the sampled workers were overexposed (Figure 1). An overexposure severity factor was defined when the TWA exposure level was divided by the OSHA-calculated PEL. The overexposure severity factor was estimated at 0.17, less than 1. Our findings were eight times lower than Galster’s (1997) findings of 30% of air samples over the OSHA PEL.
Our estimates of the number of workers exposed were consistent with an earlier study done by Linch et al. (1998), which reported approximately 132,000 workers in the construction industry with three-digit SIC code 174 to be potentially exposed to airborne silica during the 1981–1983 national hazard survey. The results of this study suggest that the number of workers potentially exposed to crystalline silica in the construction industry with SIC codes 1741, 1742, and 1743 combined was almost three times (44,989 workers) lower in 2003 than it was in 1981–1983 (Table 5). Linch et al. (1998) also reported that an estimated 41,700 workers in the research testing services industry with a three-digit SIC code 873 were exposed to airborne silica at least twice the NIOSH-recommended exposure limit using the 1993 IMIS database. The number of workers exposed in the testing laboratories services industry (SIC 8734) has declined more than 2-fold in the last decade, from 41,700 in 1993 to 18,497 in 2003.
Although the airborne silica exposure levels declined in some industries and processes, the results showed an upward trend in the silica respirable dust exposure levels in certain industries and occupations, and exposure levels were above the ACGIH TLV of 0.050 mg/m3 (ACGIH 2001). For instance, in the gray iron foundry industry (SIC 3321), exposure levels for workers with the job title “spruer” increased from 0.098 mg/m3 (Stewart and Rice 1990) in 1979–1987 to 0.154 mg/m3 in 1988–2003, an increase of 57.1%. Airborne silica exposure levels went up from 0.068 mg/m3 in 1992–1995 to 0.080 mg/m3 in 1996–1999 (Figure 2). Because many businesses are not yet in compliance with OSHA health standards, large numbers of workers in certain industries and occupations continue to be exposed to silica dust in the course of their work (Flanagan et al. 2003).
The model of the second-order autoregressive error showed significant association between airborne silica exposure levels and OSHA inspections. Using R2 as a measure of “goodness of fit,” 3.98% of the total variation in airborne silica exposure levels was explained by the model. This low R
2 might be due to the lack of data on other explanatory variables that should be included in the model. Future research is needed to further examine other potential predictors in explaining the variability of airborne silica exposure levels.
Almost two-fifths of all inspections conducted by OSHA are programmed inspections. In programmed inspections, OSHA may identify industries with the greatest risk of injury and illness to workers, and then target firms sampled randomly within them. For general and construction industry, inspections initiated under the SEP are required to be programmed (scheduled) and conducted in accordance with the provisions in the Field Inspection Reference Manual (FIRM) and the Revised Field Operations Manual (FOM) (OSHA 1994, 1995; Dear 1996). Wherever possible, inspections focus on particular establishments where overexposures to airborne silica are most likely or there are known cases of silicosis (Dear 1996). When making an inspection, OSHA takes sampling exposure measurements of employees who may have high or low exposure over an 8-hr TWA. However, all inspections involving fatalities, complaints, follow-up, or referrals tend to have a potential bias toward high estimates of exposure levels (Linch et al. 1998). In this study, it was observed that the geometric mean of samples collected during all inspections combined was higher in eight industries than the mean of samples collected during programmed inspections (Table 2).
This study has some limitations. First, OSHA samples measure the workers’ personal breathing work environment exposure without taking into account the use of a respirator. Actual exposure levels for some workers may be much less than the workers’ ambient readings of exposure. As a result, this sampling measurement may overestimate the workers’ exposure levels. Inferences regarding OSHA inspections must be interpreted with caution, especially in cases of small sample sizes. Second, a potential limitation of the IMIS database is its inability to identify the duration of employment of the individual worker and the duration of exposure to silica dust. Third, SIC codes were used in the classification of establishments by type of primary activity in which they were engaged. For industries with multiple activities, it is possible that one may classify an industry by its processes rather than products manufactured. Fourth, job titles in the IMIS database were not well defined and coded according to a common and standardized system. Because of this lack of common classification codes, it may be necessary to categorize job titles and aggregate them into fewer categories. Finally, because the IMIS database does not represent a random sample of exposure levels, the findings of this study may not be generalizable. Nonetheless, these limitations are not serious enough to invalidate the findings of this study.
The strength of the OSHA IMIS database is its ability to provide estimates of airborne silica exposure levels and to identify high-risk industries and occupations. It is the largest source of occupational exposure data. As long as the limitations of the OSHA IMIS data set are understood, it provides an important source of information regarding occupational exposure. It also may provide a useful tool to generate hypotheses that could be tested in future studies.
Conclusions
Although occupational exposure to crystalline silica dust levels declined in some industries and occupations, the results showed that workers in certain industries and occupations were still overexposed. Approximately 3.6% of the sampled workers were overexposed to airborne silica above the OSHA-calculated PEL. OSHA regulatory efforts are needed to further increase industry compliance with occupational exposure limits by enforcing effective engineering controls and to protect workers from overexposure to crystalline silica. Furthermore, OSHA needs to increase its compliance assistance and outreach efforts to assist businesses in establishing programs to reduce overexposure to silica.
Figure 1 Prevalence of elevated crystalline silica exposure by TWA exposure levels.
Figure 2 Geometric mean airborne silica exposure levels by year.
Table 1 Arithmetic mean (AM), geometric mean (GM), their standard deviations (ASD, GSD), and median of exposure measurements of crystalline silica (mg/m3) by industry, IMIS (1988–2003).
Industrya (SIC code) No.b AM ASD GM GSD Median
Metal valves and pipe fitting (3494) 8 0.229 0.161 0.166 0.943 0.243
Industrial supplies (5085) 5 0.175 0.090 0.161 0.431 0.147
Roofing siding and sheet metal (1761) 11 0.224 0.170 0.150 1.029 0.230
Special industry machinery (3559) 15 0.193 0.167 0.127 0.978 0.110
Automotive repair paint shop (7532) 13 0.161 0.143 0.107 0.968 0.050
Mining machinery equipment (3532) 10 0.080 0.075 0.046 1.323 0.050
Plastics plumbing fixtures (3088) 14 0.054 0.033 0.044 0.682 0.050
Plastering drywall work (1742) 13 0.045 0.046 0.031 0.920 0.022
Tile, marble, and mosaic work (1743) 12 0.036 0.027 0.025 0.958 0.035
Surgical appliances supplies (3842) 5 0.024 0.019 0.017 0.931 0.018
a The 10 industries with the highest and lowest geometric mean where at least five samples were available.
b Number of personal TWA sample measurements.
Table 2 Geometric mean (GM) and GSD of exposure measurements of crystalline silica (mg/m3) by industry and type of inspection, IMIS (1988–2003).
All inspections (n = 2,512)
Programmed inspections (n = 948)
Industrya (SIC code) No.b GM GSD No.b GM GSD
Soap and other detergents (2841) 6 0.102 0.757 5 0.108 0.831
Testing laboratories services (8734) 53 0.099 0.896 19 0.082 0.656
Cut stone and stone products (3281) 405 0.091 0.956 164 0.075 0.963
General contractors (1541) 28 0.091 0.900 8 0.057 0.346
Coating engraving (3479) 75 0.075 0.839 26 0.072 0.842
Gray iron foundries (3321) 1,760 0.073 0.877 782 0.082 0.899
Concrete work (1771) 94 0.073 0.705 38 0.072 0.720
Manufacturing explosives (2891) 9 0.070 0.841 5 0.058 0.581
Bridge tunnel construction (1622) 91 0.070 0.827 41 0.069 0.761
Stonework masonry (1741) 274 0.065 0.732 111 0.063 0.803
All 7,209 0.073 0.919 2,868 0.077 0.935
a The industries where at least five samples were collected during inspections.
b Number of personal TWA sample measurements.
Table 3 Arithmetic mean (AM), geometric mean (GM), their standard deviations (ASD, GSD), and median of exposure measurements of crystalline silica (mg/m3) by occupation in the gray iron foundry industry (SIC 3321), IMIS (1988–2003).
Occupation No.a AM ASD GM GSD Median
Spruer 22 0.232 0.182 0.154 0.100 0.205
Hunter operator 10 0.157 0.151 0.093 1.144 0.050
Charger 8 0.146 0.156 0.091 0.999 0.050
Core maker 89 0.129 0.135 0.078 1.033 0.050
Grinder 371 0.112 0.123 0.075 0.821 0.050
Molder 308 0.116 0.129 0.073 0.910 0.050
Abrasive blast operator 56 0.103 0.110 0.070 0.821 0.050
Sorter 23 0.098 0.108 0.067 0.827 0.050
Reline cupola 29 0.096 0.113 0.067 0.725 0.050
Furnace operator 47 0.096 0.110 0.066 0.766 0.050
Core setter 23 0.086 0.082 0.066 0.671 0.051
Craneman 16 0.097 0.106 0.066 0.815 0.050
Cleaning department 36 0.094 0.117 0.060 0.879 0.050
Inspector 21 0.118 0.146 0.057 1.298 0.050
Ladle repair 30 0.081 0.098 0.055 0.829 0.050
a Number of personal TWA sample measurements.
Table 4 Arithmetic mean (AM), geometric mean (GM), their standard deviations (ASD, GSD), and median of exposure measurements of crystalline silica (mg/m3) by occupation in the stonework masonry industry (SIC code 1741), IMIS (1988–2003).
Occupation No.a AM ASD GM GSD Median
Helper 6 0.175 0.198 0.099 1.143 0.050
Stone cutter 33 0.097 0.096 0.070 0.814 0.050
Bricklayer 30 0.091 0.086 0.067 0.742 0.050
Laborer 48 0.093 0.102 0.067 0.731 0.050
Masonry worker 74 0.088 0.090 0.065 0.713 0.050
Foreman 8 0.085 0.081 0.064 0.748 0.050
Tuckpointer 18 0.086 0.110 0.062 0.647 0.050
Grinder 35 0.055 0.020 0.052 0.372 0.050
Hod carrier 5 0.092 0.123 0.042 1.540 0.050
All 257 0.088 0.093 0.065 1.140 0.050
a Number of personal TWA sample measurements.
Table 5 Estimates of the number and percentage of workers potentially exposed to crystalline silica by selected industries, IMIS (1988–2003).
Industrya (SIC code) No.b of workers in the establishment Percent of workers exposedc Total no. of potentially exposed workersd
Metal valves and pipe fittings (3494) 18,080 0.63 114
Special industry machinery (3559) 111,312 0.56 623
Automotive repair paint shop (7532) 205,906 12.2 25,027
Soap and other detergents (2841) 30,352 1.4 438
Testing laboratories services (8734) 82,786 22.3 18,497
Gray iron foundries (3321) 82,749 1.7 1,395
Manufacturing explosives (2891) 21,322 5.3 1,131
Fabricated rubber products (3069) 56,079 1.2 698
Masonry, stonework (1741) 168,155 12.7 21,302
Brick, stone, related material (5032) 34,241 6.4 2,203
Repair shops, NEC (7699) 212,049 8.0 17,022
Transmission equipment (3568) 20,884 2.1 438
Chemical preparations, NEC (2899) 34,873 7.9 2,766
Mining machinery equipment (3532) 13,631 2.4 329
Plastics plumbing fixtures (3088) 16,793 15.9 2,670
Plastering drywall work (1742) 262,530 4.8 12,459
Tile, marble, and mosaic work (1743) 38,051 29.5 11,228
Surgical appliances supplies (3842) 96,154 1.1 1,041
Total 1,505,947 7.9 119,381
NEC, not elsewhere classified.
a Industries with the highest and lowest geometric mean where at least five samples were available.
b Number of workers in the establishments, as reported to the U.S. Census Bureau (1997)
c Percentage of workers exposed was calculated by dividing the number of workers exposed as determined by the inspector, and the number of workers in the establishment, as reported to the OSHA inspector by the facility.
d Total number of potentially exposed workers in an SIC was calculated by taking the product of the proportion of workers exposed in each SIC by the average worker population employed nationally in each SIC, as reported to the U.S. Census Bureau (1997).
==== Refs
References
ACGIH 1980. Silica, Quartz. The Documentation of the Threshold Limit Values. 4th ed. Cincinnati, OH:American Conference of Governmental Industrial Hygienists.
ACGIH 1986. Silica, Crystalline-Quartz. The Documentation of the Threshold Limit Values and Biological Exposure Indices. 5th ed. Cincinnati, OH:American Conference of Governmental Industrial Hygienists.
ACGIH 2001. Silica, Crystalline-Quartz. The Documentation of the Threshold Limit Values and Biological Exposure Indices. 7th ed. Cincinnati, OH:American Conference of Governmental Industrial Hygienists.
Akbar-Khanzadeh F Brillhart RL 2002 Respirable crystalline silica dust exposure during concrete finishing (grinding) using hand-held grinders in the construction industry Ann Occup Hyg 46 341 346 12176721
Altindag ZZ Baydar T Isimer A Sahin G 2003 Neopterin as a new biomarker for the evaluation of occupational exposure to silica Int Arch Occup Environ Health 76 318 322 12768284
American Thoracic Society 1997 Adverse effects of crystalline silica exposure: American Thoracic Society Committee of the Scientific Assembly on Environmental Occupational Health Am J Respir Crit Care Med 155 761 765 9032226
Dear JA 1996. Memorandum to the Regional Administrators. Special Emphasis Program (SEP) for Silicosis. Washington, DC:U.S. Department of Labor, Occupational Safety and Health Administration. Available: http://www.osha.gov/Silica/SpecialEmphasis.html [accessed 20 October 2004].
Engholm G Englund A 1995 Mortality and cancer incidence in various groups of construction workers Occup Med 10 453 481 7667753
Flanagan ME Seixas N Majar M Camp J Morgan M 2003 Silica dust exposures during selected construction activities Am Ind Hyg Assoc J 64 319 328
Flynn MR Susi P 2003 Engineering controls for selected silica and dust exposures in the construction industry—a review Appl Occup Environ Hyg 18 4 268 277 12637237
Galster C 1997 A significant workplace exposure to crystalline silica Appl Occup Environ Hyg 12 522 523
Goldsmith DF 1997. Are other health effects of silica exposure being overlooked? Washington, DC:U.S. Department of Labor, Occupational Safety and Health Administration. Available: http://www.osha-slc.gov/SLTC/silicacrystalline/overlooked.html [accessed 20 November 2003].
Hnizdo E Vallyathan V 2003 Chronic obstructive pulmonary disease due to occupational exposure to silica dust: a review of epidemiological and pathological evidence Occup Environ Med 60 237 243 12660371
Hughes JM Weill H Rando RJ Shi R McDonald AD McDonald JC 2001 Cohort mortality study of North American industrial sand workers. II. Case-referent analysis of lung cancer and silicosis deaths Ann Occup Hyg 45 201 207 11295143
IARC (International Agency for Research on Cancer). 1987 Silica, some silicates IARC Monogr Eval Carcinog Risk Hum 42 suppl 7 341 343
IARC (International Agency for Research on Cancer) 1997 Silica, some silicates, coal dust and para-aramid fibrils IARC Monogr Eval Carcinog Risk Hum 68 42 242
Irwin A 2003 Overexposure to crystalline silica in a foundry operation Appl Occup Environ Hyg 18 1 18 21 12650545
Jeffress CN 1998. Memorandum to the U.S. House of Representatives. Special Emphasis Program (SEP) for Silicosis. Washington, DC:U.S. Department of Labor, Occupational Safety and Health Administration.
Kane F 1997 The campaign to end silicosis Job Safety Health Q 8 16 19
Knutsson A Damber L Jarvholm B 2000 Cancers in concrete workers: results of a cohort study of 33,668 workers Occup Environ Med 57 264 267 10810113
Linch KD Miller WE Althouse RB Groce D Hale J 1998 Surveillance of respirable crystalline silica dust exposure using OSHA compliance data (1979–1995) Am J Ind Med 34 547 558 9816412
Lynge E Kurppa K Kristofersen L Malker H Sauli H 1986 Silica dust and lung cancer: results from the Nordic occupational mortality and cancer incidence registers J Natl Cancer Inst 77 883 889 3020298
NIOSH 1991. Work-Related Lung Disease Surveillance Report. NIOSH Publication No. 91-113. Cincinnati, OH:National Institute for Occupational Safety and Health.
NIOSH 1998. NIOSH Manual of Analytical Methods. 4th ed. Cincinnati, OH:National Institute for Occupational Safety and Health.
NIOSH 2002. Health Effects of Occupational Exposure to Respirable Crystalline Silica. DHHS Publication No. 2002-129. Cincinnati, OH:National Institute for Occupational Safety and Health.
Office of Management and Budget 1987. Standard Industrial Classification Manual. Springfield, VA:National Technical Information Service.
OSHA 1989. Industrial Exposure and Control Technologies for OSHA Regulated Hazardous Substances. Vol 2: Substances K–Z and Indices. Washington, DC:Occupational Safety and Health Administration.
OSHA 1993. Air Contaminants Correction: Final Rules. 29 CFR Part 1910.1000, 58 FR 40191, 27 July 1993. Washington, DC:Occupational Safety and Health Administration.
OSHA 1994. Field Inspection Reference Manual (FIRM). OSHA Instruction CPL 2.103. 26 September. Washington, DC:Occupational Safety and Health Administration.
OSHA 1995. The Revised Field Operations Manual (FOM). OSHA Instruction CPL 2.45B. 3 March. Washington, DC:Occupational Safety and Health Administration.
OSHA 1996. Quartz and Cristobalite in Workplace Atmosphere: Method No. ID-142. OSHA Sampling and Analytical Methods. Salt Lake City, UT:Occupational Safety and Health Administration, Analytical Laboratory.
OSHA 2001. Air Contaminants. 29 CFR 1910.1000. Washington, DC:Occupational Safety and Health Administration.
OSHA 2003. Occupational Exposure to Crystalline Silica. Semiannual Regulatory Agenda. Fed Reg 68:30583–30594 Available: http://www.osha.gov/SLTC/silicacrystalline/standards.html [revised 27 September 2004].
OSHA 2004. Safety and Health Topics: Silica, Crystalline. Washington, DC:Occupational Safety and Health Administration. Available: http://www.osha.gov/SLTC/silicacrystalline [revised 27 September 2004].
OSHA IMIS 2003. Integrated Management Information System (IMIS): Sungard Database. Office of Management Data Systems. Washington, DC: Occupational Safety and Health Administration.
Parks CG Cooper GS Nylander-French LA Sanderson WT Dement JM Cohen PL 2002 Occupational exposure to crystalline silica and risk of systemic lupus erythematosus: a population-based, case-control study in the southeastern United States Arthritis Rheum 46 7 1840 1850 12124868
Rappaport SM Goldberg M Susi P Herrick RF 2003 Excessive exposure to silica in the U.S. construction industry Ann Occup Hyg 47 2 111 122 12581996
Robinson C Stern F Halperin W Venable H Petersen M Frazier T 1995 Assessment of mortality in the construction industry in the United States, 1984–1986 Am J Ind Med 28 1 49 70 7573075
Rosenman KD Reilly MJ Henneberger PK 2003 Estimating the total number of newly recognized silicosis cases in the United States Am J Ind Med 44 141 147 12874846
SAS Institute, Inc 1999. SAS Language: Reference, Version 8.2. Cary, NC:SAS Institute, Inc.
Stern F Schulte P Sweeney MH Fingerhut M Vossenas P Burkhardt G 1995 Proportionate mortality among construction laborers Am J Ind Med 27 485 509 7793421
Stewart AP Rice C 1990 A source of exposure data for occupational epidemiology studies Appl Occup Environ Hyg 5 6 359 363
U.S. Census Bureau 1997 County Business Patterns for the United States. Washington, DC:Bureau of the Census. Available: http://www.census.gov/epcd/cbp/view/us97.txt [accessed 10 December 2003].
|
15743711
|
PMC1253748
|
CC0
|
2021-01-04 23:40:57
|
no
|
Environ Health Perspect. 2005 Mar 6; 113(3):255-260
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7384
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7276ehp0113-00026115743712ResearchArticlesIntersexuality and the Cricket Frog Decline: Historic and Geographic Trends Reeder Amy L. 1Ruiz Marilyn O. 2Pessier Allan 3Brown Lauren E. 4Levengood Jeffrey M. 5Phillips Christopher A. 7Wheeler Matthew B. 1Warner Richard E. 6Beasley Val R. 51Department of Animal Sciences, and2Department of Veterinary Pathobiology, University of Illinois at Urbana-Champaign, Champaign, Illinois, USA3University of Illinois Zoological Pathology Program, Loyola University Medical Center, Maywood, Illinois, USA4Department of Biological Sciences, Illinois State University, Normal, Illinois, USA5Department of Veterinary Biosciences, and6Department of Natural Resources and Environmental Sciences, University of Illinois at Urbana-Champaign, Champaign, Illinois, USA7Center for Biodiversity, Illinois Natural History Survey, Champaign, Illinois, USAAddress correspondence to V.R. Beasley, Department of Veterinary Biosciences, College of Veterinary Medicine, University of Illinois, 2001 S. Lincoln Ave., Urbana, IL 61802 USA. Telephone: (217) 333-9360. Fax: (217) 244-1652. E-mail:
[email protected] thank M. Post for technical assistance. We greatly appreciate the following individuals and their respective institutions for allowing us to examine cricket frogs in their natural history collections: H. Voris and A. Resetar, Field Museum of Natural History; R. Axtell, Department of Biological Sciences, Southern Illinois University; E. Moll, Department of Zoology, Eastern Illinois University; R. Brandon, Department of Zoology, Southern Illinois University; K. Cummings, Illinois Natural History Survey; the Department of Biological Sciences, Illinois State University; R.P. Reynolds and R. McDiarmid, National Museum of Natural History, Smithsonian Institution; G. Thurow, Department of Biology, Western Illinois University; J.R. Purdue and D. Bakken, Illinois State Museum; G. Schneider, Museum of Zoology, University of Michigan; R. Vasile, M. Hennen, and S. Sullivan, Chicago Academy of Sciences; E. Censky, Carnegie Museum of Natural History; J. Cadle, Academy of Natural Sciences; and J.W. Wright, Natural History Museum of Los Angeles County.
Funding was provided by the John G. Shedd Aquarium through support from the Dr. Scholl Foundation.
The authors declare they have no competing financial interests.
3 2005 7 12 2004 113 3 261 265 24 5 2004 7 12 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Exposure to anthropogenic endocrine disruptors has been listed as one of several potential causes of amphibian declines in recent years. We examined gonads of 814 cricket frogs (Acris crepitans) collected in Illinois and deposited in museum collections to elucidate relationships between the decline of this species in Illinois and the spatial and temporal distribution of individuals with intersex gonads. Compared with the preorganochlorine era studied (1852–1929), the percentage of intersex cricket frogs increased during the period of industrial growth and initial uses of polychlorinated biphenyls (PCBs) (1930–1945), was highest during the greatest manufacture and use of p,p-dichlorodiphenyltrichloroethane (DDT) and PCBs (1946–1959), began declining with the increase in public concern and environmental regulations that reduced and then prevented sales of DDT in the United States (1960–1979), and continued to decline through the period of gradual reductions in environmental residues of organochlorine pesticides and PCBs in the midwestern United States (1980–2001). The proportion of intersex individuals among those frogs was highest in the heavily industrialized and urbanized northeastern portion of Illinois, intermediate in the intensively farmed central and northwestern areas, and lowest in the less intensively managed and ecologically more diverse southern part of the state. Records of deposits of cricket frog specimens into museum collections indicate a marked reduction in numbers from northeastern Illinois in recent decades. These findings are consistent with the hypothesis that endocrine disruption contributed to the decline of cricket frogs in Illinois.
Acris crepitansamphibiancricket frogsendocrine disruptionenvironmental contaminantsIllinoisintersexuality
==== Body
Amphibian declines have been documented in many parts of the world (Alford et al. 2001; Blaustein and Wake 1990; Houlahan et al. 2000; Tyler 1991), which is of concern because these species are important grazers, prey species, and predators in aquatic and terrestrial ecosystems and serve as valuable sentinels of ecologic integrity. For many amphibian species, including the cricket frog Acris crepitans, the causes of declines are unclear. This species is indigenous to the eastern half of the United States and has experienced a marked decline in portions of its range in the last 25 years (Brodman and Kilmurry 1998; Caspar 1998; Jung 1993; Mierzwa 1998; Minton 1998; Moriarity 1998; Mossman et al. 1998). In 1961, it was the most common amphibian in Illinois (Smith 1961), and it is still abundant in southern Illinois. However, cricket frogs were rarely encountered in amphibian surveys conducted in portions of northern Illinois in recent decades (Ludwig et al. 1992; Vogt 1981; Phillips CA, Brown LE, personal observation).
A variety of industrial compounds and by-products disrupt endocrine function, and exposure to such chemicals may contribute to amphibian declines. Polychlorinated biphenyls (PCBs), polychlorinated dibenzofurans (PCDFs), and polychlorinated dibenzo-p-dioxins (PCDDs) may produce estrogenic, antiestrogenic, and antiandrogenic effects (Jansen et al. 1993; Krishnan and Safe 1993; Li and Hansen 1996; Li et al. 1994; Malby et al. 1992). For example, PCBs may affect sexual differentiation in the slider turtle Trachemys scripta (Bergeron et al. 1994), various frogs (Qin et al. 2003), and fish (Matta et al. 1998). Moreover, our laboratory associated exposures of cricket frog tadpoles to antiestrogenic PCBs and PCDFs with marked masculinization of sex ratios (Reeder et al. 1998). In addition, polycyclic aromatic hydrocarbons (PAHs) from coal tar and smoke from combustion of coal, oil, gas, wood, and garbage are widely disseminated endocrine disruptors (Chaloupka et al. 1992, 1993; Machala et al. 2001; ATSDR 1995; Thomas and Budiantara 1995).
Pesticides now banned from the market and compounds still sold can adversely affect animal reproduction. For example, the organochlorine pesticide p,p-dichlorodiphenyl-trichloroethane (DDT) and its metabolites/ environmental products have demasculinized birds (e.g., gulls, Larus californicus and L. occidentalis), reptiles (Alligator mississippiensis), and fish (Baatrup and Junge 2001; Fry and Toone 1981; Guillette et al. 1994, 1995; Metcalfe et al. 2000). Also, DDT induced vitellogenin production in male African clawed frogs (Xenopus laevis) and slider turtles (T. scripta), and the organochlorine insecticides toxaphene and dieldrin induced this protein in male X. laevis (Palmer and Palmer 1995; Palmer et al. 1998). Furthermore, there is concern that the widely used herbicide atrazine may impair reproduction and/or development of amphibians. At high concentrations, atrazine decreased growth in gray treefrogs (Hyla versicolor) and increased time to metamorphosis in X. laevis (Diana et al. 2000; Sullivan and Spence 2003). At much lower concentrations, atrazine in combination with nitrate reduced growth of X. laevis (Sullivan and Spence 2003). Hayes et al. (2002, 2003) associated hermaphrodism and gonadal dysgenesis in amphibians with very low aquatic concentrations of atrazine (0.1 μg/L), whereas Carr et al. (2003) observed significantly increased intersexuality only at higher concentrations (25 μg/L).
Although it is apparent that exposure to anthropogenic compounds may harm amphibians through changes in functional sex ratios, reduced size at metamorphosis, and delayed maturation, the distribution of intersex frogs geographically and historically remains to be characterized. In this study, we examined gonads of A. crepitans from museum specimens to elucidate relationships between the decline of this species and the temporal and spatial occurrence of intersexuality.
Materials and Methods
Natural history museums are valuable resources for estimations of species distributions and health status over time (Shaffer et al. 1998). We examined specimen records from 16 museums to determine where and when cricket frogs were collected in Illinois. To determine whether cricket frogs were not available because collecting was not conducted, we compared cricket frog records with those of all anuran collections from the state. Our rationale was that scientists collecting anurans and placing them in museums as voucher specimens would not consistently preclude cricket frogs.
Museum specimens from throughout Illinois (Figure 1) were examined to compare cricket frog gonadal sex in three regions of the state during five time periods. The three regions are distinguished by human population density and physiographic characteristics. The northeast region includes 11 counties with high human population densities in and surrounding the Chicago metropolitan area. The central band of 66 counties, which was formerly largely prairie, is dominated by low topographic relief, fertile soils, intensive maize and soy agriculture, and low human population density. The southernmost region includes 25 counties with mixed crops, pastures, and wooded hills as well as low human population density. The five time periods studied included a) a preorganochlorine period (1852–1929); b) an era of PCB use and industrialization that predates use of DDT (1930–1945); c) a period of rapidly increasing DDT use and further industrialization (1946–1959); d ) a period of declining use and then a ban on sales of DDT as well as initial measures to limit pollution from industries (1960–1979); and e) a period associated with a substantial decline in environmental residues of organochlorine insecticides and other persistent halogenated organic air and water pollutants in the Midwest (1980–2001).
The gonads of 814 cricket frogs were examined in situ with a dissecting microscope to identify sex. Because there is no evidence that testicular tissue develops within the female tract, females were identified by the presence of oocytes and excluded from further analysis. Testes, intersex gonads, and poorly differentiated gonads were removed for histologic examination. When museums limited the proportion of cricket frogs from which gonads could be taken, we used a random numbers table to select a subset for histologic study. Collection dates, collecting localities, and notes from museum catalogs were recorded. Gonads were immersed in 70% ethanol, embedded in paraffin, and sectioned at 5 μm. Depending on gonad size, longitudinal sections were obtained beginning 60–150 μm from the outer edge. Two or three sections 60–120 μm apart were selected for processing. Slides were stained with hematoxylin and eosin and examined with a light microscope for the presence of sperm production and oocytes. When oocytes were present within testicular tissue, they were relatively few in number, but each was several-fold larger than the spermatic ducts and thus took up a substantial percentage of testicular volume, making them easy to identify.
We used Systat 10.2 (SPSS, Inc., Chicago, IL) to construct contingency tables and perform Pearson chi-square analyses comparing proportions of male, female, and intersex individuals among the five time periods and three areas of Illinois. Further analysis incorporating temporal and spatial dimensions simultaneously was not possible because of the limited numbers of intersex specimens at some time points. Specifically, tables based on all five time periods and three regions broken down by sex would have included cells with no data. The null hypotheses tested whether the proportion of male, intersex, and female frogs is the same for frogs captured during the five time periods and in the three areas of the state. We used the 5% significance level as the indicator of a statistically significant association.
Results
Records for all anurans totaled 12,661 specimens. Of these, 2,570 (20%) were A. crepitans, the frog species most often collected in Illinois. Years of collection ranged from 1852 to 2001. A trend of increasing numbers of frogs collected started in the late 1930s; there was a marked reduction during World War II, and then the rate of collecting markedly increased through the mid-1950s. Numbers of individual anurans collected declined sharply in the late 1950s, increased during the mid-1960s, and declined during the 1970s and 1980s. The numbers of frogs collected in Illinois have since increased. Cricket frog numbers were largely proportional to those of other anurans (Figure 2A). Other frog and toad species have been collected from the Chicago region in proportion to other regions of the state since 1960; however, few cricket frogs were obtained from that area in the same time frame (Figure 2B). Moreover, from 1980 to 2001, cricket frog collections remained high in the central and southern regions but declined even further around Chicago (Figure 3).
Intersexuality (hermaphrodism) was manifested in two forms: most intersex frogs (n = 37) had an ovotestis where proportionately large ova were present within testicular tissue, and a few (n = 6) had a complete testis and complete ovary. The proportions of specimens in each gonadal sex class differed significantly among the geographical regions in Illinois (χ2 = 20.2, 4 df, p < 0.001; Table 1, Figure 4A). Notably, in the urbanized northeastern portion of the state, the proportion of frogs that were intersex was much greater than in other areas, and the proportion of females was smaller than elsewhere. In southern Illinois, where agriculture and urbanization are least intensive, the proportion of intersex individuals was considerably smaller than in the other regions.
The proportion of specimens in each gonadal sex class differed markedly among the time periods of collection (χ2 = 31.1, 8 df, p < 0.001; Table 1, Figure 4B). From 1930 to 1945, the percentage of intersex individuals was notably increased, and from 1946 to 1959 it was greater than during any other time frame examined. Also, during 1946–1959, the proportion of females was reduced. During the most recent period, the proportion of intersexes was lowest of any period except for 1852–1929. In the 1990s, however, few cricket frogs were available from areas that previously had the most elevated intersex rates.
Discussion
Environmental contamination probably accounted for the historical and geographical trends in gonadal sex in Illinois cricket frogs and likely contributed to the decline of the species. In this research, it would not have been productive to assay contaminants in tissues of the frogs because of their small size, and because frogs are individually tagged but stored together in jars of fixative with conspecific individuals, which would enable postmortem cross-contamination. Moreover, such use would consume the specimens, preventing any future examination for other research aims. Also, it would not be meaningful to assay contaminant mixtures at sites today because they would no longer be representative of what was present when the frogs were collected.
The absence of cricket frogs from northeastern Illinois in museum collections is consistent with reports indicating virtual disappearance of cricket frogs from this area (Ludwig et al. 1992; Phillips CA, Brown LE, personal observation; Vogt 1981). Heavy industrialization from the 1930s through the 1950s was accompanied by major releases of combustion products and organochlorine contaminants. Smokes contain abundant mixtures of PAHs that adsorb to particulates in air, soil, water, and sediment (Mumtaz and George 1995). Like coplanar PCDDs and similar organochlorines, some PAHs can act as antiestrogens (Chaloupka et al. 1992). By the 1930s, PCBs were being commercially produced (Hansen 1987), and coplanar PCBs and structurally similar PCDDs and PCDFs are potent antiestrogens. Thus, intensive industrial smoke emissions and commercial PCB production and widespread use coincided with the increase in the proportion of intersex cricket frogs. A possible outcome of exposure to various PAH and organochlorine antiestrogens is masculinization of juvenile cricket frogs and skewed sex ratios, as noted in the Chicago region in this study, which is similar to what we found previously at a hazardous waste site at Crab Orchard National Wildlife Refuge, where cricket frogs were contaminated with coplanar PCBs and PCDFs (Reeder et al. 1998).
The greatest proportions of intersex in cricket frogs of Illinois during 1946–1959 corresponded with a rapid increase in use of DDT in the United States (Mellanby 1992; U.S. Army Service Forces 1946). Large-scale DDT applications in Illinois for mosquito control began in 1945, followed by agricultural use in 1946. Production of DDT in the United States was greatest in 1959. Reduced prevalence of intersex in cricket frogs from 1960 to 1976 coincided with decreased use and the subsequent ban of most uses of DDT in the United States in 1972. Although exposure of larval tiger salamanders (Ambystoma tigrinum) to p,p-DDE (p,p-dichlorodiphenyl-dichloroethylene) stimulated growth of Mullerian ducts consistent with estrogenicity, exposure to technical-grade DDT had a paradoxical antiestrogenic effect (Clark et al. 1998). Thus, if cricket frogs responded to DDT exposure as did A. triginum, its use could have contributed to the concurrent decrease in female and increase in intersex cricket frogs during 1946–1959.
Atrazine was first marketed as a broadleaf herbicide for maize production in 1959, and use rapidly expanded. By 1993, the Midwest states of Illinois, Iowa, Nebraska, and Indiana accounted for 43% of the total amount of atrazine applied in the United States (Atrazine Ecological Risk Assessment Panel 1995), and it is still widely applied in the region. Based on findings of intersexuality at very low atrazine concentrations, Hayes et al. (2002, 2003) concluded that the widespread use of atrazine may have been a significant factor in amphibian declines. However, a recent study (Carr et al. 2003) indicated a higher threshold for atrazine-induced intersexuality in frogs. Additional research is needed to resolve this issue. Our study demonstrates that endocrine disruption and intersexuality were present in cricket frogs long before the advent of atrazine. However, the possibility that atrazine is one of the endocrine disruptors that contributed to the decline of cricket frogs and impedes expansion of its populations in central and northern Illinois is not ruled out by our findings.
Although we observed a decrease in intersex cricket frogs from Illinois after 1946–1959, McCallum and Trauth (2003) noted a progressive increase in the proportion of cricket frogs in Arkansas with external developmental abnormalities during four time periods from 1957 to 2000. Johnson et al. (2003) reported an increased prevalence of parasite-induced malformations by the trematode Ribeiroia from 1946 to 2002. Different patterns of contaminant and trematode exposures, and responses of germinal gonadal versus somatic cells to teratogenic stimuli may be responsible for the contrasting trends. Collection efforts and methods were not recorded in the catalogs and would have varied over time. Records typically were limited to the collector’s name and the location and date of acquisition in the field. Thus, bias that favored or limited collection of hermaphroditic cricket frogs cannot be completely ruled out. However, we have identified no basis for bias that would influence the likelihood of collecting intersex individuals. Hermaphroditic cricket frogs were collected by a wide range of investigators, and multiple hermaphrodites were found in the collections of many museums. Moreover, the museum records include no mention of behavioral or physical variation for any of the hermaphroditic specimens, and the collectors reported no knowledge of hermaphrodism. Finally, hermaphroditic individuals of this species can be identified only through gross dissection and histopathologic studies, which were not undertaken on these frogs prior to our research.
The geographic distribution of both endocrine disruption (intersexuality) and the decline of cricket frogs were congruent. The observed decline was evident after a period of sustained endocrine disruption, as indicated by a large increase in prevalence of intersex gonads and masculinization of the population. A plausible explanation for these observations is that exposures to antiestrogenic PAHs, PCBs, PCDFs, PCDDs, and DDT caused endocrine disruption, and this contributed to the virtual disappearance of cricket frogs from the Chicago region. The intersex prevalence in cricket frogs in recent years is low and may represent a near-baseline condition. A suite of endocrine-disrupting organochlorine contaminants persists in soils and waters of the Midwest, but at substantially reduced levels compared with earlier decades (Abramowicz 1990). However, we cannot conclude that the era of endocrine disruption in cricket frogs has come to an end, because in areas with the most severe decline in populations and most severe endocrine disruption historically, numbers of remaining cricket frogs are now insufficient to permit sampling.
Figure 1 Number by county of cricket frogs (n = 814) collected in Illinois from 1852 to 1996 and examined for gonadal sex determination.
Figure 2 (A) Numbers of cricket frog specimens from Illinois deposited in museum collections relative to numbers of other anurans in museums collected in the state from 1852 to 2001. (B) Numbers of cricket frog specimens from northeastern Illinois deposited in museum collections relative to numbers of other anurans in museums collected in that region from 1852 to 2001.
Figure 3 Distributions of total numbers of Illinois cricket frogs in museum collections for the five time periods. Each circle represents one museum specimen from that county.
Figure 4 Deviations of observed from expected values of cricket frog sex (A) by time period and (B) by region. Expected values were determined from the overall data set using the chi-square test.
Table 1 Numbers (percentages) of cricket frog specimens by gonadal sex and region and by gonadal sex and time period.
Female Intersex Male Total observed
Region
Northeast 57 (32.8) 19 (10.9) 98 (56.3) 174
Central 146 (44.7) 16 (4.9) 165 (50.5) 327
South 138 (44.1) 8 (2.6) 167 (53.4) 313
Total 341 (41.9) 43 (5.3) 430 (52.8) 814
Time period
1852–1929 44 (52.4) 1 (1.2) 39 (46.4) 84
1930–1945 35 (43.8) 6 (7.5) 39 (48.8) 80
1946–1959 46 (30.1) 17 (11.1) 90 (58.8) 153
1960–1979 76 (48.1) 10 (6.3) 72 (45.6) 158
1980–1996 140 (41.3) 9 (2.7) 190 (56.1) 339
Total 341 (41.9) 43 (5.3) 430 (52.8) 814
==== Refs
References
Abramowicz DA 1990 Aerobic and anaerobic biodegradation of PCBs: a review Biotechnology 10 241 251
Alford RA Dixon PM Pechmann JHK 2001 Ecology: Global amphibian population declines Nature 412 499 500 11484041
Atrazine Ecological Risk Assessment Panel 1995. Ecological Risk Assessment of Atrazine in North American Surface Water. Greensboro, NC:Ciba Crop Protection.
ATSDR 1995. Toxicological Profile for Polycyclic Aromatic Hydrocarbons. Atlanta, GA:Agency for Toxic Substances and Disease Registry. Available: http://www.atsdr.cdc.gov/ toxprofiles/tp69.html [accessed 14 January 2005].
Baatrup E Junge M 2001 Antiandrogenic pesticides disrupt sexual characteristics in the adult male guppy (Poecilia reticulata ) Environ Health Perspect 109 1063 1070 11675272
Bergeron JM Crews D McLachlan JA 1994 PCBs as environmental estrogens: turtle sex determination as a biomarker of environmental contamination Environ Health Perspect 102 780 781 9657710
Blaustein AR Wake DB 1990 Declining amphibian populations: a global phenomenon? Trends Ecol Evol 5 203 204
Brodman R Kilmurry M 1998. Status of amphibians in northwestern Indiana. In: Status and Conservation of Midwestern Amphibians (Lannoo MJ, ed). Iowa City, IA:University of Iowa Press, 125–136.
Carr JA Gentles A Smith EE Goleman WL Urquidi LJ Thuett K 2003 Response of larval Xenopus laevis to atrazine: assessment of growth, metamorphosis, and gonadal and laryngeal morphology Environ Toxicol Chem 22 396 405 12558173
Caspar GS 1998. Review of the status of Wisconsin amphibians. In: Status and Conservation of Midwestern Amphibians (Lannoo MJ, ed). Iowa City, IA:University of Iowa Press, 199–205.
Chaloupka K Harper N Krishnan V Santostefano M Rodriguez LV Safe S 1993 Synergistic activity of poly-nuclear aromatic hydrocarbon mixtures as aryl hydrocarbon (Ah) receptor agonists Chem Biol Interact 89 141 158 8269543
Chaloupka K Krishnan V Safe S 1992 Polynuclear aromatic hydrocarbon carcinogens as antiestrogens in MCF-7 human breast cancer cells: role of the Ah receptor Carcinogenesis 13 2233 2239 1335374
Clark EJ Norris DO Jones RE 1998 Interactions of gonadal steroids and pesticides (DDT, DDE) on gonaduct growth of larval tiger salamanders, Ambystoma tigrinum Gen Comp Endocrinol 109 94 105 9446727
Diana SG Resetarits WJ Jr Schaeffer DJ Beckmen KB Beasley VR 2000 Effects of atrazine on amphibian growth and survival in artificial aquatic communities Environ Toxicol Chem 19 2961 2967
Fry DM Toone CK 1981 DDT-induced feminization of gull embryos Science 213 922 924 7256288
Guillette LJ Jr Crain DA Rooney AA Pickford DB 1995 Organization versus activation: the role of endocrine disrupting contaminants (EDCs) during embryonic development in wildlife Environ Health Perspect 103 suppl 7 157 164 8593864
Guillette LJ Jr Gross TS Masson GR Matter JM Percival HF Woodward AR 1994 Developmental abnormalities of the gonad and abnormal sex hormone concentrations in juvenile alligators from contaminated and control lakes in Florida Environ Health Perspect 102 680 688 7895709
Hansen L 1987. Environmental toxicology of polychlorinated biphenyls. In: Environmental Toxin Series 1: Polychlorinated Biphenyls (PCBs): Mammalian and Environmental Toxicology (Safe S, Hutzinger O, eds). Vol 1. New York:Springer-Verlag, 15–48.
Hayes T Haston K Tsui M Hoang A Haeffele C Vonk A 2003 Atrazine-induced hermaphrodism at 0.1 ppb in American leopard frogs (Rana pipiens ): laboratory and field evidence Environ Health Perspect 111 568 575 12676617
Hayes TB Collins A Lee M Mendoza M Noriega N Stuart AA 2002 Hermaphroditic, demasculinized frogs after exposure to the herbicide atrazine at low ecologically relevant doses Proc Natl Acad Sci USA 99 5476 5480 11960004
Houlahan JE Findlay CS Schmidt BR Meyer AH Kuzman SL 2000 Quantitative evidence for global amphibian population declines Nature 404 752 755 10783886
Jansen HT Cook PS Porcelli J Liu TC Hansen LG 1993 Estrogenic and antiestrogenic actions of PCBs in the female rat: in vitro and in vivo studies Reprod Toxicol 7 237 248 8318755
Johnson PT Lunde KB Zelmer DA Werner JK 2003 Limb deformities as an emerging parasitic disease in amphibians: evidence from museum specimens and resurvey data Conserv Biol 17 1724 1737
Jung RE 1993 Blanchard’s cricket frogs (Acris crepitans blanchardi ) in southwest Wisconsin Tran Wisc Acad Sci Arts Lett 81 79 87
Krishnan V Safe S 1993 Polychlorinated biphenyls (PCBs), dibenzo-p -dioxins (PCDDs), and dibenzofurans (PCDFs) as antiestrogens in MCF-7 human breast cancer cells: quantitative structure-activity relationships Toxicol Appl Pharmacol 120 55 61 7685553
Li MH Hansen LG 1996 Enzyme induction and acute endocrine effects in prepubertal female rats receiving environmental PCB/PCDF/PCDD mixtures Environ Health Perspect 104 712 722 8841756
Li MH Zhao YD Hansen LG 1994 Multiple dose toxicokinetic influence on the estrogenicity of 2,2’,4,4’,5,5’-hexachloro-biphenyl Bull Environ Contam Toxicol 53 583 590 8000188
Ludwig DR Redmer M Domazlicky R Kobal S Conklin B 1992 Current status of amphibians and reptiles in DuPage County, Illinois Trans Ill St Acad Sci 85 187 199
Machala M Ciganek M Blaha L Minksova K Vondrak J 2001 Aryl hydrocarbon receptor-mediated and estrogenic activities of oxygenated polycyclic aromatic hydrocarbons and azaarenes originally identified in extracts of river sediments Environ Toxicol Chem 20 2736 2743 11764156
Malby TA Bjerke DL Moore RW Fendron-Fitzpatrick A Peterson RE 1992 In utero and lactational exposure of male rats to 2,3,7,8-tetrachlorodibenzo-p -dioxin. 3. Effects on spermatogenesis and reproductive capability Toxicol Appl Pharmacol 114 118 126 1585364
Matta MB Cairncross C Kocan RM 1998 Possible effects of polychlorinated biphenyls on sex determination in rainbow trout Environ Toxicol Chem 17 26 39
McCallum ML Trauth SE 2003 A forty-three year museum study of northern cricket frog (Acris crepitans ) abnormalities in Arkansas: upward trends and distributions J Wildl Dis 39 522 528 14567212
Mellanby K 1992. The DDT Story. Farnham, England:British Crop Protection Council.
Metcalfe TL Metcalfe CD Kiparissis Y Niimi AJ Foran CM Benson WH 2000 Gonadal development and endocrine responses in Japanese medaka (Oryzias latipes ) exposed to o,p ’-DDT in water or through maternal material Environ Toxicol Chem 19 1893 1900
Mierzwa KS 1998. Status of northeastern Illinois amphibians. In: Status and Conservation of Midwestern Amphibians (Lannoo MJ, ed). Iowa City, IA:University of Iowa Press, 115–124.
Minton SA 1998. Observations on Indiana amphibian populations: a forty-five-year overview. In: Status and Conservation of Midwestern Amphibians (Lannoo MJ, ed). Iowa City, IA:University of Iowa Press, 217–220.
Moriarity JJ 1998. Status of amphibians in Minnesota. In: Status and Conservation of Midwestern Amphibians (Lannoo MJ, ed). Iowa City, IA:University of Iowa Press, 166–168.
Mossman MJ Hartman LM Hay R Sauer JR Dhuey BJ 1998. Monitoring long-term trends in Wisconsin frog and toad populations. In: Status and Conservation of Midwestern Amphibians (Lannoo MJ, ed). Iowa City, IA:University of Iowa Press, 169–198.
Palmer BD Huth LK Pieto DL Selcer KW 1998 Vitellogenin as a biomarker for xenobiotic estrogens in an amphibian model system Environ Toxicol Chem 17 30 36
Palmer BD Palmer SK 1995 Vitellogenin induction by xenobiotic estrogens in the red-eared slider turtle and African clawed frog Environ Health Perspect 103 suppl 4 19 25 7556019
Qin ZF Zhou JM Chu SG Xu XB 2003 Effects of Chinese domestic polychlorinated biphenyls (PCBs) on gonadal differentiation in Xenopus laevis Environ Health Perspect 111 553 556 12676614
Reeder AL Foley G Nichols D Wikoff B Faeh S Eisold J 1998 Forms and prevalence of intersexuality and effects of environmental contaminants on sexuality in cricket frogs (Acris crepitans ) Environ Health Perspect 106 261 266 9647894
Shaffer HB Fisher RN Davidson C 1998 The role of natural history collections in documenting species declines Trends Ecol Evol 13 27 30 21238186
Smith PW 1961. The Amphibians and Reptiles of Illinois. Urbana, IL:Illinois Natural History Survey.
Sullivan KB Spence KM 2003 Effects of sublethal concentrations of atrazine and nitrate on metamorphosis of the African clawed frog Environ Toxicol Chem 22 627 635 12627652
Thomas P Budiantara L 1995 Reproductive life history stages sensitive to oil and naphthalene in Atlantic croaker Marine Environ Res 39 147 150
Tyler MJ 1991 Declining amphibian populations—a global phenomenon? An Australian perspective Alytes 9 43 50
U.S. Army Service Forces 1946. Application of DDT by Airplane for Mosquito Control at Savanna Ordnance Depot Proving Grounds, Illinois, 1946. Chicago:Army Service Forces, Sixth Service Command, Repairs and Utilities Division.
Vogt RC 1981. Natural History of Amphibians and Reptiles in Wisconsin. Milwaukee, WI:Milwaukee Public Museum.
|
15743712
|
PMC1253749
|
CC0
|
2021-01-04 23:40:56
|
no
|
Environ Health Perspect. 2005 Mar 7; 113(3):261-265
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7276
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7315ehp0113-00026615743713ResearchArticlesMercury in Commercial Fish: Optimizing Individual Choices to Reduce Risk Burger Joanna 12Stern Alan H. 34Gochfeld Michael 241Division of Life Sciences, Rutgers University, Piscataway, New Jersey, USA2Environmental and Occupational Health Sciences Institute, Consortium for Risk Evaluation with Stakeholder Participation, and School of Public Health, Rutgers University/University of Medicine & Dentistry of New Jersey-Robert Wood Johnson Medical School, Piscataway, New Jersey, USA3Division of Science, Research, and Technology, New Jersey Department of Environmental Protection, Trenton, New Jersey, USA4Environmental and Occupational Medicine, University of Medicine & Dentistry of New Jersey-Robert Wood Johnson Medical School, Piscataway, New Jersey, USAAddress correspondence to J. Burger, 604 Allison Rd., Rutgers University, Piscataway, New Jersey, 08854-8082 USA. Telephone: (732) 445 4319. Fax: (732) 445 5870. E-mail:
[email protected] research was supported by the Division of Science, Research, and Technology, New Jersey Department of Environmental Protection, a National Institute of Environmental Health Sciences Center grant (ESO 5022), the Consortium for Risk Evaluation with Stakeholder Participation (Department of Energy, nos. DE-FC01-95EW55084, DE-FG 26-00NT 40938), and Environmental and Occupational Health Sciences Institute. The views expressed in this paper are solely those of the authors.
The authors declare they have no competing financial interests.
3 2005 7 12 2004 113 3 266 271 9 6 2004 7 12 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Most attention to the risks from fish consumption has focused on recreational anglers and on fish caught by individuals, but the majority of fish that people eat are purchased from commercial sources. We examined mercury levels in three types of fish (tuna, flounder, bluefish) commonly available in New Jersey stores, sampling different regions of the state, in communities with high and low per capita incomes, and in both supermarkets and specialty fish markets. We were interested in species-specific levels of mercury in New Jersey fish and whether these levels were similar to data generated nationally by the Food and Drug Administration (FDA; mainly from 1990 to 1992) on the same types of fish. Such information is critical for providing public health advice. We were also interested in whether mercury levels in three common species of fish differed by region of the state, economic neighborhood, or type of store. We found significant species differences, with tuna having the highest levels and flounder the lowest levels. There were no significant differences in mercury levels as a function of type of store or economic neighborhood. There was only one regional difference: flounder from fish markets along the Jersey shore had higher mercury levels than flounder bought in other markets. We also examined mercury levels in six other commonly available fish and two shellfish from central New Jersey markets. There were significant differences in availability and in mercury levels among fish and shellfish. Both shrimp and scallops had total mercury levels < 0.02 ppm (wet weight). Large shrimp had significantly lower levels of mercury than small shrimp. For tuna, sea bass, croaker, whiting, scallops, and shrimp, the levels of mercury were higher in New Jersey samples than those reported by the FDA. Consumers selecting fish for ease of availability (present in > 50% of markets) would select flounder, snapper, bluefish, and tuna (tuna had the highest mercury value), and those selecting only for price would select whiting, porgy, croaker, and bluefish (all with average mercury levels < 0.3 ppm wet weight). Flounder was the fish with the best relationship among availability, cost, and low mercury levels. We suggest that state agencies responsible for protecting the health of their citizens should obtain information on fish availability in markets and fish preferences of diverse groups of citizens and use this information to select fish for analysis of contaminant levels, providing data on the most commonly eaten fish that will help people make informed decisions about risks from fish consumption.
commercial fishconsumptionfishmercuryNew Jerseyrisk assessmentFDA
==== Body
Fish are an important source of protein for many people throughout the world, and their importance in the diet has increased among health-conscious Americans. Not only are fish an important source of nutrients, but fishing is a popular pastime (Burger 2002; Burger et al. 1992, 1993; Knuth et al. 2003; Toth and Brown 1997), in urban as well as in rural areas (Burger et al. 1999, 2001b; Ramos and Crain 2001). Fish provide omega-3 (n-3) fatty acids that reduce cholesterol levels and the incidence of heart disease, stroke, and preterm delivery (Anderson and Wiener 1995; Daviglus et al. 2002; Patterson 2002).
However, contaminant levels, particularly methyl mercury and polychlorinated biphenyls (PCBs), are sufficiently high in some fish to cause adverse human health effects in people consuming large quantities [Hightower and Moore 2003; Hites et al. 2004; Institute of Medicine (IOM) 1991; Stern 1993]. Fish consumption is the only significant source of methyl mercury in the public (Rice et al. 2000). Methyl mercury is reported to counteract the cardioprotective effects (Guallar et al. 2002; Rissanen et al. 2000; Salonen et al. 1995) and to damage developing fetuses and young children [National Research Council (NRC) 2000]. Maternal exposures can threaten the fetus because chemicals can be transferred to the developing fetus (Gulson et al. 1997, 1998). There is a positive relationship between mercury and PCB levels in fish, fish consumption by pregnant women, and deficits in neurobehavioral development in children (IOM 1991; Jacobson and Jacobson 1996; Lonky et al. 1996; NRC 2000; Schantz 1996; Schantz et al. 2003; Sparks and Shepherd 1994; Stern et al. 2004). There is also a decline in the fecundity of women who consume large quantities of contaminated fish from Lake Ontario (Buck et al. 2000). Mercury in fish has been featured in the media frequently, and people are faced with conflicting information about the risks and benefits of consuming fish (Consumer Reports 2001; Rauber 2001).
State agencies respond to the risk of chemicals in fish by issuing consumption advisories to inform the public about possible risks (especially to at-risk populations, such as pregnant women and children). The number of fish advisories due to chemicals, such as mercury and PCBs, has increased in the United States over the last decade [U.S. Environmental Protection Agency (EPA) 2004]. With few exceptions, state advisories do not provide information on the risk from consuming fish purchased commercially. Some states, such as New York, specifically highlight that the advisories are not for fish and game sold in markets (New York State Department of Health 2002). Recently the U.S. Food and Drug Administration (FDA 2001, 2004) issued a series of consumption advisories regarding methyl mercury that suggested that pregnant women and women of childbearing age who may become pregnant should limit their fish consumption, avoid eating four types of marine fish (shark, swordfish, king mackerel, tilefish) and limit their consumption of all other low-mercury fish to 12 ounces/week (FDA 2001). These recent FDA (2001, 2003) advisories have raised concern about the safety of fish available in supermarkets, yet there are very few data on mercury levels in commercial fish, particularly for fish expected to have low levels.
In this study we examined total mercury levels in fish in New Jersey. We used a two-tiered approach: a) examination of mercury levels in tuna, bluefish, and flounder purchased over a broad geographical range stratified by region, economics, and store type; and b) examination of mercury levels in a range of different fish and shellfish purchased in central New Jersey. We were interested in species-specific levels of mercury in New Jersey fish and whether these levels were similar to data generated nationally by the FDA on the same species (mainly from 1990 to 1992). A determination of whether national data on mercury concentrations by commercial fish species represents concentrations found in local fish can help public health providers and state health officials design their health and consumption advisories. New Jersey was specifically interested in whether the mercury levels in fish commonly sold in the state were in the range where issuing consumption advisories should be considered.
We examined different regions of New Jersey because the sources of the fish might differ. That is, fish sold in stores in southern New Jersey often comes from fish markets in Philadelphia, Pennsylvania, while fish in northern New Jersey often comes from the Fulton Fish Market in New York, New York. Thus, commercial fish enter New Jersey markets from several sources: the Fulton Fish Market, the Philadelphia fish market, commercial landings along the New Jersey coast, supermarket wholesalers, and party and charter boats. Further, fish caught locally (such as flounder and bluefish) often comes from the nearest fishing ports. Similarly, upscale and downscale markets may obtain their fish from different sources, particularly for locally available fish. Thus, it is important to understand whether mercury levels might differ in fish purchased in different regions of the state. We initially selected the three types of fish, tuna, bluefish, flounder, based on their widespread availability and the belief that they are commonly consumed and would represent high, medium, and low mercury concentrations (National Fisheries Institute 2004). Other fish were selected to represent commonly available species and those we expected would have low levels of mercury. One of our objectives was to provide data to agencies and the public on species that might pose little risk from mercury, thus providing positive information that could inform personal choices.
Fish consumers face a series of choices regarding whether to eat fish they catch or commercial fish, which species to eat, what trophic level or size of fish to eat, and how much fish to eat. To make these decisions, they must know the levels of contaminants in the fish that are commercially available. The advisories promulgated by state agencies and the FDA deal with fish that have high mercury levels and often do not provide information on fish that may be low in mercury. This study partly addresses this issue. We also combined information on availability and price with mercury levels to consider how people might reduce their risk within their local community.
Methods
Our overall research design was to a) determine fish availability (and price) in the state generally (Burger et al. 2004); b) buy three types of fish from supermarkets and fish markets throughout the state, in towns with higher and lower socioeconomic status (SES); c) use the information on availability and hypothesized mercury levels to select six additional fish and two shellfish for mercury analysis to provide information on a broader range of species; d) determine the total mercury in these fish and shellfish; and e) compare the mercury data from this study with that available from the FDA that is otherwise used by state health departments and the public for guidance. The FDA generally obtains its fish by random, geographically stratified sampling (Yess 1993), combined with data gathered incidentally from inspections.
New Jersey is commonly divided into regions for administrative purposes, including the relatively urbanized north and the very rural south, as well as a large, central suburban region. For the fish availability (and price) aspect of the study (Burger et al. 2004), we visited 57 markets and fish markets in New Jersey, selected randomly from a stratified design that included four regions (north, central, south, coast), high and low SES towns, and supermarkets/fish markets. Stores were visited three times, and the fish species selected for this study were available all three times; however, a more detailed study of fish availability on a yearly basis would provide information on how availability differs seasonally, especially for winter versus summer. At a number of markets we asked about sources of fish, but the general response tied back only to the immediate suppliers. Because markets were surveyed from July through October, the data represent this time period.
For collection of fish for mercury analysis, we selected one town of higher and one of lower SES in each of the three regions and randomly selected individual stores from New Jersey’s Seafood and Fish Index Page (International Purveyor Index 2002). Both the towns within each region and the markets/ supermarkets within each town were selected randomly from those available. We defined “high” SES as above the median per-capita income for that region, and “low” SES as below the median per-capita income, and we used the U.S. Census Bureau (2000) data for per-capita income. Once we had divided the towns in New Jersey into high and low SES, we randomly selected the towns within each region for sampling. We then collected fish from two supermarkets and two fish markets in each town. Supermarkets were large chain stores selling a range of food and other grocery items, and fish markets sold primarily fish. Only fish markets were sampled along the shore, and these were mainly in shore communities with a high number of summer residents. Although we tried to balance the sample sizes from each geographical region, from high to low SES, and from fish market/supermarket, this was not always possible. In addition, we purchased the same three fish types in fish markets in the coastal area from Sandy Hook to Cape May. All purchases were made between July and October 2003.
From each market we purchased a fillet of tuna, flounder, and bluefish. Because we purchased only fillets, we do not provide data on the basis of fish size. Tuna steaks were mainly identified as yellowfin tuna (Thunnus albacaras), although verification to the species level is not certain. A variety of flatfish are sold under the rubric of flounder, and these may come from New Jersey waters or from remote parts of the globe. Bluefish (Pomatomus saltatrix) is a popular east coast sport fish and in the past decade has become widely available in stores. Tuna are large predatory fish; bluefish are medium sized predatory fish; and flounder are bottom-dwelling fish, usually reported to be low in mercury (FDA 2001). We also bought fillets of six other species of fish from markets in central New Jersey, representing widely available fish in New Jersey markets. We also purchased scallops, and large (mean mass of 20 ± 4 g) and small (mean of 8 ± 1 g) shrimp. All fish collected for this study were fresh, although we also present information on canned tuna (after Burger and Gochfeld 2004).
We analyzed mercury at the Environmental and Occupational Health Sciences Institute of Rutgers University. A 2-g (wet weight) sample of fish tissue was digested in ultrex ultrapure nitric acid in a microwave using a digestion protocol of three stages of 10 min each under 50, 100, and 150 lb per square inch (3.5, 7, and 10.6 kg/cm2) at 80× power. Digested samples were subsequently diluted in 100 mL deionized water. All laboratory equipment and containers were washed in 10% HNO3 solution before each use (Burger et al. 2001a).
Mercury was analyzed by the cold vapor technique using the Portable Zeeman Lumex (RA-915) mercury analyzer (Ohio Lumex Co., Twinsburg, OH), with an instrument detection level of 0.2 ng/g, and a matrix level of quantification of 0.002 μg/g. All concentrations are expressed in parts per million (equal to micrograms per gram) of total mercury on a wet-weight basis. In another study (Burger et al. 2001c) we found that the dry weight ranged from 23% to 33% of the corresponding wet weight (i.e., water content of 67–77%) for 11 species of fish. Many studies have shown that almost all of the mercury in fish tissue is methyl mercury, and 90% is a reasonable approximation of this proportion, which does vary somewhat among fish types and laboratories. We used a DORM-2 Certified dogfish tissue (National Research Council of Canada, Institute of Environmental Research and Technology, Ottawa, Ontario, Canada) as the initial calibration verification standard. Recoveries between 90 and 110% were accepted to validate the calibration. All specimens were run in batches that included blanks, a standard calibration curve, two spiked specimens, and one duplicate. The accepted recoveries for spikes ranged from 85 to 115%; no batches were outside of these limits. We analyzed each digested fish sample twice, with agreement of ± 5%. In addition, 10% of samples were digested twice and analyzed as blind replicates (with agreement within 15%). For further quality control, a random subset totaling 12% of samples was sent to the Quebec Laboratory of Public Health. The correlation between the two laboratories was 0.92 (p < 0.0001).
We used Kruskal-Wallis nonparametric one-way analysis of variance (ANOVA; generating a chi-square statistic) to examine differences among fish species and locations. We also used ANOVA with Duncan multiple range tests to identify the significant differences (SAS Institute 1995). The level for significance was designated as p < 0.05, but values up to p < 0.10 are presented to allow the reader to evaluate whether increased sample sizes would have resulted in significance.
Results
There were significant differences in mercury levels among tuna, bluefish, and flounder, with tuna having the highest levels and flounder the lowest levels (χ2 = 26.3, p < 0.001). However, for all three species, there were few differences in mercury as a function of region, type of market, and economic neighborhood (Table 1). Indeed, there was remarkably little variation in mercury levels among fish types (i.e., low standard errors). From a risk perspective, knowing the percentage of fish that may have mercury levels > 0.3 or 0.5 ppm may be important in their selection process. For fresh tuna, the species with the highest mercury levels, 42% of the fillets had mercury levels > 0.5 ppm (Table 2).
There were also significant differences in mercury levels among the other species of fish and shellfish examined (Table 3). Large shrimp had significantly lower levels of mercury than small shrimp (χ2 = 7.7, p < 0,006), perhaps because there is growth dilution in large shrimp.
Once a personal choice has been made to eat fish, the consumer must decide what types to eat. This decision may be based on several social and economic factors besides mercury concentrations, including price and availability. The fish examined in this study were not equally available in all stores, nor were they equally priced (Figure 1). Only whiting, croaker, red snapper, and tuna were available in > 50% of the stores. Fish priced < $5.00/lb ($2.27/kg) included whiting, porgy, croaker, and bluefish. If consumers selected the fish that were most available, there was a range of potential mercury exposures. If consumers selected on the basis of cost, then the range of mercury levels in these fish were even lower (Figure 2). Consumers who consistently selected the fish that were the most available and the lowest priced would select whiting, flounder, porgy, and bluefish, with bluefish having the highest mercury values (Figure 2).
Discussion
Mercury levels in commercial fish.
Other than the mercury levels in commercial fish and shellfish reported by the FDA (2004), there are few peer-reviewed, published articles that give mercury levels. In one article reporting mercury levels in canned tuna (Burger and Gochfeld 2004), total mercury levels averaged 0.37 ppm for white tuna and 0.118 ppm for light tuna. Since the FDA only presents means and ranges, but no measures of variation, a detailed statistical comparison is not possible. However, the comparison of means is still instructive (FDA 2004; Table 4). For most species of fish we tested, the New Jersey data showed somewhat higher mean mercury levels (even accounting for the FDA data as methyl mercury). The discrepancies could be due to year (fish for this paper were collected in 2003, compared to 1990–1992 for most FDA data), differences in the source (New Jersey may get its fish from local areas with higher levels of mercury in the marine waters), lumping data for many years, or differences in the sizes of the fish (larger fish usually have higher mercury levels) (Bidone et al. 1997; Burger et al. 2001b; Lange et al. 1994). For example, tuna can come from many different oceans, be different species of tuna, and larger individuals accumulate higher levels of mercury than smaller ones. We anticipated that mercury levels might have declined over time due to over-harvesting of large individuals and a shift to harvesting smaller individuals. The FDA database appears to be cumulative from work from 1990 to 1992, and the discrepancies suggest that the FDA and state governments should undertake a broad spectrum survey of mercury and other contaminants in fish to update their database. Further, national averages, as computed by the FDA, include the normal variation found in the regions sampled. From a state regulatory perspective, data that show discrepancies between local data and the FDA data (i.e., fresh tuna) suggests that site-specific data may be required before consumption information or advisories are prepared.
Most of the risk assessments for fish consumption examine chronic exposure, and not a single meal. However, there is recent concern that one meal of fish with a very high mercury content (a pulsed exposure) might adversely impact a developing fetus at a critical developmental period. Ginsberg and Toal (2000) have suggested that there may be risk during pregnancy for even a single-meal exposure, particularly for fish with levels of > 2.0 ppm. In the present study, we found that only tuna fillets had > 2 ppm mercury. We report the percentage of fillets that had levels > 0.5 ppm because of the need to know the percentage of times an exposure in a single meal may approach the tolerable daily intake (Berti et al. 1998). Providing information on risk from single-meal exposures, especially for pregnant women, is a public health communication challenge.
Balancing risk with availability and price.
People are faced with making rational decisions about whether to eat fish or not and what fish to eat. Their choices are influenced by both the benefits and the risks of consuming fish (Egeland and Middaugh 1997; Knuth et al. 2003; Ponce et al. 2000) and by countervailing risks of consuming red meat compared to fish. Their choice not only depends on the available information and their own personal state (e.g., pregnant or not, thinking of becoming pregnant), but it is limited by both availability of different kinds of fish and shellfish, and at least for many Americans, price. Remarkably, although some studies have examined fish consumption as a function of seasonal availability of fish, fish quality, and education and income of the consumer (Bose and Brown 2000; Trondsen et al. 2003), studies have not examined availability and price of fish as a variable in the types of fish consumed. To our knowledge, ours is the first study that examines mercury levels in commercial fish within a context of availability and price for a geographical region the size of New Jersey.
Many of the fish and shellfish examined in this study had levels of mercury < 0.10 ppm and would pose little risk to a developing fetus. Our data suggest that consumers have choices of both shellfish and fish with low mercury levels, and such information should be provided to the public. Information on mercury levels in commercial fish will also be useful to the public in balancing the risks from self-caught and commercial fish. That is, with information on mercury (or other contaminants) in fish from their local lakes or streams, anglers or the family cook can determine whether to eat commercial or self-caught fish and how much of each species to eat. We are a long way from having sufficient information on mercury for people to make these decisions, but we suggest that agencies should go in this direction. From a public health standpoint, commercial fish is the main point of intervention to reduce methyl mercury exposure in the public.
Risk communication.
Risk communication is effective only if the intended message reaches the audience, and if people have acquired sufficient information to feel that they are making informed decisions. Public health officials also hope that risk communication changes behavior in the desired direction. Yet people cannot make rational decisions about whether to eat fish and what kinds of fish to eat unless they have information on the risks from different choices. In our view, this means knowing not only which fish have high levels of mercury—the communication the FDA and states provide—but information on fish species that usually have low contaminant levels. Although some mercury data have been available for many years, only recently have the concentrations of omega-3 fatty acids in different fish been publicized.
It has so far proven easier for agencies to promulgate advisories that tell the public or at-risk audiences what fish not to eat than to advise them about what species of fish are low in contaminants and therefore good to eat. There are several reasons this may be true. First, contaminant analyses are expensive and time-consuming, and agencies concentrate their effort where there is a known or suspected risk. Second, advising people not to eat a fish when contaminant levels have actually declined does not have the same potential adverse effect as telling people to eat a fish that turns out to have high levels (in other words, the cost of being wrong is lower). Third, telling people that one or two species of fish are low in contaminants, while not addressing others, may pose a problem in terms of the marketplace or industry equity, and, finally, the availability of different species of fish differs among geographical regions of the state, and contaminant data on the commonly available fish will be most useful. A regional breakdown is not available in the FDA data (FDA 2004; Yess 1993).
Public health officials and appropriate state agencies should consider making available to the public information on fish that are low in mercury. This would balance the information that is currently available on fish that are high in mercury and allow people to continue to eat fish (often in large quantities) without undue harm to themselves or their children. In addition, there are ethnic preferences in fish (Burger et al. 1999, 2004), and these should be taken into account in obtaining contaminant information to disseminate to the public. Finally, the way fish are labeled is not always accurate. Many species from different parts of the world may be sold under a common rubric such as tuna or flounder. For example, a molecular analysis of fish sold as red snapper revealed that only 45% were actually that fish (Consumer Reports 2001).
We suggest that state agencies responsible for the health of their citizens conduct three kinds of studies: a) fish preferences of consumers as a function of economic, social, and ethnic background; b) fish availability in different regions and in different economic strata; and c) contaminant levels using a suite of fish that optimize for trophic level, consumer preferences, and market availability. This information could then be made available for the state overall, to specific geographical regions, and to different target audiences. With such information, people can make informed decisions about the species of fish to eat within their region and incomes. People’s perceptions, needs, and values with respect to fish consumption are only one part of the equation; the affected communities themselves should be involved in every step of the fish consumption advisory process (Burger 2000; Burger et al. 2003; Jardine 2003; Jardine et al. 2003). That is, stakeholders should be involved in determining which fish to analyze for mercury levels, and how risk information about specific fish should be communicated within their communities.
People do not necessarily respond similarly to positive and negative information (Liu et al. 1998), suggesting that considerable thought should go into how to present data on contaminants. Liu et al. (1998) found that people respond more quickly to negative media coverage than to positive information; but the effect of negative coverage was reduced by positive information relative to consumption. Knuth et al. (2003) showed that people would change their behavior if they were presented with risk/risk and risk/benefit information about fish consumption. In their study, the questionnaire described the health benefits and risks from consuming fish, rather than examining general knowledge. Appropriate changes in behavior are possible only if people have knowledge of the nature of the risks for a range of species, allowing them to choose what they wish to eat. We also suggest that similar information be available on the benefits of specific fish, including levels of omega-3 fatty acids.
Conclusions
Overall, we found no significant differences in mercury levels in tuna, bluefish, and flounder as a function of type of store or economic neighborhood, except that flounder from fish markets along the Jersey shore had higher levels of mercury than flounder bought in other markets. Flounder from shore markets came from very local sources, whereas for the other regions the source of fish may have been from regional fish markets or distribution centers. There were significant differences in mean mercury levels in the fish and shellfish examined. Further, for tuna, sea bass, croaker, whiting, and shrimp, the levels of mercury were higher in New Jersey samples than those reported by the FDA (2004). This suggests that regional differences in mercury levels should be reported when national data on mercury levels are aggregated, allowing state agencies to evaluate possible risk for their citizens. It may also be useful to obtain information on levels of mercury as a function of the source of commercial fish, as well as seasonal trends.
There were significant differences in availability (and cost). We found that consumers optimizing for easy availability would select flounder, snapper, bluefish and tuna, whereas those selecting only for price would select whiting, porgy, croaker, and bluefish. Flounder demonstrated the best relationship among availability, cost, and low mercury levels. We suggest that agencies responsible for protecting human health should obtain information on fish availability and cost in markets, as well as fish preferences, and use this information to select fish for analysis of contaminant levels. This would provide data on the most commonly eaten fish. Public health officials could then provide the public with information on mercury, cost, and availability for commercial fish, allowing them to make informed decisions about which fish to eat.
Correction
In the original manuscript published online, the authors stated that they found “single fillets of tuna, Chilean sea bass, croaker, and red snapper that had > 2 ppm mercury.” This statement has been corrected here to indicate that “only tuna fillets had > 2 ppm mercury.”
Figure 1 Availability (A), price (B), and total mercury levels (wet weight; C) in commercial fish in New Jersey (mean ± SE).
Figure 2 Total mercury levels (wet weight; mean ± SE) in fish if consumers selected the fish that are most available (A), cheapest (B), and optimized for price and availability (C). Letters that differ indicate significant differences (Duncan’s multiple range test).
Table 1 Mercury levels (ppm, wet weight) in commercial fish from New Jersey markets sampled in 2003.
Tuna Bluefish Flounder
Overall sample size (n) 50 53 55
Overall means 0.6 ± 0.1 0.3 ± 0.02 0.05 ± 0.01
New Jersey region
North 0.8 ± 0.2 (12) 0.2 ± 0.02 (15) 0.05 ± 0.01 (17)
Central 0.8 ± 0.2 (16) 0.3 ± 0.02 (16) 0.03 ± 0.01 (16)
South 0.5 ± 0.1 (16) 0.3 ± 0.03 (16) 0.05 ± 0.01 (16)
Shore 0.4 ± 0.1 (6) 0.4 ± 0.09 (6) 0.07 ± 0.02 (6)
χ2 (p) NS NS 8.8 (0.03)
Type
Supermarket 0.8 ± 0.2 (21) 0.2 ± 0.02 (20) 0.05 ± 0.01 (21)
Market 0.5 ± 0.1 (29) 0.3 ± 0.02 (33) 0.05 ± 0.01 (34)
χ2 (p) 2.8 (0.09) NS NS
Socioeconomic status
High 0.6 ± 0.1 (29) 0.3 ± 0.02 (27) 0.05 ± 0.007 (26)
Low 0.7 ± 0.1 (21) 0.2 ± 0.02 (26) 0.04 ± 0.006 (26)
χ2 (p) NS NS NS
NS, not significant. Values shown are mean ± SE (n) except where shown.
Table 2 Overall levels (ppm, wet weight) of mercury in fish collected throughout New Jersey.
Tuna Bluefish Flounder
Sample size (n) 50 53 55
Mean ± SE 0.6 ± 0.1 0.3 ± 0.02 0.05 ± 0.01
Geometric mean 0.4 0.2 0.04
Low value 0.084 0.009 0.002
High value 2.5 0.76 0.14
Percent > 0.3 ppm 62 32 0
Percent > 0.5 ppm 42 2 0
Percent > 0.75 ppm 26 2 0
Table 3 Mercury levels (ppm, wet weight) in commercial fish from New Jersey markets (sampled in 2003).
Species (n) Mean ± SE Geometric mean Minimum Maximum
Chilean sea bass (7) 0.4 ± 0.1a 0.3 0.2 0.6
Red snapper (4) 0.2 ± 0.01b 0.2 0.2 0.3
Cod (7) 0.1 ± 0.006c 0.1 0.08 0.1
Croaker (14) 0.1 ± 0.02c 0.1 0.06 0.3
Porgy (14) 0.08 ± 0.02c 0.08 0.02 0.2
Whiting (14) 0.03 ± 0.004d 0.03 0.006 0.1
Scallops (12) 0.01 ± 0.001d 0.012 0.007 0.02
Shrimp, small (12) 0.02 ± 0.001d 0.01 0.008 0.02
Shrimp, large (12) 0.01 ± 0.001d 0.01 0.002 0.02
χ2 (p) 81 (0.0001)
Different letters indicate significant differences by Duncan’s multiple range test; the same letter indicates no difference between means.
Table 4 Comparison of mercury concentrations (ppm) in fish from the FDA (2004) and from the present study.
Species Present study [mean ± SE (n)] FDA (2004) [mean (n)]
Tuna (fresh) 0.64 ± 0.09 (50) 0.38 (131)
Chilean sea bass 0.38 ± 0.02 (7) 0.27 (35)
Bluefish 0.26 ± 0.02 (53) 0.31 (22)
Porgy 0.08 ± 0.02 (14) —a
Red snapper 0.24 ± 0.01 (4)b 0.19 (25)
Croaker 0.14 ± 0.02 (14) 0.05 (21)
Cod 0.11 ± 0.06 (7) 0.11 (20)
Flounder 0.05 ± 0.01 (55) 0.05 (22)
Whiting 0.03 ± 0.04 (14) ND (2)
Scallop 0.01 ± 0.00 (12) 0.05 (66)
Shrimp 0.02 ± 0.00 (24) ND (24)
Tuna (canned albacore) 0.37 ± 0.02 (123)c 0.35 (179)
ND, not detectable. Our values are total mercury, but FDA (2004) values are sometimes given as total mercury and sometimes as methyl mercury. A subset analyzed for methyl mercury indicated that methyl mercury is 89% of total mercury, at least for canned tuna (Burger and Gochfeld 2004).
a Not examined.
b In a 2000 sample of 80 fish, we obtained lower values for mercury.
c Results from Burger and Gochfeld (2004) from our laboratory.
==== Refs
References
Anderson PD Wiener JB 1995. Eating fish. In: Risk versus Risk: Tradeoffs in Protecting Health and the Environment (Graham JD, Wiener JB, eds). Cambridge, MA:Harvard University Press, 104–123.
Berti PR Receveur O Chan HM Kuhnlein HV 1998 Dietary exposure to chemical contaminants from traditional food among adult Dene/Metis in the western Northwest Territories, Canada Environ Res 76 1 131 142 9515068
Bidone ED Castilhos ZC Santos TJS Souza TMC Lacerda LD 1997 Fish contamination and human exposure to mercury in Tartarugalzinho River, Northern Amazon, Brazil. A screening approach Water Air Soil Pollut 97 1 9 15
Bose S Brown N 2000 A preliminary investigation of factors affecting seafood consumption behaviour in the inland and coastal regions of Victoria, Australia J Consumer Studies Home Econ 24 4 257 262
Buck GM Vena JE Schisterman EF Dmochowski J Mendola P Sever LE 2000 Parental consumption of contaminated sport fish from Lake Ontario and predicted fecundability Epidemiology 11 4 388 393 10874544
Burger J 2000 Consumption advisories and compliance: the fishing public and the deamplification of risk J Environ Plan Manage 43 4 471 488
Burger J 2002 Consumption patterns and why people fish Environ Res 90 1 125 135 12483803
Burger J Cooper K Gochfeld M 1992 Exposure assessment for heavy metal ingestion from a sport fish in Puerto Rico: estimating risk for local fishermen J Toxicol Environ Health 36 4 355 365 1507267
Burger J Gaines KF Boring CS Stephens WL Jr Snodgrass J Gochfeld M 2001a Mercury and selenium in fish from the Savannah River: species, trophic level, and locational differences Environ Res 87 1 108 118 11683594
Burger J Gaines KF Gochfeld M 2001b Ethnic differences in risk from mercury among Savannah River fishermen Risk Anal 21 3 533 544 11572431
Burger J Gaines KF Stephens WL Jr Boring CS Brisbin IL Jr Snodgrass J 2001c Radiocesium in fish from the Savannah River and Steel Creek: potential food chain exposure to the public Risk Anal 21 3 545 559 11572432
Burger J Gochfeld M 2004 Mercury in canned tuna: white versus light and temporal variation Environ Res 96 2 239 249 15364590
Burger J McDermott MH Chess C Bochenek E Perez-Lugo M Pflugh KK 2003 Evaluating risk communication about fish consumption advisories: efficacy of a brochure versus a classroom lesson in Spanish and English Risk Anal 23 4 791 803 12926571
Burger J Pflugh KK Lurig L von Hagen LA von Hagen SA 1999 Fishing in urban New Jersey: ethnicity affects information sources, perception, and compliance Risk Anal 19 2 217 229 10765401
Burger J Staine K Gochfeld M 1993 Fishing in contaminated waters: knowledge and risk perception of hazards by fishermen in New York City J Toxicol Environ Health 3 1 95 105 8492332
Burger J Stern AH Dixon C Jeitner C Shukla S Burke S 2004 Fish availability in supermarkets and fish markets in New Jersey Sci Total Environ 333 1 89 97 15364521
Consumer Reports 2001. America’s fish: fair or foul? Yonkers, NY:Consumers Union. Available: http://www.consumerre-ports.org/special/consumerInteret/Reports/0102fis0.html [accessed 1 April 2004].
Daviglus M Sheeshka J Murkin E 2002 Health benefits from eating fish Comments Toxicol 8 4–6 345 374
Egeland GM Middaugh JP 1997 Balancing fish consumption benefits with mercury exposure Science 278 1904 1905 9417640
FDA 2001. FDA Consumer Advisory. Washington, DC:Food and Drug Administration. Available: http//www.fda.gov/bbs/topics/ANSWERS/2000/advisory.html [accessed 1 December 2001].
FDA 2003. FDA Consumer Advisory. Washington, DC:Food and Drug Administration. Available: http//www.fda.gov/bbs/topics/ANSWERS/2000/advisory.html [accessed 1 January 2004].
FDA 2004. Mercury Levels in Commercial Fish and Shellfish. Washington, DC:Food and Drug Administration. Available: http://vm.cfsan.fda.gov/~frf/sea-mehg.html [accessed 1 April 2004].
Ginsberg GL Toal BF 2000 Development of a single-meal fish consumption advisory for methyl mercury Risk Anal 20 1 41 47 10795337
Guallar E Sanz-Gallardo MI van’t Veer P Bode P Aro A Gomez-Aracena J 2002 Heavy metals and Myocardial Infarction Study Group: mercury, fish oils, and the risk of myocardial infarction N Engl J Med 347 22 1747 1754 12456850
Gulson BL Jameson CS Mahaffey KR Mizon KJ Korsch MJ Vimpani G 1997 Pregnancy increases mobilization of lead from maternal skeleton J Lab Clin Med 130 1 51 62 9242366
Gulson BL Mahaffey KR Jameson CW Mizon KJ Korsch MJ Cameron MA 1998 Mobilization of lead from the skeleton during the postnatal period is larger than during pregnancy J Lab Clin Med 131 4 324 329 9579385
Hightower JM Moore D 2003 Mercury levels in high-end consumers of fish Environ Health Perspect 111 604 608 12676623
Hites RA Foran JA Carpenter DO Hamilton MC Knuth BA Schwager SJ 2004 Global assessment of organic contaminants in farmed salmon Science 303 5655 226 229 14716013
International Purveyor Index 2002. Fish and Seafood: New Jersey. Lakewood, CO:International Purveyor Index. Available: http://www.ipindex.com/listing.lasso [accessed 10 January 2002].
IOM (Institute of Medicine) 1991. Seafood Safety. Washington, DC:National Academy Press.
Jacobson JL Jacobson SW 1996 Intellectual impairment in children exposed to polychlorinated biphenyls in utero N Engl J Med 335 11 783 789 8703183
Jardine C Hrudey S Shortreed J Craig L Krewski D Furgal C 2003b Risk management frameworks for human health and environmental risks J Toxicol Environ Health B Crit Rev 6 569 720 14698953
Jardine CG 2003 Development of a public participation and communication protocol for establishing fish consumption advisories Risk Anal 23 3 461 471 12836839
Knuth B Connelly NA Sheeshka J Patterson J 2003 Weighing health benefits and health risk information when consuming sport-caught fish Risk Anal 23 6 1185 1197 14641893
Lange TR Royals HE Connor LL 1994 Mercury accumulation in largemouth bass (Micropterus salmoides ) in a Florida Lake Arch Environ Contam Toxicol 27 4 466 471 7811106
Liu S Huang JC Brown GL 1998 Information and risk perception: a dynamic adjustment process Risk Anal 18 6 689 699 9972578
Lonky E Reihman J Darvill T Mather J Sr Daly H 1996 Neonatal behavioral assessment scale performance in humans influenced by maternal consumption of environmentally contaminated fish J Great Lakes Res 22 2 198 212
New York State Department of Health 2002. Health Advisories: Chemicals in Sportfish and Game. Albany, NY:New York State Department of Health. Available: http://www.health.state.ny.us/nysdoh/environ/fish98.htm [accessed 19 January 2005].
NFI 2004. Top 10 Seafoods. McLean, VA:National Fisheries Institute. Available: http://www.nfi.org/?a=news&b=News%20Releases&year=&x=2317 [accessed 31 October 2004].
NRC (National Research Council) 2000. Toxicological Effects of Methylmercury. Washington, DC:National Academy Press.
Patterson J 2002 Introduction—comparative dietary risk: balance the risks and benefits of fish consumption Comments Toxicol 8 4–6 337 344
Ponce RA Bartell SM Wong EY LaFlamme D Carrington C Less RC 2000 Use of quality-adjusted life year weights with dose-response models for public health decisions: a case study of the risks and benefits of fish consumption Risk Anal 20 4 529 542 11051076
Ramos AM Crain EF 2001 Potential health risks of recreational fishing in New York City Ambulat Pediatr 1 5 252 255
Rauber P 2001. Fishing for life. Sierra, November:42–49.
Rice G Swartout J Mahaffey K Schoeny R 2000 Derivation of U.S. EPS’s oral reference dose (RfD) for methylmercury Drug Chem Toxicol 23 1 41 54 10711388
Rissanen T Voutilainen S Nyyssonen K Lakka TA Salonen JT 2000 Fish oil-derived fatty acids, docosahexaenoic acid and docosaphentaenoic acid, and the risk of acute coronary events: the Kuopio ischaemic heart disease risk factor study Circulation 102 22 2677 2679 11094031
Salonen JT Seppanen K Nyyssonen K Korpela H Kauhanen J Kantola M 1995 Intake of mercury from fish, lipid peroxidation, and the risk of myocardial infarction and coronary, cardiovascular, and any death in eastern Finnish men Circulation 91 3 645 655 7828289
SAS Institute 1995. SAS Users’ Guide. Cary, NC:SAS Institute, Inc.
Schantz SL 1996 Developmental neurotoxicity of PCBs in humans: what do we know and where do we go from here? Neurotoxicol Teratol 18 3 217 227 8725628
Schantz SL Widholm JJ Rice DC 2003 Effects of PCB exposure on neuropsychological function in children Environ Health Perspect 111 357 376 12611666
Sparks P Shepherd R 1994 Public perceptions of the potential hazards associated with food production: an empirical study Risk Anal 14 5 799 808 7800864
Stern AH 1993 Re-evaluation of the reference dose for methylmercury and assessment of current exposure levels Risk Anal 13 3 355 364 8341810
Stern AH Jacobson JL Ryan L Burke TA 2004 Do recent data from the Seychelles Islands alter the conclusions of the NRC report on the toxicological effects of methylmercury? [Editorial] Environ Health 3 2 14754462
Toth JF Jr Brown RB 1997 Racial and gender meanings of why people participate in recreational fishing Leisure Sci 19 2 129 146
Trondsen T Scholderer J Lund E Eggen AE 2003 Perceived barriers to consumption of fish among Norwegian women Appetite 41 3 301 314 14637329
U.S. Census Bureau 2000. New Jersey QuickFacts. Washington, DC:U.S. Census Bureau. Available: http://quickfacts.census.gov/qfd/states/34000.html [accessed 12 November 2002].
U.S. EPA 2004. National Listing of Fish Advisories. Washington, DC:U.S. Environmental Protection Agency. Available: http://map1.epa.gov [accessed 30 October 2004].
Yess NJ 1993 Food and Drug Administration survey of methylmercury in canned tuna J AOAC Int 76 36 38 8448441
|
15743713
|
PMC1253750
|
CC0
|
2021-01-04 23:40:57
|
no
|
Environ Health Perspect. 2005 Mar 7; 113(3):266-271
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7315
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7370ehp0113-00027215743714ResearchArticlesPCB Exposure and in Vivo CYP1A2 Activity among Native Americans Fitzgerald Edward F. 1Hwang Syni-An 2Lambert George 3Gomez Marta 2Tarbell Alice 41University at Albany, School of Public Health, Rensselaer, New York, USA2New York State Department of Health, Center for Environmental Health, Troy, New York, USA3University of Medicine and Dentistry of New Jersey, Robert Wood Johnson Medical School, New Brunswick, New Jersey, USA4Akwesasne Task Force on the Environment, Mohawk Nation at Akwesasne, Hogansburg, New York, USAAddress correspondence to E.F. Fitzgerald, University at Albany, School of Public Health, One University Place, Rensselaer, NY 12144 USA. Telephone: (518) 402-1062. Fax: (518) 402-0380. E-mail:
[email protected] thank the study participants, the Akwesasne Task Force on the Environment, and the following persons for their past and present help: A. Casey, M. Cayo, A. Jacobs, K. Jock, B. LaFrance, K. Langguth, T. Lauzon, F.H. Lickers, and P. Worswick.
This work was supported in part by the National Institute of Environmental Health Sciences (grants 11256 and 2P42-ES04913), Agency for Toxic Substances and Disease Registry (grant H75/ ATH298312), and the U.S. Environmental Protection Agency (grant R829391).
The authors declare they have no competing financial interests.
3 2005 9 12 2004 113 3 272 277 30 6 2004 9 12 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Cytochrome P-450 1A2 (CYP1A2) is an enzyme involved in the metabolic activation of some carcinogens and is believed to be induced by xenobiotics. Very few studies, however, have investigated the association between environmental exposures and in vivo CYP1A2 activity in humans. To address this issue, a study was conducted of CYP1A2 activity among Native Americans exposed to polychlorinated biphenyls (PCBs) from the consumption of fish from the St. Lawrence River. At the Mohawk Nation at Akwesasne (in New York and in Ontario and Quebec, Canada), 103 adults were interviewed, and they donated blood for serum PCB analysis and underwent the caffeine breath test (CBT), a safe and noninvasive procedure that uses caffeine as a probe for CYP1A2 activity in vivo. The results supported the findings of other studies that CBT values are higher among smokers and men and lower among women who use oral contraceptives. Despite a relatively low average total PCB body burden in this population, the sum of serum levels for nine mono- or di-ortho-substituted PCB congeners showed positive associations with CBT values (p = 0.052 wet weight and p = 0.029 lipid adjusted), as did toxic equivalent quantities (TEQs; p = 0.091 for wet weight and 0.048 for lipid adjusted). Regarding individual congeners, serum levels of PCB-153, PCB-170, and PCB-180 were significantly correlated with CBT values. The results support the notion that CYP1A2 activity may be a marker of an early biological effect of exposure to PCBs in humans and that the CBT may be a useful tool to monitor such effects.
cytochrome P-450 1A2hazardous wasteIndiansNorth AmericanPCBpolychlori-nated biphenyls
==== Body
Cytochrome P-450 1A2 (CYP1A2) is a member of the cytochrome P-450 superfamily of isozymes. It is involved in the metabolic activation of several carcinogens such as aromatic and heterocyclic amines, nitrosamines, and mycotoxins (Eaton et al. 1995). In humans, CYP1A2 has been detected primarily in the liver, in contrast to the closely related CYP1A1, which is expressed in extrahepatic tissues such as lung, placenta, and lymphocytes (Kawajiri 1999). The induction of CYP1A2 has been reported as a consequence of cigarette smoking (Kalow and Tang 1991a; Kotake et al. 1982), the consumption of certain foodstuffs such as charbroiled meat (Conney et al. 1976) and cruciferous vegetables (Pantuck et al. 1979; Vistisen et al. 1992), and therapeutic drugs such as rifamin (Wietholtz et al. 1995), carbamazepine (Parker et al. 1998), and omeprazole (Rost et al. 1994). There is wide variability in CYP1A2 expression among individuals in most ethnic and racial groups studied (Landi et al. 1999), but other than a rare point mutation detected among the Chinese (Huang et al. 1999), no genetic polymorphisms for CYP1A2 have been identified (Nakajima et al. 1994).
Like CYP1A1, CYP1A2 is thought to be induced by exposure to xenobiotics such as 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), polychlorinated biphenyls (PCBs), and other structurally related chemicals that have the ability to bind to the aryl hydrocarbon (Ah) receptor. The evidence for this belief is derived primarily from animal models (Safe 1994) or in vitro studies of mRNA or enzyme levels in treated human liver cells (Lake et al. 1996; Zeiger et al. 2001). Very few studies have investigated in vivo CYP1A2 activity in humans exposed to TCDD, PCBs, or related chemicals, and the results have been contradictory. For example, Lambert et al. (1990) found that persons exposed to polybrominated biphenyls (PBBs) in Michigan had higher levels of CYP1A2-dependent caffeine metabolism than did unexposed controls, but no significant associations were observed between caffeine metabolism and serum TCDD levels among exposed chemical workers (Halperin et al. 1995). The present study addresses the question of whether PCB exposure has affected in vivo CYP1A2 activity among Mohawk men and women at Akwesasne.
Akwesasne is a Native American community of > 10,000 persons located along the St. Lawrence River in New York and in Ontario and Quebec, Canada (Figure 1). Less than 100 ft to the west of Akwesasne is the General Motors–Central Foundry Division Superfund hazardous waste site. This facility used Aroclor 1248, a commercial mixture of various PCB congeners, as a hydraulic fluid in its die-casting machines from 1959 to 1974 (Lacetti 1993). When these machines leaked, the fluids were collected in the wastewater system and disposed of on the property. In the past, concentrations of PCBs have ranged up to 40,000 ppm in on-site soils and sludges, and up to 5,700 ppm offshore in St. Lawrence River sediment (RMT 1986). The Aluminum Company of America (ALCOA) operates two aluminum-processing facilities in the area (ALCOA Plant West and ALCOA Plant East, the latter being formerly operated by Reynolds Metals, Inc.) and also has used Aroclor 1248 in its heat-transfer equipment. These facilities also have released PCBs into the St. Lawrence and its tributaries (Ecology and Environment Inc. 1992). The PCBs have entered the local food chain, with some species of local fish, reptiles, amphibians, birds, and mammals having levels that exceed the U.S. Food and Drug Administration’s tolerance limits for human consumption of 2 ppm (wet weight) for local fish and 3 ppm (lipid weight) for poultry (Skinner 1992; Sloan and Jock 1990). Dredging of the St. Lawrence River offshore from the General Motors facility has been completed, but remedial alternatives for the St. Lawrence River offshore from Reynolds and for the Grasse River near ALCOA are still being evaluated. On-site remediation is complete at Reynolds and ALCOA, but plans for remedial work at some on-site locations at General Motors await final review and approval.
The pollution is a major concern of the Mohawk people because their tradition and culture emphasize the interdependence of humans and the environment and because many residents formerly depended on local fish, waterfowl, and mammals for food. Previous articles described local fish consumption patterns among 139 Mohawk men (Fitzgerald et al. 1996, 1999) and 111 pregnant Mohawk women (Fitzgerald et al. 2004) and their association with serum PCB levels. In these reports we noted a 3-fold decline in the average rate of local fish consumption among both men and women in the past year relative to > 2 years prior. Such changes may be related to the advisories that have been issued over the past decade by Mohawk, state, and provincial authorities against the consumption of contaminated local fish [New York State Department of Environmental Conservation (NYSDEC) 2003; New York State Department of Health (NYSDOH) 2002]. The geometric mean serum PCB concentration was 2.8 ppb for men and 1.2 ppb for women. In both cases, a significant correlation was observed between estimated cumulative lifetime exposure to PCBs from local fish consumption and serum PCB levels.
In the earlier investigations (Fitzgerald et al. 1996, 1999, 2004), we used serum PCB concentrations as a marker of internal dose, whereas in this study we expanded the focus to include a measure of an early biological effect of exposure. More specifically, we tested the hypothesis that serum PCB levels are positively correlated with CYP1A2 activity among Mohawk men and women. We used a breath test that uses caffeine as a metabolic probe to safely and noninvasively monitor CYP1A2 activity in vivo (Lambert et al. 1983). The project was a collaborative effort among the New York State Department of Health, the St. Regis Mohawk Tribe, the Mohawk Council of Akwesasne, the Akwesasne Task Force on the Environment, and the State University of New York at Albany.
Materials and Methods
Ascertainment and interview.
Detailed descriptions of ascertainment and interview methods are published elsewhere (Fitzgerald et al. 1996, 1999, 2004). Briefly, 111 Mohawk women living at Akwesasne who became pregnant between 1 April 1992 and 31 March 1995 were identified through prenatal care clinics and other sources, interviewed in the second trimester, and asked to donate a nonfasting 20 mL venous blood sample for PCB analysis. The participation rate was 79%. Similarly, 139 adult Mohawk men, who were the husbands or close relatives of the women, also took part (participation rate of 69%). Both the men and women were asked about demographic characteristics; height and weight; use of medications; occupational, residential, and reproductive histories; recreational pursuits (e.g., gardening, swimming, fishing); alcohol and cigarette use; drinking-water source; and diet, emphasizing local foods such as fish, wildlife, meat, dairy products, and fruits and vegetables.
Serum PCB analysis.
The blood was allowed to clot and then centrifuged to provide 10 mL serum. The chemical analysis was performed using methods (including quality assurance and control, accuracy, and precision) published elsewhere (Bush et al. 1982, 1984). Briefly, approximately 10 mL of serum was extracted using methanol, diethyl ether, and hexane and then transferred to a Florisil cleanup column containing 10 g of 4% deactivated Florisil topped with 1 cm anhydrous sodium sulfate. The eluate was evaporated to 1 mL and analyzed with a Hewlett-Packard 5890 gas chromatograph (Hewlett-Packard, Houston, TX) using a phenylmethyloctadecyl silyl-bonded fused-silica capillary column and an electron-capture detector. A computerized data management system reported each of 68 PCB-containing zones or peaks and summed the congener concentrations to report total PCBs. In some cases, the capillary column was unable to resolve two or more congeners, so the result was reported as a mixed peak.
The method detection limit (MDL) for the 68 congeners in serum ranged from 0.01 to 0.10 ppb, with a median MDL of 0.02 ppb per congener. However, values less than the MDL were reported by the laboratory and included in the statistical analysis. This decision was based on the fact that many chemists and statisticians believe that a reported result, even if it is below the “criterion for detection,” remains the best available estimate of the true value and is preferable to assigning an arbitrary constant such as one-half the detection limit in the statistical analysis [American Society for Testing and Materials (ASTM) 1989].
In addition to the determination of PCB congeners, the lipid content of the serum samples was also measured gravimetrically. However, given the relatively low lipid content of serum, this method may be prone to error. Consequently, serum cholesterol and triglycerides were measured enzymatically, and total lipids were calculated using the Centers for Disease Control and Prevention formula (Phillips et al. 1989). This change was implemented midway through the study period, so unfortunately these data were available for only 46 of the 103 participants.
Caffeine breath test.
Medical histories were taken to identify those with a history of heart disease, stroke, seizure disorders, uncontrolled hypertension, arrhythmia, hepatitis, jaundice or other types of liver disease, adverse reaction to caffeine, or chemotherapy within the past 5 years that would preclude their participation in the caffeine breath test (CBT). Those currently taking prescription medications other than oral contraceptives and women who were currently breast-feeding also were excluded. Participants were asked to refrain from caffeine consumption for 24 hr and to fast for 8 hr before the CBT. Height and weight were measured, and blood pressure and heart rate were taken to ensure normal readings before the CBT was administered. Each participant signed an informed consent and was compensated $30 for his or her time and effort. The women were tested after they delivered to avoid any potential risk of the caffeine to the fetus.
The substrate was synthesized (3-13C-methyl)caffeine (Kotake et al. 1982). The labeled caffeine dose, 3 mg/kg up to a maximum of 200 mg, was dissolved in 20 mL sterile water and ingested by the participants, followed by ingestion of a 20-mL water wash of the container. A 20-mL breath sample of expired air was collected immediately before and after the ingestion of the labeled caffeine at 30- and 60-min intervals, and stored in a Vacutainer. Pharmacologically, the labeled caffeine is rapidly absorbed and transported to the liver, where it is metabolized through 3-N-demethylation (Kotake et al. 1982). It then traverses to the one carbon pool and is exhaled in the breath as labeled CO2. The 13CO2:12CO2 ratio is determined by differential gas-isotope ratio mass spectrometry (Schoeller and Klein 1979). The excess 13C is calculated from the ratio found in the breath sample just before and after ingestion of the substrate and expressed as the dose exhaled per hour. Because 3-N-demethylation is catalyzed by CYP1A2, caffeine metabolism reflects hepatic CYP1A2 activity (Landi et al. 1999).
Statistical analysis.
We used multiple linear regression analysis to test for the association between serum PCB concentrations and the CBT values, after controlling for significant background variables that could potentially confound any such association. Potential confounders consisted of a set of background variables [age, sex, body mass index (BMI), cigarette smoking, alcohol consumption, coffee consumption, occupational and recreational exposures to chemicals, medical conditions, and the use of illicit, prescription, and over-the-counter drugs], some of which have been related to CBT values in other studies (Horn et al. 1995; Kalow and Tang 1991b; Rost et al. 1994; Vistisen et al. 1992). As an initial screen, bivariate analyses were conducted to identify variables that were associated with the CBT values at p < 0.20. These variables were then regressed on the CBT values, and backward elimination was used to delete one at a time those that were associated at p > 0.10. The serum PCB concentrations were then added to the model to estimate the strength of their association with the CBT values after adjustment for all remaining background variables. Both the serum PCB concentrations and CBT values were log-transformed to normalize their distributions and stabilize their variances. The inclusion of the background variables in the final regression model was confirmed by determining whether the parameter estimates for the exposure variables changed by ≥10% when the background variables were deleted (Rothman and Greenland 1998).
The serum PCB levels were added to the regression models in four ways. First, the sum of concentrations for all 68 congeners was entered as total PCBs. Second, the sum of concentrations for the 3 congeners that are mono-ortho-substituted [International Union of Pure and Applied Chemistry (IUPAC) congeners 105, 118, 167] and the 6 that are di-ortho-substituted (IUPAC congeners 138, 153, 158, 170, 180, 194) derivatives of non-ortho-substituted PCBs (∑PCBs) were entered. Because the laboratory was not able to measure the non-ortho-substituted congeners themselves, the 9 congeners listed above (∑PCBs) represented the subset of the 68 congeners analyzed with the greatest affinity for the Ah receptor and consequently those that were most likely to induce CYP1A2 activity. Toxic equivalents (TEQs) were also computed for these nine congeners, using the World Health Organization (Van den Berg et al. 1998) toxic equivalency factors (TEFs), and then added to the regression models. Finally, individual regression models were also fitted for individual congeners. However, to prevent misconceptions regarding the level of certainty attached to the results, these congeners were limited to the five that had a median or mean concentration that equaled or exceeded their individual MDL. Additionally, the regressions were performed using the serum PCB concentrations of the subset of 46 participants with cholesterol and trigylceride determinations after expressing their results as nanograms per gram of lipid.
Results
Of the 250 men and women in the parent studies, 172 (68.8%) agreed to undergo the CBT. Of this number, 69 (40.1%) were determined to be ineligible, yielding a final sample size of 103. Selected characteristics of these participants are described in Table 1. The mean age was 28 years, with a range of 15–67 years. Sixty-two percent were male. The median percent caffeine dose exhaled in an hour was 1.6%, with a range of 0.1–6.1%. Approximately one-half had smoked cigarettes in the past 2 years. Forty-three percent of the women had taken oral contraceptives during the past 6 months.
The median serum total PCB level was 1.86 ppb (wet weight), with a maximum of 14.91 ppb (Table 2). The median serum concentrations for the nine mono- or di-ortho-substituted congeners ranged from non-detectable to 0.28 ppb, and their median sum was 0.83 ppb. The median TEQ for these congeners was 0.01 ppt. The most commonly detected congener was PCB-153, with 95% of all the samples having a concentration that exceeded the MDL.
The bivariate analyses revealed that smokers, men, older persons, those with lower body mass indices, those without a history of hypertension, current coffee drinkers, and those who did not take antibiotics had higher median CBT values at p < 0.20. Only smoking and sex, however, were associated with CBT values at p < 0.10 in the multiple regression analysis and affected the parameter estimates for serum PCB by ≥10% (Table 3). Consequently, those two factors were included in the final regression models. Among women, oral contraceptive use was associated with lower CBT values (p = 0.006) after adjustment for cigarette smoking. However, this variable could not be included in the final multiple regression analysis of CBT values on serum PCB concentrations because this analysis included both sexes and oral contraceptive use was restricted to women. It is important to note, however, that the median CBT value of 1.68 for women who did not use oral contraceptives was identical to that for men, and that the results of a regression analysis limited to women and controlling for oral contraceptive use were similar to those of the final models for both sexes combined (data not shown).
Table 4 gives the results of the multiple regression analysis of CBT values on serum concentrations (both wet weight and lipid adjusted) of total PCBs, the ∑PCBs, and TEQs. It also displays the findings for the five individual mono- or di-ortho-substituted congeners that had median or mean serum concentrations that exceeded their respective MDLs. After adjusting for cigarette smoking and sex, serum total PCB was not associated with CBT values in either the wet-weight or lipid-adjusted analysis. However, the sum of the mono- and di-ortho-substituted congeners was significantly related to CBT values in both analyses. Positive associations were also observed for PCB-153 (p = 0.045 for wet weight, p = 0.011 for lipid adjusted), PCB-170 (p = 0.079 for wet weight, p = 0.010 for lipid adjusted), and PCB-180 (p = 0.086 for wet weight, p = 0.009 for lipid adjusted). TEQs were also positively associated with CBT values (p = 0.091 for wet weight, p = 0.028 for lipid adjusted).
Discussion
The results confirmed other studies indicating that smoking, sex, and oral contraceptive use significantly impact CBT values. Smoking is a potent inducer of CYP1A2 (Kalow and Tang 1991a; Kotake et al. 1982), probably due to polycyclic aromatic hydrocarbons and other carcinogens found in tobacco smoke. Oral contraceptive use appears to inhibit CYP1A2 activity in vivo (Abernethy and Todd 1985; Campbell et al. 1987b; Rietveld et al. 1984), thereby delaying caffeine metabolism. Some investigators have attributed the higher CBT values of men relative to women to parity (Horn et al. 1995), but oral contraceptives may also be involved because women who did not use oral contraceptives had an average CBT value identical to men in the present study. Kalow and Tang (1991b) also reported no principal gender difference when women using oral contraceptives were excluded from their analysis.
It is not surprising that serum total PCB was not related to CBT values because most of the 68 congeners measured in this investigation are not known to induce CYP1A2. When the analysis was restricted to the ∑PCBs believed to have some affinity for the Ah receptor, however, significant positive associations were found. To estimate the dioxin-like activity of these congeners, we calculated TEQs. Although this approach has uncertainties because of possible nonadditive effects, differences in the shape of the dose–response curve, and species responsiveness (van den Berg et al. 1998), TEQs and CBT values were positively correlated. In fact, after lipid adjustment, this relationship was statistically significant, probably because, relative to the wet-weight analysis, the lipid adjustment controls for variability in PCB levels due to differences in lipid content of the nonfasting serum samples (Phillips et al. 1989).
When the results were restricted to only those congeners with median serum levels greater than their MDL, PCB-153, PCB-170, and PCB-180 were statistically significant in either the wet-weight or lipid-adjusted analysis. PCB-153 and PCB-180 are persistent congeners that, together with PCB-138, were found in the greatest concentration in Mohawk serum. These congeners typically are the most dominant in human tissue worldwide (Hansen 1999). PCB-170 is also persistent but usually found in lower concentrations than are PCB-153 and PCB-180. None of these three congeners is found in Aroclor 1248 (Frame et al. 1996), the commercial mixture used locally, and as such may reflect more general exposures, possibly from Lake Ontario and the St. Lawrence River (Bush et al. 1985).
PCB-153 and PCB-180 are generally considered phenobarbital-type inducers of cytochrome P-450 (Parkinson et al. 1981). They differ from non-ortho-substituted PCBs, which are 3-methylcholanthrene-type inducers, in that they are more likely to induce the CYP2A family of isozymes than the CYP1A family (Safe 1994). The other seven mono- and di-ortho-substituted congeners measured in the present study, including PCB-170, are mixed type and induce both families (McFarland and Clark 1989). The significant association between PCB-153 and PCB-180 and CBT values may reflect overlap in the ability of PCBs to induce P-450 enzymes, because phenobarbital-type inducers may also induce CYP1A to some extent and methylcholanthrene-type inducers may induce CYPA2 (Wolff and Toniolo 1995). Given the tendency of serum concentrations of individual congeners to be correlated (DeVoto et al. 1997; Gladen et al. 1999; Koopman-Esseboom et al. 1994), PCB-153 and PCB-180 may also be proxies for other congeners that were not measured, especially non-ortho-substituted congeners that have a high affinity for the Ah receptor. In fact, Longnecker et al. (2000) have reported Pearson correlation coefficients between PCB-153 and PCB-180 on the one hand and selected non-ortho-substituted PCBs on the other that range from 0.35 to 0.86.
It is important to note that these associations between serum PCB concentrations and CBT values were observed despite the relatively low average body burden of PCBs in this population. The median was 1.8 ppb, which is less than the general population value of 3.1 ppb reported by Patterson et al. (1994) during the same time period. This finding probably reflects the low current rate of local fish consumption among the Mohawks, a behavioral change that may be related to the fish advisories issued over the past decade by tribal, state, and provincial agencies (Fitzgerald et al. 1999, 2004). It is also uncertain whether Native Americans possess the polymorphisms that control induction. Such polymorphisms have not yet been identified, but in a study of CYP1A2 phenotypes from Australia, China, Japan, Italy, and the United States, Kadlubar (1994) found a wide variation in the metabolic proficiency for CYP1A2 within each country. Although Native peoples were not included, such results suggest that they, like other racial and ethnic subgroups, include at least a subset of inducible persons. Knowledge of which individuals were genetically capable of induction would have clearly strengthened the correlations observed in the present study.
Another limitation is the lack of information on the concentrations of non-ortho-substituted congeners in the serum of study participants. This issue is important because these congeners are those most likely to induce CYP1A2 in vitro or in animal models (Safe 1994). Unfortunately, our laboratory was unable to reliably quantify at the time that the study was conducted with the very low level of non-ortho-substituted congeners typically found in human serum. As noted previously by Longnecker et al. (2000), however, serum concentrations of individual congeners tend to be highly correlated, so persons who had higher levels of the congeners that were measured would likely have higher levels of non-ortho-substituted and any other congeners that were not determined. Similarly, no serum data were available for TCDD or other dioxins, which are the most potent inducers of CYP1A2 (Safe 1994). However, not only are levels of PCB congeners in human serum intercorrelated, but so are levels of PCBs and dioxins (Gladen et al. 1999; Koopman-Esseboom et al. 1994; Patterson et al. 1994); consequently, the former may also be a surrogate for the latter, at least when exposures are at background levels (Longnecker et al. 2000).
Despite these limitations, the general pattern of results between serum PCB concentrations and CBT values is generally consistent with at least one of the two other studies that, to date, have attempted to link xenobiotic exposure to human CYP1A2 activity in vivo. Specifically, Lambert et al. (1990) found that Michigan residents exposed to PBBs had a significantly higher median CBT value than did a control group of urban nonsmokers. They also observed a significant correlation between serum PBB levels above the detection limit and CBT values in the exposed group. In contrast, Halperin et al. (1995) found little evidence of an overall association between serum TCDD concentrations and CYP1A2 activity among occupationally exposed herbicide workers. The only suggestion of a relationship was when three of four categories of workers defined by increasing concentrations of serum TCDD showed a greater risk of having an elevated level of CYP1A2 activity relative to unexposed controls, but the results were not statistically significant. However, Halperin et al. (1995) used the caffeine metabolite ratio (CMR) to indicate in vivo CYP1A2 activity, not the CBT. The CMR measures caffeine metabolites in urine, metabolites that are dependent on different enzymes and pathways than the CBT (Campbell et al. 1987a). There is some uncertainty about what metabolites are most appropriate for the urinary ratio (Butler et al. 1992) and, although the comparative ordering of values is unaffected, the CMR underestimates the true magnitude of CYP1A2 activity (Kalow and Tang 1993), suggesting that it may be a less sensitive indicator than the CBT.
The results of the present study are also consistent with two other studies that, although they did not measure in vivo CYP1A2 activity, did monitor human placental CYP1A1 induction. Lagueux et al. (1999) found that CYP1A1 activity was elevated in the placental tissue of Inuit women living in northern Quebec who are exposed to PCBs and other organochlorine compounds from the consumption of marine mammals. Similarly, Lucier et al. (1987) reported that Yu-Cheng women exposed to PCBs and dibenzofurans had higher levels of placental CYP1A1 activity than an unexposed control group, and that such activity was inversely correlated with the birth weight of their offspring.
Conclusion
In conclusion, the results of the present study support previous observations that smokers and men have higher levels of in vivo CYP1A2 activity than do nonsmokers and women and that oral contraceptive use inhibits CYP1A2 activity. It is one of the first investigations to report positive correlations between serum PCB concentrations and CYP1A2 activity, despite the relatively low PCB body burdens of this population and the lack of data on individual non-ortho-substituted PCBs or dioxins. While serum PCB concentrations serve as a marker of internal dose, CYP1A2 activity indicates an early biological effect of such exposure, at least among those persons genetically predisposed. Although the health implications in humans remain uncertain, CYP1A2 is involved in the metabolic activation of some carcinogens, and consequently, individual differences may reflect susceptibility to environmentally related cancer risk (Landi et al. 1999). The data support the notion that human exposure to PCBs may induce CYP1A2 activity and that the CBT is a useful tool to monitor such effects in vivo.
Figure 1 Map of the Mohawk Nation at Akwesasne.
Table 1 Selected characteristics of study participants (63 Mohawk men and 40 Mohawk women), Akwesasne, 1992–1995.
Characteristica Median Mean ± SE Range
Age (years) 28 30.3 ± 0.9 15–67
BMI (height/weight2) 26.4 27.1 ± 0.4 18.7–38.9
CBT (% dose) 1.6 1.8 ± 0.1 0.1–6.1
Cigarette smoking in past 2 years (% yes) 52.4
Oral contraceptive use in past 6 months (women only, % yes) 42.9
Current alcohol consumption (% yes) 55.0
Current coffee consumption (% yes) 65.5
a Sample size < 103 for some characteristics due to missing data.
Table 2 Serum PCB concentrations (ppb) in Mohawk men (n = 63) and women (n = 40), Akwesasne, 1992–1995.
Congener Median Mean ± SE Range Percent > MDL
PCB-105 < MDL 0.009 ± 0.004 < MDL–0.267 7.8
PCB-118 0.055 0.088 ± 0.015 < MDL–0.881 66.0
PCB-138 0.279 0.390 ± 0.047 < MDL–2.330 80.6
PCB-153 0.258 0.395 ± 0.044 < MDL–2.375 95.1
PCB-158 < MDL 0.007 ± 0.005 < MDL–0.484 7.8
PCB-167 < MDL 0.004 ± 0.002 < MDL–0.134 4.9
PCB-170 < MDL 0.091 ± 0.028 < MDL–2.600 35.0
PCB-180 0.157 0.408 ± 0.064 < MDL–2.948 58.3
PCB-194 < MDL 0.022 ± 0.007 < MDL–0.399 10.7
Total PCBs 1.864 2.808 ± 0.293 0–14.911 99.0a
∑PCBsb 0.830 1.415 ± 0.164 0–9.206 97.1a
TEQ (ppt) 0.007 0.033 ± 0.007 0–0.558 75.7a
a For total PCBs, ∑PCBs, and TEQ, values are the percentage of samples with a reportable result, not percentage below MDL, because MDL is determined only for individual congeners.
b Sum of IUPAC PCB congeners 105, 118, 138, 153, 158, 167, 170, 180, 194.
Table 3 Multiple regression analysis of log-transformed CBT value on background variables in Mohawk men (n = 63) and women (n = 40), Akwesasne, 1992–1995.
Background variable β-Value SE (β) p-Value
Cigarette smoking in past 2 years (yes/no) 0.360 0.136 0.009
Sex (men/women) 0.303 0.139 0.032
Oral contraceptive use in past 6 months (yes/no)a −0.697 0.234 0.006
β, regression coefficient.
a Women only (information on oral contraceptive use was missing for five women).
Table 4 Multiple regression analysis of log-transformed CBT valuea on serum PCB concentrations (wet weight and lipid adjusted) in Mohawk men and women, Akwesasne, 1992–1995.
Wet weight (n = 103)
Lipid adjusted (n = 46)
Congener β SE (β) p-Value β SE (β) p-Value
PCB-118 0.030 0.045 0.511 0.185 0.106 0.090
PCB-138 0.017 0.034 0.624 0.215 0.106 0.048
PCB-153 0.145 0.071 0.045 0.346 0.130 0.011
PCB-170 0.084 0.047 0.079 0.324 0.120 0.010
PCB-180 0.080 0.046 0.086 0.207 0.075 0.009
Total PCBs 0.061 0.059 0.306 0.221 0.119 0.070
∑PCBsb 0.116 0.059 0.052 0.356 0.112 0.003
TEQ 0.054 0.032 0.091 0.154 0.068 0.028
β, regression coefficient.
a Adjusted for cigarette smoking in the past 2 years and sex.
b Sum of PCB congeners 105, 118, 138, 153, 158, 167, 170, 180, and 194.
==== Refs
References
Abernethy DR Todd EL 1985 Impairment of caffeine clearance by chronic use of low-dose oestrogen-containing oral contraceptives Eur J Clin Pharmacol 28 425 428 4029248
ASTM 1989. Committee on Standards. Designation, D4210-89. West Conshohocken, PA:American Society for Testing and Materials.
Bush B Snow J 1982 Glass capillary chromatography for sensitive, accurate polychlorinated biphenyl analysis J Assoc Offic Anal Chem 65 555 566
Bush B Snow J Connor S 1985 Polychlorinated biphenyl congeners (PCBs), p,p ′-DDE and hexachlorobenzene in human milk in three areas of upstate NY Arch Environ Contam Toxicol 14 443 450 3929701
Bush B Snow J Koblintz R 1984 Polychlorobiphenyl (PCB) congeners, p,p ′-DDE and hexachlorobenzene in maternal, and fetal cord blood from mothers in upstate NY Arch Environ Contam Toxicol 13 517 527 6435547
Butler MA Lang NP Young JF Caporaso NE Vineis P Hayes RB 1992 Determination of CYP1A2 and NAT2 phenotypes in human populations by analysis of caffeine urinary metabolites Pharmacogenetics 2 116 127 1306111
Campbell ME Grant DM Inaba T Kalow W 1987a Biotransformation of caffeine, paraxanthine, theophylline, and theobromine by polycyclic aromatic hydrocarbon-inducible cytochrome(s) P-450 in human liver microsomes Am Soc Pharmacol Exp Ther 15 237 249
Campbell ME Spielberg S Kalow W 1987b A urinary metabolite ratio that reflects systemic caffeine clearance Clin Pharmacol Ther 42 157 165 3608349
Conney AH Pantuck EJ Hsiao KC Garland WA Anderson KE Alvares AP 1976 Enhanced phenacetin metabolism in human subjects fed charcoal-broiled beef Clin Pharmacol Ther 20 633 642 991534
DeVoto E Fiore B Millikan R Anderson H Sheldon L Sonzogni W 1997 Correlations among human blood levels of specific PCB congeners and implications for epidemiologic studies Am J Ind Med 32 606 613 9358917
Eaton DL Gallagher EP Bammler TK Kunze KL 1995 Role of cytochrome P4501A2 in chemical carcinogenesis: implications for human variability in expression and enzyme activity Pharmacogenetics 5 259 274 8563766
Ecology and Environment Inc 1992. River and Sediment Investigation of the Grasse River for Aluminum Company of America. Lancaster, NY:Ecology and Environment Inc.
Fitzgerald EF Brix KA Deres DA Hwang S Bush B Lambert G 1996 Polychlorinated biphenyl (PCB) and dichloro-diphenyl dichloroethylene (DDE) exposure among Native American men from contaminated Great Lakes fish and wildlife Toxicol Ind Health 12 361 368 8843553
Fitzgerald EF Deres DA Hwang S Bush B Yang B Tarbell A 1999 Local fish consumption and serum PCB concentrations among Mohawk men at Akwesasne Environ Res 80 97 103
Fitzgerald EF Hwang S Langguth K Cayo M Yang B Bush B 2004 Dietary, occupational, and residential exposure and serum PCB concentrations among Mohawk women at Akwesasne Environ Res 94 160 170 14757379
Frame GM Cochran JW Bowadt SS 1996 Complete PCB congener distributions for 17 Aroclor mixtures determined by 3 HRGC systems optimized for comprehensive, quantitative, congener-specific analysis J High Resol Chromatogr 19 657 668
Gladen BC Longnecker MP Schecter AJ 1999 Correlations among polychlorinated biphenyls, dioxins, and furans in humans Am J Ind Med 35 15 20 9884741
Halperin W Kalow W Sweeney MH Tang BK Fingerhut M Timpkins B 1995 Induction of P-450 in workers exposed to dioxin Occup Environ Med 52 86 91 7757172
Hansen LG 1999. The Ortho Side of PCBs: Occurrence and Disposition. Boston:Kluwer Academic Publishers.
Horn EP Tucker MA Lambert G Silverman D Zametkin D Sinha R 1995 A study of gender-based cytochrome P4501A2 variability: a possible mechanism for the male excess of bladder cancer Cancer Epidemiol Biomarkers Prev 4 529 533 7549810
Huang J Guo W Lai M Guo Y Lambert GH 1999 Detection of a novel cytochrome P-450 1A2 polymorphism (F21L) in Chinese Am Soc Pharmacol Exp Ther 27 98 101
Kadlubar FF 1994 Biochemical individuality and its implications for drug and carcinogen metabolism: recent insights from acetyltransferase and cytochrome P4501A2 phenotyping and genotyping in humans Drug Metab Rev 16 37 46 8082575
Kalow W Tang B 1991a Caffeine as a metabolic probe: exploration of the enzyme-inducing effect of cigarette smoke Clin Pharmacol Ther 49 44 48 1988240
Kalow W Tang B 1991b Use of caffeine metabolite ratios to explore CYP1A2 and xanthine oxidase activities Clin Pharmacol Ther 50 508 519 1934864
Kalow W Tang B 1993 The use of caffeine for enzyme assays: a critical appraisal Clin Pharmacol Ther 53 503 514 8491061
Kawajiri K 1999 CYP1A1 IARC Sci Publ 148 159 172 10493257
Koopman-Esseboom C Huisman M Weisglas-Kuperus N Van der Paauw CG Tuinstra LGM Boersma ER 1994 PCB and dioxin levels in plasma and human milk of 418 Dutch women and their infants, predictive value of PCB congener levels in maternal plasma for fetal and infant’s exposure to PCBs and dioxins Chemosphere 28 1721 1732
Kotake AN Schoeller DA Lambert GH Baker AL Schaffer DD Josephs H 1982 The caffeine CO2 breath test: dose response and route of N -demethylation in smokers and nonsmokers Clin Pharmacol Ther 32 261 269 6807598
Lacetti G 1993. A Public Health Assessment: General Motors/Central Foundry Division, Massena, St. Lawrence County, NY. Albany, NY:New York State Department of Health.
Lagueux J Pereg D Ayotte P Dewailly E Poirier GG 1999 Cytochrome P450 CYP1A1 enzyme activity and DNA adducts in placenta of women environmentally exposed to organochlorines Environ Res 80 369 382 10330311
Lake BG Charzat C Tredger JM Renwick AB Beamand JA Price RJ 1996 Induction of cytochrome P450 isoenzymes in cultured precision-cut rat and human liver slices Xenobiotica 26 297 306 8730921
Lambert GH Kotake AN Schoeller D 1983 The CO2 breath tests as monitors of the cytochrome P450 dependent mixed function monooxygenase system Dev Pharmacol 135 119 145
Lambert GH Schoeller DA Humphrey HEB Kotake AN Lietz H Campbell M 1990 The caffeine breath test and caffeine urinary metabolite ratios in the Michigan cohort exposed to polybrominated biphenyls: a prelimary study Environ Health Perspect 89 175 181 1965165
Landi MT Sinha R Lang NP Kadlubar FF 1999 Human cytochrome P4501A2 IARC Sci Publ 148 173 195 10493258
Longnecker MP Ryan JJ Gladen BC Schecter AJ 2000 Correlations among human plasma levels of dioxin-like compounds and polychlorinated biphenyls (PCBs) and implications for epidemiologic studies Arch Environ Health 55 195 200 10908103
Lucier GW Nelson KG Everson RB Wong TK Philpot RM Tiernan T 1987 Placental markers of human exposure to polychlorinated biphenyls and polychlorinated dibenzo-furans Environ Health Perspect 76 79 87 2834196
McFarland VA Clarke JU 1989 Environmental occurrence, abundance, and potential toxicity of PCB congeners: considerations for a congener-specific analysis Environ Health Perspect 81 225 239 2503374
Nakajima M Yokoi T Mizutani M Shin S Kadlubar FF Kamataki T 1994 Phenotyping of CYP1A2 in Japanese population by analysis of caffeine urinary metabolites: absence of mutation prescribing the phenotype in the CYP1A2 gene Cancer Epidemiol Biomarkers Prev 3 413 421 7920209
NYSDEC 2003. Health Advisory, New York State 2000–02 Fishing Regulations Guide. Albany, NY:New York State Department of Environmental Conservation.
NYSDOH 2002. 2002–2003 Health Advisories: Contaminants in Sportfish and Game. Albany, NY:New York State Department of Health.
Pantuck EJ Pantuck CB Garland WA Min BH Wattenberg LW Anderson KE 1979 Stimulatory effect of brussels sprouts and cabbage on human drug metabolism Clin Pharmacol Ther 25 88 95 758247
Parker AC Pritchard P Preston T Choonara I 1998 Induction of CYP1A2 activity by carbamazepine in children using the caffeine breath test Br J Clin Pharmacol 45 176 178 9491835
Parkinson A Robertson LW Safe L Safe S 1981 Poly-chlorinated biphenyls as inducers of hepatic microsomal enzymes: effects of di-ortho substitution Chem Biol Interact 35 1 12 6781768
Patterson DG Jr Todd GD Turner WE Maggio V Alexander LR Needham LL 1994 Levels of non-ortho -subsituted (coplanar), mono- and di-ortho -substituted polychlorinated biphenyls, dibenzo-p -dioxins, and dibenzofurans in human serum and adipose tissue Environ Health Perspect 102 suppl 1 195 204 8187709
Phillips DL Pirkle JL Burse VW Bernert JT Henderson LO Needham LL 1989 Chlorinated hydrocarbon levels in human serum: effects of fasting and feeding Arch Environ Contam Toxicol 18 495 500 2505694
Rietveld EC Brockman MM Houben JJ Eskes AB van Rossum JM 1984 Rapid onset of an increase in caffeine residence time in young women due to oral contraceptives Eur J Clin Pharmacol 26 371 373 6734698
RMT 1986. Draft Remedial Investigation (Task 10). Report for Remedial Investigation/Feasibility Study at GM-CFD Massena, New York. Madison, WI:RMT Inc.
Rost KL Brosicke H Heinemeyer G Roots I 1994 Specific and dose-dependent enzyme induction by omeprazole in human beings Hepatology 20 1204 1212 7927253
Rothman KJ Greenland S 1998. Modern Epidemiology. Philadelphia, PA:Lippincott-Raven.
Safe SH 1994 Polychlorinated Biphenyls (PCBs): environmental impact, biochemical and toxic responses, and implications for risk assessment Crit Rev Toxicol 24 87 149 8037844
Schoeller DA Klein PD 1979 A microprocessor controlled mass spectrometer for the fully automated purification and isotopic analysis of breath carbon dioxide Biomed Mass Spectrom 6 350 355 497361
Skinner L 1992. Chemical Contaminants in Wildlife from the Mohawk Nation at Akwesasne and the Vicinity of the General Motors Corporation/Central Foundry Division, Massena, NY Plant. Albany, NY:New York State Department of Environmental Conservation.
Sloan R Jock K 1990. Chemical Contaminants in Fish from the St. Lawrence River Drainage on Lands of the Mohawk Nation at Akwesasne and Near the General Motors Corporation/Central Foundry Division, Massena, NY Plant. Technical Document 90-1 (BEP). Albany, NY:New York State Department of Environmental Conservation.
Van den Berg M Birmbaum L Bosveld A Brunstrom B Cook P Feeley M 1998 Toxic equivalency factors (TEFs) for PCBs, PCDDs, PCDFs for humans and wildlife Environ Health Perspect 106 775 792 9831538
Vistisen K Poulsen H Loft S 1992 Foreign compound metabolism capacity in man measured from metabolites of dietary caffeine Carcinogenesis 13 1561 1568 1394840
Wietholtz H Zysset T Marschall HU Generet K Matern S 1995 The influence of rifampin treatment on caffeine clearance in healthy man Hepatology 22 78 81
Wolff MS Toniolo PG 1995 Environmental organochlorine exposure as a potential etiologic factor in breast cancer Environ Health Perspect 103 141 145 8593861
Zeiger M Haag R Hockel J Schrenk D Schmitz HJ 2001 Inducing effects of dioxin-like polychlorinated biphenyls on CYP1A in the human hepatoblastoma cell line HepG2, the rat hepatoma cell line H4IIE, and rat primary hepatocytes: comparison of relative potencies Toxicology 63 65 73
|
15743714
|
PMC1253751
|
CC0
|
2021-01-04 23:40:56
|
no
|
Environ Health Perspect. 2005 Mar 9; 113(3):272-277
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7370
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7522ehp0113-00027815743715ResearchArticlesBinding of Estrogenic Compounds to Recombinant Estrogen Receptor-α: Application to Environmental Analysis Pillon Arnaud 1Boussioux Anne-Marie 1Escande Aurélie 1Aït-Aïssa Sélim 2Gomez Elena 3Fenet Hélène 3Ruff Marc 4Moras Dino 4Vignon Françoise 1Duchesne Marie-Josèphe 1Casellas Claude 3Nicolas Jean-Claude 1Balaguer Patrick 11INSERM (Institut National de la Santé et de la Recherche Médicale), Unité 540, Montpellier, France2INERIS (Institut National de l’Environnement Industriels et des Risques), Unité Evaluation des Risques Ecotoxicologiques, Verneuil-en-Halatte, France3 UMR 5569 “Hydrosciences,” Département des Sciences de l’Environnement et Santé Publique, Faculté de Pharmacie, Montpellier, France4IGBMC (Institut de Génétique et de Biologie Moléculaire et Cellulaire), Laboratoire de Biologie et Génomique Structurale, Illkirch, FranceAddress correspondence to P. Balaguer, INSERM, Unité 540, 60 rue de Navacelles, 34090 Montpellier, France. Telephone: 33-467043703. Fax: 33-467540598. E-mail:
[email protected]. is financially supported by a grant from the Languedoc-Roussillon Région and the Institut National de l’Environnement Industriels et des Risques.
The authors declare they have no competing financial interests.
3 2005 9 12 2004 113 3 278 284 25 8 2004 9 12 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Estrogenic activity in environmental samples could be mediated through a wide variety of compounds and by various mechanisms. High-affinity compounds for estrogen receptors (ERs), such as natural or synthetic estrogens, as well as low-affinity compounds such as alkylphenols, phthalates, and polychlorinated biphenyls are present in water and sediment samples. Furthermore, compounds such as polycyclic aromatic hydrocarbons, which do not bind ERs, modulate estrogen activity by means of the aryl hydrocarbon receptor (AhR). In order to characterize compounds that mediate estrogenic activity in river water and sediment samples, we developed a tool based on the ER-αligand-binding domain, which permitted us to estimate contaminating estrogenic compound affinities. We designed a simple transactivation assay in which compounds of high affinity were captured by limited amounts of recombinant ER-αand whose capture led to a selective inhibition of transactivation. This approach allowed us to bring to light that water samples contain estrogenic compounds that display a high affinity for ERs but are present at low concentrations. In sediment samples, on the contrary, we showed that estrogenic compounds possess a low affinity and are present at high concentration. Finally, we used immobilized recombinant ER-αto separate ligands for ER and AhR that are present in river sediments. Immobilized ER-α, which does not retain dioxin-like compounds, enabled us to isolate and concentrate ER ligands to facilitate their further analysis.
aryl hydrocarbon receptorbioluminescent cell linesenvironmental samplesestrogen receptorxenoestrogens
==== Body
Endocrine-disrupting compounds (EDCs) are a newly defined category of environmental contaminants that interfere with endocrine system function (Sumpter 1998). Many alterations of the reproductive system observed in the aquatic environment are attributed to the presence of endocrine disruptors. Numbers of studies have focused on compounds that are agonists for the estrogen receptors αand β (ER-αand ER-β) (Kuiper et al. 1998; Paris et al. 2002). These compounds include a wide range of molecules, such as natural or pharmaceutical estrogens, alkylphenols, organochlorine pesticides, and phthalates, that exhibit different binding affinities. Natural and pharmaceutical estrogens have high affinity (dissociation constant Kd < 1 nM) for ERs, whereas the other groups of molecules display lower affinity (Kd > 10 nM) and are called xenoestrogens. Furthermore, compounds such as polycyclic aromatic hydrocarbons (PAHs) or dioxin mediate estrogen responses by binding the aryl hydrocarbon receptor (AhR), which in turn forms a complex with ERs (Ohtake et al. 2003). Other compounds, such as hydroxy-PAHs, might bind ERs and AhR (Fertuck et al. 2001).
Sewage treatment plants (STPs) receive a large spectrum of molecules from domestic, agricultural, and/or industrial wastes that are not totally eliminated during treatment processes. At the STP outlets, a complex mixture of molecules, including incompletely eliminated waste water molecules but also metabolites formed during treatment processes, are finally discharged into rivers. In this context, STP discharges are considered a major source of estrogenic water pollution that may play a role in environmental contamination. Several studies reported a correlation between reproductive abnormalities in fish and exposure to STP effluents (Harries et al. 1999; Jobling et al. 2002; Purdom et al. 1994).
Given the difficulty in identifying all of these EDCs, several authors have attempted to detect estrogenic activity and quantify its potency in water samples by targeting their research on specific molecules such as the natural hormones estrone (E1), 17β -estradiol (E2), and estriol (E3); the synthetic estrogen ethynylestradiol (EE2); and/or alkylphenols (Aerni et al. 2004; Baronti et al. 2000; Solé et al. 2000). We and others evaluated overall estrogenic activity in water samples (Aerni et al. 2004; Balaguer et al. 2000; Körner et al. 1999). Analytical fractionation systems combined with in vitro biological assays were also developed to identify estrogenic compounds present in water. Desbrow et al. (1998) showed, indeed, that compounds with high affinity (E2, E1, and EE2) are responsible for the major part of estrogenic activity in U.K. effluents. A similar observation was made by Snyder et al. (2001) in water samples taken from mid-Lake Michigan and Lake Mead (USA) and by Cargouët et al. (2004) in water samples taken from the river Seine (France). In river sediment samples, conversely, low-affinity compounds such as alkylphenols might contribute to estrogenic activity (Fenet et al. 2003) even if E2 and E1 are present (Peck et al. 2004).
The objective of this study was to develop tools for characterizing substances that mediate estrogenic activity in complex mixtures, that is, to determine if the estrogenic compounds were ER activators by direct binding (with high or low affinity) or ER activators by another mechanism of action (AhR activation). Estrogenic activity was evaluated with the MELN cell line (Balaguer et al. 1999). Two complementary methodologies were proposed for complex mixture characterization. The first one enabled the capture of compounds of high affinity for ER-αby limited amounts of ER-αligand-binding domain (LBD); this event led to a selective inhibition of luciferase gene expression in MELN cells. The second method allowed ER ligand separation from other compounds by recombinant ER-αimmobilized on agarose columns. Furthermore, estrogen binding columns, which do not retain compounds interacting with AhR only, enabled us to purify and concentrate ER ligands. Estrogen and dioxin-like activities were followed with specific bioluminescent cell lines, MELN and HAhLP cells, respectively. These methodologies were developed with pure compounds and validated with environmental samples, for their applicability on complex mixtures.
Materials and Methods
Materials.
Materials for cell culture were obtained from Invitrogen (Cergy-Pontoise, France). Luciferin and isopropylthiogalactopyranoside were purchased from Promega (Charbionnières, France). E2, E1, E3, genistein, coumestrol, α-zearalanol, zearalenone, androstenediol, phenol red dye, dichlorodiphenyl-dichloroethylene (DDE), dioxin, nonylphenol mixture (NPm, ring and chain isomers), 4n-nonylphenol (4-NP), bisphenol A (BPA), and 4-tert-octylphenol (OP) were purchased from Sigma Chemical Co. (St. Louis, MO, USA). These effectors were dissolved in dimethyl sulfoxide at 10−2 M. [3H]-E2 (specific activity, 41.3 Ci/mmol) was purchased from NEN Life Sciences Products (Paris, France).
Plasmids.
Recombinant ER-αwas produced with hER-αLBD(Lys302 → Pro552) Cys(381,417,530) → Ser triple mutant in fusion with six histidine residues plasmid (as described by Gangloff et al. 2001). Cytochrome P450 1A1–luciferase (CYP1A1-Luc) plasmid was a gift from J.M. Pascussi and P. Maurel (INSERM, U632, Montpellier, France).
Generation of stably transfected reporter cell lines.
The stably transfected luciferase reporter cell lines (MELN and HAhLP) were obtained as previously described (Balaguer et al. 2001), and the ligand-inducible luciferase expressing clones were identified with a photon-counting camera (NightOWL LB 981; Berthold Technologies, Bad Wildbad, Germany). Briefly, to obtain MELN cells, we transfected ER-α–positive breast cancer MCF-7 cells with the estrogen-responsive gene ERE-βGlob-Luc-SVNeo (Balaguer et al. 1999). Selection of resistant clones by geneticin was performed at 1 mg/mL. The most E2-responsive clone was isolated and called MELN 4.1. Basal MELN cell activity was around 15% of maximal activity (10 nM E2).
The dioxin reporter cell line was obtained by transfecting HeLa cells with CYP1A1-Luc and pSG5-puro plasmids. Selection of resistant clones by puromycin was performed at 0.5 μg/mL. The most dioxin-responsive clone was denominated HAhLP 1.15. Basal HAhLP cell activity was around 20% of maximal activity (10 nM dioxin).
Cell culture conditions.
For strain cultures, cells were grown in phenol red containing Dulbecco’s modified Eagle medium, 1 g/L glucose, supplemented with 5% fetal calf serum (FCS), and 1% antibiotic (penicillin/streptomycin) in a 5% CO2 humidified atmosphere at 37°C. Because of phenol red and FCS estrogenic activity, in vitro experiments were achieved in phenol red–free medium supplemented with 6% dextran-coated charcoal (DCC)–treated FCS (test culture medium).
Cell luciferase assay.
Cells were seeded at a density of 5 × 104 cells/well in 96-well white opaque tissue culture plates (Becton Dickinson, Le Pont de Claix, France) in 150 μL test culture medium. Compounds to be tested were prepared 4× concentrated in the same medium and 50 μL was added per well 8 hr after seeding. Cells were incubated with compounds for 16 hr. Experiments were performed in quadruplicate and repeated twice. At the end of incubation, effector containing medium was removed and replaced by 3 × 10−4 ration, luciferin diffuses into the cell and produces a luminescent signal that is stable from 5 min on. It is approximately 10-fold less intense than a signal after cell lysis would be, but it is perfectly stable for several hours. The 96-well plate was then introduced in a microplate luminometer (Centro LB 960, Berthold Technologies), and intact living cell luminescence measured for 2 sec. Results are expressed as a percentage of maximum luciferase activity. The maximum value, taken as 100, was obtained in the presence of 10 nM E2 and dioxin in MELN and HAhLP cell media, respectively. The basal activity (in the absence of ligands) is 15 and 30% of the maximal activity for MELN and HAhLP, respectively. For each estrogenic compound, estrogenic potency corresponding to the concentration yielding half-maximum activity (EC50 value) and relative transactivation potency (RTP) were calculated {RTP = [EC50 (E2)/EC50 (test compound)] × 100}. EC50 values were evaluated using Graph-Pad Prism statistics software (version 4.0; GraphPad Software Inc., San Diego, CA, USA).
Environmental samples.
Surface water and sediments were sampled at site U on the Seine watershed (Fenet et al. 2003). Site U is subjected to high inputs of pollutants from an STP in an urban area. Surface water was collected in January 2000 and extracted within 48 hr to minimize bacterial sample degradation. Twenty liters were filtered through a solvent-rinsed Whatman GF/C filter. The filtrate (5 L/column) was concentrated onto preconditioned (20 mL methanol followed by 20 mL water) 5 g C18 solid-extraction (SPE) mini-columns. SPE columns were vacuum dried and stored at −20°C. After thawing at room temperature, columns were extracted with 20 mL methanol followed by 20 mL hexane. Methanol eluate volume was reduced to approximately 10 mL, and concentrates were stored at 4°C. Hexane eluates were evaporated to dryness, and residues were taken up with 10 mL methanol. The water sample was therefore 2,000 times concentrated (20 L water giving 10 mL methanol solution).
Sediments (0–5 cm) were collected in November 1999. They were homogenized and sieved through a 2-mm mesh before lyophilization. Lyophilizates (50 g) were extracted twice with dicholoromethane:methanol (2:1) for 20 and 30 min. Extracts were combined and dried by passing through anhydrous sodium sulfate on glass microfibers. The extracts were concentrated (1:100) in double-distilled water to allow extraction of active compound onto the C18 cartridge. Compounds bound to the C18 phase were eluted with 5 mL methanol. Thus, 1 mL methanol corresponded to 10 g lyophilized sediment.
Sediment and water methanol extracts were applied to MELN and HAhLP cells at 0.3% (vol/vol) maximal concentration in test culture medium, and luciferase transactivation was measured.
Recombinant receptor production.
The recombinant ER-αcoding plasmid was transformed in BL21 DE3 electrocompetent Escherichia coli cells using the Promega procedure, and the resulting bacteria were plated in ampicillin plates. One colony, after a pre-growth step, was inoculated in 1 L 20% sucrose solution (50% wt/vol) containing Luria Bertani media (10 g/L bactotryptone, 5 g/L bactoyeast extract, 10 g/L NaCl; pH 7.5), until a 0.1 optical density (OD600nm) was reached. Cells were then amplified up to OD600nm = 0.2 under 300 rpm agitation and at 37°C. From this point, temperature slowly reached 15°C (in 3 hr), and recombinant receptor synthesis was induced with 0.6 mM isopropylthiogalactopyranoside under the same agitation for 16 hr. Final OD600nm was about 1.4. Cells were centrifuged at 4,000 rpm at 4°C for 40 min. They were homogenized in 100 mL lysis buffer (20 mM Tris HCl, pH 8, 100 mM NaCl, 10% glycerol, 10 mM MgCl2, 1 mM MnCl2, 1 mg/mL lysozyme, 5 mM β-mercaptoethanol, 1 mg/mL Sigma protease inhibitor cocktail, 14,000 U DNase, and 0.1% Nonidet P40) by rolling at 4°C for 2 hr. Cells were sonicated for 15 min (amplitude, 40; pulse, 2 sec) and centrifugated at 45,000g for 60 min. Ligand-binding analysis was performed on supernatant (supplemented with 20% glycerol). The concentration was around 2.5 μM. The soluble recombinant ER-αwas then frozen at −80°C.
In order to purify recombinant ER-α, 2.5 mL of Ni-NTA-agarose phase (Qiagen, Courtaboeuf, France) was washed with washing buffer [WB: 20 mM Tris HCl, pH 7.5, 300 mM NaCl, 20% glycerol, 0.1 mg/mL charcoal-treated bovine serum albumin (BSA), and 10 mM imidazole] and incubated in a column with 100-mL recombinant receptor solution. After rolling for 16 hr, agarose phase was washed with WB, and the receptor was eluted with 7 mL eluting buffer (EB: 20 mM Tris HCl, pH 7.5, 300 mM NaCl, 20% glycerol, 0.1 mg/mL charcoal-treated BSA, and 100 mM imidazole). Protein presence and concentration of each elution fraction were evaluated by SDS-PAGE followed by blue stain reagent coloration. The recombinant ER-α–rich elution fraction was supplemented with 30% glycerol to give a 10 μM purified recombinant ER-α solution and frozen at −20°C.
Ligand-binding analysis experiments.
For saturation ligand-binding analysis and dissociation constant (Kd) determination, 0.1 pmol recombinant ER-αwas incubated with a range of [3H]-E2 (41.3 Ci/mmol specific activity) concentrations in the presence or absence of a 300-fold excess of unlabeled E2 in a final volume of 500 μL binding buffer (BB: 20 mM Tris HCl, pH 7.5, 5 mM dithioerythreitol, 2 mg/mL BSA). After shaking at 4°C for 16 hr, bound and free ligands were separated by DCC (2% charcoal, 0.2% dextran in BB). The mixture was left on ice for 2 min and then centrifuged at 3,000 rpm and 4°C for 2 min. Supernatant [3H] radioactivity was liquid scintillation counted (LS-6000-SC, Beckman-Coulter, Roissy, France). The Kd was calculated as the free concentration of radio-ligand at half-maximal specific binding by fitting data to the Hill equation and by linear Scatchard transformation.
For relative binding affinity (RBA) determination, 0.75 pmol recombinant ER-αwas incubated with 2 nM [3H]-E2 and increasing concentrations of competitors (xenoestrogens or E2), in a final volume of 500 μL BB. Experiments were performed as described above in duplicate and repeated twice. For each competitor, the concentration required to inhibit specific E2 binding by 50% (IC50) was determined as the competitor concentration required to inhibit specific radioligand binding by 50%. IC50 values were evaluated using Graph-Pad Prism statistics software. Specific RBA was calculated as the ratio of IC50 values of E2 to competitor. The RBA value for E2 was arbitrarily set at 100.
Inhibition test of MELN activation.
MELN cells were seeded in 96-well white opaque tissue culture plates as described above. In separate tubes, estrogenic compounds at nonsaturating concentration mediating about 80% MELN cell activity or 0.1% methanol extract for environmental samples, were prepared 4×-concentrated and preincubated with the same volume of 4×-concentrated purified recombinant ER-α(1–100 nM final concentration) in test culture medium at 4°C for 16 hr. Medium from MELN cell culture plates was then removed and replaced by 100 μL of test culture medium supplemented with the same volume of preincubation medium. After 6 hr incubation at 37°C, luciferase activity was determined.
Purification of estrogenic compounds by immobilized recombinant receptor.
Ten nanomoles of recombinant ER-αwere immobilized on 500 μL Ni-NTA-agarose phase. Estrogenic compounds were prepared in 500 μL WB at different nonsaturating concentrations in regard to their respective estrogenic activities (0.1 nM for E2; 3 nM for E3, E1, and α-zearalanol; 100 nM for Δ5-androstenediol, genistein, OP, and BPA; 300 nM NPm; 10 μM for phenol red) and added to the immobilized receptor. After rolling for 16 hr, flow-through and three 500-μL washings with WB were collected. Liganded receptor was then eluted with 3 × 500 μL EB, and eluate was heated at 65°C for 30 min in order to denature recombinant ER-α. Collected fractions were diluted 10-fold in culture medium before their relative estrogenic activity was evaluated with MELN reporter cells.
Environmental samples (50 μL sediment extract diluted 30-fold in WB; final volume, 1.5 mL) were added to the immobilized receptor. Flow-through (1.5 mL), washing, and elution fractions (500 μL) were collected. Precolumn and flow-through fractions were diluted 10-fold in culture medium before their relative activities were evaluated with MELN and HAhLP reporter cells. Washing and elution fractions were diluted 30-fold in culture medium to take into account the fact that they were 3× concentrated.
Results
Recombinant ER-α.
In order to obtain large amounts of ER-α, we decided to produce a mutant ER that would be highly expressed in bacteria. Three of its cysteine residues (381, 417, 530) were mutated into serine residues, which circumvented aggregation and denaturation problems. The mutant protein bound E2 with wild-type affinity but had limited transcriptional capacity (Gangloff et al. 2001). Because it had never been tested for its affinity toward xenoestrogens, we tested it by ligand binding ability. Kd for E2 was 0.25 nM, which is close to wild-type ER-αvalue (Figure 1). We also estimated competitor IC50 values in our binding conditions by the concentration required to inhibit specific 2 nM [3H]-E2 binding by 50%. In our conditions, IC50 value for E2 was about 5.9 nM. Tritiated E2 was displaced with an excess of cold compounds such as natural estrogens, (E1, E3), phytoestrogen (genistein), alkylphenols (4-NP, NPm), and BPA (Figure 2). IC50 values and specific relative binding affinities (RBAs) are shown in Table 1. The RBA ranking order was E2 > E3 = E1 > genistein > BPA > NPm > 4-NP. The same compounds were tested by whole cell binding in MELN cells. In these cells, the same ranking order was again observed, confirming that recombinant ER-αtriple mutant exhibited the same binding properties as wild-type ER-α(data not shown).
Dose–response curves of estrogenic compounds in MELN cells.
A great number of compounds able to activate ER-αwere tested with our MELN cells. We subsequently defined three classes of ligands according to their estrogenic potency (EC50 values). The first class was composed of ligands with the highest affinity for ER-α, EC50 values ranging from 10 pM to 1 nM. It included EE2, a pharmaceutical estrogen, natural estrogens E2, E3, and E1, and mycoestrogen zearalenone and its metabolite α-zearalanol (Figure 3A). The second class was composed of ligands with an EC50 values from 1 nM to 1 μM, such as natural estrogen Δ5-androstenediol, phytoestrogens coumestrol and genistein, alkylphenols OP and NPm, and BPA (Figure 3B). Finally, the last class contained compounds such as DDE insecticides, 4-NP, and phenol red dye, which had the lowest affinity for ER-α, with an EC50 values of up to 10 μM (Figure 3C). For each tested compounds, the RTP was calculated and reported in Table 2.
Comparison between binding to recombinant ER-αand transactivation efficiency showed that a good correlation was obtained for all compounds except E3 (Figure 4). This linear regression exhibited an R2 value of 0.9578, but it reached 0.9849 when E3 was not taken into account in the correlation analysis (result not shown). E3 exhibited an IC50 value for recombinant ER-αsimilar to that of E1, whereas E1 was 7-fold less efficient in MELN cells than was E3.
Inhibition test of MELN activation.
High-affinity estrogens such as E2, EE2, E3, and E1 could participate in the estrogenic activity of environmental samples from an urban source. To identify the presence of such compounds having a high affinity for ER-α, present at low concentration and, as a consequence, not easily detectable by classical analytical techniques, we set up a method that we called an inhibition test of MELN activation, in which high-affinity estrogenic compound transactivation of cellular ER-αwas competitively inhibited by limited amounts of recombinant ER-α. Keeping in mind that only free estrogens are able to bind cellular ER-αand activate luciferase expression, we preincubated a group of estrogens with recombinant ER-α. Their binding to recombinant ER-αproduced a diminution of free compound concentration. In a second step, liganded recombinant ER-α preincubation medium was added to cell culture medium and tested for its MELN cell transactivation activity. Sequestered ligands were thus not able to be taken into cells and show estrogen-mediated luciferase activity. The greater the recombinant ER-αconcentration, the more efficient the estrogen capture and inhibition of transactivation.
Capture efficiency of a group of estrogens having very different affinities for ER-α(E2, E3, E1, zearalenone, genistein, and NPm) was determined. As indicated in “Materials and Methods,” they were preincubated with 1–100 nM recombinant ER-αat concentrations necessary to obtain about 80% of MELN cell transactivation. Figure 5 shows that only compounds exhibiting a high affinity for ER-αwere captured and therefore yielded to an apparent inhibition of transactivation activity. E3, E1, and zearalenone were captured less efficiently than was E2, and compounds with lower affinity such as genistein and NPm showed only a slight or no inhibition even at high recombinant ER-α concentration. Although apparent affinities of E1 and E3 for recombinant ER-αwere similar (Figure 2), less efficient ER-αinhibition of E3 MELN transactivation was observed. It could reflect the 7-fold greater efficiency of E3 to transactivate cellular ER-α(Figure 3A).
Purification of estrogens by immobilized recombinant ER-α.
As described above, low ER-αconcentrations would only bind high-affinity estrogens. On the other hand, recombinant ER-αimmobilized at micromolar concentration was able to capture all estrogenic compounds present in environmental samples. Recombinant ER-αwas immobilized on Ni-NTA-agarose, incubated with different estrogenic compound, and column treated as described in “Materials and Methods.” Figure 6 shows a typical diagram obtained with E2 by evaluating estrogenic activity of all the collected fractions with the MELN cell luciferase assay. Table 3 clearly demonstrates the efficiency of capture and the good recovery of various estrogenic compounds. Another application is the purification of estrogenic compounds from a mixture. The estrogenic compound present in phenol red (Bindal et al. 1988) was efficiently separated from the dye by immobilized ER-α(Figure 7).
Dose–response curves of sediment and water extracts in MELN cells.
Estrogenic activities of sediment and water extracts of river Seine in an urban site were evaluated with the help of MELN cell luciferase assay (Figure 8). Sediments and water methanol extracts were applied to MELN cells, and luciferase transactivation was measured. When 0.15% water methanol extract was applied to MELN cell culture medium, a transactivation signal equivalent to that obtained with 15 pM E2 was observed (E2 EC50 value). E2 equivalence in water methanol extract was therefore 10 nM. Taking into account the 2,000×-concentrated methanol extract, as described in “Materials and Methods,” estrogen concentration in water was evaluated to 5 pM E2 equivalents (E2eq).
When 0.12% sediment extract was applied to cell culture medium, a transactivation signal equivalent to that obtained with 15 pM E2 was observed. E2 equivalence in sediment extract was therefore 12.5 nM. The whole sediment extract (5 mL from 50 g sediment) contained 62.5 pmol E2eq, and estrogen concentration in sediment was 1.25 pmol E2eq/g. In a previous work (Fenet et al. 2003), we showed that the estrogenic activity in sediments could be explained in great part by the alkylphenol concentration. On the contrary, alkylphenol concentration was too low to contribute to the observed river water estrogenic activity. We therefore hypothesized that other compounds, such as natural and synthetic hormones, could contribute in the overall water activity (Fenet et al. 2003).
Inhibition test of MELN activation with water and sediment extracts.
In order to confirm the above hypothesis, we performed an inhibition test of MELN cell activation with water and sediment of the same environmental site (Figure 9). Methanol extracts (0.1% vol/vol of test culture medium) corresponding to 10 pM and 12.5 pM E2eq for water and sediment, respectively, were added to cells in the presence of variable amounts of recombinant ER-α. Dose–response curves clearly identified the presence of high-affinity compounds in water samples because inhibition of transactivation was great with water extracts, whereas it was small with sediment extracts even at 100 nM recombinant ER-α. Similar results were obtained with a great number of water and sediment river samples (results not shown). Thus, different compositions in high- and low-affinity estrogenic compounds in river water and sediments are evidenced with our assay.
Purification of sediment extract estrogenic compounds by immobilized recombinant ER-α.
In river sediments, various substances were shown to bind to AhR (Michallet-Ferrier et al. 2004). These compounds can be dioxins, some PAHs, polychlorinated biphenyls (PCBs), and various pesticides. In order to characterize AhR activity of the sediment sample, we established AhR-responsive HeLa cell lines (HAhLP). In HAhLP cells, dioxin induced luciferase expression with an EC50 value of 0.2 nM (Figure 10). As we have already shown (Balaguer et al. 1999), dioxin was also able to partially activate MELN cells (Figure 9). This estrogenic activation by AhR ligands is mediated by a ternary complex (ER-α, AhR, and Arnt) in MCF-7 cells (Ohtake et al. 2003). As expected, sediment extract had a strong dioxin-like activity (0.2 nmol dioxin equivalents/g sediment), whereas water extract had a weak AhR activity (Figure 11). This strong dioxine-like activity could be due to PAHs widely found in river sediments (Hilscherova et al. 2001; Michallet-Ferrier et al. 2004).
The biological activities of sediment extracts could be due to compounds able to bind each receptor (ER-αand AhR) or a mixture of compounds able to bind only one of the two receptors. In order to address this problem, we used the recombinant ER-αcolumn to separate ER ligands from other compounds. Sediment extracts were applied to the column and ER-α, and AhR activities were measured in the different fractions (Figure 12). Most of the estrogenic activity was in the elution fraction. A small part was not retained by the column and was in the flow-through fraction. This weak estrogenic activity may be due to AhR ligands because most AhR activity was in the flow-through and wash fractions. A small part of AhR activity was in the fraction eluting with recombinant ER-α. Because estrogens did not activate luciferase expression in the AhR-responsive cell line (results not shown), we conclude that some compounds have a double activity (estrogenic and dioxin-like).
Discussion
Environmental estrogenic activity is mediated by a wide variety of compounds that may be differentially distributed in water or sediments. These chemicals include a wide range of molecules from natural, pharmaceutical, agricultural, or industrial origin. Nevertheless, STP effluents are considered a major source of estrogenic water pollution that may play a role in environmental contamination. High-affinity compounds for ERs, such as natural or synthetic estrogens, as well as low-affinity compounds, such as alkylphenols, phthalates, and hydroxylated PCBs, have been identified in river water and sediments samples. Given the difficulty in identifying all of these EDCs, numerous authors attempted to detect and quantify the estrogenic potency of water samples by targeting their research on specific molecules (Aerni et al. 2004; Baronti et al. 2000; Solé et al. 2000). Analytical extraction systems combined with in vitro biological assays were also developed to identify estrogenic compounds present in water and sediments (Cargouët et al. 2004; Desbrow et al. 1998; Fenet et al. 2003; Peck et al. 2004; Snyder et al. 2001).
Nevertheless, it is difficult to assert if the observed effects are due to compounds of low or high affinity before they are identified. We developed a tool using a recombinant ER-α LBD in order to trap estrogenic molecules. We first used it to characterize the affinity of unknown estrogenic compounds. It is a simple assay in which compounds of high affinity were captured by limited amounts of recombinant ER-αleading to a selective inhibition of transactivation in estrogen-responsive cells. This approach allowed us to discriminate between compounds present at low concentration but displaying a high affinity for ER, and compounds present at higher than 10 nM concentration but with a corresponding lower affinity. Furthermore, this recombinant ER-α, immobilized on columns, can be used to extract and concentrate all xenoestrogens, independently from their affinity. In a complex mixture, this procedure would facilitate their analytical identification.
A second best-characterized pathway for endocrine disruption is ligand binding to AhR. This would lead to endocrine-disrupting effects by activating AhR-responsive genes, such as CYP1A1, which encodes for cytochrome P450 1A1 involved in endogenous steroid hormone metabolism (Denison and Nagy 2003, Hahn et al. 1996) and/or by modulating ER-responsive gene expression (Ohtake et al. 2003; Wormke et al. 2003). In the aquatic environment, various organic substances were shown to bind AhR. For example, PAHs are known to bind AhR (Billiard et al. 2002), whereas some PAHs and metabolites bind ERs (Charles et al. 2000; Clemons et al. 1998; Fertuck et al. 2001).
Many environmental organic chemicals are hydrophobic and are associated with particulate matter in aquatic ecosystems. Sediments act as both sink and source for these contaminants. They can sorb these chemicals and release them back directly to the food web by ingestion (i.e., benthic organisms) or via resuspension and possible release to the water phase, according to physical-chemical factors and partitioning equilibrium (Gewurtz et al. 2000). In our study, sediments showed both AhR and ER agonistic activities. These activities may be due to a) a compound able to bind both ERs and AhR, such as PAHs (Fertuck et al. 2001; Fielden et al. 2000), polybrominated diphenyl ether (PBDE; de Wit 2002), or PCBs (Yoon et al. 2001), or b) a mixture of compounds able to bind either one of the two receptors. In order to choose between the two possibilities, we immobilized our recombinant ER-αupon columns to isolate ER ligands from the other compounds and measured ER and AhR activities. It clearly indicated that most AhR ligands did not bind ERs. Altogether, our results indicate that river sediment estrogenic activity is mediated by a) low-affinity estrogens that bind only ERs, b) most AhR ligands that activate ER-mediated expression through AhR, and c) a minority of AhR ligands that activate both ERs and AhR. These hypotheses also address recent findings suggesting the participation of AhR ligands with low estrogenic capacity such as PAHs (Hilscherova et al. 2001; Michallet-Ferrier et al. 2004) and/or PBDEs (Meerts et al. 2001) in estrogenic activities measured in river sediments.
In environmental samples, compounds with high affinity for ER are present mainly in water, whereas medium- or low-affinity compounds are more likely present in sediments. Xenoestrogen trapping mediated by nuclear receptor and coupled to gene expression measurement is more than a screening method. This battery of in vitro tests is a powerful, simple, and rapid tool that enables the characterization of compounds present in environmental compartments.
Figure 1 E2 binding ability of recombinant ER-α. Binding of [3H]-E2 to recombinant ER-αwas performed in the presence or absence of non-radioactive E2. Unbound radioligand was removed as described in “Materials and Methods,” and specific bound radioligand concentration was calculated after nonspecific bound counts were subtracted from total bound counts. (Inset) Linear Scatchard transformation of specific binding giving a Kd of 0.25 nM for recombinant ER-α.
Figure 2 Competitive binding curves of selected nonradioactive chemicals to recombinant ER-α. Recombinant ER-α(0.75 pmol) was incubated with 2 nM [3H]-E2 together with increasing concentrations of unlabeled test chemicals and incubated in 500 μL at 4°C for 16 hr as described in “Materials and Methods.” The percentage of [3H]-E2 binding (100% in the absence of unlabeled test chemical) was expressed as a function of the molar concentration of tested compound (mean ± SEM of quadruplicates). IC50 values and RBAs are shown in Table 1.
Figure 3 MELN cell luciferase assay of natural estrogens and xenoestrogens. (A) Compounds with EC50 values from 10 pM to 1 nM. (B) Compounds with EC50 values from 1 nM to 1 μM. (C) Compounds with EC50 values > 1 μM. Results are expressed as a percentage of luciferase activity measured per well (mean ± SEM of quadruplicates). The value obtained in the presence of 10 nM E2 was taken as 100. EC50 values and RTP are shown in Table 2.
Figure 4 Correlation between binding and transactivation. Linear regression of the RBAs as a function of the RTP of E2, E3, E1, genistein, BPA, NPm, and 4-NP. Values were extracted from Tables 1 and 2. R2 = 0.9578.
Figure 5 Inhibition test of MELN activation with various estrogens. Luciferase activity induced by E2, E3, E1, zearalenone, genistein, and NPm at concentrations giving about 80% of transactivation was evaluated in MELN cells in the presence of variable amounts of recombinant ER-α(1–100 nM). Results are expressed as the percentage of luciferase activity measured per well (mean ± SEM of quadruplicates). The value obtained in the presence of 10 nM E2 was taken as 100.
Figure 6 MELN cell luciferase assay of fractions obtained after E2 purification on recombinant ER-α agarose column. Recombinant ER-α(10 nmol) was prefixed on 100 μL Ni-NTA-agarose phase. E2 (0.1 nM, i.e., 500 fmol) was added, and 500 μL fractions (flow-through, washing, and elution) were collected. The percentage of transactivation of MELN cell luciferase was then measured (values in Table 3). Results are expressed as a percentage of luciferase activity measured per well (mean ± SEM of quadruplicates). The value obtained in the presence of 10 nM E2 was taken as 100.
Figure 7 MELN cell luciferase assay of fractions obtained after purification of phenol red on recombinant ER-αagarose column. Recombinant ER-α (10 nmol) was prefixed on 100 μL Ni-NTA-agarose phase. Phenol red (10 μM, i.e., 50 nmol) was added, and 500 μL fractions (flow-through, washing, and elution) were collected. The percentage of trans-activation was then measured (values in Table 3). The left ordinate expresses the percentage of luciferase activity measured per well (mean ± SEM of quadruplicates). The value obtained in the presence of 10 nM E2 was taken as 100. The right ordinate expresses phenol red absorbance (λ, 562 nm) of collected fractions.
Figure 8 MELN cell luciferase assay of water and sediment extracts. Results are expressed as a percentage of luciferase activity measured per well (mean ± SEM of quadruplicates) as a function of methanol extract percentage. The value obtained in the presence of 10 nM E2 was taken as 100.
Figure 9 Inhibition test of MELN activation with water and sediment extracts. Induction of luciferase activity by 0.1% water and by sediment methanol extract in culture medium was evaluated in MELN cells in the presence of variable amounts of recombinant ER-α(1–100 nM). Results are expressed as a percentage of luciferase activity measured per well (mean ± SEM of quadruplicates). The value obtained in the presence of 10 nM E2 was taken as 100.
Figure 10 Induction of luciferase activity by dioxin in HAhLP and MELN cell lines. Results are expressed as a percentage of luciferase activity measured per well (mean ± SEM of quadruplicates). The values obtained in the presence of 10 nM dioxin and E2 with HAhLP and MELN cells, respectively, were taken as 100. The basal signal was 20 and 15% for HAhLP and MELN cells, respectively.
Figure 11 Induction of luciferase activity by water and sediment extracts in HAhLP cell line. Results are expressed as a percentage of luciferase activity measured per well (mean ± SEM of quadruplicates). The value obtained in the presence of 10 nM dioxin with HAhLP cells was taken as 100%.
Figure 12 Induction of luciferase activity in MELN and HAhLP cells by column fraction obtained after purification of sediment extract on recombinant ER-αagarose column. Ten nanomoles of recombinant ER-αwere prefixed on 100 μL Ni-NTA-agarose phase. Sediment extract (50 μL methanol extract 30-fold diluted in WB) was added. Flow-through (1.5 mL), washing, and elution (500 μL) fractions were collected and the percentage of transactivation measured. Dilution factors used with both cell lines were 10 for precolumn and flow-through and 30 for washing and elution fractions. Results are expressed as a percentage of luciferase activity measured per well (mean ± SEM of quadruplicates). The values obtained in the presence of 10 nM dioxin and E2 with HAhLP and MELN cells, respectively, were taken as 100.
Table 1 Binding affinity of various compounds for recombinant ER-α.
Compound IC50 ± SE RBA
E2 5.90 nM ± 1.19 100
E3 62.7 nM ± 10.9 9.41
E1 65.3 nM ± 10.9 9.04
Genistein 381 nM ± 130 1.55
BPA 889 nM ± 127 0.66
NPm 1.86 μM ± 0.11 0.32
4-NP 5.60 μM ± 1.12 0.11
IC50 values were determined from competitive binding experiments performed as described in “Materials and Methods” (Figure 2). Competitor RBAs were calculated as the ratio of IC50 values of E2 to competitor. RBA value for E2 was arbitrarily set at 100.
Table 2 Estrogenic potency of tested compounds.
Compound EC50 ± SE RTP
EE2 7.14 pM ± 1.09 246
E2 17.6 pM ± 4.61 100
E3 100 pM ± 10.8 17.6
α -Zearalanol 135 pM ± 31.2 13.0
Zearalenone 313 pM ± 39.2 5.62
E1 694 pM ± 131 2.54
Δ5-androstenediol 13.1 nM ± 5.40 0.13
Genistein 26.7 nM ± 14.7 0.064
Coumestrol 43.5 nM ± 7.91 0.040
4-OP 54.2 nM ± 13.8 0.032
BPA 96.3 nM ± 27.3 0.018
NPm 339 nM ± 126 0.0051
2,4′-DDE 2.74 μM ± 0.92 0.00063
4-NP 11.0 μM ± 2.83 0.00016
4,4′-DDE 25.6 μM ± 11.4 0.00007
Phenol red 36.9 μM ± 23.0 0.00005
EC50 values were concentrations required to produce half-maximal induction in MELN cell line, determined from Figure 3. The RTP of each compound was calculated as the ratio of EC50 values of E2 to compound. RTP value for E2 was arbitrarily set at 100.
Table 3 Induction of luciferase activity (%) by different fractions of the recombinant ER-αcolumn incubated with natural estrogens and xenoestrogens.
Compound Precolumn Flow-through Washing Elution
E2 (0.1 nM) 95 ± 5 19 ± 4 16 ± 2 91 ± 4
E3 (3 nM) 62 ± 3 16 ± 0.5 15 ± 1 60 ± 3
α -Zearalanol (3 nM) 88 ± 2 17 ± 2 16 ± 1 82 ± 6
E1 (3 nM) 48 ± 2 19 ± 3 21 ± 3 39 ± 1
Δ5-Androstenediol (100 nM) 93 ± 3 15 ± 0.5 16 ± 0.5 90 ± 3
Genistein (100 nM) 97 ± 5 16 ± 2 17 ± 2 79 ± 2
Coumestrol (100 nM) 71 ± 5 15 ± 3 15 ± 3 66 ± 6
OP (100 nM) 73 ± 3 16 ± 3 15 ± 2 69 ± 2
BPA (100 nM) 70 ± 6 17 ± 2 16 ± 2 70 ± 2
NPm (300 nM) 57 ± 4 17 ± 1 16 ± 2 56 ± 2
Phenol red (10 μM) 36 ± 5 16 ± 2 15 ± 3 40 ± 4
Estrogenic compounds were added to the recombinant ER-α column. The volume of each collected fraction was 500 μL, and their relative estrogenic activity was evaluated with MELN reporter cells. Results are expressed as a percentage of luciferase activity measured per well (mean ± SEM of quadruplicates). The value obtained in the presence of 10 nM E2 was taken as 100.
==== Refs
References
Aerni HR Kobler B Rutishauser BV Wettstein FE Fischer R Giger W 2004 Combined biological and chemical assessment of estrogenic activities in wastewater treatment plant effluents Anal Bioanal Chem 378 688 696 14574437
Balaguer P Boussioux AM Demirpence E Nicolas JC 2001 Reporter cell lines are useful tools for monitoring biological activity of nuclear receptor ligands Luminescence 16 153 158 11312541
Balaguer P Fenet H Georget V Comunale F Térouanne B Gilbin R 2000 Reporter cell lines to monitor steroid and antisteroid potential of environmental samples Ecotoxicology 9 115 114
Balaguer P Francois F Comunale F Fenet H Boussioux AM Pons M 1999 Reporter cell lines to study the estrogenic effects of xenoestrogens Sci Total Environ 233 47 56 10492897
Baronti C Curini R D’Ascenzo G Di Corcia A Gentili A Samperi R 2000 Monitoring natural and synthetic estrogens at activated sludge sewage treatments plants in a receiving river water Environ Sci Technol 34 5059 5066
Billiard SM Hahn ME Franks DG Peterson RE Bols NC Hodson PV 2002 Binding of polycyclic aromatic hydrocarbons (PAHs) to teleost aryl hydrocarbon receptors (AHRs) Comp Biochem Physiol B Biochem Mol Biol 133 55 68 12223212
Bindal RD Carlson KE Katzenellenbogen BS Katzenellenbogen JA 1988 Lipophilic impurities, not phenolsulfonphthalein, account for the estrogenic activity in commercial preparations of phenol red J Steroid Biochem 31 287 293 3419159
Cargouët M Perdiz D Mouatassim-Souali A Tamisier-Karolak S Levi Y 2004 Assessment of river contamination by estrogenic compounds in Paris area (France) Sci Total Environ 324 55 66 15081696
Charles GD Bartels MJ Zacharewski TR Gollapudi BB Freshour NL Carney EW 2000 Activity of benzo(a )pyrene and its hydroxylated metabolites in an estrogen receptor-alpha reporter gene assay Toxicol Sci 55 320 326 10828263
Clemons JH Allan LM Marvin CH Wu Z McCarry BE Zacharewski TR 1998 Evidence of estrogen- and TCDD-like activities in crude and fractionated extracts of PM10 air particulate material using in vitro gene expression assays Environ Sci Technol 32 1741 1864
Denison MS Nagy SR 2003 Activation of the aryl hydrocarbon receptor by structurally diverse exogenous and endogenous chemicals Annu Rev Pharmacol 43 309 334
Desbrow C Routledge J Brighty GC Sumpter JP Waldock M 1998 Identification of estrogenic chemicals in STW effluent. 1. Chemical fractionation and in vitro biological screening Environ Sci Technol 32 1549 1558
de Wit CA 2002 An overview of brominated flame retardants in the environment Chemosphere 46 583 624 11999784
Fenet H Gomez E Pillon A Rosain D Nicolas JC Casellas C 2003 Estrogenic activity in water and sediments of a French river: contribution of alkylphenols Arch Environ Contam Toxicol 44 1 6 12447603
Fertuck KC Kumar S Sikka HC Matthews JB Zacharewski TR 2001 Interaction of PAH-related compounds with the alpha and beta isoforms of the estrogen receptor Toxicol Lett 121 167 177 11369471
Fielden MR Wu ZF Sinal CJ Jury HH Bend JR Hammond GL 2000 Estrogen receptor- and aryl hydrocarbon receptor-mediated activities of a coal-tar creosote Environ Toxicol Chem 19 1261 1271
Gangloff M Ruff M Eiler S Duclaud S Wurtz JM Moras D 2001 Crystal structure of a mutant hERalpha ligand-binding domain reveals key structural features for the mechanism of partial agonism J Biol Chem 276 15059 15065 11278577
Gewurtz SB Lazar R Haffner GD 2000 Comparison of polycyclic aromatic hydrocarbon and polychlorinated biphenyl dynamics in benthic invertebrates of Lake Erie, USA Environ Toxicol Chem 19 2943 2950
Hahn ME Woodward BL Stegemann JJ Kennedy SW 1996 Rapid assessment of induced cytochrome P4501A protein and catalytic activity in fish hepatoma cells grown in multiwell plates: response to TCDD, TCDF and two planar PCBs Environ Toxicol Chem 15 582 591
Harries JE Janbakhsh A Jobling S Mathiesen P Sumpter JP Tyler CR 1999 Estrogenic potency of effluent from two sewage treatment works in the United Kingdom Environ Toxicol Chem 18 932 937
Hilscherova K Kannan K Kang YS Holoubek I Machala M Masunaga S 2001 Characterization of dioxin-like activity of sediments from a Czech river basin Environ Toxicol Chem 20 2768 2777 11764160
Jobling S Beresford N Nolan M Rodgers-Gray T Brighty GC Sumpter JP 2002 Altered sexual maturation and gamete production in wild roach (Rutilus rutilus ) living in rivers that receive treated sewage effluents Biol Reprod 66 272 281 11804939
Körner W Hanf V Schuller W Kempter C Metzger J Hagenmeier H 1999 Development of asensitive E-screen assay for quantitative analysis of estrogenic activity in municipal sewage plant in Germany Sci Total Environ 225 33 48 10028701
Kuiper GG Lemmen JG Carlsson B Corton JC Safe SH van der Saag PT 1998 Interaction of estrogenic chemicals and phytoestrogens with estrogen receptor beta Endocrinology 139 4252 4263 9751507
Meerts I Letcher RJ Hoving S Marsh G Bergman A Lemmen JG 2001 In vitro estrogenicity of polybrominated diphenyl ethers, hydroxylated PBDEs, and polybrominated bisphenol A compounds Environ Health Perspect 109 399 407 11335189
Michallet-Ferrier P Aït-Aïssa S Balaguer P Dominik J Haffner GD Pardos M 2004 Assessment of estrogen receptor (ER) and aryl hydrocarbon receptor (AhR) mediated activities in organic sediment extracts of the Detroit River, using in vitro bioassays based on human MELN and teleost PLHC-1 cell lines J Great Lakes Res 30 82 92
Ohtake F Takeyama K Matsumoto T Kitagawa H Yamamoto Y Nohara K 2003 Modulation of oestrogen receptor signalling by association with the activated dioxin receptor Nature 423 545 550 12774124
Paris F Balaguer P Térouanne B Servant N Lacoste C Cravedi JP 2002 Phenylphenols, biphenols, bisphenol-A and 4-tert -octylphénol exhibit αand βestrogen activities and antiandrogen activity in reporter cell lines Mol Cell Endocrinol 193 43 49 12161000
Peck M Gibson RW Kortenkamp A Hill EM 2004 Sediments are major sinks of steroidal estrogens in two United Kingdom rivers Environ Toxicol Chem 23 945 952 15095890
Purdom CE Hardiman PA Bye VJ Eno NC Tyler CR Sumpter JP 1994 Estrogenic effects of effluents from sewage treatment works Chem Ecol 8 275 285
Snyder SA Villeneuve DL Snyder EM Giesy JP 2001 Identification and quantification of estrogen receptor agonists in wastewater effluents Environ Sci Technol 35 3620 3625 11783637
Solé M de Alda MJL Castillo M Porte C Ladegaard-Pesdersen K Barcelo D 2000 Estrogenic determination in sewage treatment plants and surface waters from the Catalonian area (NE Spain) Environ Sci Technol 34 5076 5083
Sumpter JP 1998 Xenoendocrine disrupters—environmental impacts Toxicol Lett 102 337 342 10022275
Wormke M Stoner M Saville B Walker K Abdelrahim M Burghardt R 2003 The aryl hydrocarbon receptor mediated degradation of estrogen receptor αthrough activation of proteasomes Mol Cell Biol 23 1843 1855 12612060
Yoon K Pallaroni L Stoner M Gaido K Safe S 2001 Differential activation of wild-type and variant forms of estrogen receptor alpha by synthetic and natural estrogenic compounds using a promoter containing three estrogen-responsive elements J Steroid Biochem Mol Biol 78 25 32 11530281
|
15743715
|
PMC1253752
|
CC0
|
2021-01-04 23:40:57
|
no
|
Environ Health Perspect. 2005 Mar 9; 113(3):278-284
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7522
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7451ehp0113-00028515743716ResearchArticlesOccupational Exposure to Carbofuran and the Incidence of Cancer in the Agricultural Health Study Bonner Matthew R. 1Lee Won Jin 12Sandler Dale P. 3Hoppin Jane A. 3Dosemeci Mustafa 1Alavanja Michael C. R. 11Occupational and Environmental Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, Maryland, USA2Department of Preventive Medicine, College of Medicine, Korea University, Seoul, Korea3Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, North Carolina, USAAddress correspondence to M.R. Bonner, Occupational and Environmental Epidemiology Branch, National Cancer Institute, 6120 Executive Blvd., EPS 8121, MSC 7240, Bethesda, MD 20892-7240 USA. Telephone: (301) 402-7825. Fax: (301) 402-1819. E-mail:
[email protected] work was supported by intramural funds from the National Cancer Institute.
The authors declare they have no competing financial interests.
3 2005 2 12 2004 113 3 285 289 27 7 2004 2 12 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Carbofuran is a carbamate insecticide registered for use on a variety of food crops including corn, alfalfa, rice, and tobacco. An estimated 5 million pounds of carbofuran is used annually in the United States, and 45% of urban African-American women have detectable levels of carbofuran in their plasma. Nitrosated carbofuran has demonstrated mutagenic properties. We examined exposure to carbofuran and several tumor sites among 49,877 licensed pesticide applicators from Iowa and North Carolina enrolled in the Agricultural Health Study. We obtained information regarding years of use, frequency of use in an average year, and when use began for 22 pesticides using self-administered questionnaires. Poisson regression was used to calculate rate ratios (RR) and 95% confidence intervals (CIs) adjusting for potential confounders. Lung cancer risk was 3-fold higher for those with > 109 days of lifetime exposure to carbofuran (RR = 3.05; 95% CI, 0.94–9.87) compared with those with < 9 lifetime exposure days, with a significant dose–response trend for both days of use per year and total years of use. However, carbofuran use was not associated with lung cancer risk when nonexposed persons were used as the referent. In addition, carbofuran exposure was not associated with any other cancer site examined. Although carbamate pesticides are suspected human carcinogens, these results should be interpreted cautiously because there was no a priori hypothesis specifically linking carbofuran to lung cancer.
agriculturecancer incidencecarbofuranlung cancerpesticides
==== Body
Carbofuran (2,3-dihydro-2,2-dimethylbenzofuran-7-yl methylcarbamate) is a carbamate insecticide registered for use on a variety of food crops including corn, alfalfa, rice, and tobacco (Tobin 1970). An estimated 5 million pounds of carbofuran are used annually in the United States, 48% of which is used on corn crops (Thelin and Gianessi 2000). In addition to agriculturally related exposure, the general U.S. population may also be commonly exposed to carbofuran. Forty-five percent of urban African-American women and their newborns had detectable levels of carbofuran in maternal plasma and umbilical cord blood (Whyatt et al. 2003).
Carbofuran has been demonstrated to have weak mutagenic activity in some, but not all, strains of Salmonella typhimurium (Hour et al. 1998; Moriya et al. 1983). Carbofuran induces chromosomal aberrations and micronucleus formation in exposed mice (Chauhan et al. 2000) and N-nitrosocarbofuran, derived from the nitrosation of carbofuran, has demonstrated mutagenic properties (Yoon et al. 2001). The evidence from animal models is inconclusive. Two studies demonstrated that carbofuran was able to induce lymphoma in Swiss mice (Borzsonyi and Pinter 1977; Borzsonyi et al. 1976), but carcinogenicity of carbofuran was not evident in several 2-year dietary studies conducted on rats (Gupta 1994).
In addition to the potential carcinogenicity of N-nitrosocarbofuran, carbamate pesticides have been shown to impair immunity in mice (Barnett et al. 1980; Street and Sharma 1975) and in humans (Fiore et al. 1986). Several epidemiologic investigations have examined exposure to carbamate pesticides, including carbofuran, and the risk of cancer. McDuffie et al. (2001) found elevated risk for non-Hodgkin lymphoma (NHL) associated with the use of carbamate pesticides [odds ratio (OR) = 1.9; 95% confidence interval (CI), 1.2–3.0], but not with carbofuran specifically (OR = 1.6; 95% CI, 0.7–3.9). Zheng et al. (2001) observed elevated risk among farmers who used carbofuran (OR = 1.6; 95% CI, 1.1–2.3). In a nested case–control study of structural pest control workers in Florida, Pesatori et al. (1994) reported an increase in the OR for lung cancer among those who used carbamate insecticides (OR = 16.3; 95% CI, 2.2–122.5). Increased risk of lung cancer was not evident, however, in a population-based case–control study among residents of Saskatchewan, Canada (McDuffie et al. 1990). Considering the limited epidemiologic data on carbofuran and cancer, we examined the relationship between occupational exposure to carbofuran and several tumor sites in the Agricultural Health Study.
Materials and Methods
A detailed description the Agricultural Health Study (AHS) has been previously published (Alavanja et al. 1996). Briefly, the AHS is a prospective cohort study of 57,311 licensed restricted-use pesticide applicators and 32,347 of their spouses in Iowa and North Carolina. Licensed pesticide applicators include private applicators who are farmers and commercial applicators who are employed by pest control companies or businesses that use pesticides such as warehouse operators and grain millers. Recruitment started in December 1993 and ended 4 years later in December 1997. The National Death Index and state death registries were used to ascertain the vital status of cohort members. Incident cancers diagnosed between December 1993 and 31 December 2001 were identified through tumor registries and coded using the International Classification of Diseases for Oncology (ICD-O-2) (Percy et al. 1990). The average follow-up time was 6.4 years. Participants (n = 946) who moved out of either Iowa or North Carolina were censored in the year they moved. All participants provided informed consent; the protocol was approved by all appropriate Institutional Review Boards.
Exposure assessment.
Study participants were asked to complete a self-administered questionnaire at the time of enrollment. We obtained information on 50 pesticides. Detailed data about years of use, frequency of use in an average year, and when use began were collected for 22 pesticides including carbofuran, and information on ever/never use of 28 other pesticides was collected at the time of enrollment. In addition, information regarding application methods and the use of personal protective equipment was collected. Participants also supplied information about important potential confounders such as smoking habits, alcohol intake, fruit and vegetable consumption, other agricultural activities, and non-farm–related occupational exposures. A previous analysis of the reliability of the AHS questionnaire showed that the level of agreement for pesticide use was similar to other factors routinely estimated with epidemiologic questionnaires (Blair et al. 2002).
For these analyses, we estimated exposure with total lifetime exposure-days to carbofuran. Lifetime exposure-days was defined as the product of the number of years a participant personally mixed or applied carbofuran and the number of days in an average year that carbofuran was used. In addition, we incorporated an algorithm developed by Dosemeci et al. (2002) to estimate an exposure intensity score and applied it to lifetime exposure-days metric. Briefly, the intensity score was designed to incorporate aspects of pesticide use that can modify actual exposure, including whether an applicator personally mixed or prepared the pesticides for application, what type of application methods were used, the repair of pesticide application equipment, and the use of personal protective equipment during these activities. Dermal absorption is generally considered the major route of exposure for pesticide applicators (Maroni et al. 2000; Tobin 1970). Therefore, the intensity score heavily weighted the use of protective gloves and to a lesser extent protective clothing. We calculated intensity-weighted exposure-days as the product of the intensity score and total lifetime exposure-days. In addition to these exposure metrics, we also assessed the frequency (i.e., number of days/year applied) and the duration (total number of years applied) of carbofuran exposure in relation to cancer risk.
Statistical analysis.
Prevalent cancer cases (n = 1,074) and applicators who failed to provide information about carbofuran use (n = 6,360) were excluded, leaving 49,877 cohort members from this analysis. Most of the subjects who were missing information on carbofuran use and other potential confounders were from North Carolina (64%). Two reference groups were used for these analyses: pesticide applicators who reported never using carbofuran and pesticide applicators whose use of carbofuran was in the lowest tertile of exposure.
We used Poisson regression to calculate rate ratios (RR) and 95% CIs. Lifetime exposure-days and intensity-weighted lifetime exposure-days to carbofuran were categorized into tertiles based on the distribution in all the cancer cases. The highest tertile was then divided at its midpoint to increase the resolution at higher exposure levels. We limited analyses to tumor sites where there were more than five cases in each category of exposure. Models were adjusted for age at enrollment (< 40, 40–49, 50–59, ≥ 60 years), sex, education (≤ high school graduate, > high school graduate), smoking (by pack-years: never, ≤ 14, > 14), alcohol consumption during the last 12 months (yes/no), family history of cancer (yes/no), year at enrollment, state of residence (Iowa/North Carolina), and the five pesticides most highly correlated with carbofuran use [permethrin (crop), S-ethyl dipropylthiocarbamate (EPTC), chlorpyrifos, fonofos, and trichlorfon: never, low, high exposure]. The correlation coefficients for these five pesticides ranged between 0.69 (permethrin) and 0.85 (trichlorfon). The cut point that dichotomized low and high exposure for each pesticide correlated with carbofuran was determined by the median for lifetime exposure-days for that particular pesticide. We based the cut points for days of use per year and years of use on the categorical responses to the following questions: “In an average year when you personally used this pesticide, how many days did you use it?” (< 5 days; 5–9 days; 10–19 days; 20–39 days; 40–59 days; 60–150 days; or > 150 days) and “How many years did you personally mix or apply this pesticide?” (≤ 1 year or less; 2–5 years; 6–10 years; 11–20 years; 21–30 years; or > 30 years). For the analysis, we collapsed the upper categories to ensure that there were approximately five or more cases in each category.
We determined the most parsimonious model (reduced) with −2 log-likelihood ratio tests by removing each covariate from the saturated (full) model and retaining only those variables that resulted in significant −2 log-likelihood ratio (Hosmer and Lemeshow 1989). The most parsimonious model included age, smoking (never, < 14 pack-years, and ≥ 14 pack-years of smoking), family history of cancer, and trichlorofon and permethrin exposure.
To further control for potential confounding by smoking, we also adjusted for several other smoking variables including smoking status (never, former, current), pack-years of smoking, duration of smoking, and number of cigarettes smoked per day. The inclusion of these additional smoking variables did not appreciably alter the risk estimates and were not retained in the models. Linear trends were assessed using the p-value of the coefficient of the exposure treated as a continuous value using the median value for each tertile of exposure in the models also adjusting for covariates (Breslow and Day 1987). Tests for interaction were performed by determining the significance of the coefficient of the product term of the exposure and the purported effect modifier.
Results
Twenty-five percent of the pesticide applicators reported ever using carbofuran. Demographic characteristics of the non-carbofuran exposed and carbofuran exposed [categorized as low (tertile 1) and high exposure (tertiles 2 and 3)] are depicted in Table 1. The non-carbofuran exposed tended to be younger than either the low- or high-exposed carbofuran cohorts. The nonexposed were also more likely to be female than the exposed, although there were few women applicators in the study overall. Smoking status (never, former, or current), alcohol consumption in the last 12 months, attained education, state of residence, years of follow-up, and family history of cancer were all similar between the three groups. The mean number of smoking pack-years; however, sequentially increased between nonexposed, low-exposed, and the high-exposed groups. Cohort members exposed to carbofuran were more likely than nonexposed cohort members to be involved in corn production. Additionally, those exposed to carbofuran used more types of pesticides than non-carbofuran–exposed subjects.
We report on all cancer sites combined and tumor sites where sufficient numbers (at least five cases per cell) of cases occurred during follow-up to warrant statistical analyses: all lymphatic–hematopoietic cancers (Hodgkin, non-Hodgkin, multiple myeloma, and leukemia), NHL, and colon, lung, and prostate cancers.
Carbofuran exposure was not associated with the incidence of all cancers combined (Table 2) or with any tumor site examined except lung cancer. Lung cancer risk appeared to be positively associated with exposure to carbofuran when the low exposed were used as the reference group, although a test of the linear trend was not significant (p for trend = 0.07). The lung cancer rate ratio was increased 3-fold among those with more than 109 lifetime-days of use (RR = 3.05; 95% CI, 0.94–9.87). When the nonexposed were used as the reference group, however, exposure to carbofuran was not associated with the lung cancer rate ratio.
An exposure–response relationship with the intensity-weighted lifetime exposure-days was not clearly evident for lung cancer (Table 3). Although the upper category of the intensity-weighted lifetime exposure-days suggests an increase in the relative risk, the exposure–response gradient was not monotonic. Regarding the other cancer sites examined, there was no evidence of an association with intensity-weighted lifetime exposure-days when either the nonexposed or the low-exposed subjects were used as the referent (data not shown).
The risk of lung cancer also increased when the frequency of exposure (number of days of carbofuran use/year) and duration of exposure (number of years carbofuran was used) were examined separately (Table 3). However, the risk was only elevated in applicators who used carbofuran for > 10 years and for > 10 applications days per year.
To further examine and characterize the association between carbofuran exposure and lung cancer, we stratified by smoking status (never, former, and current), state of residence (Iowa and North Carolina), histology (adenocarcinoma and non-adenocarcinoma), and applicator type (farmer and commercial). The analyses stratified by smoking status were limited in that only one case of lung cancer was identified among never smokers and precluded an analysis restricted to never smokers. The risk estimates increased as exposure increased for both former and current smokers (Table 4), and the p for interaction was not significant (p = 0.36). Carbofuran exposure was associated with nonsignificant increases in risk in both Iowa (2nd tertile: RR = 3.79, 95% CI, 0.73–19.55; 3rd tertile: RR = 5.90, 95% CI, 1.25–27.81) and North Carolina (2nd tertile: RR = 0.91, 95% CI, 0.20–4.05; 3rd tertile: RR = 2.49, 95% CI, 0.77–8.14). Although the point estimates of risk were greater in Iowa, the p-value for the interaction between state and carbofuran exposure was not significant (p for interaction = 0.53). Rate ratios were increased for both adenocarcinoma (2nd tertile: RR = 3.95, 95% CI, 0.41–38.02; 3rd tertile: RR = 7.87, 95% CI, 0.94–65.62) and non-adenocarcinoma (2nd tertile: RR = 1.35, 95% CI, 0.39–4.68; 3rd tertile: RR = 2.90, 95% CI, 1.0–8.36). Although the risk was considerably higher for adenocarcinoma, the p for interaction between histology and carbofuran use was not significant (p = 0.32). There was no evidence that applicator type either confounded or modified the association between carbofuran and lung cancer risk, although the number of commercial applicator lung cancer cases was low.
Discussion
An association between carbofuran and lung cancer has not been previously reported. Several studies, however, have found pesticides (Brownson et al. 1993; Wesseling et al. 1999) and more specifically carbamate pesticides (Pesatori et al. 1994) to be associated with lung cancer, although not all studies have reported this association (McDuffie et al. 1990). In our study, lung cancer was associated with lifetime exposure-days where risk increased across exposure categories to more than a 3-fold increase in the RR in the highest category when compared with those who had applied < 9 lifetime exposure-days. The risk estimates were also elevated when the components of the lifetime exposure-days exposure metric were considered separately. Lung cancer risk, however, was not associated with carbofuran exposure when the intensity-weighted exposure-days metric was used or when non-carbofuran–exposed pesticide applicators were used as the referent.
This inconsistency between the lung cancer risk estimates when nonexposed subjects were used as the referent may be caused partly by differences between nonexposed and low-exposed groups with regard to unknown factors. Initial descriptive analyses indicated that the nonexposed and the low-exposed groups had substantial differences with regard to corn production and the total number of pesticides used. The observed differences between those with carbofuran exposure and those without carbofuran exposure raise the possibility of confounding due to other unmeasured differences between the groups. Given these differences, the low-exposed subjects may be a more appropriate reference group, although the low-exposed group may be biased as well. In addition, the inconsistency observed between the lifetime exposure-days and intensity-weighted lifetime exposure-days metrics may have occurred because the AHS intensity-weighted algorithm greatly weights dermal exposure, and this route may be less appropriate for sites where the respiratory tract is the predominant exposure route, such as the lung. Further, the intensity-weighted algorithm, as constructed, also reflects more recent use of personal protective equipment and application methods. Malignant neoplasms generally have a long latency period. To the extent that recent exposure intensity does not accurately reflect past activities, the algorithm may increase exposure misclassification rather than reduce it.
The association between lung cancer and carbofuran exposure that we observed when the low-exposed group was used as the referent is unlikely to be confounded by smoking because pack-years of smoking was not correlated with lifetime exposure-days (r = 0.03) or intensity-weighted lifetime exposure-days (r = 0.02). Furthermore, we adjusted for smoking (never, < 14 pack-years, and ≥ 14 pack-years) in the models. Even when we used pack-years as a continuous variable or a combination of smoking status (never, former, current), number of cigarettes smoked per day and number of years smoked, the risk estimates were similar with each respective model. We also stratified by smoking status and found that the association was relatively consistent between former and current smokers. There were too few lung cancer cases to determine whether carbofuran was associated with lung cancer independent of smoking. Therefore, we cannot rule out the possibility that the association between carbofuran and the risk of lung cancer is limited to smokers and former smokers.
Agricultural exposure to endotoxin from rearing livestock has been hypothesized to reduce the risk of lung cancer (Lange et al. 2003a, 2003b, 2003c; Mastrangelo et al. 1996). Although we did not formally assess exposure to endotoxin, we conducted an analysis stratifying the cohort into those who were engaged in animal husbandry and those who were not. There was no indication that animal husbandry modified the effect of carbofuran use on lung cancer risk. In addition, engaging in animal husbandry did not confound the association between carbofuran use and lung cancer because the RRs were not altered when we included a binary animal husbandry variable in the model.
Several previous investigations of NHL have observed increases in risk associated with carbofuran exposure (McDuffie et al 2001; Zheng et al. 2001). In addition, results from several animal models support the hypothesis that exposure to carbofuran could be a risk factor for NHL (Borzsonyi and Pinter 1977; Borzsonyi et al. 1976). We found little evidence to support an association between NHL and carbofuran exposure, although relatively few cases of NHL had accrued at the time of this analysis.
There is evidence that carcinogenic N-nitrosocarbofuran is formed from carbofuran and nitrites in the stomach. A priori, we expected carbofuran exposure to be associated with increased risk for stomach cancer; however, at the time these analyses were conducted, too few cases of stomach cancer had occurred in the carbofuran exposed cohorts for meaningful analysis.
There are some important limitations of this study. Although the incidence of cancers will increase as the cohort ages, currently we remain constrained by small numbers of cases for many tumor sites. For instance, only five cases of stomach cancer with exposure to carbofuran were available for analysis. The resulting statistical imprecision makes interpretation of risk estimates difficult in some instances. Another potential concern in prospective studies is loss to follow-up. However, losses to follow-up (< 2%) were few and were unlikely to substantially bias the risk estimates. In addition, pesticides are commonly used as formulations where only a percentage of the total product applied is the active ingredient. Given that pesticides are applied as complex mixtures or solutions, we cannot rule out the possibility that the combination or the “inert” ingredients are the actual carcinogenic compound(s).
The strengths of this study include the prospective design, where exposure to pesticides was determined before the onset of disease, thereby eliminating the potential for recall bias. In addition, the exposure metrics used in this study represent a major improvement in the classification of pesticide exposure over previous studies, although, undoubtedly, some exposure misclassification is present in our estimates as well.
Multicolinearity between pesticides used may be another potential limitation of this study. We assessed exposure to 50 pesticides in registered pesticide applicators who, on average, used numerous pesticides. Because it is possible that carbofuran use is related to several other pesticides, we identified the five most correlated pesticides and adjusted for them in the model. Overall, exposure to other individual pesticides was highly correlated with carbofuran exposure. The correlation coefficients ranged between 0.69 (permethrin) and 0.85 (trichlorfon). However, these pesticides did not confound the association between carbofuran and lung cancer because the risk estimates were not altered when they were removed from the model. In addition, we also adjusted for cumulative lifetime application days of all pesticides, which did not appreciably alter the risk estimates.
Overall, we examined the risk of several cancer sites in relation to the carbofuran exposure. Carbofuran is a carbamate insecticide with questionable carcinogenic properties in animals. The parent compound does not seem to be genotoxic. However, the metabolites of carbofuran may be mutagenic, and there is good evidence that nitrosated carbofuran is mutagenic. This study suggests that carbofuran may be associated with an increase in the incidence of lung cancer. Conversely, carbofuran exposure was not associated with other tumor sites investigated. The results for lung cancer are provocative but should be interpreted cautiously in light of the paucity of other studies to corroborate these findings, and a reevaluation of carbofuran in the AHS cohort once more cancer cases have accrued is warranted.
Table 1 Selected characteristics of applicators, by carbofuran exposure [no. (%)] in the AHS (1993–1997).
Characteristic Nonexposed Low exposed High exposed
Age (years)
< 40 14,023 (37.6) 1,032 (21.8) 1,739 (22.1)
40–49 10,217 (27.4) 1,470 (31.0) 2,532 (32.1)
50–59 6,802 (18.3) 1,216 (25.7) 2,056 (26.1)
≥ 60 6,210 (16.7) 1,016 (21.5) 1,557 (19.7)
Sex
Male 36,069 (96.8) 4,698 (99.2) 7,819 (99.2)
Female 1,190 (3.2) 36 (0.8) 65 (0.8)
State
Iowa 25,459 (68.3) 3,421 (72.3) 4,908 (62.3)
North Carolina 11,800 (31.7) 1,313 (27.7) 2,976 (37.7)
Applicator type
Farmer 33,341 (89.5) 4,574 (96.6) 7,355 (93.3)
Commercial 3,918 (10.5) 160 (3.4) 529 (6.7)
Smoking
Never 19,976 (54.0) 2,509 (53.2) 4,056 (51.6)
Former 10,587 (28.7) 1,577 (33.4) 2,560 (32.6)
Current 6,396 (17.3) 635 (13.5) 1,241 (15.8)
Alcohol usea
Yes 25,352 (69.0) 3,260 (69.1) 5,290 (67.8)
Education
≤ High school 21,270 (57.2) 2,503 (53.0) 4,372 (55.5)
> High school 15,897 (42.8) 2,219 (47.0) 3,504 (44.5)
Family history of cancer
Yes 13,339 (38.0) 2,099 (46.5) 3,404 (45.9)
Corn production
Yes 24,967 (67.0) 3,801 (80.0) 6,226 (79.0)
Other pesticide use
Trichlorofon 305 (0.8) 37 (0.8) 160 (2.1)
Fonofos 5,410 (14.5) 1,591 (34.4) 2,969 (38.6)
Chlorpyrifos 12,908 (34.7) 2,534 (53.8) 4,982 (63.5)
EPTC 6,112 (16.8) 1,351 (29.5) 2,417 (31.8)
Permethrinb 4,078 (11.1) 913 (19.9) 2,060 (27.1)
Person-years 240549.2 29867.9 50852.2
No. of other pesticides usedc 11.5 ± 6.6 18.3 ± 6.6 20.4 ± 7.2
Follow-up (years)c 6.5 ± 1.4 6.3 ± 1.4 6.5 ± 1.4
Smoking (pack-years)c
Former smokers 15.4 ± 20.1 15.0 ± 18.9 15.8 ± 20.2
Current smokers 22.0 ± 19.9 24.9 ± 21.3 27.0 ± 22.2
a Reported alcohol consumption within the last 12 months.
b Permethrin for use on crops.
c Mean ± SD.
Table 2 RRs for selected cancers, by lifetime exposure-days to carbofuran among AHS (1993–1997) applicators with nonexposed and low-exposed groups as referents.
Lifetime exposure daysa Cases (n) Nonexposed referent RR (95% CI) Low-exposed referent RR (95% CI)
All cancers
0 1,012 1.0
> 0–9 151 0.95 (0.80–1.14) 1.0
10–39 115 0.95 (0.78–1.15) 1.00 (0.78–1.27)
40–109 80 1.05 (0.83–1.33) 1.11 (0.83–1.49)
> 109 51 0.94 (0.70–1.26) 0.96 (0.67–1.37)
Trendb 0.79 0.94
Lymphatic–hematopoietic cancers
0 103 1.0
> 0–9 11 0.68 (0.36–1.30) 1.0
10–39 10 0.82 (0.42–1.60) 1.05 (0.44–2.51)
40–109 11 1.38 (0.72–2.65) 1.56 (0.62–3.92)
> 109 5 0.86 (0.34–2.23) 0.77 (0.23–2.57)
Trendb 0.93 0.74
Non-Hodgkin lymphoma
0 44 1.0
> 0–9 6 0.77 (0.31–1.86) 1.0
10–39 7 1.27 (0.55–2.91) 1.33 (0.44–4.02)
40–109 7 1.40 (0.59–3.30) 1.08 (0.31–3.74)
Trendb 0.40 0.94
Colon
0 80 1.0
> 0–9 10 0.88 (0.45–1.72) 1.0
10–39 9 0.99 (0.49–2.02) 1.03 (0.41–2.56)
40–109 5 0.84 (0.33–2.12) 0.77 (0.25–2.42)
> 109 6 1.34 (0.54–3.31) 1.16 (0.36–3.71)
Trendb 0.68 0.85
Lung
0 98 1.0
> 0–9 6 0.42 (0.18–0.97) 1.0
10–39 8 0.68 (0.33–1.43) 1.61 (0.55–4.69)
40–109 9 1.09 (0.54–2.22) 2.54 (0.85–7.67)
> 109 8 1.38 (0.63–2.99) 3.05 (0.94–9.87)
Trendb 0.46 0.07
Prostate
0 372 1.0
> 0–9 85 1.30 (1.01–1.66) 1.0
10–39 48 0.99 (0.73–1.35) 0.79 (0.55–1.13)
40–109 29 1.03 (0.70–1.53) 0.86 (0.55–1.36)
> 109 17 0.88 (0.53–1.47) 0.73 (0.41–1.31)
Trendb 0.70 0.34
Rate ratios adjusted for age, sex, education, family history of cancer, smoking, alcohol, year of enrollment, state of residence, and exposure to EPTC, fonofos, trichlorofon, chlorpyrifos, and permethrin.
a Years of use × days of use per year.
b p-Value for trend test.
Table 3 RRs for lung cancer by carbofuran intensity-weighted lifetime exposure days, exposure frequency (days per year), and exposure duration (years of use) in the AHS (1993–1997).
Cases (n) Full model RR (95% CI)a Reduced model RR (95% CI)b
Intensity-weighted lifetime exposure daysc
> 0–63 6 1.0 1.0
64–196 11 2.11 (0.77–5.78) 2.42 (0.89–6.54)
197–487 5 1.19 (0.35–4.03) 1.58 (0.48–5.19)
> 487 9 2.10 (0.69–6.39) 3.40 (1.21–9.58)
Trendd 0.40 0.23
Days of use/year
< 5 9 1.0 1.0
5–9 9 1.53 (0.59–3.95) 1.67 (0.66–4.21)
10–19 9 2.98 (1.07–8.33) 3.84 (1.52–9.71)
≥ 20 4 4.13 (1.13–15.08) 5.63 (1.73–18.35)
Trendd < 0.01 < 0.01
Years of use
≤ 5 16 1.0 1.0
6–10 6 0.80 (0.30–2.10) 1.00 (0.39–2.55)
> 10 9 1.95 (0.80–4.77) 3.00 (1.32–6.81)
Trendd 0.02 < 0.01
a Rate ratios adjusted for age, sex, education, family history of cancer, smoking, alcohol, year of enrollment, state of residence, and exposure to EPTC, fonofos, trichlorofon, chlorpyrifos, and permethrin.
b Rate ratios adjusted for age, smoking (never, < 14 pack-years, ≥ 14 pack-years), family history of cancer, and exposure to trichlorofon and permethrin.
c Years of use × days of use per year × intensity score.
d p-Value for trend test.
Table 4 RRs for lung cancer and lifetime exposure-days to carbofuran, by smoking status in the AHS (1993–1997).
Former smokers
Current smokers
Lifetime exposure daysa Cases (n) RR (95% CI) Cases (n) RR (95% CI)
> 0–9 3 1.0 3 1.0
10–39 3 1.87 (0.42–8.37) 4 1.75 (0.39–7.90)
> 39 11 4.88 (1.36–17.52) 6 2.49 (0.62–10.00)
Trendb < 0.01 0.23
p for interaction 0.36
Rate ratios adjusted for age, smoking (never, < 14 pack-years, ≥ 14 pack-years), family history of cancer, exposure to trichlorofon and permethrin.
a Years of use × days of use per year.
b p-Value for trend test.
==== Refs
References
Alavanja MC Sandler DP McMaster SB Zahm SH McDonnell CJ Lynch CF 1996 The Agricultural Health Study Environ Health Perspect 104 362 369 8732939
Barnett JB Spyker-Cranmer JM Avery DL Hoberman AM 1980 Immunocompetence over the lifespan of mice exposed in utero to carbofuran or diazinon. I. Changes in serum immunoglobulin concentrations J Environ Pathol Toxicol 4 5–6 53 63 7217860
Blair A Tarone R Sandler D Lynch CF Rowland A Wintersteen W 2002 Reliability of reporting on lifestyle and agricultural factors by a sample of participants in the Agricultural Health Study from Iowa Epidemiology 13 1 94 99 11805592
Borzsonyi M Pinter A 1977 The carcinogenicity of N -nitroso compounds formed endogenously in mice from benzimidazole carbamate pesticides Neoplasma 24 1 119 122 576495
Borzsonyi M Pinter A Surjan A Farkas I 1976 Transplacental induction of lymphomas in Swiss mice by carbendazim and sodium nitrite Int J Cancer 17 6 742 747 988851
Breslow NE Day NE 1987. Statistical Methods in Cancer Research II–The Design and Analysis of Cohort Studies. Lyon:International Agency for Research on Cancer.
Brownson RC Alavanja MC Chang JC 1993 Occupational risk factors for lung cancer among nonsmoking women: a case-control study in Missouri (United States) Cancer Causes Control 4 5 449 454 8218877
Chauhan LK Pant N Gupta SK Srivastava SP 2000 Induction of chromosome aberrations, micronucleus formation and sperm abnormalities in mouse following carbofuran exposure Mutat Res 465 1–2 123 129 10708977
Dosemeci M Alavanja MC Rowland AS Mage D Zahm SH Rothman N 2002 A quantitative approach for estimating exposure to pesticides in the Agricultural Health Study Ann Occup Hyg 46 2 245 260 12074034
Fiore MC Anderson HA Hong R Golubjatnikov R Seiser JE Nordstrom D 1986 Chronic exposure to aldicarb-contaminated groundwater and human immune function Environ Res 41 2 633 645 3490967
Gupta RC 1994 Carbofuran toxicity J Toxicol Environ Health 43 4 383 418 7990167
Hosmer DW Lemeshow S 1989. Applied Logistic Regression. New York:John Wiley & Sons.
Hour TC Chen L Lin JK 1998 Comparative investigation on the mutagenicities of organophosphate, phthalimide, pyrethroid and carbamate insecticides by the Ames and lactam tests Mutagenesis 13 2 157 166 9568589
Lange JH Mastrangelo G Fedeli U Fadda E Rylander R Lee E 2003a Endotoxin exposure and lung cancer mortality by type of farming: is there a hidden dose-response relationship? Ann Agric Environ Med 10 2 229 232 14677917
Lange JH Mastrangelo G Fedeli U Rylander R Christiani DC 2003b There is an alternative reason for lower-than-expected rates of lung cancer in farmers Arch Environ Health 58 5 316 317 14738278
Lange JH Rylander R Fedeli U Mastrangelo G 2003c Extension of the “hygiene hypothesis” to the association of occupational endotoxin exposure with lower lung cancer risk J Allergy Clin Immunol 112 1 219 220 12847509
Maroni M Colosio C Ferioli A Fait A 2000 Biological monitoring of pesticide exposure: a review. Introduction Toxicology 143 1 5 8
Mastrangelo G Marzia V Marcer G 1996 Reduced lung cancer mortality in dairy farmers: is endotoxin exposure the key factor? Am J Ind Med 30 5 601 609 8909609
McDuffie HH Klaassen DJ Dosman JA 1990 Is pesticide use related to the risk of primary lung cancer in Saskatchewan? J Occup Med 32 10 996 1002 2262830
McDuffie HH Pahwa P McLaughlin JR Spinelli JJ Fincham S Dosman JA 2001 Non-Hodgkin’s lymphoma and specific pesticide exposures in men: cross-Canada study of pesticides and health Cancer Epidemiol Biomarkers Prev 10 11 1155 1163 11700263
Moriya M Ohta T Watanabe K Miyazawa T Kato K Shirasu Y 1983 Further mutagenicity studies on pesticides in bacterial reversion assay systems Mutat Res 116 3–4 185 216 6339892
Percy C Van Holten V Muir C 1990. International Classification of Diseases for Oncology. Geneva:World Health Organization.
Pesatori AC Sontag JM Lubin JH Consonni D Blair A 1994 Cohort mortality and nested case-control study of lung cancer among structural pest control workers in Florida (United States) Cancer Causes Control 5 4 310 318 8080942
Street JC Sharma RP 1975 Alteration of induced cellular and humoral immune responses by pesticides and chemicals of environmental concern: quantitative studies of immunosuppression by DDT, aroclor 1254, carbaryl, carbofuran, and methylparathion Toxicol Appl Pharmacol 32 3 587 602 50651
Thelin GP Gianessi LP 2000. Method for estimating pesticide use for county areas of the conterminous United States. Sacramento, CA:U.S. Geological Survey.
Tobin JS 1970 Carbofuran: a new carbamate insecticide J Occup Med 12 1 16 19 5410616
Wesseling C Antich D Hogstedt C Rodriguez AC Ahlbom A 1999 Geographical differences of cancer incidence in Costa Rica in relation to environmental and occupational pesticide exposure Int J Epidemiol 28 3 365 374 10405835
Whyatt RM Barr DB Camann DE Kinney PL Barr JR Andrews HF 2003 Contemporary-use pesticides in personal air samples during pregnancy and blood samples at delivery among urban minority mothers and newborns Environ Health Perspect 111 749 756 12727605
Yoon JY Oh SH Yoo SM Lee SJ Lee HS Choi SJ 2001 N -nitrosocarbofuran, but not carbofuran, induces apoptosis and cell cycle arrest in CHL cells Toxicology 169 2 153 161 11718956
Zheng T Zahm SH Cantor KP Weisenburger DD Zhang Y Blair A 2001 Agricultural exposure to carbamate pesticides and risk of non-Hodgkin lymphoma J Occup Environ Med 43 7 641 649 11464396
|
15743716
|
PMC1253753
|
CC0
|
2021-01-04 23:40:57
|
no
|
Environ Health Perspect. 2005 Mar 2; 113(3):285-289
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7451
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7300ehp0113-00029015743717ResearchArticlesAssociation of Ambient Air Pollution with Respiratory Hospitalization in a Government-Designated “Area of Concern”: The Case of Windsor, Ontario Luginaah Isaac N. 1Fung Karen Y. 2Gorey Kevin M. 3Webster Greg 4Wills Chris 21Department of Geography, University of Western Ontario, London, Ontario, Canada2Department of Mathematics and Statistics, and3School of Social Work, University of Windsor, Windsor, Ontario, Canada4Canadian Institute for Health Information, Toronto, Ontario, CanadaAddress correspondence to I.N. Luginaah, Department of Geography, Room 1409 Social Science Centre, University of Western Ontario, London, Ontario, N6A 5C2 Canada. Telephone: (519) 661-2111, Ext. 86944. Fax: (519) 661-3750. E-mail:
[email protected] research was supported in part by a Natural Sciences and Engineering Research Council of Canada operating grant to K.Y.F., a Canadian Institutes of Health Research (CIHR) investigator award to K.M.G., and an associated CIHR partnership appointment to I.N.L.
The authors declare they have no competing financial interests.
3 2005 14 12 2004 113 3 290 296 28 5 2004 14 12 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. This study is part of a larger research program to examine the relationship between ambient air quality and health in Windsor, Ontario, Canada. We assessed the association between air pollution and daily respiratory hospitalization for different age and sex groups from 1995 to 2000. The pollutants included were nitrogen dioxide, sulfur dioxide, carbon monoxide, ozone, particulate matter ≤10 μm in diameter (PM10), coefficient of haze (COH), and total reduced sulfur (TRS). We calculated relative risk (RR) estimates using both time-series and case-crossover methods after controlling for appropriate confounders (temperature, humidity, and change in barometric pressure). The results of both analyses were consistent. We found associations between NO2, SO2, CO, COH, or PM10 and daily hospital admission of respiratory diseases especially among females. For females 0–14 years of age, there was 1-day delayed effect of NO2 (RR = 1.19, case-crossover method), a current-day SO2 (RR = 1.11, time series), and current-day and 1- and 2-day delayed effects for CO by case crossover (RR = 1.15, 1.19, 1.22, respectively). Time-series analysis showed that 1-day delayed effect of PM10 on respiratory admissions of adult males (15–64 years of age), with an RR of 1.18. COH had significant effects on female respiratory hospitalization, especially for 2-day delayed effects on adult females, with RRs of 1.15 and 1.29 using time-series and case-crossover analysis, respectively. There were no significant associations between O3 and TRS with respiratory admissions. These findings provide policy makers with current risks estimates of respiratory hospitalization as a result of poor ambient air quality in a government designated “area of concern.”
air pollutionarea of concernOntariorespiratory diseaseWindsor
==== Body
Poor environmental quality has been an important public health issue for some time now. Research using large-scale data sets has shown a fairly consistent relationship between air pollutant levels and respiratory diseases in a variety of communities in the industrialized world (e.g., Atkinson et al. 1999; Dockery et al. 1993; Lin et al. 2002, 2004; Pope et al. 1995; Schwartz 1994).
In Canada, several reports have been published linking air pollution to adverse population health in cities based on data that were collected in the 1980s and early 1990s (e.g., Burnett et al. 1994, 1999; Goldberg et al. 2001). Windsor, Ontario, with a population of 208,402, is one of the cities that has been identified as heavily polluted (Burnett et al. 1998). The city is one of the most industrialized cities in Canada, with major industries including three automobile assembly plants, an engine plant, a foundry, and a scrap metal recycling plant. In addition, there is the outstanding problem of transboundary air and water pollution from the U.S. states of Ohio, Illinois, and Michigan. The city is immediately downwind of major steel mills with associated coking operations in Detroit, Michigan, the wastewater treatment plant of Detroit and associated sludge incineration facilities, and a major power plant that until recently was coal fired. Consequently, Windsor and surrounding communities have been identified as an “area of concern” and in need of further health investigation (Health Canada 2000).
Furthermore, in line with Windsor’s ranking as a city with a high level of pollution compared with other Canadian cities (Burnett et al. 1998), a recent community-health profile by Gilbertson and Brophy (2001) indicated mortality and morbidity rates from various cancers, circulatory, and respiratory disorders were higher in Windsor than in the rest of the province of Ontario. This work aroused a lot of public sentiments, and several calls were made for further investigation into the “alarming trends” of morbidity and mortality. To respond to the call for an in-depth analysis of the health of Windsorites, we assessed the association between daily ambient air quality and cardiovascular disease hospitalization (Fung et al. 2005). We reported, among other things, that short-term effects of sulfur dioxide were associated significantly with daily cardiac hospital admissions for people ≥65 years of age. The main focus of this article is on respiratory diseases. We used the most recent hospitalization data available from 1995 through 2000 to quantify the association between ambient air pollution and respiratory hospitalization, with temperature, humidity, and change in barometric pressure as covariates. We are especially interested in investigating whether there is an age or sex difference in respiratory admissions. This research will provide policy makers as well as the public with estimates of current risks of respiratory hospitalization as a result of poor ambient air quality.
Materials and Methods
Data acquisition.
The study population consisted of all people who were admitted into one of the four hospitals in Windsor with primary diagnoses of respiratory disease [International Classification of Diseases, 9th Revision (ICD-9) codes 460–519 (World Health Organization [WHO] 1975)] from 1 April 1995 through 31 December 2000 and were registered with the Ontario Health Insurance Plan (OHIP). Daily hospital admission records for OHIP patients were obtained from the Canadian Institute for Health Information (CIHI) Discharge Abstract Database (CIHI 2002). The data included date of respiratory admission, age, and sex. Our analysis focused on finding the association between air pollution and daily respiratory hospitalizations. It was not able to address events that happened after admission.
The hourly air pollution data from the four fixed monitoring stations in Windsor were obtained from the Ontario Ministry of the Environment (MOE 2000). To capture the effects of exposure, the highest reading for each day was used for the analysis (see Chock et al. 2000). The pollutants were nitrogen dioxide, SO2, carbon monoxide, ozone, inhalable particles [particulate matter ≤10 μm in diameter (PM10)], coefficient of haze (COH), and total reduced sulfur compounds (TRS). We included COH in our analysis following the recommendation by Goldberg et al. (2001). According to Goldberg et al. (2001), despite the infrequent use of the COH in time-series analyses, it is a reliable measure of the concentration of ambient carbon particles (generally from internal combustion), with only limited contributions from other pollutants, such as sulfates, nitrates, or particle mass. Respirable particles (PM ≤2.5 μm in diameter) data were available only from 1998 through 2001 and were not included in our analysis. Daily weather data including maximum and minimum temperature, humidity, and change in maximum or minimum barometric pressure from the previous day were obtained from the Environment Canada (2002).
Statistical analysis.
First, we linked together > 2,000 days of records from several databases comprising pollutants, temperature, humidity and pressure, and number of respiratory admissions. Data from CIHI were given to us in a ready-to-use format. Because we used the maximum of daily hourly pollutant values from four stations, there were not many missing values (< 1%). If missing values were sporadic, we replaced the missing values by the mean of nearby points (3 days before and 3 days after). If missing values occurred for a series of days, we substituted the linear trend value for those points using other pollutants and covariates as predictors. In very few cases, if the highest hourly maximum was deemed extreme, it was replaced by the next highest value.
To relate short-term effects of air pollution on the number of respiratory hospitalizations, we used two different statistical techniques: time-series and case crossover methods. Both procedures have been used extensively to analyze this type of data (Burnett et al. 1994; Goldberg et al. 2001; Lee and Schwartz 1999; Lin et al. 2002, 2004; Neas et al. 1999). Detailed formulas are available in the literature.
Since 2002, significant developments in these methodologies have taken place. For time series, the usual smoothing method that has been used for producing residuals with no seasonality was locally weighted regression smoothers (LOESS) within the generalized additive models (GAMs) (Hastie and Tibshirani 1990). It was later discovered (Dominici et al. 2002; Ramsay et al. 2003; Samet et al. 2003) that the default settings of the GAM function in the software package S-Plus (Insightful Corp. 2001) do not assure convergence of its iterative estimation procedure and can provide biased estimates of regression coefficients and standard errors, especially when the concurvity is high. Dominici et al. (2002) reanalyzed the National Morbidity, Mortality, and Air Pollution Study data with the default implementation and found that the estimates were biased upward (i.e., higher than they should be). Since then, either the default option was set to a smaller number, such as 10−8 (S-Plus has already done that in their new release), or another smoother called natural splines has been used in the general linear model function.
For case-crossover analysis, Navidi modified his bidirectional design (Navidi 1998) and proposed the semisymmetric bidirectional design (Navidi and Weinhandl 2002). Fung et al. (2003) compared all these methods using simulations, and we used what was recommended in that report—natural splines (ns) in time series and bidirectional case crossover.
For the time-series analysis in this article, daily concentrations of each pollutant and covariates were related to the natural logarithm of hospital admissions, y, by the model
where E(y) is the mean of y and DOW is the day-of-the-week effect, which takes on values 1–7. For each age and sex group, we first found the degrees of freedom (df) for ns(time) such that after fitting the smoothed time effect and DOW, we had a time series of residuals that is as close to white noise as possible, as determined by Bartlett’s test (Priestly 1981). We then extended the model by incorporating the smoothed weather variables. Different combinations of smoothed weather variables (minimum or maximum temperature, humidity, and change in barometric pressure) were examined, and the combination that yielded the lowest Akaike Information Criterion (Akaike 1973) was chosen. Last, we added the air pollutant into the model. Regression models with current-day pollution value (lag 1), average of current day and yesterday (lag 2), and average of current and 2 previous days (lag 3) were examined. Relative risk (RR) was calculated as exp(β̂× IQR), where β̂ is the estimated regression coefficient for pollutant in the above log-linear model and IQR is the interquartile range (75th percentile to 25th percentile) of the pollutant. This implies that the percentage change in the mean number of daily hospitalizations is (RR − 1) × 100% for an increase of IQR unit of pollutant. Ninety-five percent confidence intervals (CIs) of the RRs were obtained under the assumption that the estimated regression coefficients were normally distributed.
The case-crossover design of Maclure (1991) has recently been suggested as an alternative to time-series analysis. This design is essentially a case–control design in which cases serve as their own controls. Risk estimates are based on within subject comparisons of exposures at failure times with exposure at times both before and after failure, using matched case–control methods. This procedure is used to investigate whether a recent exposure has triggered the occurrence of a particular adverse health outcome and is particularly useful for estimating effects that are transient or acute. Because each subject serves as its own control, the case-crossover approach controls for effects of stable subject specific covariates such as sex and race, and for potential time varying confounders such as seasonal effects or personal habits such as smoking. In this study, we used the bidirectional design (Navidi 1998), which can control for different patterns of time trends in exposures and outcomes and gives the least biased estimate compared with the pre- or post-unidirectional design (Fung et al. 2003). We selected an interval of 2 weeks between case and control periods to minimize autocorrelation between case and control exposures and to control for seasonal effects. Conditional logistic regression analysis using the same covariates as time series were performed via the Cox proportional hazards model. Maximum likelihood estimates of the parameters were obtained by choosing the “exact” option in S-Plus. Details of this model can be found in Navidi (1998) or Fung et al. (2003).
Results
A total of 4,214 overall admissions due to respiratory diseases occurred in the study period. Table 1 gives the summary statistics of daily respiratory admissions for the three age groups (0–14, 15–64, ≥65 years). Overall, there seem to be more male hospitalizations than female in the early years, but the opposite is true for later years. Summary statistics of weather variables and daily high concentrations of all the pollutants are also provided in Table 1. An analysis of the Windsor yearly air pollution data for the period 1990–2000 showed an overall decreasing trend in ambient air pollutants (NO2, SO2, CO, COH), likely due to regulatory measures implemented by the government in the preceding 10 years (MOE 2000). There was an increasing trend in O3 and TRS, whereas PM10 did not change much. Based on the air quality index, there were 165 days of poor air quality, 583 days of moderate air quality, and 1,352 days of good air quality during the entire study period.
Table 2 gives the correlation coefficients for the air pollutants and weather variables. Most of the pollutants are positively correlated with each other, except SO2 and O3 (r = −0.02), and TRS and O3 (r = −0.01). Maximum temperature and minimum humidity were highly correlated with O3.
Tables 3 and 4 give the time-series and case-crossover RR estimates by age and sex groups. 95% CIs were also given for the current day (lag 1), lag 2, and lag 3 of the pollutants that were used in the analyses.
The time-series analysis showed elevated effects of NO2 on the respiratory admissions of females overall and the 0–14 and 15–64 age groups (Table 3). The results of the case-crossover analysis somewhat concurred with those of the time series. We found NO2 lag 2 to be significantly associated with respiratory hospitalization of females 0–14 years age, with an RR of 1.19 (95% CI, 1.002–1.411) (Table 4). Although the effects of NO2 on omen in the 15–64 and ≥ 65 age groups were all elevated, none of these were significant. There were no significant associations between NO2 and male hospitalization in any of the age groups (Tables 3 and 4).
Time-series results showed a significant current-day effect of SO2 on the admission of females 0–14 years of age, with an RR of 1.11(95% CI, 1.011–1.221). The case-crossover method also showed an RR of 1.12, and it is almost significant. Other than this, there were no significant association between SO2 and hospitalization for respiratory diseases in females and males using both methods of analysis. However, the effects of SO2 on female respiratory admissions were consistently elevated in all age groups.
Although the time-series analysis showed elevated effects of CO on respiratory hospitalization of females, only CO lag 2 was significantly associated with the hospitalization of females 0–14 years of age (RR = 1.07; 95% CI, 1.001–1.139). The case-crossover results showed that CO had both immediate and delayed effects on respiratory admissions for females 0–14 years of age, with RRs of 1.15 (95% CI, 1.006–1.307), 1.19 (95% CI, 1.020–1.379), and 1.22 (95% CI, 1.022–1.459) for lags 1, 2, and 3, respectively. The effects of CO on the respiratory admissions of females in the 15–64 and ≥ 65 age groups were elevated, but none were significant. There were no significant associations between CO and respiratory admissions in any of the male age groups.
We also found no significant association between O3 and respiratory admissions on either females or males, although the effects were elevated mostly among the young and elderly age groups in the case-crossover analysis.
The time-series results showed that PM10 lag 2 is significantly associated with respiratory hospitalization for males 15–64 years of age, with an RR of 1.18 (95% CI, 1.036–1.332). In the case-crossover analysis, the effects of PM10 on respiratory admissions were mostly elevated, but not significant, in all the groups except for males 0–14 years of age.
COH (lag 3) was significantly associated with the admission of all females (RR = 1.07; 95% CI, 1.004–1.135) and for females 15–64 years of age (RR = 1.15; 95% CI, 1.020–1.296) in the time-series analysis. When all the age groups were combined, the case-crossover analysis also showed that COH had an immediate effect on the admission of women for respiratory disease, with an RR of 1.09 (95% CI, 1.037–1.176). COH lags 2 and 3 were also significantly associated with respiratory admissions for females 15–64 years of age, with RRs of 1.20 (95% CI, 1.003–1.426) and 1.29 (95% CI, 1.051–1.582) respectively. None of the effects of COH on the hospitalization of females 0–14 and ≥ 65 years of age for respiratory disease was significant. Furthermore, none of the male groups showed a significant association between COH and respiratory admissions.
Using both methods, we found no significant associations between TRS and respiratory admissions for any group, but the case-crossover results suggested there might be a delayed effect of TRS on the younger age groups.
Taken together, both the time-series and case-crossover analyses show that young (0–14 years) and adult (15–64 years) females were more likely to be admitted for air-pollution–induced respiratory diseases than were males.
Discussion
Although ambient pollution levels (NO2, SO2, CO, COH) in Windsor “area of concern” decreased during the study period, we still see existing levels of some pollutants that had significant effects on respiratory hospitalization. Consistent with Lin et al. (2002), we saw some differences in results between time-series and case-crossover analyses. CIs on RR estimates from the bidirectional case-crossover analysis were slightly wider than those from time series, implying lower statistical power for the bidirectional case-crossover design, as documented previously (Bateson and Schwartz 1999; Fung et al. 2003). Because of the sex dimension we introduced into our analysis, together with differences in analytical approaches, control variables, populations studied, exposure variable averaging times, and cut points, comparison of our findings with other studies is not entirely straightforward (e.g., Burnett et al. 1997). Despite the fact that no comparable RRs can be given, our findings are consistent with those of existing studies qualitatively.
Although NO2 has been known to increase susceptibility to respiratory infections (Speizer et al. 1980), results of different studies that examined the link between NO2 and respiratory outcomes continued to vary. For instance, Atkinson et al. (1999), working in London, reported no significant associations between NO2 and respiratory admissions overall or within any of three age groups (0–14, 15–64, and ≥65 years). As part of the Air Pollution and Health: A European Approach (APHEA) project, Spix et al. (1998) reported no significant association between NO2 and respiratory admissions for the 15–64 and ≥65 year age groups. In Paris, France (Dab et al. 1996), and in Birmingham, England (Wordley et al. 1997), a lack of associations between NO2 and hospital admissions for respiratory diseases was observed. On the other hand, Wong et al. (1999) reported significant associations between NO2 and respiratory admissions for 0–4, 5–64 and ≥65 year age groups in Hong Kong. Similarly, in London, England, Ponce de Leon et al. (1996) found a significant association between summer exposure to NO2 lag 2 and respiratory admissions for children 0–14 years of age. In the present analysis, we found a significant association between NO2 lag 2 and respiratory admissions for females 0–14 years of age, but not for any of the other female or male groups.
The effect of SO2 on respiratory hospitalization varies considerably, especially at low levels of exposure. For example, Spix et al. (1998), Sunyer et al. (2003), and Wordley et al. (1997) reported no consistent association between SO2 and respiratory admissions. However, studies in Milan, Italy (Vigotti et al. 1996), in Paris, France (Dab et al. 1996), and in London, England (Walters et al. 1994), found SO2 levels influenced hospital admissions for all respiratory diseases. Atkinson et al. (1999) reported a strong association between SO2 and respiratory admissions among 0- to 14-year-olds. Wong et al. (1999) observed significant short-term effects between SO2 and respiratory admissions in the ≥ 65 age group but not among younger age groups. Furthermore, Ponce de Leon et al. (1996) found a positive association between SO2 lag 1 (in cool season) with respiratory admissions for adults 15–64 years of age; there was no significant association in either the 0–14 or ≥65 age groups. Bates and Sizto (1987) found an association between SO2 (2-day lag) and respiratory admissions in southern Ontario. Consistent with these findings, the time-series analysis in this study showed a significant association between SO2 (lag 1) and respiratory admissions for females 0–14 years of age. However, the significance of SO2 in all other age groups may be minimal because ambient concentrations of SO2 in Ontario have decreased by more than 86% over recent decades (MOE 2000). Nonetheless, there is a need for continuous attention because of the number of people exposed and the existence of high-risk groups.
According to Burnett et al. (1999), because there is a strong correlation between CO and other pollutants regularly used in air pollution studies, it is usually difficult to examine the effects of CO independent of all other pollutants. It is therefore not surprising that the literature on the effects of CO on respiratory illness has also been mixed at best. For instance, Atkinson et al. (1999) found no association between CO and respiratory admissions either overall or by age group. However, in Korea, Cho et al. (2000) after controlling for seasonal and temperature effects, found an association between CO and hospital admissions for respiratory disease with RRs ranging from 1.21 to 3.55, depending on whether the area is rural or urban. In this study, we found that females 0–14 years of age were more likely to be admitted as a result of their exposure to CO in both the time-series and case-crossover models, although only CO lag 2 was significant in the former case. Although the effects of CO on respiratory admissions of women ≥ 65 years of age were elevated for all lags, they were not statistically significant. It is important to note that significant reduction in CO had been achieved in the preceding 10 years in Windsor (mean = 1.0 ppm in 1991 to 0.3 in 2000) because of more stringent regulatory effort in air quality (MOE 2000).
There are contrasting reports on the effect of O3 on respiratory admissions. For instance, studies in The Netherlands (Schouten et al. 1996), in London (Atkinson et al. 1999) and in Paris (Dab et al. 1996) found no significant associations between O3 and respiratory hospitalization. However, Burnett et al. (1997) reported an association between O3 and respiratory admissions in several Canadian cities, using data from 1981 through 1991. In Hong Kong, Wong et al. (1999) reported that O3 had a significant effect on respiratory admissions with an RR of 1.022. Ponce de Leon et al. (1996) found an association between O3 and daily respiratory admissions for the 15–64 and ≥ 65 age groups but not for the 0–14 age group. Spix et al. (1998) observed a consistent association between O3 and respiratory admissions in five European cities, and the effects were stronger in the ≥65 age group. In our analysis, we found elevated risk in the 0–14 and ≥65 age groups; however, none of these RRs was statistically significant.
Several studies have reported positive and significant effects of PM10 on respiratory admissions. In Toronto, Canada (Burnett et al. 1999), and in Hong Kong (Wong et al. 1999), PM10 has been found to be associated with respiratory admissions. A study by Schwartz (1996) in Spokane, Washington (USA), found PM10 to be significantly associated with respiratory hospitalization of women ≥65 years of age. The association between PM10 and respiratory admission was demonstrated further by Atkinson et al. (1999), who found significant effects in all age groups (0–14, 15–64, and ≥ 65), although the effect was strongest in the 0–14 age group. In the present study, PM10 (lag 2) was significantly associated with respiratory admission of males 15–64 years of age. The elevated effects of PM10 found in this study for all female age groups and for adult and elderly males are in line with the notion that PM10 influences inflammatory mechanisms in respiratory organs (Hitzfeld et al. 1997).
Compared with other pollutants, the effect of COH on respiratory admissions has not been frequently examined (Goldberg et al. 2001). However, one study found that COH was the strongest predictor of hospitalizations for respiratory diseases among particle-related pollutants examined in both single- and multiple-pollutant regression models (Burnett et al. 1997). Consistent with this later report, we found COH to be significantly related to female respiratory hospitalization, and more so among adult females.
Overall, our results show that there were more elevated effects with female respiratory hospitalization in relation to ambient air pollution compared with males. The reasons for these differences are unclear. However, several authors have suggested possible explanations for existing sex differences observed in respiratory health. According to Redline and Gold (1994), sex differences in respiratory diseases relate to differences in hormonal status, potentially influencing airway inflammation and smooth muscle and vascular functions. Differences may also be related to differences in the rates of lung growth and decline, and the relative changes in airway and parenchymal size, in females and males. For instance, the deposition of pollution particles in the lung has been shown to vary by sex, with greater lung deposition fractions of 1-μm particles in females compared with males (Kim and Hu 1998; Kohlhaufl et al. 1999), leading to a more female susceptibility to respiratory diseases.
Additionally, despite significant social progress, industrial and domestic jobs continue to be different for men and women. In particular, women as a group are poorer than men and may experience different psychosocial stresses. Also, women usually perform the bulk of child care, cooking, dusting, and vacuum cleaning. It is therefore possible that women experience greater exposures to viral infections, nitrogen oxides, household irritants, and aeroallergens (Redline and Gold, 1994). Moreover, some studies have shown that women are more sensitive than men to the effect of smoking, with the effects of smoking on lung function greater in women than in men (e.g., Chen et al. 1999; Prescott et al. 1997; Xu et al. 1994). The increased probability of female hospitalization for respiratory disease probably reflects the increase in smoking among women, relative to men, in the last half-century (Canadian Council for Tobacco Control 2002).
Sex differences in respiratory morbidity, may also reflect differences in the management of morbidity. For instance, Goodman et al. (1994) suggested that increased asthma morbidity in women may relate to their less adequate medical management. The complex social and biologic differences in women and men, underscore the need for more work to aid in our understanding of the bases for a female susceptibility to respiratory diseases.
Limitations of this study are the same as in studies of this kind. They include the adequacy of covariate control and the impact of measurement error in the exposure and outcome variables. However, for most of the risk factors such as the presence of chronic conditions and cigarette smoking, there is no reason to believe that the individual risk factors are correlated with the daily changes in air pollution; hence, they are not likely to be confounders in this study. Furthermore, the limitations of using fixed monitors to represent the entire population in environmental exposure studies have been frequently discussed (Goldberg et al. 2001). Hence, these results must be interpreted with caution. Nevertheless, the findings still have implications for public health policy.
Conclusion
This study has found associations between ambient air pollution (NO2, SO2, CO, COH, and PM10) and daily hospital admission of respiratory diseases especially among females in the Windsor “area of concern.” The findings are generally consistent with other studies. Even though the risks of respiratory disease due to ambient air pollution in the general population may seem low, it is reasonable to assume that the risks are much higher among susceptible groups, and our findings here support this hypothesis especially for females in the 0–14 age group. Hence, we recommend that in addressing the intense public concern about the health impacts of environmental quality in this “area of concern” must not only involve stricter guidelines (which will be beneficial) but also include environmental risk communication, aimed at improving public perception of risk due to poor air quality. In addition, the events of 11 September 2001 brought renewed concerns about the effects of air pollution in the Windsor area. There have been increasing delays resulting in long lines of trucks at the border crossing points. The idling trucks are spewing toxic pollutants from their archaic exhaust systems into the air. With Windsor located on the downwind side of Detroit, which is a major source of industrial pollutants, the combined effect of these factors is that the improvements that have been suggested here may no longer be possible to attain. We recommend that more frequent studies examining the link between ambient air quality and health effects be conducted to monitor any changes that may be taking place.
Table 1 Summary statistics of the daily high concentrations of air pollutants and respiratory admissions, 1 April 1995 through 31 December 2000.
Variable (unit) Mean ± SD Minimum Maximum (AAQCa)
0–14 years
Female (n = 626) 0.33 ± 0.60 0 4
Male (n = 976) 0.52 ± 0.79 0 6
15–64 years
Female (n = 573) 0.30 ± 0.56 0 4
Male (n = 310) 0.16 ± 0.41 0 3
≥ 65 years
Female (n = 938) 0.50 ± 0.75 0 5
Male (n = 791) 0.42 ± 0.66 0 5
Total (n = 4,214) 2.23 ± 1.76 0 14
SO2 (ppb) 27.5 ± 16.5 0 129 (100/24 hr)
NO2 (ppb) 38.9 ± 12.3 0 117 (100/24 hr)
O3 (ppb) 39.3 ± 21.4 1 129 (80/hr)
CO (ppm) 1.3 ± 1.0 0 11.82 (3/hr)
TRS (ppb) 8.1 ± 10.6 0 132 (27/hr)
PM10 (μg/m3) 50.6 ± 35.5 9 349 (30/24 hr)
COH 0.6 ± 0.4 0 3.6 (1.0/24 hr)
Maximum temperature (°C) 14.2 ± 11.2 −15.8 35.7
Minimum temperature (°C) 5.3 ± 9.8 −21.4 25.6
Maximum humidity 86.1 ± 9.2 50.0 100.0
Minimum humidity 53.4 ± 15.0 17.0 98.0
Maxp 0.00 ± 0.54 −2.36 2.06
Minp 0.00 ± 0.70 −3.42 3.12
Abbreviations: Maxp, change in maximum barometric pressure from the previous day; Minp, change in minimum barometric pressure from the previous day.
a Ambient air quality criteria (MOE 2000).
Table 2 Correlation coefficients between air pollutants and weather variables.
NO2 SO2 CO O3 COH PM10 TRS Mint Minh Maxt Maxh Maxp Minp
PM10
NO2 1.00
SO2 0.22 1.00
CO 0.38 0.16 1.00
O3 0.26 −0.02 0.10 1.00
COH 0.49 0.14 0.31 0.23 1.00
PM10 0.33 0.22 0.21 0.33 0.39
TRS 0.06 0.13 0.11 −0.01 0.15 0.05 1.00
Mint −0.22 −0.12 −0.06 −0.45 −0.16 −0.26 −0.10 1.00
Minh 0.06 −0.06 0.02 0.67 0.21 0.25 0.08 −0.19 1.00
Maxt 0.15 −0.01 0.08 0.74 0.28 0.34 0.06 0.95 −0.34 1.00
Maxh −0.09 −0.08 0.03 −0.20 0.03 −0.09 0.09 −0.02 0.63 −0.07 1.00
Maxp −0.06 −0.03 −0.08 −0.04 −0.05 −0.14 −0.02 −0.13 −0.18 −0.14 −0.23 1.00
Minp −0.03 −0.01 −0.04 −0.04 −0.05 −0.13 0.04 −0.13 −0.18 −0.15 −0.27 0.67 1.00
Abbreviations: Maxh, maximum humidity; Maxp, change in maximum barometric pressure from the previous day; Maxt, maximum temperature; Minh, minimum humidity; Minp, change in minimum barometric pressure from the previous day; Mint, minimum temperature.
Table 3 RRs (95% CIs) for single-pollutant models using time-series method for an increase in IQR.a
All age groups
0–14 years
15–64 years
≥65 years
Pollutants (IQR) Female Male Female Male Female Male Female Male
NO2 (16 ppb)
Lag 1 1.035 (0.971–1.104) 0.944 (0.886–1.006) 1.114 (0.994–1.248) 0.955 (0.866–1.054) 1.013 (0.893–1.150) 0.942 (0.790–1.122) 1.020 (0.930–1.1198) 0.9196 (0.832–1.016)
Lag 2 1.027 (0.967–1.094) 0.958 (0.900–1.021) 1.107 (0.990–1.238) 0.918 (0.833–1.012) 1.044 (0.918–1.187) 0.992 (0.833–1.182) 0.987 (0.881–1.106) 0.9620 (0.854–1.084)
Lag 3 1.036 (0.970–1.107) 0.970 (0.909–1.036) 1.108 (0.987–1.245) 0.927 (0.838–1.025) 1.121 (0.978–1.285) 1.012 (0.841–1.216) 0.962 (0.847–1.093) 0.9773 (0.854–1.118)
SO2 (19.25 ppb)
Lag 1 1.041 (0.987–1.098) 0.953 (0.900–1.009) 1.111 (1.011–1.221)* 0.952 (0.874–1.037) 1.031 (0.930–1.144) 0.971 (0.845–1.115) 1.030 (0.951–1.115) 0.9409 (0.860–1.029)
Lag 2 1.041 (0.979–1.107) 0.984 (0.925–1.048) 1.090 (0.977–1.216) 0.981 (0.892–1.078) 1.068 (0.950–1.202) 1.046 (0.898–1.218) 1.030 (0.927–1.145) 0.9490 (0.845–1.066)
Lag 3 1.046 (0.982–1.114) 0.987 (0.925–1.053) 1.066 (0.952–1.194) 0.995 (0.904–1.096) 1.054 (0.931–1.192) 0.985 (0.837–1.159) 1.074 (0.949–1.215) 0.9561 (0.834–1.096)
CO (1.17 ppm)
Lag 1 1.049 (0.993–1.108) 0.989 (0.932–1.049) 1.077 (0.979–1.184) 1.034 (0.949–1.126) 1.072 (0.962–1.195) 0.994 (0.854–1.157) 1.029 (0.947–1.118) 0.9010 (0.817–0.994)
Lag 2 1.032 (0.993–1.188) 0.986 (0.946–1.029) 1.068 (1.001–1.139)* 0.996 (0.933–1.062) 1.025 (0.944–1.112) 0.988 (0.884–1.104) 1.030 (0.928–1.144) 0.9041 (0.803–1.019)
Lag 3 1.051 (0.993–1.112) 0.987 (0.929–1.048) 1.100 (0.997–1.213) 0.968 (0.881–1.064) 1.081 (0.963–1.213) 0.951 (0.806–1.121) 1.013 (0.899–1.142) 0.9632 (0.845–1.098)
O3 (29 ppb)
Lag 1 0.947 (0.819–1.096) 1.039 (0.923–1.170) 1.048 (0.830–1.322) 0.944 (0.745–1.196) 0.817 (0.621–1.075) 0.959 (0.661–1.393) 0.945 (0.777–1.150) 1.0961 (0.920–1.306)
Lag 2 1.006 (0.852–1.188) 1.063 (0.917–1.232) 1.084 (0.829–1.433) 0.955 (0.731–1.246) 0.759 (0.549–1.048) 1.268 (0.832–1.932) 1.008 (0.807–1.259) 1.0624 (0.852–1.325)
Lag 3 1.043 (0.873–1.246) 1.057 (0.891–1.254) 1.092 (0.796–1.497) 1.001 (0.755–1.328) 0.893 (0.633–1.261) 1.346 (0.851–2.128) 0.963 (0.763–1.215) 0.9767 (0.757–1.261)
PM10 (31 μg/m3)
Lag 1 0.996 (0.950–1.044) 1.008 (0.965–1.054) 1.023 (0.948–1.104) 0.980 (0.912–1.053) 1.047 (0.962–1.140) 1.096 (0.982–1.222) 0.967 (0.900–1.040) 1.0033 (0.934–1.078)
Lag 2 1.015 (0.963–1.069) 1.036 (0.986–1.089) 1.035 (0.948–1.130) 1.001 (0.925–1.083) 1.049 (0.946–1.163) 1.175 (1.036–1.332)* 0.993 (0.913–1.079) 1.0298 (0.941–1.127)
Lag 3 1.022 (0.968–1.078) 1.027 (0.974–1.083) 1.047 (0.956–1.147) 0.980 (0.901–1.065) 1.030 (0.922–1.150) 1.080 (0.938–1.243) 0.998 (0.910–1.094) 1.0768 (0.972–1.193)
COH (0.5)
Lag 1 1.051 (0.994–1.113) 0.977 (0.922–1.036) 1.085 (0.986–1.195) 1.004 (0.923–1.093) 1.103 (0.994–1.223) 0.955 (0.820–1.113) 0.996 (0.912–1.088) 0.9381 (0.852–1.033)
Lag 2 1.032 (0.982–1.086) 0.991 (0.942–1.043) 1.066 (0.979–1.161) 0.980 (0.907–1.058) 1.056 (0.958–1.164) 0.996 (0.871–1.141) 0.989 (0.884–1.107) 0.9841 (0.876–1.106)
Lag 3 1.067 (1.004–1.135)* 1.001 (0.940–1.066) 1.094 (0.985–1.216) 0.972 (0.884–1.070) 1.150 (1.020–1.296)* 0.948 (0.799–1.126) 0.998 (0.875–1.137) 1.0609 (0.928–1.213)
TRS (8 ppb)
Lag 1 0.990 (0.939–1.038) 0.997 (0.961–1.035) 0.957 (0.887–1.031) 0.993 (0.938–1.052) 1.013 (0.942–1.090) 0.981 (0.896–1.074) 0.997 (0.945–1.051) 1.0126 (0.958–1.070)
Lag 2 0.987 (0.939–1.038) 0.999 (0.950–1.051) 1.002 (0.913–1.100) 0.982 (0.908–1.063) 1.023 (0.926–1.130) 1.015 (0.904–1.140) 0.961 (0.892–1.034) 1.0089 (0.9341–1.090)
Lag 3 0.976 (0.924–1.032) 1.003 (0.949–1.060) 1.063 (0.965–1.171) 0.990 (0.909–1.079) 0.980 (0.874–1.100) 0.988 (0.866–1.128) 0.925 (0.845–1.011) 1.0227 (0.934–1.120)
a Adjusted for temperature, humidity, and change in barometric pressure.
* Statistically significant at p < 0.05.
Table 4 RRs (95% CIs) for single-pollutant models using case-crossover method for an increase in IQR.a
All age groups
0–14 years
15–64 years
≥65 years
Pollutants (IQR) Female Male Female Male Female Male Female Male
NO2 (16 ppb)
Lag 1 1.078 (0.995–1.168) 0.957 (0.883–1.036) 1.145 (0.996–1.317) 0.981 (0.873–1.103) 1.004 (0.870–1.159) 0.988 (0.806–1.210) 1.081 (0.964–1.212) 0.915 (0.810–1.034)
Lag 2 1.100 (0.998–1.213) 0.960 (0.873–1.055) 1.189 (1.002–1.411)* 0.933 (0.810–1.074) 1.055 (0.883–1.260) 1.004 (0.789–1.277) 1.063 (0.925–1.222) 0.959 (0.832–1.105)
Lag 3 1.085 (0.972–1.210) 0.951 (0.854–1.057) 1.178 (0.973–1.427) 0.910 (0.777–1.066) 1.114 (0.915–1.356) 0.972 (0.744–1.268) 1.001 (0.856–1.172) 0.973 (0.829–1.142)
SO2 (19.25 ppb)
Lag 1 1.047 (0.978–1.122) 0.939 (0.874–1.009) 1.119 (0.995–1.259) 0.923 (0.831–1.025) 1.002 (0.879–1.141) 0.944 (0.798–1.116) 1.020 (0.924–1.126) 0.968 (0.867–1.082)
Lag 2 1.062 (0.969–1.164) 1.003 (0.914–1.101) 1.126 (0.957–1.325) 0.984 (0.859–1.128) 1.057 (0.893–1.252) 1.071 (0.859–1.334) 1.011 (0.888–1.152) 0.994 (0.861–1.147)
Lag 3 1.073 (0.963–1.195) 0.989 (0.886–1.103) 1.100 (0.907–1.335) 0.961 (0.819–1.126) 1.055 (0.864–1.289) 1.022 (0.785–1.330) 1.044 (0.896–1.216) 1.008 (0.852–1.192)
CO (1.17 ppm)
Lag 1 1.037 (0.968–1.111) 0.950 (0.884–1.020) 1.147 (1.006–1.307)* 1.003 (0.904–1.113) 1.005 (0.884–1.141) 1.036 (0.870–1.233) 1.014 (0.922–1.116) 0.867 (0.775–0.970)
Lag 2 1.063 (0.976–1.158) 0.945 (0.862–1.036) 1.186 (1.020–1.379)* 0.997 (0.871–1.141) 1.007 (0.859–1.181) 1.033 (0.821–1.299) 1.024 (0.907–1.156) 0.865 (0.752–0.994)
Lag 3 1.087 (0.982–1.203) 0.965 (0.866–1.075) 1.221 (1.022–1.459)* 0.970 (0.824–1.141) 1.032 (0.858–1.240) 0.991 (0.760–1.293) 1.035 (0.893–1.200) 0.946 (0.807–1.109)
O3 (29 ppb)
Lag 1 1.013 (0.766–1.339) 1.064 (0.930–1.217) 1.046 (0.800–1.367) 1.070 (0.854–1.340) 0.937 (0.723–1.214) 0.899 (0.630–1.282) 1.122 (0.919–1.369) 1.095 (0.896–1.339)
Lag 2 1.066 (0.778–1.462) 1.037 (0.889–1.211) 1.084 (0.797–1.474) 1.024 (0.797–1.316) 0.838 (0.625–1.123) 0.974 (0.651–1.457) 1.147 (0.912–1.444) 1.039 (0.826–1.308)
Lag 3 1.007 (0.712–1.424) 1.015 (0.855–1.207) 1.013 (0.721–1.425) 1.032 (0.786–1.355) 0.877 (0.639–1.203) 0.972 (0.625–1.513) 1.161 (0.901–1.496) 0.987 (0.765–1.273)
PM10 (31 μg/m3)
Lag 1 1.034 (0.974–1.098) 0.997 (0.942–1.056) 1.040 (0.944–1.146) 0.965 (0.887–1.050) 1.038 (0.937–1.151) 1.055 (0.926–1.203) 1.027 (0.936–1.125) 0.999 (0.912–1.094)
Lag 2 1.045 (0.972–1.124) 1.022 (0.953–1.097) 1.032 (0.916–1.162) 0.948 (0.857–1.048) 1.051 (0.920–1.200) 1.136 (0.964–1.339) 1.051 (0.943–1.171) 1.059 (0.942–1.191)
Lag 3 1.054 (0.970–1.145) 1.008 (0.930–1.092) 1.052 (0.919–1.204) 0.914 (0.815–1.025) 1.020 (0.872–1.194) 1.026 (0.852–1.236) 1.073 (0.949–1.214) 1.125 (0.985–1.284)
COH (0.5)
Lag 1 1.092 (1.037–1.176)* 0.974 (0.906–1.048) 1.101 (0.971–1.245) 1.025 (0.925–1.134) 1.135 (0.997–1.292) 1.013 (0.845–1.214) 1.058 (0.946–1.184) 0.898 (0.799–1.008)
Lag 2 1.097 (0.998–1.206) 1.001 (0.913–1.098) 1.119 (0.953–1.314) 1.004 (0.880–1.144) 1.196 (1.003–1.426)* 1.040 (0.823–1.315) 1.029 (0.897–1.181) 0.966 (0.837–1.115)
Lag 3 1.104 (0.989–1.232) 1.020 (0.915–1.136) 1.086 (0.903–1.307) 0.995 (0.853–1.160) 1.289 (1.051–1.582)* 0.968 (0.740–1.267) 1.016 (0.865–1.193) 1.048 (0.886–1.241)
TRS (8 ppb)
Lag 1 1.007 (0.961–1.054) 0.990 (0.945–1.037) 0.982 (0.899–1.072) 0.991 (0.923–1.063) 0.985 (0.903–1.076) 0.994 (0.895–1.103) 1.030 (0.965–1.098) 0.990 (0.925–1.061)
Lag 2 1.000 (0.940–1.064) 1.009 (0.948–1.075) 1.056 (0.941–1.184) 1.015 (0.921–1.118) 0.960 (0.858–1.074) 1.035 (0.907–1.181) 0.987 (0.903–1.078) 0.992 (0.902–1.092)
Lag 3 1.005 (0.935–1.081) 1.018 (0.944–1.098) 1.144 (0.999–1.310) 1.015 (0.933–1.185) 0.932 (0.813–1.069) 1.016 (0.867–1.192) 0.967 (0.872–1.073) 0.991 (0.886–1.110)
a Adjusted for temperature, humidity, and change in barometric pressure.
* Statistically significant at p < 0.05.
==== Refs
References
Akaike H 1973. Information theory and an extension of the maximum likelihood principle. In: Second International Symposium on Information Theory (Petrov BN, Csaki F, eds). Budapest:Academiai Kiado, 267–281.
Atkinson RW Anderson HR Strachan DP Bland JM Bremner SA Ponce de Leon A 1999 Short-term associations between outdoor air pollution and visits to accident and emergency departments in London for respiratory complaints Eur Respir J 13 2 257 265 10065665
Bates CV Sizto R 1987 Air pollution and hospital admissions in southern Ontario: the acid summer haze effect Envrion Res 43 317 331
Bateson TF Schwartz J 1999 Control for seasonal variation and time trend in case-crossover studies of acute effects of environmental exposures Epidemiology 10 539 544 10468428
Burnett RT Brook JR Yung WT Dales RE Krewski D 1997 Association between ozone and hospitalization for respiratory diseases in 16 Canadian cities Environ Res 72 24 31 9012369
Burnett RT Cakmak S Brook JR 1998 The effect of the urban ambient air pollution mix on daily mortality rates in Canadian Cities Can J Public Health 89 3 152 156 9654797
Burnett RT Dales RE Raizenne ME Krewski D Summers PW Roberts GR 1994 Effect of low ambient levels of ozone and sulfates on the frequency of respiratory admissions to Ontario hospitals Environ Res 65 172 179 8187735
Burnett RT Smith Doiron M Stieb D Cakmak S Brook JR 1999 Effects of particulate and gaseous air pollution on cardio-respiratory hospitalizations Arch Environ Health 54 130 139 10094292
Canadian Council for Tobacco Control 2002. How Have Smoking Rates Changed in the Last 30 Years? Ottawa, Ontario:National Clearinghouse on Tobacco and Health. Available: http://www.ncth.ca/NCTH_new.nsf/Docs/DirectLink~Smokingrates last30years?OpenDocument [accessed 14 November 2004].
Chen Y Dales R Krewski D Breithaupt K 1999 Increased effects of smoking and obesity on asthma among female Canadians: the National Population Health Survey, 1994–1995 Am J Epidemiol 150 255 262 10430229
Cho B Choi J Yum YT 2000 Air pollution and hospital admissions for respiratory disease in certain areas of Korea J Occup Health 42 4 185 191
Chock DP Winker SL Chen C 2000 A study of the association between daily mortality and ambient air pollution concentrations in Pittsburg, Pennsylvania J Air Waste Manage Assoc 50 1481 1500
CIHI 2002. Discharge Abstract Database. Toronto, Ontario: Canadian Institute for Health Information. Available: http://secure.cihi.ca/cihiweb/dispPage.jsp?cw_page=services_dad_e.html [accessed 14 August 2002].
Dab W Medina S Quenel P 1996 Short-term respiratory health effects of ambient air pollution: results of the APHEA project in Paris J Epidemiol Community Health 50 l S42 S46 8758223
Dockery DW Pope AC III Xu X Spengler JD Ware JH Fay ME 1993 An association between air pollution and mortality in six U.S. cities N Engl J Med 329 1753 1759 8179653
Dominici F McDermott A Zeger SL Samet JM 2002 On the use of generalized additive models in time series of air pollution and health Am J Epidemiol 156 193 203 12142253
Environment Canada 2002. Daily Climate Data. Toronto, Ontario:Atmospheric Issues Division, Ontario Climate Centre.
Fung KY Krewski D Chen Y Burnett RT Cakmak S 2003 Comparison of time series and case-crossover analyses of air pollution and hospital admission data Int J Epidemiol 32 1064 1070 14681275
Fung K Luginaah IN Gorey K Webster G 2005 Air pollution and daily hospital admissions for cardiovascular diseases in Windsor, Ontario Can J Public Health 96 1 29 33 15682690
Gilbertson M Brophy J 2001 Community health profile of Windsor, Ontario, Canada: anatomy of a Great Lakes area of concern Environ Health Perspect 109 827 843 11744501
Goldberg MS Burnett R Bailar JC III Brook J Bonvalot Y Tamblyn R 2001 The association between daily mortality and short-term effects of ambient air particle pollution in Montreal, Quebec. 1. Nonaccidental mortality Environ Res A86 12 25 11386737
Goodman DE Israel E Rosenberg M Johnston R Weiss ST Drazen JM 1994 The influence of age, diagnosis, and gender on proper use of metered-dose inhalers Am J Respir Crit Care Med 150 5 1256 1261 7952549
Hastie T Tibshirani R 1990. Generalized Additive Models. London:Chapman & Hall.
Health Canada 2000. Data and Statistics Compilations for Great Lakes Areas of Concern. Ottawa:Great Lakes Health Effects Program, Health Canada.
Hitzfeld B Friedrichs KH Ring J Behrendt H 1997 Airborne particulate matter modulates the production of reactive oxygen species in human polymorphonuclear granulocytes Toxicology 120 3 185 195 9217305
Insightful Corp 2001. S-Plus 6, Windows. Seattle, WA:Insightful Corp.
Kim CS Hu SC 1998 Regional deposition of inhaled particles in human lungs: comparison between men and women J Appl Physiol 84 1834 1844 9609774
Kohlhaufl M Brand P Scheuch G Meyer TS Schulz H Haussinger K 1999 Increased fine particles deposition in women with asymptomatic nonspecific airway hyper-responsiveness Am J Respir Crit Care Med 159 902 906 10051270
Lee JT Schwartz J 1999 Reanalysis of the effets of air pollution on daily mortality in Seoul, Korea, a case-crossover design Environ Health Perspect 107 633 636 10417360
Lin M Chen Y Burnett RT Villeneuve P Krewski D 2002 Effect of short-term exposure to gaseous pollution on asthma hospitalization in children: a bi-directional case-crossover analysis J Epidemiol Community Health 57 50 55 12490649
Lin M Chen Y Villeneuve PJ Burnett RT Lemyre L Hertzman C 2004 Gaseous air pollutants and asthma hospitalization of children with low household income in Vancouver, British Columbia, Canada Am J Epidemiol 159 3 294 303 14742290
Maclure M 1991 The case-crossover design: a method for studying transient effects on the risk of acute events Am J Epidemiol 133 144 153 1985444
MOE 2000. The Air Quality in Ontario. Toronto:Ontario Ministry of the Environment. Available: http://www.ene.gov.on.ca/ envision/air/AirQuality/2000report.htm [accessed 9 August 2002].
Navidi W 1998 Bidirectional case-crossover designs for exposures with time trends Biometrics 54 596 605 9629646
Navidi W Weinhandl E 2002 Risk set sampling for case-crossover designs Epidemiology 13 1 100 105 11805593
Neas LM Schwartz J Dockery D 1999 A case-crossover analysis of air pollution and mortality in Philadelphia Environ Health Perspect 107 629 631 10417359
Ponce de Leon A Anderson HR Bland JM Strachan DP 1996 Effects of air pollution on daily hospital admissions for respiratory disease in London between 1987–88 and 1991–92 J Epidemiol Community Health 33 suppl S63 S70 8758227
Pope C Dockery D Schwartz J 1995 Review of epidemiological evidence of health effects of particulate air pollution Inhal Toxicol 7 1 18
Prescott E Bjerg AM Anderson PK Lange P Vestbo J 1997 Gender differences in smoking effects on lung function and risk of hospitalization for COPD: results from a Danish longitudinal population study Eur Respir J 10 822 827 9150319
Priestly MB 1981. Spectral Analysis and Time Series. New York:Academic Press.
Ramsay T Burnett RT Krewski D 2003 Exploring bias in generalized additive model for spatial air pollution data Environ Health Perspect 111 1283 1288 12896847
Redline S Gold D 1994 Challenges in interpreting gender differences in asthma Am J Respir Crit Care Med 150 1219 1221 7952543
Samet JM Dominici F McDermott A Zeger SL 2003 New problems for an old design: time-series analyses of air pollution and health Epidemiology 14 1 11 12 12500038
Schouten JP Vonk JM de Gaaf A 1996 Short term effects of air pollution on emergency hospital admissions for respiratory disease: results of the APHEA project in two major cities in the Netherlands, 1977–89 J Epidemiol Community Health 50 suppl 1 S22 S29 8758220
Schwartz J 1994 Air pollution and hospital admissions for the elderly in Detroit, Michigan Am J Respir Crit Care Med 150 648 655 8087333
Schwartz J 1996 Air pollution and hospital admissions for respiratory disease Epidemiology 7 1 20 28 8664396
Speizer FE Ferris B Jr Bishop YM Spengler J 1980 Respiratory disease rates and pulmonary function in children associated with NO2 exposure Am Rev Respir Dis 121 3 10 7352711
Spix C Anderson HR Schwartz J Vigotti MA Le Tertre A Vonk JM 1998 Short term effects of air pollution on hospital admissions of respiratory diseases in Europe. A quantitative summary of APHEA study results Arch Environ Health 53 54 64 9570309
Sunyer J Atkinson R Ballester F Le Tertre A Ayres JG Forastiere F 2003. Respiratory effects of sulphur dioxide: a hierarchical multicity analysis in the APHEA 2 study. Occup Environ. Med 60:e2. Available: http://www.occenvmed.com/cgi/content/full/60/8/e2 [accessed 27 January 2005].
Vigotti MA Rossi G Bisanti L Zanobetti A Schwartz J 1996 Short term effects of urban air pollution on respiratory health in Milan, Italy, 1980–89 Epidemiol Community Health 33 suppl S63 S70
Walters S Griffiths R Ayres J 1994 Temporal association between hospital admissions for asthma in Birmingham and ambient levels of sulphur dioxide and smoke Thorax 49 133 140 8128402
WHO 1975. Manual of the International Statistical Classification of Diseases, Injuries, and Causes of Death. 9th revision. Geneva:World Health Organization.
Wong TW Lau TS Yu TS Neller A Wong SL Tam W 1999 Air pollution and hospital and cardiovascular diseases in Hong Kong Occup Environ Med 56 679 683 10658547
Wordley J Walters S Ayres JG 1997 Short term variations in hospital admissions and mortality and particulate air pollution Occup Environ Med 54 108 116 9072018
Xu X Li B Wang L 1994 Gender difference in smoking effects on adult pulmonary function Eur Respir J 7 477 483 8013605
|
15743717
|
PMC1253754
|
CC0
|
2021-01-04 23:40:57
|
no
|
Environ Health Perspect. 2005 Mar 14; 113(3):290-296
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7300
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7330ehp0113-00029715743718ResearchArticlesNecessity to Measure PCBs and Organochlorine Pesticide Concentrations in Human Umbilical Cords for Fetal Exposure Assessment Fukata Hideki 12Omori Mariko 1234Osada Hisao 25Todaka Emiko 246Mori Chisato 241Department of Environmental Medical Science,2Environmental Health Science Project for Future Generations,3Department of Reproductive Medicine, and4Department of Bioenvironmental Medicine, Graduate School of Medicine, Chiba University, Chiba, Japan5Department of Obstetrics and Gynecology, Chiba University Hospital, Chiba, Japan6Center for Environment, Health and Field Sciences, Chiba University, Kashiwa, JapanAddress correspondence to C. Mori, Department of Bioenvironmental Medicine, Graduate School of Medicine, Chiba University, Chiba 260-8670 Japan. Telephone: 81-43-226-2017. Fax: 81-43-226-2018. E-mail:
[email protected] work was supported by grants from the Ministry of the Environment (Government of Japan) and the Ministry of Education, Culture, Sports, Science and Technology (Government of Japan).
The authors declare they have no competing financial interests.
3 2005 14 12 2004 113 3 297 303 16 6 2004 14 12 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Three types of tissue samples—umbilical cord (UC), umbilical cord serum (CS), and maternal serum (MS)—have often been used to assess fetal exposure to chemicals. In order to know the relationship of contamination between mothers and fetuses, we measured persistent chemicals in comparable sets of the three tissue samples. Also, we analyzed the association between the chemicals in maternal and fetal tissues to know which tissue is the best sample for fetal exposure assessment. On a wet basis, the chemical concentrations were of the order MS > CS > UC, except for some chemicals such as cis-chlordane and endosulfan. On a lipid basis, the concentrations in UC were nearly equal or often higher than in MS, but the concentrations in CS were usually lower than in others. Hexachlorocyclohexanes and penta-, hexa-, and heptachlorinated biphenyls showed an association between the concentrations in UC versus MS, and UC versus CS. These chemicals also showed high correlation coefficients between the chemical concentrations in UC of first babies and maternal age. These chemicals were closely related to each other when grouped on the basis of their concentrations using cluster analysis. In conclusion, we insist that UC is the best sample to assess fetal contamination status of persistent chemicals. There is a possibility that the assessment based on the contamination levels in CS result in an underestimation.
cord bloodmaternal bloodorganochlorine pesticidespolychlorinated biphenyls (PCBs)umbilical cord
==== Body
It is believed that humans are exposed to multiple chemicals from food, air, water, and so forth, including natural products; industrial products, such as polychlorinated biphenyls (PCBs), pesticides, and pharmaceuticals; and nonintentional products, such as dioxins. Human fetuses are exposed to multiple chemicals through placenta in Japan (Mori 2001; Mori et al. 2003; Todaka and Mori 2002), and infants are exposed to these chemicals through milk (Borgert et al. 2003). A number of persistent organochlorine pollutants have been detected in human follicular fluid (De Felip et al. 2004) and amniotic fluid (Foster et al. 2000). Because human fetuses and infants are considered significantly more sensitive to a variety of environmental toxicants compared with adults (Branum et al. 2003; Charnley and Putzrath 2001; Needham and Sexton 2000), the adverse effects of chemicals on these fetuses and infants are of concern.
Three types of tissue samples—umbilical cord (UC), umbilical cord serum (CS), and maternal serum (MS)—have often been used to assess fetal exposure to chemicals. There are several reports indicating that the chemical concentrations were higher in maternal blood than in cord blood (Sarcinelli et al. 2003; Waliszewski et al. 2000; Walker et al. 2003). The assessments using cord blood have suggested fetal contamination. However, the chemical concentrations in fetal tissues are still unclear. There are only a few reports using fetal tissues such as UC (Covaci et al. 2002; Grandjean et al. 2001).
In order to know the relationship of contamination between mothers and fetuses, we measured persistent chemicals in comparable sets of the three tissue samples (UC, CS, and MS). Also, we analyzed the association between the chemicals in maternal and fetal tissues to know which tissue is the best sample for fetal exposure assessment.
Materials and Methods
Sample.
Thirty-two pregnant women who were general citizens and lived in the cities of Chiba and Yamanashi, near Tokyo, Japan, were surveyed in 2002 and 2003. UC (~ 20 cm), maternal blood (10 mL), and cord blood (10 mL) were collected from the cases delivered by cesarean section. The deliveries were conducted at least 12 hr after the last meal. UC without cord blood and MS and CS were stored at −20°C until use in glassware that had been checked to be without contamination. In the whole-study subjects, 20 mothers had complete samples (MS, CS, and UC), and their average age at delivery was 32.8 ± 4.0 years. There were 12 mothers without CS samples, and their average age was 31.9 ± 4.9 years. In total, 32 cases were used for the analysis of correlation between maternal age and chemical concentrations. This study has been approved by the Congress of Medical Bioethics of Chiba University and the University of Yamanashi, and all the samples were obtained after receipt of written informed consent.
Chemicals measured.
We measured 19 organochlorine pesticides: dichlorodiphenyl-trichloroethane (DDT) and its metabolites [dichlorodiphenyldichloroethylene (DDE) and dichlorodiphenyldichloroethane (DDD): p,p′-DDT, o,p′-DDT, p,p′-DDE, o,p′-DDE, p,p′-DDD, o,p′-DDD], chlordane and its metabolites (cis-chlordane, trans-chlordane, trans-nonachlor, oxychlordane), heptachlor and its metabolites (heptachlor, heptachlor epoxide), methoxychlor, “drins” (dieldrin, aldrin, endrin), endosulfan isomers (mixture of α- and β-endosulfan), hexachlorobenzene (HCB), and hexachlorocyclohexane (HCH) isomers (mixture of α-, β-, γ-, and δ -HCH). We also measured 10 groups of PCB congeners grouped by their number of chlorines from 1 to 10.
Pretreatment.
MS (4–5 mL), CS (3–4 mL), and UC (17–27 g) were used for the preparation of samples for gas chromatography–mass spectrometry. The details were revealed to the public through the homepage of the Ministry of Environment of the Government of Japan (2002). Briefly, the UC samples were homogenized with ethanol/hexane (1:3) and sodium sulfuric anhydride by a Polytron PT3100 (Kinematica AG, Littau-Lucerne, Switzerland) after 13C12-labeled PCB, 13C6-labeled β-HCH, 13C6-labeled HCB, 13C9-labeled endosulfan-I, 13C12-labeled pentaCB, and 13C12-labeled p,p′-DDT had been added as quantitative standards. After filtration, the filtrate and an additional filtrate of the rehomogenate of the residue were washed with water twice. The resulting hexane extract was dehydrated using sodium sulfuric anhydride and concentrated by evaporation. One-sixth of the concentrated extract was used for measurement of PCBs, another sixth for that of organochlorine pesticides, and half for the gravimetric fat determination.
The MS and CS samples were extracted twice using an ether/hexane (3:1) mixture after addition of the quantitative standards. The resulting ether/hexane extract was dehydrated using sodium sulfuric anhydride and concentrated by evaporation (crude extract). A fourth the crude extract was used for measurement of PCBs, and another fourth for organochlorine pesticides.
Measurement of PCBs.
After the crude extract was treated with 1 mol/L KOH/ethanol for 18 hr, it was extracted using hexane three times and was concentrated with nitrogen. The concentrate was then eluted through a silica gel 60 column (70-230 ASTM-mesh; Merck, Darmstadt, Germany) with 10 mL hexane, evaporated to a final volume of 0.1 mL, and analyzed after the addition of 13C12-labeled PCB.
PCBs were quantitated by gas chromatography–mass spectrometry. Gas chromatography was performed using a Hewlett Packard HP6800 series equipped with a Micromass AutoSpec Ultima mass spectrometer (Micromass Ltd., Manchester UK). An HT8 fused silica capillary column [0.25 mm inner diameter (i.d.) × 25 m with a 0.33-mm film thickness; SGE International Pty Ltd., Austin, TX, USA] was used to separate each PCB congener. The column temperature was maintained at 100°C for 2 min, raised to 180°C at a rate of 5°C/min, maintained at 180°C for 0.5 min, raised to 270°C at a rate of 20°C/min, then to 300°C at a rate of 5°C/min, and finally maintained at 300°C for 2 min. The carrier gas (helium) flow rate was 1 mL/min. The ionizing current was 600 μA, the ionizing energy was 38 eV, and the accelerating voltage was 8 kV. The resolution of the mass spectrometer was maintained at approximately > 10,000 (10% valley) throughout, and the analysis was carried out according to selected ion monitoring.
Measurement of organochlorine pesticides.
The crude extract was evaporated to a final volume of 0.5 mL and extracted twice with hexane-saturated acetonitrile. The resulting acetonitrile extract was added to water and extracted with hexane twice, then dehydrated using sodium sulfuric anhydride, and evaporated with nitrogen. The concentrate was eluted through a Florisil column (1 g/6 cc, Seppak Vac Florisil; Waters, Milford, MA, USA) using 10 mL hexane, evaporated to a final volume of 0.1 mL, and analyzed after the addition of fluoranthene-d10.
Organochlorine pesticides were quantitated by gas chromatography-mass spectrometry in the same manner as for PCBs, except that the column was a BPX-25 fused silica capillary column, 0.22 mm i.d. × 30 m with a 0.25-mm film thickness (SGE International Pty Ltd.). The column temperature was maintained at 60°C for 1 min, raised to 300°C at a rate of 10°C/min, and finally maintained at 300°C for 10 min.
Lipid contents.
Lipid contents in the UC samples were determined gravimetrically, and lipid contents in MS and CS were determined enzymatically as the sum of the total cholesterol, triglycerides, and phospholipids.
Statistical analysis.
The statistical analysis was performed using Microsoft Excel 2002 (Microsoft, Redmond, WA, USA). Cluster analysis was performed by the cosine correlation method using GeneMaths software (version 1.50; Applied Maths BVBA, Sint-Martens-Latem, Belgium).
Results
Detection rate.
Tables 1–4 show the concentration of organochlorine pesticides (Tables 1 and 2) and PCBs (Tables 3 and 4) in the three types of tissues (MS, CS, and UC). It became clear that human fetuses were contaminated with multiple chemicals in Japan. However, o,p′-DDE, o,p′-DDD, aldrin, endrin, and methoxychlor were not detected in any of the tissues in this study. Other chemicals were detected in MS and/or UC, but the detection rate was very low in the CS (Tables 1 and 2). In particular, cis-chlordane, endosulfan, p,p′-DDT, dieldrin, p,p′-DDD, and heptachlor were not detected in CS; however, both were detected in MS (detection rate > 70%) and UC. PCB congeners with five to seven chlorines were detected in all samples, whereas other congeners showed a relatively low detection rate in CS (Tables 3 and 4).
Contamination levels.
The highest concentrations found were p,p′-DDE, HCHs, and HCB in all three tissues both on a lipid basis (Table 1) and wet basis (Table 2). Generally, the chemical concentrations on a wet basis were of the order MS > CS > UC. This is due to the difference in lipid content. Lipid content in MS, CS, and UC (20 complete samples) was 0.76 ± 0.13%, 0.23 ± 0.04%, and 0.11 ± 0.02%, respectively. Remarkably, the concentrations of some chemicals in UC on a wet basis, such as cis-chlordane and endosulfan, were almost equal to those in MS (Table 2). On the other hand, on a lipid basis, the concentrations of the following chemicals in UC were nearly equal or often higher than in MS: HCHs, p,p′-DDT, cis-chlordane, trans-chlordane, endosulfan, and heptachlor epoxide (p < 0.001, paired t-test; Table 1). The chemical concentrations in CS were usually lower than in other tissues.
PCB congeners grouped on the basis of their number of chlorines showed different patterns of distribution depending on the number of chlorines. TetraCB and pentaCB concentrations were higher in MS than in UC (p < 0.05, paired t-test), whereas hexaCB and heptaCB concentrations were higher in UC than in MS (p < 0.001, paired t-test) on a lipid basis (Table 3); particularly, heptaCBs and octaCBs showed a high UC:MS ratio. The UC:MS ratio varied according to the number of chlorines in the range of 3–8: UC < MS for congeners with 3–5 chlorines, and UC > MS for congeners with 6–8 chlorines (Table 3). The detection rates of congeners with 1 or 2 chlorines were higher in UC than in MS, whereas those with of 9 or 10 chlorines were higher in MS than in UC. The concentrations (average and median, on a lipid basis) of congeners with 9 or 10 chlorines were higher than those with 1 or 2 chlorines in MS, whereas concentrations of congeners with 1 or 2 chlorines were higher than those with 9 or 10 chlorines in UC. These facts suggest that the accumulation of PCBs in UC is different depending on the number of chlorines; PCB congeners with 1, 2, 6, 7 and 8 chlorines easily accumulate in UC compared with other congeners.
Association between the chemical concentrations among chemicals.
We reported that correlation existed between total PCBs and other persistent chemicals, such as p,p′-DDE, HCB, and HCHs, in human UC (Mori et al. 2003). To confirm our previous findings, we applied a cluster analysis technique in the present study. We used the cluster analysis to discover “natural” groupings of objects that reflect evolutionary or functional relationships among the objects; some of the cluster analyses often done in toxicogenomics research have this objective (Immermann and Huang 2003). The cluster analysis was performed using cosine correlation matrix for chemical concentrations in UC for UC, and the clustering results were represented in the dendrogram (Figure 1). Consequently, we found that PCBs with 5–8 chlorines and some organochlorines, such as p,p′-DDE, HCB, and HCHs, were closely related to each other (Figure 1).
Association between the chemical concentrations among the three types of tissues.
Correlation of organochlorine pesticide concentrations among the three types of tissues is shown in Table 5. Some organochlorine pesticides showed no association between MS versus CS and/or between CS versus UC. Between MS versus CS, HCB, HCHs, heptachlor epoxide, and PCBs with chlorines showed a relatively high correlation coefficient (r > 0.7). Between CS versus UC, HCHs, p,p′-DDE, and PCBs with 5–8 chlorines showed relatively high correlation (r > 0.7). Comparing MS and UC, HCHs and PCBs with 4–7 chlorines showed a relatively high correlation coefficient (r > 0.7).
Association between the chemical concentrations in UC and maternal age.
Several studies have reported that chemical concentrations were dependent upon maternal age at delivery (Mori et al. 2003; Rhainds et al. 1999). Our present results confirmed that HCHs, pentaCBs, hexaCBs, heptaCBs, and octaCBs showed such correlation (Table 5). A significant correlation was found between CS versus UC and age versus UC (r = 0.75; Table 5). Also, relatively significant correlation was found between MS versus UC and age versus UC (r = 0.64; Table 5). However, we found no correlation between MS versus CS and age versus UC (r = 0.04; Table 5). That is, HCHs, pentaCBs, hexaCBs, and heptaCBs tended to show relatively high association of concentrations in CS versus UC and MS versus UC. Also, these chemicals showed high correlation coefficients between the chemical concentrations in UC of first babies and maternal age.
Discussion
We investigated the distribution of organo-chlorine pesticides and PCBs in three types of tissues (UC, CS, and MS). We analyzed the chemical contamination status mainly on a lipid basis because the liposolubility rate is thought to be a major factor influenced by rates of accumulation and elimination from tissues and organs (Parham et al. 1997) and because the existing differences depend principally on lipid content of the tissues (Henriksen et al. 1998). Several studies have reported that the concentration levels of persistent chemicals showed association between cord blood and maternal blood (Sala et al. 2001; Waliszewski et al. 2000; Walker et al. 2003). In our study, we found strong correlation between MS versus CS (Table 5) in some organochlorine pesticides and PCB congeners. Also, Grandjean et al. (2001) showed high associations between cord blood and UC. The tendency was confirmed in our study of HCHs, p,p′-DDE, and some PCB congeners (Table 5). However, we found no report that compared the concentration levels among UC, CS, and MS. Hence, we compared the data among these three tissues.
In the present study, we found that the chemical concentrations were often higher in UC than in CS on a lipid basis, and the detection rates and the concentrations in CS were often lower than in MS and UC. In past studies, chemical concentrations were higher in adipose tissues than in serum (López-Carrillo et al, 1999; Pauwels et al. 2000), and in other studies, concentrations were higher in serum lipid than in breast tissues (Waliszewski et al. 2003). Moreover, as suggested by Pauwels et al. (2000), the concentration levels of persistent chemicals varied dramatically depending on the tissues (Tables 1 and 3). One of the reasons for the confusion may be the pharmaco-kinetics of chemicals in blood. Mohammed et al. (1990) and Norén et al. (1999) reported that chemicals in blood are bound to lipoproteins and albumin rather than being dissolved in lipid, and the distribution in plasma vary according to the chemicals. It is possible that a free form of chemicals is distributed by simple equilibrium, but distribution or transport of bound form of chemicals to protein in blood is more complicated, so the chemical concentration in CS might be lower than in MS and UC. Further studies on the distribution of contaminants in different body tissues and fetal tissues are required.
In conclusion, we believe that UC is the best sample to assess fetal contamination status of persistent chemicals. There is a possibility that assessment based on the contamination levels in CS result in an underestimation.
Figure 1 Cluster analysis of chemical concentrations among UC samples. Similarity values were calculated by cosine correlation matrix for chemical concentrations in UC for UC; the results are shown as a dendrogram.
Table 1 Organochlorine pesticide concentrations (pg/g-lipid) in three types of tissue.
Organochlorine pesticide, tissue Detectiona (%) Mean ± SD Minimum 25th percentile Median 75th percentile Maximum
HCB
MS 100 15,500 ± 6,220 3,600 10,000 16,000 17,800 31,000
CS 100 10,900 ± 3,680** 5,200 8,800 11,000 12,000 18,000
UC 95 17,700 ± 6,360## ND 16,000 18,000 20,000 28,000
HCHs
MS 100 27,400 ± 10,630 13,000 22,000 26,000 30,000 55,000
CS 100 33,800 ± 19,300 12,000 24,000 28,000 39,000 100,000
UC 100 36,200 ± 14,920** 18,000 26,000 30,000 45,000 69,000
p,p′-DDT
MS 80 3,380 ± 3,240 ND 1,000 2,400 5,100 11,000
CS 0 — — — — —
UC 50 5,550 ± 7,160** ND ND 1,100 9,300 19,000
o,p′-DDT
MS 15 38 ± 104 ND ND ND ND 340
CS 0 — — — — — —
UC 0 — — — — — —
p,p′-DDE
MS 100 89,700 ± 33,600 19,000 71,000 93,000 110,000 150,000
CS 100 33,000 ± 16,500** 14,000 22,000 28,000 42,000 75,000
UC 100 79,600 ± 26,200## 29,000 64,000 78,000 90,000 140,000
p,p′-DDD
MS 85 766 ± 982 ND 200 360 950 3,800
CS 0 — — — — —
UC 15 215 ± 527 ND ND ND ND 1,600
cis-Chlordane
MS 100 240 ± 165 63 110 200 330 660
CS 0 — — — — —
UC 70 1,220 ± 1,230** ND ND 1,200 1,700 4,400
trans-Chlordane
MS 95 320 ± 257 ND 160 240 430 1,200
CS 20 198 ± 449 ND ND ND ND 1,400
UC 55 644 ± 848** ND ND 290 1,200 3,000
Oxychlordane
MS 85 2,640 ± 4,160 ND 620 1,200 3,900 19,000
CS 40 978 ± 1,630 ND ND ND 1,600 6,300
UC 60 2,120 ± 2,100 ND ND 1,900 3,700 6,100
trans-Nonachlor
MS 100 7,230 ± 2,840 2,000 5,600 7,000 9,000 14,000
CS 80 3,780 ± 6,470 ND 1,400 1,900 3,800 30,000
UC 100 7,660 ± 2,580 2,500 6,200 6,700 8,300 14,000
Dieldrin
MS 70 495 ± 454 ND ND 440 770 1,600
CS 0 — — — — — —
UC 45 1,970 ± 3,170* ND ND ND 2,200 9,600
Endosulfan
MS 90 380 ± 267 ND 280 340 460 1,100
CS 0 — — — — — —
UC 70 2,090 ± 2,440** ND ND 1,600 2,900 9,400
Heptachlor
MS 25 150 ± 272 ND ND ND 100 700
CS 0 — — — — —
UC 10 505 ± 1,620 ND ND ND ND 6,500
Heptachlor epoxide
MS 100 142 ± 729 310 950 1,200 1,700 3,000
CS 95 1,580 ± 844 ND 1,100 1,500 1,900 3,400
UC 100 2,790 ± 1,280**,## 160 2,000 2,700 3,500 6,000
ND, not detected.
a Detection rate is shown as a percentage (n = 20).
* p < 0.05 and
** p < 0.001 compared with MS.
## p < 0.001 compared with CS.
Table 2 Organochlorine pesticide concentrations (pg/g-wet) in three types of tissue.
Organochlorine pesticide, tissue Detectiona (%) Mean ± SD Minimum 25th percentile Median 75th percentile Maximum
HCB
MS 100 120 ± 55.2 20 81 120 140 230
CS 100 23.9 ± 8.42** 13 20 23 25 46
UC 95 19.6 ± 6.52** ND 17 20 23 33
HCHs
MS 100 208 ± 84.7 100 160 190 240 430
CS 100 74.5 ± 39.3** 33 49 70 82 190
UC 100 39.8 ± 7.8**,## 17 29 35 48 95
pp′-DDT
MS 80 26.40 ± 26.5 ND 8.0 17 42 90
CS 0 — — — — — —
UC 50 5.76 ± 7.53* ND ND 1.0 11 27
op′-DDT
MS 15 0.32 ± 0.89 ND ND ND ND 3
CS 0 — — — — — —
UC 0 — — — — — —
pp′-DDE
MS 100 680.0 ± 277 190 480 640 900 1,200
CS 100 71.9 ± 30.7** 26 50 72 95 130
UC 100 86.5 ± 26.1**,# 31 76 88 94 150
pp′-DDD
MS 85 6.11 ± 7.99 ND 1.6 2.7 7.1 30
CS 0 — — — — — —
UC 15 0.26 ± 0.63 ND ND ND ND 2.1
cis-Chlordane
MS 100 1.81 ± 1.25 0.54 0.70 1.3 2.6 4.8
CS 0 — — — — — —
UC 70 1.20 ± 1.19 ND ND 1.1 2.0 4.4
trans-Chlordane
MS 95 2.46 ± 2.45 ND 1.2 1.9 3.1 12
CS 20 0.41 ± 0.90 ND ND ND ND 2.9
UC 55 0.68 ± 0.91* ND ND 0.25 1.1 2.9
Oxychlordane
MS 85 22.80 ± 45.4 ND 4.9 11 24 210
CS 40 2.19 ± 3.45 ND ND ND 3.6 12
UC 60 2.48 ± 2.50 ND ND 2.3 4.5 6.9
trans-Nonachlor
MS 100 55.00 ± 23.2 15 38 53 68 100
CS 80 8.02 ± 12.1** ND 3.1 4.3 9.7 56
UC 100 8.52 ± 3.17** 2.9 6.8 7.9 10.3 17
Dieldrin
MS 70 3.75 ± 3.30 ND ND 3.4 5.9 10
CS 0 — — — — — —
UC 45 2.02 ± 3.01 ND ND 2.7 2.6 8.5
Endosulfan
MS 90 2.90 ± 2.07 ND 2 2.6 3.9 8.4
CS 0 — — — — — —
UC 70 2.83 ± 2.61 ND ND 1.9 3.3 10
Heptachlor
MS 25 1.44 ± 2.58 ND ND ND 1.2 7.2
CS 0 — — — — — —
UC 10 0.57 ± 1.82 ND ND ND ND 7.2
Heptachlor epoxide
MS 100 10.70 ± 5.67 2.3 6.9 9 13 24
CS 95 3.51 ± 1.80** ND 2.4 3.3 4.2 7.3
UC 100 2.89 ± 1.03** 0.3 2.2 3.1 3.5 5.1
ND, not detected.
a Detection rate is shown as a percentage (n = 20).
* p < 0.05 and
** p < 0.001 compared with MS.
# p < 0.05 and
## p < 0.001 compared with CS.
Table 3 PCB concentrations (pg/g-lipid) in three types of tissue.
PCB, tissue Detectiona (%) Mean ± SD Minimum 25th percentile Median 75th percentile Maximum
MonoCBs
MS 25 8.4 ± 30.5 ND ND ND 28 110
CS 0 — — — — — —
UC 95 480 ± 405* ND 100 470 640 1,400
DiCBs
MS 70 44 ± 37 ND ND 44 67 120
CS 0 — — — — — —
UC 80 354 ± 276** ND 220 370 450 1,200
TriCBs
MS 100 1,630 ± 639 720 1200 1400 2,000 2,900
CS 65 1,630 ± 1770 ND ND 1,500 2,200 6,700
UC 90 1,210 ± 977 ND 560 1100 1,800 3,900
TetraCBs
MS 100 7,000 ± 2120 4,000 7,400 7,100 8,000 12,000
CS 95 4,360 ± 3750** ND 1,800 3,300 5,600 14,000
UC 95 3,190 ± 2,200** ND 2,100 3,000 4,000 10,000
PentaCBs
MS 100 15,000 ± 4,630 7,700 11,000 15,000 18,000 25,000
CS 100 12,700 ± 6,080** 3,700 8,000 13,000 17,000 24,000
UC 100 13,200 ± 6,100* 5,100 7,900 12,000 18,000 25,000
HexaCBs
MS 100 25,600 ± 8,410 11,000 20,000 26,000 30,000 42,000
CS 100 31,200 ± 11,000** 14,000 23,000 31,000 38,000 51,000
UC 100 32,600 ± 12,000** 13,000 24,000 35,000 40,000 53,000
HeptaCBs
MS 100 9,640 ± 3,610 3,900 7,400 8,600 12,000 17,000
CS 100 12,300 ± 5,420** 3,500 8,000 12,000 13,500 23,000
UC 100 15,200 ± 5,860**,## 7,700 11,000 14,000 20,000 29,000
OctaCBs
MS 100 1,750 ± 718 590 1,500 1,800 2,500 3,100
CS 75 1,700 ± 1,380 ND 830 1,400 2,600 4,400
UC 100 3,130 ± 1,360**,## 1,700 2,100 2,700 3,900 5,900
NonaCBs
MS 70 212 ± 174 ND ND 220 290 530
CS 35 146 ± 291 ND ND ND 200 1,200
UC 50 148 ± 221 ND ND 60 210 910
DecaCBs
MS 85 114 ± 65 ND 91 115 150 240
CS 35 130 ± 257 ND ND ND 220 1,100
UC 55 148 ± 173* ND ND 96 255 570
Total PCBs
MS 100 61,500 ± 18,400 29,000 46,000 61,000 72,000 96,000
CS 100 63,800 ± 23,300 31,000 44,000 63,000 77,000 110,000
UC 100 70,000 ± 26,100*,# 34,000 47,000 73,000 88,000 130,000
ND, not detected.
a Detection rate is shown as a percentage (n = 20).
* p < 0.05 and
** p < 0.001 compared with MS.
# p < 0.05 and
## p < 0.001 compared with CS.
Table 4 PCB concentrationsa (pg/g-wet) in three types of tissue.
PCB, tissue Detectiona (%) Mean ± SD Minimum 25th percentile Median 75th percentile Maximum
MonoCBs
MS 25 0.10 ± 0.21 ND ND ND 0.02 0.68
CS 0 — — — — — —
UC 95 0.52 ± 0.47 ND 0.16 0.36 0.82 1.7
DiCBs
MS 70 8.65 ± 0.28 ND ND 0.35 0.52 0.89
CS 0 — — — — — —
UC 80 0.38 ± 0.30 ND 0.24 0.36 0.50 1.2
TriCBs
MS 100 13.0 ± 6.14 6.1 8.5 10 15 31
CS 65 3.78 ± 4.42** ND ND 3.6 4.8 17
UC 90 1.38 ± 1.15**,# ND 0.45 1.3 1.8 4.4
TetraCBs
MS 100 53.2 ± 17.75 22 40 50 65 91
CS 95 9.59 ± 8.32** ND 4.2 6.9 13 35
UC 95 3.69 ± 3.13**,## ND 2.4 2.9 4.5 15
PentaCBs
MS 100 115 ± 42.3 51 81 110 140 190
CS 100 27.5 ± 12.8** 8.6 19 26 34 54
UC 100 14.6 ± 7.54**,## 5.2 10 13 18 37
HexaCBs
MS 100 195 ± 68.4 90 140 210 240 340
CS 100 69.3 ± 25.9** 26 51 68 88 130
UC 100 36.1 ± 15.3**,## 16 26 35 43 78
HeptaCBs
MS 100 73.3 ± 26.7 34 55 73 94 120
CS 100 27.9 ± 13.8** 6.2 19 26 32 61
UC 100 17.1 ± 8.26**,## 8.6 12 16 20 43
OctaCBs
MS 100 14.5 ± 5.57 4.6 11 15 18 26
CS 75 4.03 ± 3.96** ND 1.4 3.4 5.1 16
UC 100 3.57 ± 1.86**,# 1.4 2.1 3.4 4.3 8.3
NonaCBs
MS 70 1.54 ± 1.26 ND ND 1.6 2.5 3.8
CS 35 0.32 ± 0.64 ND ND ND 0.52 2.7
UC 50 0.17* ± 0.27* ND ND 0.065 0.26 1.1
DecaCBs
MS 85 0.87 ± 0.50 ND 0.73 0.86 1.0 1.7
CS 35 0.29 ± 0.58 ND ND ND 0.49 2.5
UC 55 0.18 ± 0.23** ND ND 0.094 0.33 0.85
Total PCBs
MS 100 467 ± 154 220 340 490 570 780
CS 100 139 ± 56.4** 56 100 130 180 270
UC 100 77.4 ± 35.5**,## 35 57 73 91 190
ND, not detected.
a Detection rate is shown as a percentage (n = 20).
* p < 0.05 and
** p < 0.001 compared with MS.
# p < 0.05 and
## p < 0.001 compared with CS.
Table 5 Correlation coefficients (r) of chemicals among tissues and between maternal age and chemical concentrations in UC of first babies.
Among tissuesa Between maternal age and concentrations in UC of first babies (age vs. UC)
MS vs. CS CS vs. UC MS vs. UC
HCB 0.73 0.30 0.39 −0.16
HCHs 0.72 0.76 0.80 0.83
p,p′-DDE 0.46 0.76 0.29 0.28
cis-Chlordane — — 0.03 −0.02
trans-Nonachlor 0.18 0.20 0.11 0.47
Endosulfan — — 0.19 −0.20
Heptachlor epoxide 0.72 0.22 0.02 0.10
TriCBs — — 0.35 −0.03
TetraCBs 0.51 0.41 0.73 0.37
PentaCBs 0.83 0.89 0.84 0.75
HexaCBs 0.87 0.87 0.82 0.76
HeptaCBs 0.68 0.85 0.72 0.85
OctaCBs 0.32 0.70 0.47 0.81
NonaCBs — — −0.25 —
DecaCBs — — 0.40 —
Total PCBs 0.82 0.82 0.81 0.80
Correlation coefficients (r) b between “among tissues” and age vs. UC 0.04 0.75 0.64 —
—, not calculated.
a The values shown were calculated when the detection rate in the tissue was ≥70%.
b Total PCBs were excluded from this calculation.
==== Refs
References
Borgert CJ LaKind JS Witorsch RJ 2003 A critical review of methods for comparing estrogenic activity of endogenous and exogenous chemicals in human milk and infant formula Environ Health Perspect 111 1020 1036 12826475
Branum AM Collman GW Correa A Keim SA Kessel W Kimmel CA 2003 The National Children’s Study of environmental effects on child health and development Environ Health Perspect 111 642 646 12676629
Charnley G Putzrath RM 2001 Children’s health, susceptibility, and regulatory approaches to reducing risks from chemical carcinogens Environ Health Perspect 109 187 193 11266331
Covaci A Jorens P Jacquemyn Y Schepens P 2002 Distribution of PCBs and organochlorine pesticides in umbilical cord and maternal serum Sci Total Environ 298 45 53 12449328
De Felip E di Domenico A Miniero R Silvestroni L 2004 Polychlorobiphenyls and other organochlorine compounds in human follicular fluid Chemosphere 54 1445 1449 14659946
Foster W Chan S Platt L Hughee C 2000 Detection of endocrine disrupting chemicals in samples of second trimester human amniotic fluid Clin Endocrinol Metab 85 2954 2957
Grandjean P Weihe P Burse VW Needham LL Storr-Hansen E Heinzow B 2001 Neurobehavioral deficits associated with PCB in 7-year-old children prenatally exposed to seafood neurotoxicants Neurotoxicol Teratol 23 305 317 11485834
Henriksen EO Gabrielsen GW Skaare JU 1998 Validation of the use of blood samples to assess tissue concentrations of organochlorines in glaucous gulls, Larus hyperboreus Chemosphere 37 2627 2643
Immermann F Huang Y 2003. An introduction to cluster analysis. In: An Introduction to Toxicogenomics (Burczynski ME, ed). Boca Raton:CRC Press LLC, 45–78.
López-Carrillo L Torres-Sánchez L López-Cervantes M Blair A Cebrián ME Uribe M 1999 The adipose tissue to serum dichlorodiphenyldichloroethan (DDE) ratio: some methodological considerations Environ Res A 81 142 145
Ministry of Environment, Government of Japan 2002. Research on Chemicals Detected in Human Umbilical Cord [in Japanese]. Tokyo:Ministry of Environment. Available: http://www.env.go.jp/chemi/end/kento1402/mat/mat04-1.pdf [accessed 7 February 2005].
Mohammed A Eklund A Ostlund-Lindgvist AM Slanina P 1990 Distribution of toxaphene, DDT, and PCB among lipoprotein fractions in rat and human plasma Arch Toxicol 64 567 571 2127352
Mori C 2001 Possible effects of endocrine disruptors on male reproductive function Acta Anatomica Nippon 76 361 368
Mori C Komiyama M Adachi T Sakurai K Nishimura D Takashima K 2003 Application of toxicogenomic analysis to risk assessment of delayed long-term effects of multiple chemicals including endocrine disruptors in human fetuses Environ Health Perspect 111 803 809
Needham LL Sexton K 2000 Assessing children’s exposure to hazardous environmental chemicals: an overview of selected research challenges and complexities J Expo Anal Environ Epidemiol 10 611 629 11138654
Norén K Weistrand C Karpe F 1999 Distribution of PCB congeners, DDE, hexachlorobenzene, and methylsulfonyl metabolites of PCB and DDE among various fractions of human blood plasma Arch Environ Contam Toxicol 37 408 414 10473799
Parham FM Kohn MC Matthews HB DeRosa C Portier CJ 1997 Using structural information to create physiologically based pharmacokinetic models for all polychlorinated biphenyls. I. Tissue:blood partition Toxicol Appl Pharmacol 144 340 347 9194418
Pauwels A Covaci A Weyler J Delbeke L Dhont M De Sutter P 2000 Comparison of persistent organic pollutant residues in serum and adipose tissue in a female population in Belgium, 1996–1998 Arch Environ Contam Toxicol 39 265 270 10871430
Rhainds M Levallois P Dewailly E Ayotte P 1999 Lead, mercury, and organochlorine compound levels in cord blood in Quebec, Canada Arch Environ Health 54 40 47 10025415
Sala M Ribas-Fitó N Cardo E de Muga ME Marco E Mazón C 2001 Levels of hexacholorobenzene and other organochlorine compounds in cord blood: exposure across placenta Chemosphere 43 895 901 11372882
Sarcinelli PN Pereira ACS Mesquita SA Oliveira-Silva JJ Meyer A Menezes MAC 2003 Dietary and reproductive determinants of plasma organochlorine levels in pregnant women in Rio de Janeiro Environ Res 91 143 150 12648476
Todaka E Mori C 2002 Necessity to establish new risk assessment and risk communication for human fetal exposure to multiple endocrine disruptors in Japan Congent Anom Kyto 42 87 93
Waliszewski SM Aguirre AA Infanzón RM Siliceo J 2000 Carry-over of persistent organochlorine pesticides through placenta to fetus Salud Publica Mex 42 384 390 11125622
Waliszewski SM Infanzon RM Hart M 2003 Differences in persistent organochlorine pesticides concentration between breast adipose tissue and blood serum Bull Environ Contam Toxicol 70 920 926 12719816
Walker JB Seddon L McMullen E Houseman J Tofflemire K Corriveau A 2003 Organochlorine levels in maternal and blood plasma in Arctic Canada Sci Total Environ 302 27 52 12526896
|
15743718
|
PMC1253755
|
CC0
|
2021-01-04 23:40:57
|
no
|
Environ Health Perspect. 2005 Mar 14; 113(3):297-303
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7330
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7447ehp0113-00030415743719ResearchArticlesEffects of Air Pollution on Heart Rate Variability: The VA Normative Aging Study Park Sung Kyun 1O’Neill Marie S. 1Vokonas Pantel S. 2Sparrow David 2Schwartz Joel 11Department of Environmental Health, Harvard School of Public Health, Boston, Massachusetts, USA2VA Normative Aging Study, Veterans Affairs Boston Healthcare System and the Department of Medicine, Boston University School of Medicine, Boston, Massachusetts, USAAddress correspondence to S.K. Park, Exposure, Epidemiology and Risk Program, Harvard School of Public Health, Landmark Center East, 3-111-19, 401 Park Dr., Boston, MA 02215 USA. Telephone: (617) 384-8873. Fax: (617) 384-8745. E-mail:
[email protected] thank E.R. Dibbs and J.D. Auerbach for their invaluable assistance in conducting the heart rate variability measurements and other contributions to the VA Normative Aging Study (NAS).
This work was supported by the National Institute of Environmental Health Sciences (NIEHS) (ES00002) and the U.S. Environmental Protection Agency (EPAR827353). The VA NAS is supported by the Cooperative Studies Program/Epidemiology Research and Information Center of the U.S. Department of Veterans Affairs and is a component of the Massachusetts Veterans Epidemiology Research and Information Center, Boston. S.K.P. and M.S.O. were supported by training grant T32 ES07069 from the NIEHS, National Institutes of Health. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIEHS. M.S.O. was supported by the Robert Wood Johnson Foundation Health and Society Scholars program.
The authors declare they have no competing financial interests.
3 2005 6 12 2004 113 3 304 309 26 7 2004 6 12 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Reduced heart rate variability (HRV), a marker of poor cardiac autonomic function, has been associated with air pollution, especially fine particulate matter [< 2.5 μm in aerodynamic diameter (PM2.5)]. We examined the relationship between HRV [standard deviation of normal-to-normal intervals (SDNN), power in high frequency (HF) and low frequency (LF), and LF:HF ratio] and ambient air pollutants in 497 men from the Normative Aging Study in greater Boston, Massachusetts, seen between November 2000 and October 2003. We examined 4-hr, 24-hr, and 48-hr moving averages of air pollution (PM2.5, particle number concentration, black carbon, ozone, nitrogen dioxide, sulfur dioxide, carbon monoxide). Controlling for potential confounders, HF decreased 20.8% [95% confidence interval (CI), 4.6–34.2%] and LF:HF ratio increased 18.6% (95% CI, 4.1–35.2%) per SD (8 μg/m3) increase in 48-hr PM2.5. LF was reduced by 11.5% (95% CI, 0.4–21.3%) per SD (13 ppb) increment in 4-hr O3. The associations between HRV and PM2.5 and O3 were stronger in people with ischemic heart disease (IHD) and hypertension. The associations observed between SDNN and LF and PM2.5 were stronger in people with diabetes. People using calcium-channel blockers and beta-blockers had lower associations between O3 and PM2.5 with LF. No effect modification by other cardiac medications was found. Exposures to PM2.5 and O3 are associated with decreased HRV, and history of IHD, hypertension, and diabetes may confer susceptibility to autonomic dysfunction by air pollution.
air pollutiondiabetesheart rate variabilityhypertensionischemic heart diseaseozonePM2.5
==== Body
Short- and long-term exposure to air pollution has been associated with increased cardiovascular mortality and morbidity (Pope et al. 2002; Samet et al. 2000; Schwartz 1999), and individuals with underlying cardiovascular disease, including heart failure, arrhythmia, or diabetes, are at greater risk (Bateson and Schwartz 2004; Goldberg et al. 2001; Mann et al. 2002; Zanobetti and Schwartz 2002). Possible mechanisms for these associations include effects on the autonomic nervous system through direct reflexes from airways or through inflammatory response, chemical effects on ion channel function in myocardial cells, ischemic response in the myocardium, and inflammatory responses that trigger endothelial dysfunction, atherosclerosis, and thrombosis (Utell et al. 2002).
Heart rate variability (HRV) is a widely used noninvasive and quantitative marker of cardiac autonomic control. HRV reflects autonomic modulation of the rhythmic activity of the sinus node and is analyzed in the time or frequency domains (Task Force 1996). Sustained reductions of HRV have been associated with increased risk of mortality in middle-age and elderly subjects, in patients with diabetes, and in survivors of myocardial infarction and other cardiovascular diseases (Dekker et al. 1997; Gerritsen et al. 2001; Tapanainen et al. 2002; Tsuji et al. 1996). Air pollution, especially particulate matter < 2.5 μm in aero-dynamic diameter (PM2.5), has been associated with alterations in HRV (Creason et al. 2001; Devlin et al. 2003; Gold et al. 2000; Holguin et al. 2003; Liao et al. 1999, 2004; Magari et al. 2001, 2002; Pope et al. 1999, 2004). However, only two studies explored whether clinical conditions or other subject characteristics modified the association between air pollution and HRV (Holguin et al. 2003; Liao et al. 2004). Little has been reported to date on associations with particle components.
In this study we examine the relationship between alterations in HRV and ambient air pollutants among community residents. We also investigated modifying effects of hypertension, ischemic heart disease (IHD), diabetes, and use of commonly prescribed antihypertensive medications that increase cardiac vagal activity (Lampert et al. 2003; Tomiyama et al. 1998; Townend et al. 1995).
Materials and Methods
Study population.
The Normative Aging Study is a longitudinal study of aging established by the Veterans Administration in 1963, when 2,280 men from the Greater Boston area (21–81 years of age) confirmed to be free of known chronic medical conditions were enrolled (Bell et al. 1972). Participants were asked to return for examinations every 3–5 years. Among active cohort members, 603 persons were examined from 14 November 2000 through 30 October 2003.
Participants visited the study center in the morning, after an overnight fast and abstinence from smoking. Weight and height were measured to compute body mass index (BMI). With the subject seated, heart rate and systolic and diastolic blood pressures were measured by a physician. The mean of the left and right arm measurements was used. For this study, we defined mean arterial blood pressure (MAP) as diastolic pressure plus one-third of the difference between systolic and diastolic blood pressure. Subjects with diabetes were defined by a physician’s diagnosis of type 2 diabetes and/or use of a diabetes medication (e.g., oral hypoglycemic drug, metformin, or insulin). Hypertension was defined as systolic blood pressure of ≥140 mm Hg, diastolic blood pressure of ≥90 mm Hg, or reported use of hypertension medication. Cigarette smoking, alcohol consumption, and subjects’ use of medications were assessed by questionnaire. Medication use was confirmed by a physician interview. Prevalent IHD was identified using the Framingham Heart Study criteria for myocardial infarction and angina pectoris (Shurtleff 1974). Temperature of the room where the electrocardiogram (ECG) was taken was recorded.
HRV measurement.
We measured HRV between 0600 and 1300 hr using a two-channel (five-lead) ECG monitor (Trillium 3000; Forest Medical, East Syracuse, NY). A detailed description of the HRV measurement protocol is provided elsewhere (Pope et al. 2001). Briefly, after the participants had rested for 5 min, the ECG was recorded (sampling rate of 256 Hz per channel) for approximately 7 min with the subject seated. We used the best 4-consecutive-minute interval for the HRV calculations. The ECG digital recordings were processed, and heart rate and HRV measures were calculated using PC-based software (Trillium 3000 PC Companion Software for MS Windows; Forest Medical). Beats were automatically detected and assigned tentative annotations, which were then reviewed by an experienced scanner to correct for any mislabeled beats or artifacts. Only normal-to-normal (NN) beat intervals were included in the analysis. We computed standard deviation of NN intervals (SDNN), the square root of the mean of the squared differences between adjacent NN intervals (r-MSSD), high-frequency power (HF) (0.15–0.4 Hz), low-frequency power (LF) (0.04–0.15 Hz), and LF:HF ratio. Ninety-two subjects with problematic heart rate measurements (atrial fibrillation, atrial bigeminy and trigeminy, pacemakers, irregular rhythm, irregular sinus rhythm, frequent ventricular ectopic activity, ventricular bigeminy, multifocal atrial tachycardia, or measurement time < 3.5 min) were excluded.
Air pollution and weather data.
Continuous PM2.5, particle number concentration (PN), and black carbon (BC) were measured at the Harvard School of Public Health monitoring site, 1 km from the exam site, using a Tapered Element Oscillating Microbalance (TEOM) (model 1400A; Rupprecht & Pataschnick Co., East Greenbush, NY), condensation particle counter (model 3022A; TSI Inc., Shoreview, MN), and aethalometer (Magee Scientific, Berkeley, CA), respectively. Because the TEOM sample filter is heated to 50°C, a season-specific correction was used to compensate for the loss of semivolatile mass that occurs at this temperature (Allen et al. 1997). Ozone, sulfur dioxide, nitrogen dioxide, carbon monoxide, temperature, and dew-point temperature measurements were obtained from the Massachusetts Department of Environmental Protection local monitoring sites. The gaseous pollutants are measured hourly using U.S. Environmental Protection Agency (EPA) reference methods (U.S. EPA 2002).
To control for weather, we used apparent temperature, defined as a person’s perceived air temperature (O’Neill et al. 2003). It was calculated with the following formula: −2.653 + (0.994 × air temperature) + (0.0153 × dew-point temperature). We estimated missing PM2.5, PN, and BC measures using a regression model with date, day of week, hour of day, temperature, relative humidity, pressure, and NO2 as predictors (6.4% missing for PM2.5, 7.5% for PN, and 0.5% for BC). To evaluate lagged effects of air pollutants, we used 4-hr, 24-hr, and 48-hr moving averages of air pollution matched on the time of measuring ECG for each subject. These averaging times were chosen based on previous reports in the literature.
Statistical methods.
Measures of HRV were log10-transformed to improve normality and stabilize the variance. Linear regression analyses were carried out to evaluate the relation of HRV with each air pollutant. Cardiac medications were categorized as beta-blocker, calcium-channel blocker, and angiotensin-converting enzyme (ACE) inhibitor. After 14 subjects with missing values of the potential confounding factors were excluded, 497 subjects with complete data were available for the analyses.
The following variables were chosen a priori as clinically important predictors and included in the models: age, BMI, fasting blood glucose (FBG), cigarette smoking, use of cardiac medications, room temperature, season, and the lagged moving average of apparent temperature corresponding to the same moving average period for each air pollutant. MAP was also included because this changed the estimated effect of some air pollutants by more than 10%. To model the nonlinear association of apparent temperature with HRV, we used a cubic spline with 3 degrees of freedom (df).
We estimated the percent change in each HRV parameter for 1 SD increase for each pollutant as [10(β × SD) – 1] × 100%, with 95% confidence intervals (CI) {10[SD × (β± 1.96 × SE)] – 1} × 100%, where βand SE are the estimated regression coefficient and its standard error. To test whether observed associations in single-pollutant models were robust to inclusion of another pollutant, two-pollutant models were fitted. To assess modifying effects of hypertension, IHD, diabetes or use of cardiac/antihypertensive medications, we ran separate regressions stratified by those variables and compared the percent changes of each pollutant. We also ran regression models including interaction terms.
Results
Table 1 shows the demographic and clinical characteristics and HRV measurements of the subjects. The study participants were all male, with average age of 72.7 years (SD = 6.6 years). Seventy-two participants had diabetes (14.5%) on the basis of previously mentioned criteria. Hypertension and IHD prevalences were 67.4 and 28.6%, respectively. People with hypertension were older, had higher levels of BMI and FBG, and were more likely to have IHD, have diabetes, and be taking hypertension medications.
Air pollution and temperature levels are summarized in Table 2. The median time of ECG monitoring was 1000 hr. Levels of all pollutants except O3 decreased after peaking around 0700 hr. All air pollution concentrations during the study period were within the National Ambient Air Quality Standards (U.S. EPA 2004).
Of the air pollutants examined, only PM2.5 and O3 showed several significant associations with the HRV outcomes. Table 3 presents the estimated percent changes of HRV in single- and two-pollutant models for various lags of PM2.5 and O3. After adjusting for potential confounders, HF decreased by 13.2% (95% CI, –1.0% to 25.4%) and LF:HF ratio increased by 14.5% (95% CI, 2.9–27.5%) per SD (8.0 μg/m3) increase in the 24-hr moving average of PM2.5. We saw stronger associations with the 48-hr PM2.5: a 20.8% (95% CI, 4.6–34.2%) decrease in HF and an 18.6% (95% CI, 4.1–35.2%) increase in LF:HF ratio per 8.0-μg/m3 increase. We observed a reduction in LF of 11.5% (95% CI, 0.4–21.3%) associated with 1 SD (13 ppb) increment in the 4-hr O3, which was similar in magnitude but only marginally significant with a 24-hr average. In two-pollutant models, the magnitudes of the percent changes for both PM2.5 and O3 diminished slightly.
We found no significant association of HRV with PN, NO2, SO2, and CO for any of the exposure averaging periods. For brevity and comparability, Table 4 presents the HRV associations using the averaging periods for gaseous pollutants that showed the strongest effect for O3 (4 hr), and the 48-hr averaging period for PN and BC to correspond with the strongest PM2.5 effects. An SD (0.47 μg/m3) elevation in 48-hr BC was associated with a 13.2% (95% CI, –1.1 to 29.6%) increase in the LF:HF ratio. The point estimates for associations between PN and BC, and HRV measures were negative, but gaseous pollutants (SO2 and CO) were positively related.
We also conducted stratified analyses by IHD, hypertension, and diabetes status (Table 5). The associations of all HRV indices with PM2.5 and O3 were stronger in people with IHD. People with IHD showed 2-fold reductions of SDNN in relation to 48-hr PM2.5 compared with people without IHD. The interaction between 4-hr O3 and IHD was statistically significant for SDNN (p = 0.02 for the interaction term), HF (p = 0.01), and LF (p = 0.004). We also observed consistently stronger associations between all HRV indices and PM2.5 and O3 among people with hypertension. The associations observed in SDNN and LF with PM2.5 were stronger in people with diabetes, with almost 4-fold higher percent changes. However, diabetes did not modify the effect of O3 on HRV.
We assessed whether each antihypertensive medication modified the effects of PM2.5 and O3 on HRV (Table 6). We found a significant interaction between use of calcium-channel blocker and PM2.5 for LF (p = 0.04). Moreover, subjects who were not taking a calcium-channel blocker showed larger reductions in SDNN and LF in relation to O3. In particular, the association of O3 exposure with reduced LF in the full cohort seems to be driven by the subjects not taking calcium-channel blockers, with a substantial (although imprecisely estimated) increase in LF associated with O3 exposure in subjects on the drug. As a result of this effect on LF as well as HF, a marginally significant association was seen between O3 and SDNN (total HRV) as well.
We found no significant interaction between PM2.5 and O3, and use of beta-blocker or ACE inhibitor. However, the effect of both pollutants on LF was substantially reduced by beta-blocker drugs. In those taking beta-blockers, the decrease in HF was larger than that in LF in relation to PM2.5, compared with those who had never taken those medications. Thus, a larger increase in LF:HF ratio was observed in participants who were taking beta-blocker. However, the association with ACE inhibitors was opposite: There was a larger increase in LF:HF ratio associated with PM2.5 among those not taking that medication.
Discussion
This study is consistent with previous evidence that PM and O3 are associated with decreased HRV, particularly for PM and HF, a parasympathetic (vagal) modulation of the heart. The associations of HRV were strongest with the 48-hr moving averages of particles, but O3 had a shorter-term impact (4 hr and 24 hr). Furthermore, subjects with IHD and hypertension appeared to have larger reductions in HRV measures in relation to both PM2.5 and O3 exposures. People with diabetes had larger decreases of SDNN and LF associated with PM2.5. In addition, we found evidence for an association with BC, a marker of traffic particles.
When we examined medications, calcium-channel blockers had the most profound effect on the pollution associations, particularly for O3. This modification was primarily on LF, suggesting that this drug is blocking effects of pollution on the sympathetic pathway. If anything, the parasympathetic response was enhanced in these subjects. As expected, beta-blockers seemed to reduce the LF response of both pollutants. By contrast, use of ACE inhibitors did not consistently or significantly modify pollution effects. Drug use patterns in these subgroups are related to underlying conditions, thus limiting the interpretability of these results. Nevertheless, they suggest that air pollution has the ability to affect both sympathetic and parasympathetic pathways. The sympathetic response seems mediated by pathways related to calcium flux into cells, whereas the parasympathetic response seems likely to be due to other mechanisms.
Previous studies have consistently reported PM associations with decreased HRV in older adults (Creason et al. 2001; Gold et al. 2000; Holguin et al. 2003; Liao et al. 1999, 2004; Pope et al. 1999, 2004) (Table 7). Our results are consistent with those. For example, estimated decreases in HF resulting from an exposure to a PM2.5 increment of 10 μg/m3 in the previous studies were 24.1, 14.9, 19.3, and 5.1%. The last result is for a 10-μg/m3 increase in PM10 and is not directly comparable. We found a 16.2% reduction. Given the CIs (Table 7), these look fairly similar.
Three studies also evaluated the effect of O3 on cardiac autonomic function, primarily HF (Gold et al. 2000; Holguin et al. 2003; Liao et al. 2004). The difference in measuring times used in the studies preclude quantitative comparisons of results, but there was substantial variability. In the present study, O3-related decreases in HF ranged from 2.6 to 11.1% depending on choice of moving averages of O3, but all estimates were insignificant.
Current knowledge about pathophysiologic mechanisms that connect air pollution exposure and alterations in the autonomic nervous system is limited. One plausible mechanism is that inhalation of PM causes oxidative stress directly or via acute pulmonary inflammation. Oxidative stress in the lungs seems to induce proinflammatory mediators, such as cytokines (Donaldson et al. 2001), to increase extracellular calcium influx possibly through activation of calcium channels in the plasma membrane (Stone et al. 2000), and to inactivate nitric oxide (Thomas et al. 2001). These effects are considered to cause an increase in sympathetic and a reduction in vagal tone (Aronson et al. 2001; Chowdhary et al. 2002; Rodenbaugh et al. 2003), which may be linked with cardiac events, such as ventricular arrhythmias and myocardial infarction. In general, we find air pollution associated with greater reductions in vagal tone than in sympathetic activity.
A study from the Utah Valley (USA) found positive associations between PM10 and r-MSSD (Pope et al. 1999). Additionally, dogs exposed to concentrated ambient air particles showed significantly higher HF and LF compared with filtered air exposure (Godleski et al. 2000). Godleski et al. (2000) argued that too much elevation in parasympathetic stimulation may deteriorate cardiac status and result in a fatal bradyarrhythmia. A large follow-up study in Rotterdam, the Netherlands, found that elderly subjects in the highest quartile as well as the lowest quartile of SDNN had significantly increased risks for cardiac mortality, suggesting that in the elderly, alterations in HRV in either direction might be adverse (de Bruyne et al. 1999).
Few previous studies have evaluated modifiers of the air pollution–HRV association. Our results agree with two such studies, which showed larger decreases in HRV among people with hypertension (Holguin et al. 2003; Liao et al. 2004). Although dysregulation of the autonomic nervous system plays a role in the pathogenesis of hypertension, the causal mechanism of modification by hypertension has not been discussed. Hypertension is associated with lower baseline HRV and endothelial dysfunction (John and Schmieder 2003; Schroeder et al. 2003; Singh et al. 1998). Hypertensive people may have higher levels of oxidative-stress–induced inflammatory responses. These existing impairments may make hypertensive people less able to accommodate the additional oxidative stress related to air pollution exposure and therefore could explain the enhanced effect on HRV.
We observed a larger reduction in HRV among people with diabetes compared with subjects without diabetes. Diabetes is known to be associated with low autonomic function (Burger and Aronson 2001; Singh et al. 2000), and has been reported to modify the association of PM with both hospital admissions (Zanobetti and Schwartz 2001) and deaths (Bateson and Schwartz 2004). Several epidemiologic studies showed that LF power, which reflects mainly sympathetic modulation, was more influenced by diabetes than any other HRV index (Burger and Aronson 2001; Singh et al. 2000). The present study also showed that decreases in LF in relation to PM2.5 exposure were larger in people with diabetes than those in people without diabetes (−19.1 vs. −5.0%). Both diabetes and PM have been associated with oxidative-stress–induced inflammation and endothelial and autonomic dysfunctions. Therefore, susceptible individuals who have preexisting inflammation due to diabetes may be more responsive to airborne particles exposure.
We found the strongest effects of PM2.5 and O3 in 48-hr and 4-hr moving averages, respectively. The rationale for the moving average model is that air pollution can lead to adverse health events occurring not only on the same day but also on several subsequent days (Schwartz 2000). Hence, the response to an acute pollution exposure could be distributed over a number of days. Because hourly measured concentrations of air pollution were available, we could evaluate several lagged models with end times matched to each participant’s ECG measure, an improvement over traditional approaches using fixed calendar days. We found stronger particle pollutant associations in longer lagged models but stronger O3 associations in shorter ones.
A potential limitation of this study is that we measured ECG once for each subject, so subject-specific variation of HRV measures may not be ruled out as a potential confounder. However, this variation would have to be correlated with air pollution levels for it to confound the observed associations. We collected information on many possible factors that would affect autonomic function, but the covariates included in the model may not cover all predictors of individual variations of HRV. A longitudinal design would provide for better adjustment of within-subject variation in the observed associations and allow examination of differences in baseline autonomic function over time.
In this study, many potential confounding factors were included in the model. BMI; blood total cholesterol, high-density lipoprotein, and triglyceride levels; alcohol consumption; and respiratory and cardiovascular disease history did not confound the association between air pollution and HRV. We also measured the ECG at a stable temperature and adjusted for the temperature of the room where the ECG was taken, as well as for ambient meteorologic factors, including apparent temperature and season. Therefore, the observed associations are less likely to reflect bias due to the confounding factors.
Although we did not conduct personal exposure monitoring during the time of the test, the monitoring site was relatively close (1 km) to the examination site. Moreover, evidence suggests that ambient measures of PM have relatively uniform spatial distribution across urban areas and the longitudinal correlation between daily changes in exposure and daily changes in ambient concentrations are high (Sarnat et al. 2000). Therefore, PM concentrations at the monitoring site should be a good surrogate of PM exposure.
This study cohort consists of all males and almost all whites. Sex and race may be important determinants of HRV as well as modifiers of the association between air pollution and HRV, as was observed by Liao et al. (2004).
This population-based study suggests that short-term exposures to PM2.5 and O3 are predictors of alterations in cardiac autonomic function as measured by HRV among older adults. Persons with IHD, hypertension, and diabetes appear to be more susceptible to autonomic dysfunction related to PM2.5 exposure. The consistency of the effect modification observed in this and other studies strengthens evidence that these conditions mark susceptibility to air pollution exposure and provides new information to guide research on underlying biologic mechanisms.
Table 1 Characteristics [mean ± SD or n (%)] of the study subjects.
Hypertension
Variable All subjects (n = 497) Without (n = 162) With (n = 335)
Age (years) 72.7 ± 6.6 71.2 ± 6.5 73.4 ± 6.5
BMI (kg/m2) 28.3 ± 4.1 27.2 ± 3.9 28.7 ± 4.1
Systolic blood pressure (mm Hg) 131.4 ± 16.3 125.0 ± 10.5 134.5 ± 17.7
Diastolic blood pressure (mm Hg) 75.7 ± 9.4 75.3 ± 7.1 75.9 ± 10.3
MAP (mm Hg) 94.3 ± 10.2 91.9 ± 7.2 95.5 ± 11.2
Heart rate (beat/min) 70.7 ± 6.7 71.4 ± 5.8 70.4 ± 7.1
Fasting blood glucose (mg/dL) 108.0 ± 29.0 103.1 ± 22.3 110.3 ± 31.5
Cholesterol (mg/dL) 197.0 ± 37.6 207.1 ± 36.2 192.1 ± 37.4
High-density lipoprotein (mg/dL) 49.7 ± 13.5 52.9 ± 15.3 48.1 ± 12.3
Triglycerides (mg/dL) 129.8 ± 71.5 122.0 ± 66.7 133.5 ± 73.5
Smoking status [n (%)]
Never smoker 160 (32.2) 58 (35.8) 102 (30.4)
Former smoker 311 (62.6) 93 (57.4) 218 (65.1)
Current smoker 26 (5.2) 11 (6.8) 15 (4.5)
Alcohol intake (≥2 drinks/day) [n (%)] 96 (19.3) 30 (18.5) 66 (19.7)
Diabetes mellitus [n (%)] 72 (14.5) 14 (8.6) 58 (17.3)
IHD history [n (%)] 142 (28.6) 16 (9.9) 126 (37.6)
Use of beta-blocker [n (%)] 163 (32.8) 0 (0.0) 163 (48.7)
Use of calcium-channel blocker [n (%)] 70 (14.1) 0 (0.0) 70 (20.9)
Use of ACE inhibitor [n (%)] 100 (20.1) 0 (0.0) 100 (29.9)
HRV
Log10 SDNN, msec 1.5 ± 0.25 1.5 ± 0.25 1.5 ± 0.25
Log10 HF, msec2 1.9 ± 0.66 1.8 ± 0.62 1.9 ± 0.68
Log10 LF, msec2 2.0 ± 0.52 2.0 ± 0.50 2.0 ± 0.54
Log10 LF:HF 0.10 ± 0.49 0.22 ± 0.47 0.04 ± 0.49
Table 2 Twenty-four–hour moving averages of outdoor air pollution and apparent temperature, and room temperature during the HRV measurement.
Mean ± SD Range
PM2.5 (μg/m3) 11.4 ± 8.0 0.45–62.9
PN concentration (no./cm3) 28,942 ± 13,527 8,538–74,675
BC (μg/m3) 0.92 ± 0.47 0.19–2.6
O3 (ppb) 23.0 ± 13.0 2.6–84.5
NO2 (ppb) 22.7 ± 6.2 7.0–40.1
SO2 (ppb) 4.9 ± 3.4 0.95–24.7
CO (ppm) 0.50 ± 0.24 0.13–1.8
Apparent temperature (°C) 11.4 ± 9.9 −5.2–35.6
Room temperature (°C) 24.5 ± 1.4 20.0–30.0
Table 3 Estimated percent changes (95% CIs) in HRV in single (PM2.5 or O3) and two-pollutant (PM2.5 and O3) models for PM2.5 and O3 in various lagged moving averages.
Outcome, model, predictor 4-hr moving average 24-hr moving average 48-hr moving average
Log10 SDNN
Single-pollutant
PM2.5 −0.1 (−5.0 to 4.9) −2.2 (−7.7 to 3.6) −5.4 (−11.8 to 1.5)
O3 −3.6 (−8.9 to 2.0) −5.3 (−11.7 to 1.7) −2.2 (−10.0 to 6.1)
Two-pollutant
PM2.5 0.2 (−4.8 to 5.5) −0.3 (−6.6 to 6.3) −5.0 (−12.2 to 2.7)
O3 −3.6 (−9.0 to 2.1) −5.1 (−12.2 to 2.5) −0.2 (−8.8 to 9.1)
Log10 HF
Single-pollutant
PM2.5 −6.3 (−17.8 to 6.7) −13.2 (−25.4 to 1.0)* −20.8 (−34.2 to −4.6)**
O3 −9.3 (−21.8 to 5.3) −11.1 (−26.2 to 7.1) −2.6 (−21.6 to 21.1)
Two-pollutant
PM2.5 −5.1 (−17.1 to 8.6) −8.6 (−22.9 to 8.3) −20.3 (−35.2 to −2.1)**
O3 −9.4 (−22.1 to 5.4) −7.9 (−24.9 to 13.0) 6.5 (−15.9 to 34.9)
Log10 LF
Single-pollutant
PM2.5 5.7 (−4.6 to 17.1) −0.6 (−11.9 to 12.1) −6.0 (−18.9 to 8.9)
O3 −11.5 (−21.3 to −0.4)** −10.9 (−23.1 to 3.3) −6.3 (−21.1 to 11.2)
Two-pollutant
PM2.5 6.2 (−4.6 to 18.1) 3.9 (−9.2 to 18.8) −3.6 (−18.1 to 13.5)
O3 −11.3 (−21.3 to −0.1)** −12.2 (−25.3 to 3.2) −5.0 (−21.2 to 14.6)
Log10 (LF:HF)
Single-pollutant
PM2.5 12.9 (3.0 to 23.7)** 14.5 (2.9 to 27.5)** 18.6 (4.1 to 35.2)**
O3 −2.4 (−12.1 to 8.3) 0.2 (−12.1 to 14.2) −3.9 (−17.4 to 11.9)
Two-pollutant
PM2.5 11.9 (1.8 to 22.9)** 13.7 (0.9 to 28.0)** 21.0 (4.8 to 39.8)**
O3 −2.1 (−12.0 to 8.8) −4.7 (−17.4 to 9.9) −10.7 (−24.4 to 5.3)
Coefficients are expressed as percent change per 1 SD (8 μg/m3 for PM2.5 and 13 ppb for O3), adjusting for age; BMI; MAP; FBG; cigarette smoking; use of beta-blocker, calcium-channel blocker, and/or ACE inhibitor; room temperature; season; and cubic smoothing splines (3 df) for moving averages of apparent temperature corresponding for the predictor.
* p < 0.1.
** p < 0.05.
Table 4 Estimated percent changes (95% CIs) in HRV for other pollutants.
48-hr moving average
4-hr moving average
Outcome PN BC NO2 SO2 CO
Log10 SDNN −0.7 (−9.3 to 8.9) −3.4 (−10.2 to 3.9) 1.2 (−3.1 to 5.7) 2.3 (−1.7 to 6.4) 2.0 (−2.9 to 7.3)
Log10 HF −4.1 (−24.7 to 22.1) −13.8 (−28.9 to 4.4) −0.9 (−11.7 to 11.2) 5.6 (−4.9 to 17.3) 8.8 (−4.6 to 24.1)
Log10 LF −7.0 (−23.2 to 12.6) −2.4 (−16.2 to 13.6) 1.1 (−7.7 to 10.7) 2.2 (−5.9 to 11.1) 3.2 (−7.0 to 14.6)
Log10 (LF:HF) −3.0 (−18.2 to 15.0) 13.2 (−1.1 to 29.6)* 2.0 (−5.9 to 10.6) −3.2 (−10.1 to 4.2) −5.1 (−13.5 to 4.1)
Coefficients are expressed as percent change per 1 SD (13,527/cm3 for PN, 0.47 μg/m3 for BC, 6.2 ppb for NO2, 3.4 ppb for SO2, and 0.24 ppm for CO) adjusting for age; BMI; MAP; FBG; cigarette smoking; use of beta-blocker, calcium-channel blocker, and/or ACE inhibitor; room temperature; season; and cubic smoothing splines (3 df) for moving averages of apparent temperature corresponding for the predictor.
* p < 0.1.
Table 5 Estimated percent changes (95% CIs) in HRV associated with 48-hr PM2.5 and 4-hr O3 stratified by hypertension, IHD, and diabetes.
Hypertension
IHD
Diabetes
Outcome, predictor Without (n = 162)a With (n = 335)a Without (n = 355) With (n = 142) Without (n = 425)b With (n = 72)b
Log10 SDNN
PM2.5 −2.4 (−13.2 to 9.8) −8.1 (−15.7 to 0.3)* −3.5 (−11.1 to 4.7) −8.4 (−20.4 to 5.5) −4.7 (−11.4 to 2.6) −16.6 (−36.3 to 9.2)
O3 1.8 (−7.4 to 11.8) −5.5 (−12.1 to 1.5)* −1.0 (−7.3 to 5.8) −8.1 (−17.7 to 2.7) −5.7 (−11.1 to 0.1)* 4.0 (−17.3 to 30.6)
Log10 HF
PM2.5 −14.4 (−36.8 to 15.9) −24.5 (−40.4 to −4.5)** −18.0 (−33.7 to 1.5)* −24.1 (−48.3 to 11.4) −20.8 (−34.8 to −3.9)** −17.0 (−58.3 to 65.1)
O3 8.8 (−14.7 to 38.7) −17.0 (−31.6 to 0.7)* 1.6 (−14.4 to 20.5) −29.4 (−47.6 to −4.9)** −13.7 (−26.3 to 1.0)* 5.7 (−40.7 to 88.1)
Log10 LF
PM2.5 −2.9 (−23.5 to 23.2) −10.5 (−25.8 to 7.9) −7.0 (−21.3 to 9.9) 0.5 (−26.7 to 37.7) −5.0 (−18.6 to 10.8) −19.1 (−54.2 to 42.9)
O3 −5.4 (−21.6 to 14.1) −12.6 (−25.0 to 1.9)* −4.8 (−16.7 to 8.8) −25.8 (−41.9 to −5.3)** −13.2 (−23.4 to −1.7)** −8.4 (−41.7 to 44.1)
Log10 LF:HF
PM2.5 13.5 (−9.4 to 42.1) 18.6 (0.4 to 40.0)** 13.3 (−2.4 to 31.6) 32.5 (0.5 to 74.7)* 20.0 (4.8 to 37.5)** −2.6 (−39.4 to 56.6)
O3 −13.1 (−27.0 to 3.5) 5.3 (−8.2 to 20.8) −6.3 (−16.7 to 5.5) 5.1 (−15.9 to 31.4) 0.6 (−9.9 to 12.4) −13.3 (−41.1 to 27.6)
Coefficients are expressed as percent change per 1 SD (8 μg/m3 for PM2.5 and 13 ppb for O3) adjusting for age; BMI; MAP; FBG; cigarette smoking; use of beta-blocker, calcium-channel blocker, and/or ACE inhibitor; room temperature; season; and cubic smoothing splines (3 df) for moving averages of apparent temperature corresponding for the predictor.
a MAP and use of beta-blocker, calcium-channel blocker, and/or ACE inhibitor not included in the model.
b FBG not included in the model.
* p < 0.1.
** p < 0.05.
Table 6 Estimated percent changes (95% CIs) in HRV associated with 48-hr PM2.5 and 4-hr O3 stratified by use of beta-blocker, calcium-channel blocker, and ACE inhibitor.
Use of beta-blocker
Use of calcium channel blocker
Use of ACE inhibitor
Outcome, predictor No (n = 334)a Yes (n = 163)a No (n = 427)b Yes (n = 70)b No (n = 397)c Yes (n = 100)c
Log10 SDNN
PM2.5 −4.6 (−12.4 to 4.0) −7.5 (−18.5 to 5.1) −6.9 (−13.8 to 0.6)* 2.8 (−14.3 to 23.3) −5.1 (−12.0 to 2.4) −1.8 (−19.4 to 19.6)
O3 −5.0 (−11.2 to 1.6) −0.5 (−11.1 to 11.4) −4.9 (−10.6 to 1.3) 1.2 (−11.7 to 16.1) −2.8 (−8.7 to 3.4) −9.2 (−21.9 to 5.5)
Log10 HF
PM2.5 −17.8 (−34.2 to 2.6)* −25.4 (−47.3 to 5.7) −23.1 (−37.1 to −6.1)** −15.6 (−49.5 to 41.2) −23.5 (−37.4 to −6.5)** 8.7 (−34.2 to 79.7)
O3 −7.0 (−21.7 to 10.6) −14.8 (−37.1 to 15.5) −10.9 (−24.2 to 4.8) −9.7 (−38.4 to 32.4) −7.0 (−21.0 to 9.6) −23.7 (−48.2 to 12.4)
Log10 LF
PM2.5 −11.3 (−25.3 to 5.4) −0.5 (−25.0 to 32.0) −9.3 (−22.4 to 6.0) −0.6 (−36.5 to 55.8) −6.0 (−19.6 to 9.8) 8.8 (−29.4 to 67.7)
O3 −13.8 (−24.5 to −1.5)** −8.1 (−28.3 to 17.8) −14.4 (−24.5 to −2.9)** 11.6 (−19.8 to 55.4) −11.3 (−21.8 to 0.6)* −12.3 (−37.0 to 22.2)
Log10 LF:HF
PM2.5 8.0 (−8.2 to 27.0) 33.4 (6.5 to 67.0)** 17.9 (2.5 to 35.7)** 17.8 (−19.0 to 71.4) 22.8 (6.7 to 41.3)** 0.1 (−30.1 to 43.5)
O3 −7.3 (−18.2 to 5.0) 7.8 (−11.5 to 31.3) −3.9 (−14.2 to 7.6) 23.5 (−5.8 to 62.0) −4.7 (−15.0 to 6.8) 15.0 (−13.1 to 52.3)
Coefficients are expressed as percent change per 1 SD (8 μg/m3 for PM2.5 and 13 ppb for O3) adjusting for age; BMI; MAP; FBG; cigarette smoking; use of beta-blocker, calcium-channel blocker, and/or ACE inhibitor; room temperature; season; and cubic smoothing splines (3 df) for moving averages of apparent temperature corresponding for the predictor.
a Use of beta-blocker not included in the model.
b Use of calcium-channel blocker not included in the model.
c Use of ACE inhibitor not included in the model.
* p < 0.1.
** p < 0.05.
Table 7 Summary of the studies that assessed the association between ambient PM and HRV.
Reference Design Population (no./mean or age range/study area) Ambient PM level (μg/m3) Covariates adjusted Main resultsa
Liao et al. 1999 Longitudinal 26 volunteers (3 weeks) Mean, 81 years Baltimore 24-hr PM2.5, 16.1 ± 6.9 Age, sex, cardiovascular health status SDNN, −8.8 (−14.9 to 0.0) HF, −24.1 (−42.5 to 0.0) LF, −22.4 (−39.7 to 0.0)
Pope et al. 1999 Longitudinal 7 (29 person days) Mean, 70 years Utah Valley PM10, no concentration reported Barometric pressure at 1700 hr mountain time, HR SDNN, −1.4 (−2.1 to −0.6) SDANN, −1.4 (−2.4 to −0.5) r-MSSD, 1.9 (−0.2 to 3.9)
Gold et al. 2000 Longitudinal 21 (163 observation) Range, 53−87 years Boston 4-hr PM2.5, 15.3 (Range, 2.9–48.6) Uses of calcium or beta-blockers, ACE inhibitor At slow breathing: SDNN, −2.9 (−7.8 to 2.1) r-MSSD, −10.6 (−18.3 to −2.9)
Creason et al. 2001 Longitudinal 56 nonsmokers (4 weeks) Mean, 82 years Baltimore 24-hr PM2.5, 20.5 (Range, 7.8–45.3) Age, sex, CV status, trend, maximum temperature, mean DPT HF, −14.9 (−25.9 to −4.5) LF, −12.9 (−20.6 to −2.3)
Holguin et al. 2003 Longitudinal 34 (384 observations) Mean, 79 years Mexico City 24-hr PM2.5, 30.4 ± 9.9 Age, HR, hypertension HF, −19.3 (−29.2 to −7.7) LF, −8.4 (−19.3 to 0.2) LF:HF, 24.2 (−7.5 to 66.7)
Pope et al. 2004 Longitudinal 88 (250 observations) Range, 54–89 years Utah 24-hr PM2.5, 23.7 ± 20.2 Interactive spline smooths for temperature, RH, HR SDNN, −2.7 (−3.9 to −1.4) SDANN, −1.7 (−3.3 to −0.2) r-MSSD, −6.1 (−9.2 to −3.0)
Liao et al. 2004 Cross-sectional 4,899 Mean, 62 years ARIC Study 24-hr PM10, 24.3 ± 11.5 Age, sex, ethnicity, BMI, education, smoking, CV medications, CHD, diabetes, hypertension, HR, season, temperature, RH, sky cover SDNN, −2.4 (−3.8 to −1.0) HF, −5.1 (−8.0 to −2.1) LF, −1.7 (−4.7 to 1.3)
Present study Cross-sectional 497 males Mean, 73 years Normative Aging Study in Boston 24-hr PM2.5, 11.4 ± 8.0 Age, MAP, smoking, FBG, use of ACE inhibitor, room temperature, apparent temperature, season SDNN, −2.7 (−9.5 to 4.6) HF, −16.2 (−30.7 to 1.3) LF, −0.7 (−14.6 to 15.4) LF:HF, 18.5 (3.7 to 35.4)
Abbreviations: SDANN, standard deviation of all 5-min NN interval means; CHD, coronary heart disease; CV, cardiovascular disease; HR, heart rate; DPT, dew-point temperature; RH, relative humidity.
a Percent change (95% CI) for an increase of 10 μg/m3 in PM2.5.
==== Refs
References
Allen G Sioutas C Koutrakis P Reiss R Lurmann FW Roberts PT 1997 Evaluation of the TEOM method for measurement of ambient particulate mass in urban areas J Air Waste Manage Assoc 47 682 689
Aronson D Mittleman MA Burger AJ 2001 Interleukin-6 levels are inversely correlated with heart rate variability in patients with decompensated heart failure J Cardiovasc Electrophysiol 12 294 300 11291801
Bateson TF Schwartz J 2004 Who is sensitive to the effects of particulate air pollution on mortality? A case-crossover analysis of effect modifiers Epidemiology 15 143 149 15127905
Bell B Rose C Damon A 1972 The Normative Aging Study: an interdisciplinary and longitudinal study of health and aging Aging Hum Dev 3 4 17
Burger AJ Aronson D 2001 Effect of diabetes mellitus on heart rate variability in patients with congestive heart failure Pacing Clin Electrophysiol 24 53 59 11227970
Chowdhary S Ng GA Nuttall SL Coote JH Ross HF Townend JN 2002 Nitric oxide and cardiac parasympathetic control in human heart failure Clin Sci (Lond) 102 397 402 11914101
Creason J Neas L Walsh D Williams R Sheldon L Liao D 2001 Particulate matter and heart rate variability among elderly retirees: the Baltimore 1998 PM study J Expo Anal Environ Epidemiol 11 116 122 11409004
de Bruyne MC Kors JA Hoes AW Klootwijk P Dekker JM Hofman A 1999 Both decreased and increased heart rate variability on the standard 10-second electrocardiogram predict cardiac mortality in the elderly: the Rotterdam Study Am J Epidemiol 150 1282 1288 10604770
Dekker JM Schouten EG Klootwijk P Pool J Swenne CA Kromhout D 1997 Heart rate variability from short electrocardiographic recordings predicts mortality from all causes in middle-aged and elderly men: the Zutphen Study Am J Epidemiol 145 899 908 9149661
Devlin RB Ghio AJ Kehrl H Sanders G Cascio W 2003 Elderly humans exposed to concentrated air pollution particles have decreased heart rate variability Eur Respir J Suppl 40 76s 80s 12762579
Donaldson K Stone V Seaton A MacNee W 2001 Ambient particle inhalation and the cardiovascular system: potential mechanisms Environ Health Perspect 109 suppl 4 523 527 11544157
Gerritsen J Dekker JM TenVoorde BJ Kostense PJ Heine RJ Bouter LM 2001 Impaired autonomic function is associated with increased mortality, especially in subjects with diabetes, hypertension, or a history of cardiovascular disease: the Hoorn Study Diabetes Care 24 1793 1798 11574444
Godleski JJ Verrier RL Koutrakis P Catalano P Coull B Reinisch U 2000 Mechanisms of morbidity and mortality from exposure to ambient air particles Res Rep Health Eff Inst 91 5 88 10817681
Gold DR Litonjua A Schwartz J Lovett E Larson A Nearing B 2000 Ambient pollution and heart rate variability Circulation 101 1267 1273 10725286
Goldberg MS Burnett RT Bailar JC III Brook J Bonvalot Y Tamblyn R 2001 The association between daily mortality and ambient air particle pollution in Montreal, Quebec. 2. Cause-specific mortality Environ Res 86 26 36 11386738
Holguin F Tellez-Rojo MM Hernandez M Cortez M Chow JC Watson JG 2003 Air pollution and heart rate variability among the elderly in Mexico City Epidemiology 14 521 527 14501266
John S Schmieder RE 2003 Potential mechanisms of impaired endothelial function in arterial hypertension and hyper-cholesterolemia Curr Hypertens Rep 5 199 207 12724051
Lampert R Ickovics JR Viscoli CJ Horwitz RI Lee FA 2003 Effects of propranolol on recovery of heart rate variability following acute myocardial infarction and relation to outcome in the Beta-Blocker Heart Attack Trial Am J Cardiol 91 137 142 12521623
Liao D Creason J Shy C Williams R Watts R Zweidinger R 1999 Daily variation of particulate air pollution and poor cardiac autonomic control in the elderly Environ Health Perspect 107 521 525 10378998
Liao D Duan Y Whitsel EA Zheng ZJ Heiss G Chinchilli VM 2004 Association of higher levels of ambient criteria pollutants with impaired cardiac autonomic control: a population-based study Am J Epidemiol 159 768 777 15051586
Magari SR Hauser R Schwartz J Williams PL Smith TJ Christiani DC 2001 Association of heart rate variability with occupational and environmental exposure to particulate air pollution Circulation 104 986 991 11524390
Magari SR Schwartz J Williams PL Hauser R Smith TJ Christiani DC 2002 The association of particulate air metal concentrations with heart rate variability Environ Health Perspect 110 875 880 12204821
Mann JK Tager IB Lurmann F Segal M Quesenberry CP Jr Lugg MM 2002 Air pollution and hospital admissions for ischemic heart disease in persons with congestive heart failure or arrhythmia Environ Health Perspect 110 1247 1252 12460805
O’Neill MS Zanobetti A Schwartz J 2003 Modifiers of the temperature and mortality association in seven US cities Am J Epidemiol 157 1074 1082 12796043
Pope CA III Burnett RT Thun MJ Calle EE Krewski D Ito K 2002 Lung cancer, cardiopulmonary mortality, and long-term exposure to fine particulate air pollution JAMA 287 1132 1141 11879110
Pope CA III Eatough DJ Gold DR Pang Y Nielsen KR Nath P 2001 Acute exposure to environmental tobacco smoke and heart rate variability Environ Health Perspect 109 711 716 11485870
Pope CA III Hansen ML Long RW Nielsen KR Eatough NL Wilson WE 2004 Ambient particulate air pollution, heart rate variability, and blood markers of inflammation in a panel of elderly subjects Environ Health Perspect 112 339 345 14998750
Pope CA III Verrier RL Lovett EG Larson AC Raizenne ME Kanner RE 1999 Heart rate variability associated with particulate air pollution Am Heart J 138 890 899 10539820
Rodenbaugh DW Collins HL Nowacek DG DiCarlo SE 2003 Increased susceptibility to ventricular arrhythmias is associated with changes in Ca2+ regulatory proteins in paraplegic rats Am J Physiol Heart Circ Physiol 285 H2605 H2613 12881214
Samet JM Dominici F Curriero FC Coursac I Zeger SL 2000 Fine particulate air pollution and mortality in 20 U.S. cities, 1987–1994 N Engl J Med 343 1742 1749 11114312
Sarnat JA Koutrakis P Suh HH 2000 Assessing the relationship between personal particulate and gaseous exposures of senior citizens living in Baltimore, MD J Air Waste Manag Assoc 50 1184 1198 10939211
Schroeder EB Liao D Chambless LE Prineas RJ Evans GW Heiss G 2003 Hypertension, blood pressure, and heart rate variability. The Atherosclerosis Risk in Communities (ARIC) Study Hypertension 42 1106 1111 14581296
Schwartz J 1999 Air pollution and hospital admissions for heart disease in eight U.S. counties Epidemiology 10 17 22 9888275
Schwartz J 2000 The distributed lag between air pollution and daily deaths Epidemiology 11 320 326 10784251
Shurtleff D 1974. Some Characteristics Related to the Incidence of Cardiovascular Disease and Death: Framingham Study, 18-Year Follow-up. Bethesda, MD:U.S. Department of Health, Education, and Welfare Publication.
Singh JP Larson MG O’Donnell CJ Wilson PF Tsuji H Lloyd-Jones DM 2000 Association of hyperglycemia with reduced heart rate variability (the Framingham Heart Study) Am J Cardiol 86 309 312 10922439
Singh JP Larson MG Tsuji H Evans JC O’Donnell CJ Levy D 1998 Reduced heart rate variability and new-onset hypertension: insights into pathogenesis of hypertension: the Framingham Heart Study Hypertension 32 293 297 9719057
Stone V Tuinman M Vamvakopoulos JE Shaw J Brown D Petterson S 2000 Increased calcium influx in a monocytic cell line on exposure to ultrafine carbon black Eur Respir J 15 297 303 10706495
Tapanainen JM Thomsen PE Kober L Torp-Pedersen C Makikallio TH Still AM 2002 Fractal analysis of heart rate variability and mortality after an acute myocardial infarction Am J Cardiol 90 347 352 12161220
Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology 1996 Heart rate variability: standards of measurement, physiological interpretation and clinical use Circulation 93 1043 1065 8598068
Thomas GD Zhang W Victor RG 2001 Impaired modulation of sympathetic vasoconstriction in contracting skeletal muscle of rats with chronic myocardial infarctions: role of oxidative stress Circ Res 88 816 823 11325874
Tomiyama H Kimura Y Sakuma Y Shiojima K Yamamoto A Saito I 1998 Effects of an ACE inhibitor and a calcium channel blocker on cardiovascular autonomic nervous system and carotid distensibility in patients with mild to moderate hypertension Am J Hypertens 11 682 689 9657627
Townend JN Al-Ani M West JN Littler WA Coote JH 1995 Modulation of cardiac autonomic control in humans by angiotensin II Hypertension 25 1270 1275 7768573
Tsuji H Larson MG Venditti FJ Manders ES Evans JC Feldman CL 1996 Impact of reduced heart rate variability on risk for cardiac events: the Framingham Heart Study Circulation 94 2850 2855 8941112
U.S. EPA 2002. List of Designated Reference and Equivalent Method. Research Triangle Park, NC:U.S. Environmental Protection Agency. Available: http://www.epa.gov/ttnamti1/refllist.pdf [accessed 15 July 2004].
U.S. EPA 2004. National Ambient Air Quality Standards. Research Triangle Park, NC:U.S. Environmental Protection Agency. Available: http://www.epa.gov/air/criteria.html [accessed 15 July 2004].
Utell MJ Frampton MW Zareba W Devlin RB Cascio WE 2002 Cardiovascular effects associated with air pollution: potential mechanisms and methods of testing Inhal Toxicol 14 1231 1247 12454788
Zanobetti A Schwartz J 2001 Are diabetics more susceptible to the health effects of airborne particles? Am J Respir Crit Care Med 164 831 833 11549541
Zanobetti A Schwartz J 2002 Cardiovascular damage by airborne particles: are diabetics more susceptible? Epidemiology 13 588 592 12192230
|
15743719
|
PMC1253756
|
CC0
|
2021-01-04 23:40:57
|
no
|
Environ Health Perspect. 2005 Mar 6; 113(3):304-309
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7447
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.6933ehp0113-00031015743720ResearchArticlesThe Role of Syntrophic Associations in Sustaining Anaerobic Mineralization of Chlorinated Organic Compounds Becker Jennifer G. Berardesco Gina *Rittmann Bruce E. †Stahl David A. ‡Department of Civil and Environmental Engineering, Northwestern University, Evanston, Illinois, USAAddress correspondence to J.G. Becker, Department of Biological Resources Engineering, University of Maryland, Building 142, College Park, MD 20742-2315 USA. Telephone: (301) 405-1179. Fax: (301) 314-9023. E-mail:
[email protected] article is based on a presentation at the conference “Bioremediation and Biodegradation: Current Advances in Reducing Toxicity, Exposure and Environmental Consequences” (http://www-apps.niehs.nih.gov/sbrp/bioremediation.html) held 9–12 June 2002 in Pacific Grove, California, and sponsored by the NIEHS Superfund Basic Research Program. The overall focus of this conference was on exploring the research interfaces of toxicity reduction, exposure assessment, and evaluation of environmental consequences in the context of using state-of-the-art approaches to bioremediation and biodegradation. The Superfund Basic Research Program has a legacy of supporting research conferences designed to integrate the broad spectrum of disciplines related to hazardous substances.
*Present address: zuChem, Inc., Chicago, IL 60610 USA.
†Present address: Center for Environmental Biotechnology, Biodesign Institute, Arizona State University, Tempe, AZ 85287-5801 USA.
‡Present address: Department of Civil and Environmental Engineering, University of Washington, Seattle, WA 98195 USA.
We thank V. Denef for his contributions as a rapporteur at the conference. We also appreciate the assistance of the Clavey Road Wastewater Treatment Plant personnel in obtaining samples of the digester contents.
This research was supported by the U.S. Environmental Protection Agency Science to Achieve Results (S.T.A.R.) grant R823351 to D.A.S. and B.E.R.
The authors declare they have no competing financial interests.
3 2005 8 12 2004 113 3 310 316 23 12 2003 17 6 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Stable associations of syntrophic fermentative organisms and populations that consume fermentation products play key roles in the anaerobic biodegradation of chlorinated organic contaminants. The involvement of these syntrophic populations is essential for mineralization of chlorinated aromatic compounds under methanogenic conditions. The fermentative production of low levels of hydrogen (H2) can also be used to selectively deliver a limiting electron donor to dehalogenating organisms and achieve complete dehalogenation of chlorinated aliphatic contaminants such as tetrachloroethene. Thus, tracking the abundance of syntrophically coupled populations should aid in the development and monitoring of sustainable bioremediation strategies. In this study, two complementary nucleic acid–based methods were used to identify and assess relative changes or differences in the abundance of potentially important populations in complex anaerobic microbial communities that mineralized chlorinated aromatic compounds. Population dynamics were related to the consumption and production of key metabolic substrates, intermediates, and products. Syntrophus-like populations were detected in 3-chlorobenzoate–degrading communities derived from sediment or sludge digesters. In the presence of H2-consuming populations, characterized Syntrophus species ferment benzoate, a central intermediate in the anaerobic metabolism of 3-chlorobenzoate and 2-chlorophenol. A DNA probe that targeted characterized Syntrophus species was developed and used to quantify rRNA extracted from the 3-chlorobenzoate– and 2-chlorophenol–degrading communities. The level of rRNA targeted by the Syntrophus-specific probe tracked with the formation of benzoate during metabolism of the parent compounds. Hybridizations with an Archaea-specific probe and/or measurement of methane production demonstrated that methanogens directly benefited from the influx of benzoate-derived electron donors, and the activities of Syntrophus-like and methanogenic populations in the contaminant-degrading communities were closely linked.
2-chlorophenol3-chlorobenzoatebenzoatebioremediationmicrobial communitiesoligonucleotide probesreductive dechlorinationribosomal RNAsyntrophic associationsSyntrophus
==== Body
Microbiologists now recognize that the greater part of microbial diversity remains to be described, primarily because culture-based methods cannot provide an adequate census of community composition (Amann et al. 1995). This has severely restricted studies in both basic and applied microbial ecology. For example, researchers understand little about the complex and dynamic microbial processes associated with transformation of pollutants in the environment. Understanding how populations within microbial communities respond to and metabolize contaminants is key to predicting contaminant fate at sites undergoing intrinsic bioremediation and to optimizing engineered bioremediation approaches. The advent of explicit molecular methods has improved our ability to describe the microbial ecology of contaminated and other environments (Liu and Stahl 2002). However, linking changes in population structure with system-level processes remains challenging when the composition of the community is not known a priori and the function of individual populations cannot be studied in defined cultures.
In particular, little is known about the composition of anaerobic microbial communities that degrade chlorinated organic compounds in situ. Culture-based description of these communities is hampered by at least two factors. First, syntrophic population associations are a hallmark of anaerobic microbial communities in general. The interdependence of syntrophic partners severely complicates their cultivation (Schink 1997). Second, the enrichment of bacteria that utilize chlorinated organic compounds such as tetrachloroethene (perchloroethylene, PCE) as the terminal electron acceptor in metabolic processes (i.e., dehalorespiration) can pose numerous challenges. These challenges include providing low-solubility chlorinated substrates (e.g., PCE) at levels that are nontoxic yet adequate to sustain growth and meeting the specific nutritional requirements of the dehalorespiring organisms (Holliger and Schumacher 1994).
This lack of information is unfortunate because the chlorinated ethenes PCE and trichloroethene are among the most commonly detected groundwater contaminants (Council on Environmental Quality 1981). Complete biodegradation of these compounds at contaminated sites is often limited by the availability of a suitable electron donor (He et al. 2002). A number of microbial populations that use PCE as the terminal electron acceptor in dehalorespiration couple the reduction of chlorinated ethenes to the oxidation of hydrogen (H2). Thus, although the direct involvement of organic electron donors, especially acetate, in dehalorespiration has been demonstrated at some contaminated sites (He et al. 2002), it is generally believed that H2 serves as the ultimate electron donor for reduction of PCE in most cases (Fennell et al. 1997; Yang and McCarty 1998). However, sustaining degradation of chlorinated ethenes through the delivery of H2 in engineered in situ bioremediation scenarios is complicated by the presence of a variety of hydrogenotrophic populations that use nonchlorinated electron acceptors, such as sulfate and carbon dioxide (CO2), in contaminated anaerobic environments and the competition of these populations with PCE-degrading organisms for H2.
One strategy for enhancing selective delivery of H2 to dehalorespiring populations involves providing H2 through the addition of certain fermentable substrates such as butyrate or propionate (Fennell et al. 1997). Fermentation of butyrate under typical culture conditions occurs slowly and is thermo-dynamically feasible only at H2 partial pressures of 10–3.5 atm or less. Even lower H2 levels are required to sustain fermentation of propionate. Dehalorespiring and other hydrogenotrophic populations in anaerobic environments maintain H2 levels low enough to allow fermentation of a wide range of organic substrates to proceed. However, production of H2 through the slow syntrophic fermentation of butyrate and similar compounds appears to favor dechlorination over other hydrogenotrophic processes. Thus, being able to track the abundance of syntrophic H2-producing and H2-consuming populations should be useful when developing and monitoring sustainable engineering strategies for remediation of chloroethene-contaminated sites.
The ability to track syntrophic populations that produce and consume H2 (and/or acetate) in complex anaerobic microbial communities that degrade chlorinated aromatic compounds is also useful because of the key roles that these populations play in sustaining biodegradation of the parent compounds (Becker et al. 2001). Therefore, we used two model microbial communities to study the degradation of 3-chlorobenzoate (3-CB) and 2-chlorophenol (2-CP). The communities were maintained in batch laboratory systems derived from two different anaerobic habitats: lake sediment and municipal wastewater sludge. Two complementary nucleic acid–based methods were used to evaluate population changes relative to substrate production and use in these systems. The complementary analyses clearly resolved the role of syntrophic associations in the degradation of both chlorinated compounds.
Materials and Methods
Source of inocula.
The 3-CB– and 2-CP–degrading communities were derived from environmental inocula obtained from anaerobic lake sediment or municipal wastewater sludge digesters. Sediment was obtained from the previously described (MacGregor et al. 1997) Fox Point sampling site in Lake Michigan during two sampling events. Anaerobic sediment was collected using a box corer and transferred to canning jars, which were filled to capacity and stored at 4°C until used (within ~ 3 months). Sediment collected during the first event provided the inoculum for a preliminary microcosm experiment conducted with 3-CB, whereas the inoculum used in mesocosm-scale experiments involving 2-CP or 3-CB was derived from sediment collected nearly 2 years later. A mixture of primary and secondary digester sludge was obtained from the North Shore Sanitary District’s Clavey Road Wastewater Treatment Plant in Highland Park, Illinois. After some material was flushed from a sampling line, canning jars were filled until they overflowed and stored at 4°C until used (within 24 hr). The digester contents were used as the inoculum in a second mesocosm-scale experiment involving 3-CB.
Establishment of cultures.
The sediment and digester inocula were diluted in anaerobic mineral medium (1:9, vol/vol), and the cultures were maintained in microcosms and mesocosms comprising 160-mL and 2-L glass vessels, respectively, with serum bottle closures, using the methods described by Becker et al. (1999). Culture preparation, sampling, and amendments were performed using strict anaerobic techniques based on the methods described by Miller and Wolin (1974). The anaerobic mineral medium used in the sediment experiments has been described previously (Freedman and Gossett 1989). The medium used to dilute the digester inoculum had a slightly different formulation and contained (per liter): 0.5 g NH4Cl, 0.4 g K2HPO4, 0.1 g MgCl2 × 6H2O, 0.001 g resazurin, 0.5 g Na2S × 9H2O, 0.1 g CaCl2 × 2H2O, 4 g NaHCO3, 0.05 g yeast extract, and 10 mL trace metal solution. The trace metal solution was modified from Tanner (1997) and contained (per liter): 1 g MnCl2 × 4H2O, 0.2 g CoCl2 × 6H2O, 0.2 g ZnSO4 × 7H2O, 0.019 g H3BO4, 0.02 g NiCl2 × 6H2O, 0.02 g Na2MoO4 × 2H2O, 0.8 g Fe(NH4)2(SO4)2, 0.02 g CuCl2 × 2H2O, 0.02 g Na2SeO3, 0.02 g Na2WO4, and 2 g nitriloacetic acid. Cultures were maintained under a headspace of 30% CO2:70% N2 (vol/vol). The initial ratio of headspace volume to slurry-phase volume in all culture vessels was 3:5 (vol/vol). All cultures and controls were incubated statically at 30°C.
Microcosm-scale biodegradation experiment.
A preliminary experiment was conducted using 160-mL serum bottle microcosms inoculated with sediment and amended with 3-CB. Sediment microcosms were prepared in triplicate and amended with 3-CB (99+%; Aldrich, Milwaukee, WI) at an initial concentration of 200 μM. Duplicate sterile controls were prepared in the same way except that the sediment slurries were autoclaved for 1 hr on each of 2 consecutive days before being amended with 3-CB. The microcosms and sterile controls were sampled regularly for analysis of 3-CB, which was resupplied to the microcosms whenever it was depleted. Slurry samples were periodically taken from the microcosms for analysis of community rDNA using denaturing gradient gel electrophoresis (DGGE).
Mesocosm-scale biodegradation experiments.
Mesocosm-scale biodegradation experiments were conducted using 2-L culture vessels inoculated with sediment or digester sludge, amended with either 3-CB (sediment and digester sludge) or 2-CP (sediment), and established and maintained using aseptic techniques. Viable 2-L mesocosms were amended with 3-CB or 2-CP (99+%; Aldrich) at an initial concentration of 200 μM. No-substrate controls (2 L) were maintained for each experiment and did not receive any chlorinated substrate additions. Sterile controls (2 L) were prepared by autoclaving the inocula for 1 hr on 3 consecutive days before combining them with sterile medium and 3-CB (digester inoculum) or 3-CB plus 2-CP (sediment inoculum). The mesocosms and control reactors were sampled at approximately 1-week intervals. For each experiment, duplicate or triplicate microcosms (160-mL) were prepared in the same way as the viable 2-CP– and 3-CB–amended mesocosms and periodically sampled to evaluate the reproducibility of the nucleic acid and chemical data obtained with the mesocosms (Becker 1998). Aromatic substrates and metabolites were monitored in all reactors amended with 3-CB and/or 2-CP. rRNA was extracted from all viable reactors. All other analyses were performed only on the viable 2-L reactors. In the interest of brevity, only the results obtained with the mesocosms are reported here.
Benzoate perturbation experiment.
At the conclusion of the mesocosm-scale biodegradation experiment involving the digester sludge inoculum, duplicate 50-mL aliquots of slurry were aseptically removed from the 3-CB–amended mesocosm and transferred to 160-mL serum bottles. Except for the difference in the ratio of headspace volume to slurry volume, the transferred 3-CB–degrading digester cultures were maintained as described above. The cultures were amended with a sterile, deoxygenated stock solution of benzoate, resulting in an initial concentration of 13.8 mM, and regularly sampled for analysis of benzoate.
Analytical methods.
Reverse-phase high-performance liquid chromatography with diode array detection was used to quantify chlorinated aromatic substrates and metabolites, as previously described (Becker et al. 1999). Headspace H2 and methane (CH4) concentrations were determined using gas chromatography and reduction gas and flame ionization detectors, respectively, according to the methods described by Becker et al. (2001).
DNA extraction, amplification, separation, and sequencing.
DNA was isolated from sediment and digester slurry samples using a modification of the freeze-thaw and lysozyme treatments, phenol–chloroform extraction, and ethanol precipitation described by Tsai and Olson (1991). Each slurry sample (1 mL) was transferred to a plastic centrifuge tube (14 mL; Sarstedt, Inc., Nümbrecht, Germany) and frozen (−20°C) until cell lysis and extraction and precipitation of DNA with ethanol was implemented. Extracted DNA was diluted (1:10) and amplified using the bacteria-specific primers GM5F-GC and S-*-Univ-0907-b-A-20 and the polymerase chain reaction (PCR) procedure described by Muyzer et al. (1993) with slight modification. The GM5F-GC primer contains a 40-bp GC clamp to introduce a high-melting-point domain into the amplified fragment. Together, primers GM5F-GC and S-*-Univ-0907-b-A-20 amplify bacterial small-subunit (SSU) rDNA in the region corresponding to positions 357–907 in Escherichia coli to produce a 550-bp fragment (not including the GC-clamp). The 50-μL reaction mixture consisted of 100–300 ng (2–5 μL) template DNA;10 × Taq polymerase buffer [500 mM KCl, 15 mM MgCl2, 100 mM Tris-HCl (Pharmacia, Piscataway, NJ); 5 μL], 20 pmol each of forward and reverse primers, 0.2 mM solution of deoxyribonucleoside triphosphates, 1.5 U Taq (Pharmacia), and 500 ng/μL bovine serum albumin (Idaho Technologies, Idaho Falls, ID). Touchdown PCR amplifications were typically performed in a thermocycler (model 200; MJ Research, Inc., Watertown, MA), as described by Becker et al. (2001). Separation of the amplified bacterial community DNA via DGGE was performed using the Bio-Rad D GENE system (Bio-Rad, Hercules, CA) with slight modifications to the manufacturer’s instructions. The PCR products were loaded onto a 6% (wt/vol) polyacrylamide gel containing a denaturing gradient of urea and formamide. The gel was run for 4 hr at 200 V at 60°C. After electrophoresis the gel was stained with ethidium bromide and the image captured with a digital camera (Kaiser Fototechnik GmbH & Co., Buchen, Germany). Bands of interest were excised from a DGGE gel with a razor blade, placed in a micro-centrifuge tube, and incubated at room temperature for 10 min in 10–15 μL of sterile distilled water. This suspension (1–2 μL) was used as template for reamplification, as described above, using primers S-D-Bact-0341-a-S-17 and S-*-Univ-0907-b-A-20. Primer S-D-Bact-0341-a-S-17 is GM4F-GC without the GC-clamp (5′-CCT ACG GGA GGC AGC AG-3′). The resulting PCR product was directly sequenced using a SequiTherm Long-Read kit (Epicenter Technologies, Madison, WI), infrared-labeled primers S-D-Bact-0341-a-S-17 and S-*-Univ-0907-b-A-20 (LI-COR Corp., Lincoln, NE), and an automated DNA sequencer (model 400L; LI-COR Corp.). The resulting sequences were locally aligned using the FASTA3 algorithm (Pearson and Lipman 1988) to identify the best matches. Multiple sequence alignment was needed for development of a group-specific phylogenetic probe and was performed using software available through the Ribosomal Database Project II (Cole et al. 2003). Additional phylogenetic analyses were performed using the PHYLIP software package (version 3.5c; Felsenstein 1993).
RNA extraction, hybridization, and quantification of extracted RNA.
The mechanical-disruption/phenol–chloroform extraction process of Stahl et al. (1988) was used with previously described modifications (Becker et al. 2001; MacGregor et al. 1997) to extract RNA from sediment and digester slurry samples. RNA slot blotting, probe labeling, prehybridization, hybridization, and washing were performed as previously described (Lin and Stahl 1995; Raskin et al. 1994; Stahl et al. 1988). Samples were transferred to nylon membranes in triplicate, pre-hybridized at 40°C, and washed at 56°C [S-D-Arch-0915-a-A-20; Amann et al. (1990)] or 51°C [S-G-Syn-0424-a-A-18; Becker et al. (2001)]. It was assumed that archaeal rRNA, which was targeted by probe S-D-Arch-0915-a-A-20, was primarily derived from methanogenic species. This is reasonable because previous studies have shown that crenarchaeotal rRNA is a minor component of the Lake Michigan sediment (MacGregor et al. 1997). Probe S-G-Syn-0424-a-A-18 targets members of the genus Syntrophus and has been described previously (Becker et al. 2001) but was developed as part of this study. The relative abundance of rRNA that hybridized with the Archaea- and Syntrophus-specific probes in a given mesocosm is reported relative to the amount of archaeal and Syntrophus-like rRNA, respectively, in the reactor at time zero.
Results and Discussion
In the preliminary studies of biodegradation of 3-CB in sediment, biodegradation was not observed for approximately 78 days. Thereafter, 3-CB was rapidly degraded in the triplicate microcosms but not in the sterile controls (data not shown). 3-CB was repeatedly degraded after 29 replenishments (~ 200-μM amendments) over an approximately 2-year period. DNA samples were obtained from the microcosms on days 330, 500, and 600 and analyzed using DGGE (Figure 1). In each of the microcosms, the DGGE separation patterns varied over time, which suggests that the structures of the 3-CB–degrading communities were not static, even after degrading repetitive additions of 3-CB. Patterns also differed among microcosms, despite their similar treatment and behavior. However, several DNA fragments migrated to similar positions in the DGGE gel in all three microcosms, even after 500 or 600 days. A number of these bands were unique to the 3-CB–degrading microcosms and did not appear in the DGGE patterns obtained from microcosms that did not adapt to 3-CB (Becker 1998).
Selected bands were excised from the DGGE gel for reamplification and comparative sequencing (Figure 1). One band (position 4) was common to all lanes. The bands in position 4 actually consisted of two DNA fragments that comigrated in the 20–70% denaturant gradient gel. The comigrating fragments could be resolved using a 30–50% denaturant gradient gel (not shown). Each of the other amplified bands corresponded to a single sequence. Sequence lengths ranged from 338 to 467 nucleotides. The sequences contained a maximum of five ambiguities, and most of the sequences contained zero to two ambiguities. Ambiguous sequence regions were not included in similarity determinations.
Sequences 3CB2-4 and 3CB3-4 are closely related to uncultured members of anaerobic communities that dechlorinate 1,2-dichloropropane (SHA-207; Schlotelburg et al. 2000) and trichlorobenzene (SJA-162; von Wintzingerode et al. 1999). 3CB2-4 shares a sequence similarity of 99 and 98% with SHA-207 and SJA-16, respectively. 3CB3-4 shares 97% sequence similarity with SHA-207 and SJA-162. Another fragment from the 3-CB-degrading sediment microcosms (3CB1-Nb) originated from a close relative of Desulfomonile tiedjei, which is able to conserve energy via the reductive dehalogenation of 3-CB (DeWeerd et al. 1990). 3CB1-Nb and D. tiedjei share > 99% sequence similarity over 429 bp.
The closest cultured relative of both 3CB1-N and 3CB2-d15 is Moorella sp. F21 (GenBank accession no. AB086398; http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db_nucleotide). Strain F21 shares 87 and 91% sequence similarity with 3CB1-N and 3CB2-d15, respectively. 3CB3-7 shares 97% sequence similarity with its closest relative, a clone of an uncultured bacterium from a thermophilic terephthalate-degrading anaerobic sludge (GenBank accession no. AY297966; http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db_nucleotide).
Two sequences are closely related to benzoate-degrading syntrophs. Conversion of benzoate to H2, acetate, and CO2 is thermo-dynamically unfavorable at standard conditions. However, in the presence of hydrogen-consuming populations that maintain low H2 partial pressures in anaerobic environments, the fermentation of benzoate to H2, acetate, and CO2 by syntrophic bacteria is thermodynamically feasible. The closest cultured relatives of 3CB1-4 are the characterized Syntrophus species S. buswellii (Mountfort et al. 1984), S. gentianae (Wallrabenstein et al. 1995), and S. aciditrophicus (Jackson et al. 1999) (Figure 2). For example, 3CB1-4 shares 99% sequence similarity with S. aciditrophicus. Although fermentation of benzoate to cyclohexane carboxylate and acetate by a pure culture of S. aciditrophicus has been observed (Elshahed and McInerney 2001), the characterized Syntrophus species appear to grow primarily via syntrophic fermentation of benzoate (Jackson et al. 1999; Mountfort et al. 1984; Wallrabenstein et al. 1995). 3CB2-6 shares 95% sequence similarity with the gram-positive benzoate-degrading syntroph Sporotomaculum syntrophicum (Qiu et al. 2003).
Benzoate is a central intermediate in the anaerobic biodegradation of a variety of aromatic compounds, including 3-CB and ortho-chlorinated phenols (Heider and Fuchs 1997) and is produced from the reductive dehalogenation of 3-CB. Consumption of H2 by a dehalogenating organism (e.g., Desulfomonile tiedjei) and/or methanogenic populations creates an environment in which benzoate fermentation is feasible and biodegradation of 3-CB can be sustained without the addition of an electron donor (Dolfing and Tiedje 1986). During the mineralization of 2-CP, benzoate is formed from phenol, the primary dehalogenation product, via sequential carboxylation and dehydroxylation reactions (Becker et al. 1999; Sharak Genthner et al. 1991; Zhang et al. 1990). A second pathway that sometimes occurs during the mineralization of 2-CP and involves benzoate has also been described (Becker et al. 1999). In this alternative pathway, 2-CP undergoes para-carboxylation and dehydroxylation to form 3-CB, which is reductively dehalogenated to form benzoate. Benzoate produced during the biodegradation of 2-CP via either pathway is subject to syntrophic conversion to H2, acetate, and CO2 in the presence of populations that consume the fermentation products (Zhang and Wiegel 1990).
We were interested in tracking the relative activity of populations that mediate syntrophic benzoate fermentation because of the importance of this process in sediment and other anaerobic environments. In particular, we focused on monitoring the activity of Syntrophus populations, partly because the DGGE results suggested that the activity of 3CB2-6 decreased with time, whereas 3CB1-4 appeared to increase in abundance (Figure 2).
A phylogenetic probe (S-G-Syn-0424-a-A-18), which specifically targets the SSU rRNAs of the three Syntrophus species characterized to date and the uncultured population from the sediment community, was designed. Probe S-G-Syn-0424-a-A-18 was used along with an existing probe that targets the SSU rRNA sequences of Archaea to quantify the relative activity of syntrophic benzoate-degrading and methanogenic populations in 2-L mesocosms inoculated with sediment and amended with 3-CB, 2-CP, or no substrate. As shown in Figure 3, transformation of 3-CB in the amended mesocosm followed the pattern observed in the microcosm study and was preceded by an adaptation period of approximately 77 days. During the adaptation period, no 3-CB removal occurred, and the amounts of Syntrophus-like rRNA in the 3-CB–amended mesocosm and the no-substrate control fluctuated over time but did not increase significantly overall, compared with the levels initially present at the time of exposure to 3-CB. Once 3-CB biodegradation began, a significant increase in Syntrophus-like rRNA levels in the 3-CB–amended mesocosm was observed, and a second increase, which nearly tripled Syntrophus-like rRNA levels compared with the initial concentration in this culture, was observed after the addition of a second 3-CB dose. In contrast, during the period of 3-CB biodegradation in the amended mesocosm, Syntrophus-like rRNA levels in the no-substrate control decreased. Although benzoate was never detected in the 3-CB–amended mesocosm, it was presumably produced via the reductive dehalogenation of the parent substrate and rapidly consumed by Syntrophus species. Thus, the results of the hybridization conducted with mesocosm rRNA extracts support the idea that a Syntrophus-like population in the sediment culture was involved in 3-CB biodegradation, as suggested by the DGGE and sequencing analyses performed during the preliminary microcosm experiment. On the basis of previous characterizations of Syntrophus species (Jackson et al. 1999; Mountfort et al. 1984; Wallrabenstein et al. 1995), it is likely that this population played a role in fermenting benzoate.
Further, the results of the hybridization between rRNA extracted from the 3-CB–amended mesocosm and no-substrate control and the Archaea-specific probe suggested that the activity of the Syntrophus-like organisms in the 3-CB–amended mesocosm was sustained by methanogenic populations, which benefited from the production of benzoate-derived H2 and/or acetate (Figure 4). In the 3-CB–amended sediment mesocosm, the level of archaeal rRNA, which presumably was derived primarily from methanogens, remained fairly constant during the adaptation period, except for the peak at around day 50, which coincided with the onset of endogenous methane production (Becker 1998). A similar pattern in the level of archaeal rRNA was observed in the no-substrate control during the adaptation period. However, after the onset of 3-CB biodegradation in the amended mesocosm, differences in the activities of methanogenic populations in the two sediment cultures began to emerge. Specifically, in the 3-CB–amended mesocosm, increases in Syntrophus-like rRNA were followed by increases in archaeal rRNA. This trend is consistent with the idea that Syntrophus and methanogenic populations are members of an syntrophic association in which the Syntrophus population, because it increases in abundance and activity, releases greater amounts of electron donors (H2 and acetate), which in turn stimulate growth of the methanogens. In contrast, an overall decrease in archaeal rRNA was observed in the no-substrate control after day 77, in the absence of benzoate-derived H2 and acetate.
Evidence of a syntrophic association between Syntrophus and methanogenic populations in the 2-CP–degrading sediment community was also obtained. The mineralization of 2-CP and associated population changes in the sediment community have been reported previously (Becker et al. 2001). Briefly, 2-CP was rapidly removed in the amended mesocosm and was replenished 5 times during the remainder of the approximately 130-day experiment (Figure 5A). In contrast to the studies conducted with 3-CB, benzoate did transiently accumulate in 2-CP–transforming systems. The onset of benzoate fermentation to acetate (Becker et al. 2001) and H2 (Figure 5B) occurred by day 49. No hydrogen “burst” was detected in the no-substrate control after the onset of benzoate metabolism in the 2-CP–amended mesocosm. Similarly, after day 49, CH4 production increased significantly because of the influx of electron donors in the 2-CP–amended reactor but leveled off in the no-substrate control as endogenous substrates in the sediment were depleted (Figure 5C). The accumulation and depletion of benzoate in the 2-CP–amended mesocosm at around day 49 were paralleled by an increase and decline, respectively, in the level of Syntrophus-like rRNA in the amended reactor (Figure 5D). Increases in Syntrophus-like rRNA in the amended reactor after day 49 presumably reflect the metabolism of benzoate produced during the biodegradation of 2-CP, although benzoate was not detected in the amended mesocosm after day 53 (Figure 5E). These increases were not observed in the no-substrate control, and overall, the level of Syntrophus-like rRNA decreased after day 53 in the control. These data suggest that a Syntrophus population also played a key role in the mineralization of 2-CP, that is, fermentation of benzoate. The observed release of H2 and increased CH4 production in the 2-CP–amended mesocosm, compared with the no-substrate control, are also reflected in the archaeal rRNA levels (Figure 5D). The first archaeal rRNA peak in the 2-CP–degrading mesocosm appeared at approximately the same time that an increase was observed in the 3-CB–amended mesocosm (Figure 4) and the no-substrate control (Figure 5E) and probably reflects, at least partly, methanogenic metabolism of endogenous substrates. However, subsequent archaeal rRNA peaks in the 2-CP–amended reactor either trail or coincide with increases in the level of Syntrophus-like rRNA. The coupling of Syntrophus-like and archaeal rRNA levels is consistent with the information on the substrates (benzoate and H2) and products (CH4) and suggests that the metabolisms of the Syntrophus and methanogenic population in the 2-CP–degrading sediment community are closely linked.
Unlike the sediment reactor communities that were studied, the communities in the 3-CB–degrading mesocosm and no-substrate control inoculated with digester sludge remained highly complex over time, as suggested by the DGGE pattern obtained from the no-substrate control at the conclusion of the nearly 130-day experiment (Figure 6). This made it difficult to track and target individual bands in the DGGE patterns obtained from the two digester cultures for further analysis. Consequently, it was also difficult to identify appropriate probe targets for a hybridization involving rRNA extracted from the digester cultures over time. Although DGGE band intensity does not necessarily correspond to population size because of biases caused by extraction efficiencies (Holben 1994) and amplification (von Wintzingerode et al. 1997; Wilson 1997), an attempt was made to facilitate identification of the band(s) associated with benzoate-fermenting population(s) by selectively stimulating their growth. This involved perturbing duplicate aliquots of the 3-CB–amended digester mesocosm contents, which were obtained after two 3-CB additions (200 μM) had been biodegraded in the mesocosm, with a high concentration of benzoate (~ 14 mM). In contrast, reductive dehalogenation of the two 3-CB additions previously exposed the community in the 3-CB–amended digester mesocosm to micro-molar doses of benzoate, which were rapidly consumed. SSU rDNA was extracted and amplified from the digester mesocosm aliquots after the large doses of benzoate were metabolized (within 40 days; data not shown). The DGGE profiles of the benzoate-perturbed digester communities are shown in Figure 6. The intense band that appears in each of these profiles was not detected in DGGE analyses of the 3-CB–degrading digester mesocosm community before perturbation with a high dose of benzoate (not shown) or in the no-substrate control (Figure 6). Sequence SBZ1-D1 was derived from one of these bands (Figure 6) and shares > 99% sequence similarity over 456 bp (excluding three ambiguities) with Syntrophus aciditrophicus. On the basis of these results, the Syntrophus-specific DNA probe (S-G-Syn-0424-a-A-18) was hybridized with rRNA obtained from the 3-CB–amended digester mesocosm and the associated no-substrate control over time. The results are shown in Figure 7. Syntrophus-like rRNA levels in both digester communities decreased significantly during the adaptation period preceding 3-CB biodegradation in the amended reactor. This trend was expected because presumably no benzoate was supplied to either community during this period. Syntrophus-like rRNA levels remained low in the no-substrate control until the conclusion of the experiment. In contrast, the onset of 3-CB biodegradation in the amended mesocosm was accompanied by a significant increase in Syntrophus-like rRNA levels. The detection of Syntrophus-like sequences in the DGGE profiles of the benzoate-perturbed digester community and the results of the hybridization conducted with the Syntrophus-specific probe strongly suggest that a Syntrophus population played a key role in the biodegradation of chlorinated aromatic compounds in the digester community, as well as in the sediment systems.
The production of CH4 in the amended digester mesocosm increased significantly after the onset of 3-CB biodegradation, compared with methanogenesis in the no-substrate control (Becker 1998). The CH4 data suggested that methanogens also played an important role in sustaining the biodegradation of the chlorinated substrates by the digester community and benefited from the activity of the Syntrophus population. However, the impact of syntrophic benzoate degradation on the activity of methanogenic populations could not be detected by hybridizing the Archaea-specific probe with rRNA extracted from the 3-CB–amended digester mesocosm and no-substrate control over time. Archaeal rRNA levels in the two cultures were of a comparable magnitude and underwent similar temporal changes. Apparently the effect of metabolism of abundant substrates that were endogenous to the digester inocula significantly influenced archaeal SSU rRNA levels and masked the effect of syntrophic benzoate fermentation reflected in the methane levels.
Conclusions
The results of this study demonstrate that the general approach of using a DNA fingerprinting technique and comparative sequencing to identify potentially important populations in contaminant-degrading communities, followed by SSU rRNA-based hybridizations to quantify changes in the abundance of these populations, can be integrated with analysis of metabolic substrates and products and applied to different complex microbiological systems. Specifically, we demonstrated that it is possible to identify and track populations in syntrophic associations that are based on the fermentation of organic intermediates and are critical for sustaining mineralization of the chlorinated parent compounds in complex anaerobic microbial communities. We anticipate that the analytical approach and methods developed in this study will be useful in the development and monitoring of sustainable engineering strategies for remediation of sites contaminated with chlorinated organic compounds.
Figure 1 Ethidium bromide–stained DGGE profiles of rDNA PCR fragments derived from DNA extracted from triplicate 3-CB–degrading microcosms inoculated with Lake Michigan sediment (3CB1, 3CB2, and 3CB3) using a 20–70% denaturant gradient gel. The DNA extracts were obtained from the microcosms on the following days: lane a, day 330; lane b, day 500; lane c, day 600. Gel portions that were excised for additional analyses are indicated with arrows plus a letter and/or number. Throughout the text and in Figure 2, these bands are referred to using the microcosm name plus the label shown in Figure 1 (e.g., 3CB1-4). Sequences derived from reamplified DGGE bands were submitted to GenBank (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db_nucleotide) with the following accession numbers: 3CB1-4, AY646230; 3CB1-Nb, AY646231; 3CB1-N, AY646232; 3CB2-4, AY646233; 3CB2-6, AY646234; 3CB2-d15, AY646235; 3CB3-4, AY646236; and 3CB3-7, AY646237.
Figure 2 Phylogenetic placement of sequence 3CB1-4, which was derived from a 3-CB–degrading sediment microcosm. The neighbor joining tree is based on 16S rRNA sequence positions 357–907 (E. coli numbering). The solid bracket shows the sequences targeted by S-G-Syn-0424-a-A-18, and the scale bar represents the estimated number of base changes per nucleotide. Bold type indicates the sequence was obtained in this study.
Figure 3 Relative abundance of Syntrophus-like SSU rRNA in the 3-CB–amended sediment mesocosm and associated no-substrate control and 3-CB biodegradation in the amended mesocosm. 3-CB concentrations in the sterile control are not shown.
Figure 4 (A) Relative abundance of Syntrophus-like and archaeal SSU rRNA in the 3-CB–amended sediment mesocosm. (B) Relative abundance of archaeal SSU rRNA in the no-substrate sediment control.
Figure 5 Metabolism of 2-CP and its effects on the activities of syntrophic populations in a 2-CP–amended sediment mesocosm. (A) 2-CP transformation and transient accumulation of benzoate in a sediment mesocosm (phenol and 3-CB also accumulated transiently, but are not shown). (B) H2 levels in the 2-CP–amended mesocosm and associated no-substrate control.(C) CH4 levels in the 2-CP–amended mesocosm and associated no-substrate control. (D) Relative abundance of Syntrophus-like and archaeal SSU rRNA in the 2-CP–amended reactor. (E) Relative abundance of Syntrophus-like and archaeal SSU rRNA in the no-substrate control. 2-CP concentrations in the sterile control are not shown. Adapted from Becker et al. (2001).
Figure 6 Ethidium bromide–stained DGGE profiles of rDNA fragments of PCR products derived from DNA extracted from mesocosm-scale reactors that were inoculated with digester sludge using a 25–70% denaturant gradient gel. Lane 1 corresponds to community DNA obtained from the no-substrate control after 126 days of incubation in the absence of any added growth substrates. Lanes 2 and 3 correspond to community DNA obtained from duplicate aliquots of the 3-CB–amended digester mesocosm (SBZ1 and SBZ2) that were obtained after ~ 130 days of incubation and 3-CB biodegradation. The aliquots were perturbed with a high dose (~ 14 mM) of benzoate. Benzoate was completely degraded in the aliquots within 40 days and before the DNA was extracted. An arrow indicates the gel portion (SBZ1-D1) that was excised, reamplified, and sequenced. Sequence SBZ1-D1 was submitted to GenBank (http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db_nucleotide) with the accession number AY646238.
Figure 7 Relative abundance of Syntrophus-like SSU rRNA in the 3-CB–amended digester mesocosm and associated no-substrate control and 3-CB biodegradation in the amended mesocosm. 3-CB concentrations in the sterile control are not shown.
==== Refs
References
Amann RI Krumholz L Stahl DA 1990 Fluorescent-oligonucleotide probing of whole cells for determinative, phylogenetic, and environmental studies in microbiology J Bacteriol 172 762 770 1688842
Amann RI Ludwig W Schleifer K-H 1995 Phylogenetic identification and in situ detection of individual microbial cells without cultivation Microbiol Rev 59 143 169 7535888
Becker JG 1998. Characterization of Anaerobic Microbial Communities That Adapt to 3-Chlorobenzoate and 2-Chlorophenol: An Integrated Approach of Chemical Measurements and Molecular Evaluations [PhD Dissertation]. Evanston, IL:Northwestern University.
Becker JG Berardesco G Rittmann BE Stahl DA 2001 Successional changes in an evolving anaerobic chlorophenol-degrading community used to infer relationships between population structure and system-level processes Appl Environ Microbiol 67 5705 5714 11722926
Becker JG Stahl DA Rittmann BE 1999 Reductive dehalogenation and conversion of 2-chlorophenol to 3-chlorobenzoate in a methanogenic sediment community: implications for predicting the environmental fate of chlorinated pollutants Appl Environ Microbiol 65 5169 5172 10543840
Cole JR Chai B Marsh TL Farris RJ Wang Q Kulam SA 2003 The Ribosomal Database Project (RDP-II): previewing a new autoaligner that allows regular updates and the new prokaryotic taxonomy Nucleic Acids Res 31 442 443 12520046
Council on Environmental Quality 1981. Contamination of Ground Water by Toxic Organic Chemicals. Washington, DC:Council on Environmental Quality.
DeWeerd KA Mandelco L Tanner RS Woese CR Suflita JM 1990 Desulfomonile tiedjei gen. nov. and sp. nov., a novel anaerobic, dehalogenating, sulfate-reducing bacterium Arch Microbiol 154 23 30
Dolfing J Tiedje JM 1986 Hydrogen cycling in a three-tiered food web growing on the methanogenic conversion of 3-chlorobenzoate FEMS Microbiol Ecol 38 293 298
Elshahed MS McInerney MJ 2001 Benzoate fermentation by the anaerobic bacterium Syntrophus aciditrophicus in the absence of hydrogen-using microorganisms Appl Environ Microbiol 67 5520 5525 11722901
Felsenstein J 1993. PHYLIP (Phylogeny Inference Package), 3.5c. Seattle, WA:Department of Genetics, University of Washington [Distributed by the author].
Fennell DE Gossett JM Zinder SH 1997 Comparison of butyric acid, ethanol, lactic acid, and propionic acid as hydrogen donors for the reductive dechlorination of tetrachloroethene Environ Sci Technol 31 918 926
Freedman DL Gossett JM 1989 Biological reductive dechlorination of tetrachloroethylene and trichloroethylene to ethylene under methanogenic conditions Appl Environ Microbiol 55 2144 2151 2552919
He J Sung Y Dollhopf ME Fathepure BZ Tiedje JM Löffler FE 2002 Acetate versus hydrogen as direct electron donors to stimulate the microbial reductive dechlorination process at chloroethene-contaminated sites Environ Sci Technol 36 3945 3952 12269747
Heider J Fuchs G 1997 Microbial anaerobic aromatic metabolism Anaerobe 3 1 22 16887557
Holben WE 1994. Isolation and purification of bacterial DNA from soils. In: Methods of Soil Analysis, Part 2, Microbiological and Biochemical Properties (Weaver RW, Angle S, Bottomley P, Bezdicek D, Smith S, Tabatabai A, et al., eds). Madison, WI:Soil Science Society of America, 727–751.
Holliger C Schumacher W 1994 Reductive dehalogenation as a respiratory process Antonie Van Leeuwenhoek 66 239 246 7747935
Jackson BE Bhupathiraju VK Tanner RS Woese CR McInerney MJ 1999 Syntrophus aciditrophicus sp. nov., a new anaerobic bacterium that degrades fatty acids and benzoate in syntrophic association with hydrogen-using microorganisms Arch Microbiol 171 107 114 9914307
Lin C Stahl DA 1995 Taxon-specific probes for the cellulolytic genus Fibrobacter reveal abundant and novel equine-associated populations Appl Environ Microbiol 61 1348 1351 7538274
Liu W-T Stahl DA 2002. Molecular approaches for the measurement of density, diversity, and phylogeny. In: Manual of Environmental Microbiology (Hurst CJ, Crawford RL, Knudsen GR, McInerney MJ, Stetzenbach LD, eds). 2nd ed. Washington, DC:ASM Press, 114–134.
MacGregor BJ Moser DP Alm EW Nealson KH Stahl DA 1997 Crenarchaeota in Lake Michigan sediment Appl Environ Microbiol 63 1178 1181 9055434
Miller TL Wolin MJ 1974 A serum bottle modification of the Hungate technique for cultivating obligate anaerobes Appl Environ Microbiol 27 985 987
Mountfort DO Brulla WJ Krumholz LR Bryant MP 1984 Syntrophus buswellii gen. nov., sp. nov.: a benzoate catabolizer from methanogenic ecosystems Int J Syst Bacteriol 34 216 217
Muyzer G de Waal EC Uitterlinden AG 1993 Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA Appl Environ Microbiol 59 695 700 7683183
Pearson WR Lipman DJ 1988 Improved tools for biological sequence comparison Proc Natl Acad Sci USA 85 2444 2448 3162770
Qiu YL Sekiguchi Y Imachi H Kamagata Y Tseng IC Cheng SS 2003 Sporotomaculum syntrophicum sp. nov., a novel anaerobic syntrophic benzoate-degrading bacterium isolated from methanogenic sludge treating waste-water from terephthalate manufacturing Arch Microbiol 179 242 249 12605290
Raskin L Stromley JM Rittmann BE Stahl DA 1994 Group-specific 16S rRNA hybridization probes to describe natural communities of methanogens Appl Environ Microbiol 60 1232 1240 7517128
Schink B 1997 Energetics of syntrophic cooperation in methanogenic degradation Microbiol Mol Rev 61 262 280
Schlotelburg C von Wintzingerode F Hauck R Hegemann W Gobel UB 2000 Bacteria of an anaerobic 1,2-dichloro-propane-dechlorinating mixed culture are phylogenetically related to those of other anaerobic dechlorinating consortia Int J Syst Evol Microbiol 50 1505 1511 10939657
Sharak Genthner BR Townsend GT Chapman PJ 1991 para -Hydroxybenzoate as an intermediate in the anaerobic transformation of phenol to benzoate FEMS Microbiol Lett 78 265 270
Stahl DA Flesher B Mansfield HR Montgomery L 1988 Use of phylogenetically based hybridization probes for studies of ruminal microbial ecology Appl Environ Microbiol 54 1079 1084 3389805
Tanner RS 1997. Cultivation of bacteria and fungi. In: Manual of Environmental Microbiology (Hurst CJ, Knudsen GR, McInerney MJ, Stetzenbach LD, Walter MV, eds). Washington, DC:ASM Press, 52–60.
Tsai Y-L Olson BH 1991 Rapid method for direct extraction of DNA from soil and sediments Appl Environ Microbiol 57 1070 1074 1647749
von Wintzingerode F Gobel UB Stackebrandt E 1997 Determination of microbial diversity in environmental samples: pitfalls of PCR-based rRNA analysis FEMS Microbiol Rev 21 213 229 9451814
von Wintzingerode F Selent B Hegemann W Gobel UB 1999 Phylogenetic analysis of an anaerobic, trichlorobenzene-transforming microbial consortium Appl Environ Microbiol 65 283 286 9872791
Wallrabenstein C Gorny N Springer N Ludwig W Schink B 1995 Pure culture of Syntrophus buswellii , definition of its phylogenetic status, and description of Syntrophus gentianae sp. nov Syst Appl Microbiol 18 62 66
Wilson IG 1997 Inhibition and facilitation of nucleic acid amplification Appl Environ Microbiol 63 3741 3751 9327537
Yang Y McCarty PL 1998 Competition for hydrogen within a chlorinated solvent dehalogenating anaerobic mixed culture Environ Sci Technol 32 3591 3597
Zhang X Morgan TV Wiegel J 1990 Conversion of 13 C-1 phenol to 13 C-4 benzoate, an intermediate step in the anaerobic degradation of chlorophenols FEMS Microbiol Lett 67 63 66
Zhang X Wiegel J 1990 Sequential anaerobic degradation of 2,4-dichlorophenol in freshwater sediments Appl Environ Microbiol 56 1119 1127 2111112
|
15743720
|
PMC1253757
|
CC0
|
2021-01-04 23:40:57
|
no
|
Environ Health Perspect. 2005 Mar 8; 113(3):310-316
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.6933
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.6939ehp0113-00031715743721ResearchArticlesComparison of Biostimulation versus Bioaugmentation with Bacterial Strain PM1 for Treatment of Groundwater Contaminated with Methyl Tertiary Butyl Ether (MTBE) Smith Amanda E. 1Hristova Krassimira 1Wood Isaac 1Mackay Doug M. 1Lory Ernie 2Lorenzana Dale 2Scow Kate M. 11Department of Land, Air and Water Resources, University of California, Davis, California, USA2Port Hueneme Naval Construction Battalion Center, Oxnard, California, USAAddress correspondence to K. Scow, Department of Land, Air and Water Resources, University of California, One Shields Ave., Davis, CA 95616 USA. Telephone: (530) 752-4632. Fax: (530) 752-1552. E-mail:
[email protected] article is based on a presentation at the conference “Bioremediation and Biodegradation: Current Advances in Reducing Toxicity, Exposure and Environmental Consequences” (http://www-apps.niehs.nih.gov/sbrp/bioremediation.html) held 9–12 June 2002 in Pacific Grove, California, and sponsored by the NIEHS Superfund Basic Research Program. The overall focus of this conference was on exploring the research interfaces of toxicity reduction, exposure assessment, and evaluation of environmental consequences in the context of using state-of-the-art approaches to bioremediation and biodegradation. The Superfund Basic Research Program has a legacy of supporting research conferences designed to integrate the broad spectrum of disciplines related to hazardous substances.
We thank undergraduate students S. Adamson and B. Watanabe for their contributions. We are also grateful to the staff at Port Hueneme Naval Construction Battalion Center for their help in setting up the plots and sampling.
This publication was made possible by grant 5 P42 ES04699 from the National Institute of Environmental Health Sciences (NIEHS), National Institutes of Health (NIH). Its contents are solely the responsibility of the authors and do not necessarily represent the official views of the NIEHS, NIH. Additional support was provided by the U.S. Environmental Protection Agency Center for Ecological Health Research, University of California (UC) Toxic Substances Program, American Petroleum Institute, Oxygenated Fuels Association, and the UC Water Resources Center.
The authors declare they have no competing financial interests.
3 2005 8 12 2004 113 3 317 322 23 12 2003 30 6 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Widespread contamination of groundwater by methyl tertiary butyl ether (MTBE) has triggered the exploration of different technologies for in situ removal of the pollutant, including biostimulation of naturally occurring microbial communities or bioaugmentation with specific microbial strains known to biodegrade the oxygenate. After laboratory studies revealed that bacterial strain PM1 rapidly and completely biodegraded MTBE in groundwater sediments, the organism was tested in an in situ field study at Port Hueneme Naval Construction Battalion Center in Oxnard, California. Two pilot test plots (A and B) in groundwater located down-gradient from an MTBE source were intermittently sparged with pure oxygen. Plot B was also inoculated with strain PM1. MTBE concentrations up-gradient from plots A and B initially varied temporally from 1.5 to 6 mg MTBE/L. Six months after treatment began, MTBE concentrations in monitoring wells down-gradient from the injection bed decreased substantially in the shallow zone of the ground-water in plots A and B, thus even in the absence of the inoculated strain PM1. In the deeper zone, downstream MTBE concentrations also decreased in plot A and to a lesser extent in plot B. Difficulties in delivery of oxygen to the deeper zone of plot B, evidenced by low dissolved oxygen concentrations, were likely responsible for low rates of MTBE removal at that location. We measured the survival and movement of strain PM1 in groundwater samples using two methods for detection of DNA sequences specific to strain PM1: TaqMan quantitative polymerase chain reaction, and internal transcribed spacer region analysis. A naturally occurring bacterial strain with > 99% 16S rDNA sequence similarity to strain PM1 was detected in groundwater collected at various locations at Port Hueneme, including outside the plots where the organism was inoculated. Addition of oxygen to naturally occurring microbial populations was sufficient to stimulate MTBE removal at this site. In some cases, however, inoculation with an MTBE-degrading culture may be warranted.
bioaugmentationbiodegradationbioremediationgroundwaterin situ remediationmicrobial ecologyMTBEpollutants
==== Body
The fuel additive methyl tertiary butyl ether (MTBE) has become a widespread environmental contaminant within the past 30 years. MTBE was the second most common volatile organic compound detected in wells monitored in urban areas nationwide between 1985 and 1995 (Clawges et al. 2000; Squillace et al. 1996). In California, for example, approximately 13,000 sites have hydrocarbon-contaminated groundwater, with more than 10,000 of these sites contaminated with MTBE (Happel et al. 1998). MTBE is very water soluble with a low sorption partition coefficient and thus is highly mobile in both groundwater and surface water. The pollutant is also moderately volatile, which can lead to redistribution and further contamination of the vadose zone, surface soils, and sediments.
There is little evidence that naturally occurring biodegradation processes, or intrinsic remediation, are substantial at many MTBE-contaminated sites, most of which are anoxic. Microcosm studies, however, have shown biodegradation to occur under some anaerobic conditions (Bradley et al. 2001a; Finneran and Lovley 2001). Aerobic biodegradation, on the other hand, is comparatively rapid if oxygen is present in or added to groundwater aquifers (Deeb et al. 2000b). Aerobic biodegradation of MTBE by native microorganisms has been measured in microcosm studies of MTBE- and oxygen-amended sediments (Bradley et al. 2001b) and groundwater samples (Salanitro et al. 2000; Wilson et al. 2002). Also, in situ MTBE bioremediation of a contaminated aquifer after addition of oxygen has been demonstrated at Port Hueneme Naval Construction Battalion Center (PH) in Oxnard, California, in both inoculated and uninoculated plots (Salanitro et al. 2000), and at Vandenberg Air Force Base, California, by native microbial communities (Wilson et al. 2002).
Our laboratory isolated an aerobic bacterium, strain PM1, that is capable of using MTBE as its sole carbon and energy source at relatively rapid rates. PM1 is a gram-negative rod and, based on 16S rDNA sequence similarity, is a member of the beta subgroup of Proteobacteria, in the family Comamonadaceae, and closely related to Aquabacterium, Rubrivivax, Leptothrix, Ideonella, and Hydrogenophaga (Bruns et al. 2001). PM1 rapidly mineralizes MTBE at concentrations up to 500 mg/L in laboratory cultures (Deeb et al. 2000a; Hanson et al. 1999) and degrades MTBE when inoculated into oxygenated groundwater or soil microcosms. Our goal was to evaluate whether in situ remediation using bioaugmentation with strain PM1 and oxygen addition was feasible to treat MTBE-contaminated groundwater.
Our specific objectives were to compare potential for and rates of MTBE removal from contaminated groundwater in field plots amended with oxygen. We compared bioaugmentation (inoculated with PM1) with biostimulation of naturally occurring MTBE-degrading microorganisms (not inoculated). We also measured the survival of strain PM1 in inoculated plots. The pilot study was conducted in an MTBE-contaminated aquifer at PH.
Materials and Methods
Biodegradation potential.
Cultures of strain PM1 were grown in mineral salts medium with MTBE as the sole carbon and energy source, as described previously (Hanson et al. 1999; Hristova et al. 2001). Cultures were incubated in 250-mL bottles sealed with Teflon-lined Mini-Nert (Dynatech Precision Sampling Corp., Baton Rouge, LA) caps at 25°C in the dark on an orbital shaker. After growth, cultures were centrifuged, and the cell pellets were washed twice, resuspended, and then used in inoculation. Inoculation densities were determined based on the standard optical density at 550 nm (OD550) versus cell plate count numbers. A microcosm study was conducted to determine the ability of strain PM1 to degrade MTBE in aquifer sediment samples from PH. Fifty-gram (dry wt) groundwater core samples were inoculated with 107 strain PM1 cells per gram of sediment and 50 mL of groundwater. MTBE degradation was measured by analysis of 50-μL headspace samples using a Shimadzu GC-14A gas chromatograph equipped with a photonionization detector (Shimadzu, Columbia, MD). All experiments were performed in triplicate; concentrations of MTBE were calculated from a standard curve, and inoculated samples were compared with sterile controls containing 1% sodium azide (by mass).
PH field trial.
A field trial was initiated in a shallow, anoxic, MTBE-contaminated groundwater aquifer at PH (Figure 1). The geology and contamination at the site are described by Salanitro et al. (2000) from a bioaugmentation pilot study at PH using a different bacterial inoculant. The shallow aquifer consists of a clay-silt layer [0–3 m below ground surface (BGS)], fine- to medium-grain sand layer (3–6 m BGS), and a clay layer (beginning at 6 m BGS). The water table is approximately 2 m BGS, and groundwater flows southwest with a hydraulic conductivity of 53,000–120,000 L per day/m2. A 1,500-m plume resulted from a large release of gasoline containing MTBE from a gas station beginning in 1984. Test plots (each 2.7 m wide × 1.4 m long, separated from each other by 14 m) were installed 610 m down-gradient from the MTBE source. In two plots (A and B), groundwater was sparged with pure oxygen at two depths (between 3.7–4.3 and 5.2–5.8 m BGS) from 26 screened oxygen release wells. Oxygen was supplied using two 303-L air compressors with an Airsep Model AS80 oxygen generator (AirSep Corp., Rochester, NY). Approximately 12 m3 of oxygen was supplied to each plot per day. In a third plot, C, air rather than oxygen was added as an electron acceptor; these results are described elsewhere (Smith 2000). Each plot contained five rows of three monitoring well clusters, with each cluster consisting of two 1.9-cm-diameter wells: shallow (2.4–3.3 m) and deep (4.9–5.8 m). Wells were labeled by row number in each plot, depth (shallow or deep), and position in the row. For example, the deep well in plot B, located in the second row along the centerline, was called B22D (Figure 2). Two sets of wells were located up-gradient and three sets of wells down-gradient from the injection bed. Plot B was inoculated with strain PM1 as described below, whereas plots A and C were not. Groundwater was intermittently sampled for analysis of MTBE, oxygen, microbial populations, and other groundwater characteristics.
Oxygen delivery began late October 1999. Strain PM1 was added to plot B on 8 November 1999 (~ 109 cells/mL in the injection solution of 220 gal of mineral salt media). Strain PM1 was injected using a Geoprobe unit (Geoprobe Systems, Salina, KS) at nine locations within the injection bed (shown as shaded area in each plot, Figure 2), in two rows interspaced between the oxygen-sparging wells.
Strain PM1 cultures for the field study were cultivated at the fermentation at Lawrence Livermore National Laboratory in Livermore, California. The cells were grown in a 1,500-L batch reactor on multiple inputs of 1,000 mg/L ethanol. After growth on ethanol, the cells were fed sequentially with 83, 192, and 255 mg/L MTBE. After removal of MTBE, the cells were harvested via continuous centrifugation and stored at 4°C until use. One week before injection, the cell paste was diluted in mineral salts media in four 55-gal plastic drums equipped with air sparging units and stirrers attached to a motor. Cells were fed 100 mg/L MTBE on a daily basis for a week and then transported to PH. At PH, the cells were mixed in a 1:1 ratio with groundwater from the site before injection.
Sample collection and MTBE analysis.
MTBE samples were collected using Cole Parmer Masterflex peristaltic pumps (Cole-Parmer Instrument Co., Vernon Hills, IL). One well volume of groundwater, 450 mL for deep wells and 160 mL for shallow wells, was removed before sample collection. For MTBE analyses, groundwater samples were placed in 40 mL amber glass vials with septa tops containing 10% sodium azide as a sterilization agent. For DNA analyses, groundwater was collected with sterile tubing for each well, placed in 250-mL sterile plastic bottles, shipped on ice to the lab at the University of California, Davis, and frozen on receipt. MTBE was analyzed in 10-mL aliquots using purge-and-trap concentration followed by gas chromatography. Instrumentation included a Tekmar LSC 2000 Purge-and-trap, a VOCARB 3000 trap, Tekmar 2060 autosampler (Shimadzu), and a Shimadzu GC-14A gas chromatograph with a 15-m × 0.53-mm DB1 column (J&W Scientific, Folsom, CA) with a photonionization detector. This method provided a detection limit of 5 μg/L MTBE. A five-point calibration curve consisting of 0, 0.5, 1.0, 4.0, and either 2.0 or 10 mg MTBE/L was used for each run. The purge-and-trap procedure included a standby temperature of 35°C, purge time of 10 min, desorb preheat of 160°C, desorb of 4 min at 175°C, and bake time of 4 min at 260°C. The temperature program to reduce peak tailing included an initial temperature of 35°C for 5 min, temperature increase at a rate of 25°C/min, and final temperature of 150°C for 10 min.
DNA extraction and analysis.
DNA was extracted from 5-mL microcosm or 130-mL groundwater samples using the same protocol. Bacterial cells were concentrated from water samples on white polycarbonate filters (diameter, 47 mm; pore size, 0.2 μm; type GTTP 2500, Millipore) (Fisher Scientific, Fair Lawn, NJ), placed on nitrocellulose support filters (47 mm, 0.45 μm) by applying a vacuum. After the tubes were frozen in liquid nitrogen, the filters were broken into small pieces, and DNA was extracted by bead beating and chloroform:isoamyl alchohol (24:1) as described by Hristova et al. (2001). The nucleic acids from the aqueous phase were concentrated and washed with 10 mM Tris-HCl, 1 mM EDTA (pH 7.8) in a microconcentrator (Centricon 100; Fisher Scientific), and the preparations were reduced to a final volume of 30 μL.
PM1-specific primers based on the internal transcribed spacer (ITS) region have been used to show presence of PM1 rDNA sequences in the groundwater. PM1-specific primers 1406F (5′-TGYACACACCGCCCGT-3′) and 1850R (5′-CGTAAGCCACTGACGCTT-3′) were designed based on alignments of sequences of the ITS and the flanking 16S and 23S rRNA genes of the ribosomal operon. The ITS PM1 primers amplify a 444-bp DNA fragment. Extracted DNA from pure cultures and groundwater samples was amplified using a Gene Amp 2400 thermal cycler (Applied Biosystems, Foster City, CA). The polymerase chain reaction (PCR) mixtures and conditions were as described by Hristova et al. (2003). PCR products were applied in 5- to 10-μL aliquots to 5% polyacrylamide gels (0.75 mm thick, 150 × 150 mm) and run on an electrophoresis unit at 150 V for 4 hr in 1 × Tris–borate/EDTA (pH 8.0) buffer. Gels were stained with SYBR Green and photographed through a yellow filter with a Kodak EDAS 290 CCD camera using Kodak 1D image analysis software (version 3.5.3; Scientific Imaging Systems, New Haven, CT).
We developed a quantitative real-time TaqMan PCR method for detection of 16S rDNA sequences specific to the MTBE-degrading strain PM1 (Hristova et al. 2001). The TaqMan method uses a fluorescent oligonucleotide probe with a 5′ reporter dye and 3′ quencher dye. During the PCR, the 5′–3′-nuclease activity of Taq DNA polymerase cleaves nucleotides from an oligonucleotide probe annealed to a target DNA strand. As the amplification reaction proceeds, more amplicons become available for probe binding, and consequently, the fluorescence signal intensity per cycle increases. The initial copy number is estimated from the exponential phase of product accumulation and by comparison with a standard curve. A 113-bp product was amplified using primers 963F and 1076R and probe 1030T (Hristova et al. 2001). Forty cycles of amplification, data acquisition, and data analysis were carried out using an ABI Prism 7700 Sequence Detector (PE Applied Biosystems). TaqMan PCR data were analyzed with Sequence Detector Software (version 1.7; Applied Biosystems). The threshold is defined as 10 times the standard deviation of the normalized fluorescent emission of the nontemplate control reaction. CT is the cycle at which a sample crosses the threshold, a PCR cycle where the fluorescence emission exceeds that of nontemplate controls. Three PCRs were performed for each environmental DNA extraction.
Results
Laboratory microcosms.
Addition of strain PM1 to groundwater sediments from PH spiked with 10 mg MTBE/L (10 ppm) resulted in more rapid MTBE removal than in uninoculated sediments (Figure 3). After 5 days, when the initial input of MTBE was degraded in the inoculated flasks, additional MTBE was added to the microcosms at the same concentration. MTBE degraded more rapidly than the first input of MTBE, suggesting an increase in the initial population density of MTBE-degrading organisms. The uninoculated samples also degraded MTBE, although after a longer lag period (200 hr, with complete degradation after 460 hr). Subsequent additions of MTBE in the uninoculated sediments, however, were degraded at rates comparable with those observed in inoculated flasks.
MTBE removal in pilot study at PH.
Oxygen sparging in plots A and B was initiated in late October 1999; intensive sampling of dissolved oxygen in groundwater was conducted to determine when sufficient oxygen was present to support the activity of PM1. Modifications had to be made to the original design of the wells to increase oxygen delivery to locations where much of the MTBE was present. By early November, high concentrations of dissolved oxygen were measurable in almost all the shallow wells and in some, but not all, of the deeper wells at the site. Strain PM1 was added to plot B on 8 November 1999. We conducted frequent sampling of the center row wells (approximately every month) for oxygen and MTBE and less frequent sampling for microbiological analyses. To simplify the graphs, not all sampling dates are included; however, the other data show similar trends. The time of the injection of strain PM1 is referred to as time zero in the presentation of results.
Figure 4A and B shows MTBE removal along the direction of groundwater flow in the shallow centerline wells of plots B and A, respectively. The initial MTBE concentrations in the shallow zone ranged from 2.5 to 3.5 mg/L in plot B and were much lower in plot A (< 0.14 mg/L 2 m down-gradient of the oxygen release zone). Down-gradient of the oxygen release wells, MTBE concentrations decreased substantially in the shallow zone of both plots, even in the absence of strain PM1 (plot A). After 6 months of treatment, MTBE concentrations declined to 0.008 mg/L or nondetectable levels (< 0.005 mg/L) in plot A and to 0.09 mg/L or nondetectable levels in plot B.
In the deeper zone, initial MTBE concentrations ranged from 5 mg/L up-gradient to < 1 mg/L down-gradient in plot A and ranged from 5.7 to 9.3 mg/L in plot B. The differences in concentrations between plots A and B are likely due partly to spatial variability in MTBE concentrations but may also indicate that some treatment had already begun 1 month after oxygen injection began. Down-gradient MTBE concentrations decreased substantially in plot A to < 0.11 mg/L (Figure 4D) but only slightly in plot B (Figure 4C). Difficulties in delivery of oxygen to the deep zone in plot B, as evidenced by the low dissolved oxygen concentrations present (shown in Figure 4F), were likely responsible for low rates of MTBE removal at that location (Figure 4C). In addition, well pump tests indicated that groundwater flow was substantially slower in the shallow zones than in the deep zones and slower in plot B than in plot A (Smith 2000).
PM1 detection and quantification in PH groundwater.
Three sets of PM1-specific primers (16S and ITS rDNA) were used to detect PM1 in groundwater samples. Using ITS-specific primers of DNA extracted from samples collected 24 days after injection of PM1, we detected PCR products with the expected length of 444 bp in all samples from plots B and A, with three exceptions (wells B-12-D, B-52-D, and A-42-S; Figure 5).
Using TaqMan PCR, we quantified the density of PM1 cells in samples (shallow and deep) from plots B and A (Figure 6A and B) at 24 days after injection (T1) of PM1. PM1 was detectable at densities ranging from 102 to 105/mL groundwater. Higher densities of PM1 were detected in deep wells, compared with shallow wells, in both test plots 31 days after inoculation. PM1 cell densities were quantified in some of the plot B wells that were up to one log order higher than those in plot A; however, this trend was not evident in other wells that showed similar densities of PM1. Cell densities declined substantially over the course of the field trial (120 days, 240 days; Figure 6) in both the shallow and deep zones. The specificity of the TaqMan PCR primers for strain PM1 was confirmed by sequencing the PCR products. Sequence analyses of 16S rDNA TaqMan PCR products obtained with extracted DNA from plots B and A showed 99–100% similarity with the bacterial strain PM1. There was a strong correspondence between positive ITS PCR detection of strain PM1 and TaqMan detection of PM1 in samples containing more than 103 cells/mL. At lower densities, the ITS conventional PCR method was not sensitive enough to detect strain PM1.
A third set of PM1-specific primers were designed to target a different region of 16S rRNA molecule than that targeted by the TaqMan primers (Hristova et al. 2003). Using this set of 16S primers with denaturing gradient gel electrophoresis (DGGE) analysis provided additional evidence of the presence of PM1 in both plots A and B. DNA sequences from the 375-bp band (from plot A and plot B) were 99% similar to the sequence of PM1’s 16S rDNA (data not shown).
In summary, our results suggest the presence of a naturally occurring strain PM1 at PH. We could not determine, however, whether the presence of PM1 in plot A was due to movement from the inoculated plot (by some unknown mechanism, perhaps related to sparging) or if the organism was native to the site. We also tested whether PM1 was present in locations far removed from the field site. Eight groundwater samples were collected outside of the field-tested plots 240 days after injection of strain PM1: two of the samples close to our plots, three up-gradient, and three down-gradient of the plots (Table 1). DNA was extracted and tested for PM1 presence by ITS and TaqMan PCR. PM1 was detected by both PCR techniques in only one of the samples located far away (down-gradient) from the test plots (CBC-51). Two more samples, one close to plot B (CBC-60-CS) and one farther down-gradient (PHA4), showed PM1 presence by TaqMan real-time PCR.
We isolated a bacterial strain from PH site PHA4 (623 m down-gradient the test plots), where 5.7 × 103 cells/mL PM1 is present in the groundwater as estimated by TaqMan PCR (Table 1). Sequencing of portions of the genome of this bacterial strain indicated that the new isolate was 100% similar to PM1 in the 16S rDNA and 99% in the ITS region. The isolate was able to degrade MTBE in laboratory microcosms but at rates far slower than those measured for strain PM1 (data not shown).
Discussion
A major objective of our study was to determine if bioaugmentation with strain PM1 was necessary to support in situ MTBE removal from contaminated groundwater. Our results indicate that rates of MTBE removal were similar in both inoculated and uninoculated plots amended with oxygen. It is possible that strain PM1 and/or a naturally occurring PM1-like organism may be responsible for some of the biological removal of MTBE in the plots, as evidenced by detection of strain PM1 sequences in groundwater samples from both plots A and B. Results of controlled microcosm studies provide further evidence that oxygen additions to uninoculated PH aquifer sediments stimulate native MTBE-degrading organisms already present in these samples. After exposure of the native community to MTBE in microcosms, additional inputs of MTBE were degraded at rates similar to those measured for the pure culture of strain PM1.
In a field study of MTBE bioremediation also conducted at PH, Salanitro et al. (2000) compared rates of MTBE removal in two oxygen-sparged test plots, one that was inoculated with a mixed culture, MC-100 and the other not inoculated. Native MTBE-degrading organisms in the uninoculated plots were also capable of MTBE removal, similar to what we observed in our study, when provided with oxygen. A long lag period elapsed, however, before MTBE removal was detectable in the uninoculated plots; no such lag was observed in the bioaugmentation plot in the study by Salanitro et al. (2000). The absence of a lag in the uninoculated plots in our study may be due to a longer period of exposure, and possible acclimation, of communities to MTBE in our plots than in the plots in the earlier study by Salanitro et al. (2000).
An unexpected discovery of our study was the detection, in groundwater microbial communities collected outside of plot B, of DNA sequences identical (in two regions of the 16S rDNA and in the ITS region) to sequences of our MTBE-degrading bacterium, strain PM1. These PM1-like sequences were found in locations far removed from where strain PM1 was inoculated and in samples collected with sterilized equipment that had not been used for sampling of inoculated plots. This result suggested that an organism similar to strain PM1 occurs naturally in groundwater at PH. We also found PM1-like sequences in groundwater samples from an MTBE-contaminated aquifer at Vandenberg Air Force Base, located approximately 90 miles north of PH (Hristova et al. 2003), and demonstrated there that PM1-like population densities reflect MTBE concentration and the presence of oxygen. Kane et al. (2001) also detected PM1-like sequences in groundwater samples from two other MTBE-contaminated aquifers in northern California. Future effort will be directed at determining how widespread is the native PM1 organism in the environment and on linking MTBE biodegradation rates to the presence of native PM1.
A limitation of our study was the inability to distinguish between the laboratory strain of PM1 inoculated into plot B and the naturally occurring PM1-like organism, making it impossible to monitor the survival and movement of the introduced strain of PM1. Other regions of strain PM1’s genome will be targeted to try to identify new sequences that may discriminate the laboratory from naturally occurring organisms sharing the same 16S rDNA sequence.
Scale-up and practical application of treatment technologies for biostimulation of native microbial communities are promising and have been demonstrated at some locations. Bruce et al. (2002) reported success with a full-scale MTBE treatment system at PH, in both inoculated and uninoculated treatment beds, with oxygen delivery via sparging. Also, other methods of oxygen delivery have been successfully field tested and shown to provide oxygen while supporting in situ biotreatment of MTBE (e.g., Landmeyer et al. 2001; Wilson et al. 2002). Bioaugmentation with MTBE-degrading organisms may be appropriate for sites where there appears to be limited MTBE biodegradation potential or where accelerated MTBE removal is desired.
Figure 1 Map of MTBE plume at Port Hueneme Naval Construction Battalion Center in Oxnard, California. BTEX: benzene, toluene, ethylbenzene, xylene.
Figure 2 Layout of field test plots. Monitoring and oxygen injection well locations (both shallow and deep wells at many locations) are shown. GW, groundwater.
Figure 3 Effect of inoculation with strain PM1 on biodegradation of MTBE in PH groundwater: microcosm studies under aerobic conditions. The control microcosms contained 1% sodium azide as inhibitor. Each value is the average of three microcosms.
Figure 4 MTBE and oxygen concentrations in wells at plot B (inoculated) and plot A (uninoculated). Numbers on x-axis to the left of 0 are up-gradient; those to the right of 0 are down-gradient. (A–F) MTBE concentrations in plot B shallow wells (A) and deep wells (C); corresponding oxygen concentrations in shallow wells (E ) and deep wells (F ); and MTBE concentrations in plot A shallow wells (B) and deep wells (D). d, days.
Figure 5 ITS analysis: PM1 presence in plot B (24 days after injection of strain PM1) and plot A (oxygen only). Abbreviations: D, deep well; S, shallow well. Inverted images of SYBR Green–stained polyacrylamide gels show PM1 ITS PCR products. Lane M, molecular marker; lane PM1, PM1 pure culture. Other lanes are labeled according to the well from which the DNA was extracted.
Figure 6 PM1 cell densities in PH groundwater from plot B and plot A as quantified by real-time PCR at three different time points: T1, 24 days after PM1 injection into plot B; T4, 120 days; T7, 240 days. Abbreviations: D, deep wells; S, shallow wells. Error bars indicate SD.
Table 1 PM1 presence in PH groundwater wells as quantified by TaqMan real-time PCR.
Groundwater well
CBC-1 CBC-10 CBC-42 CBC-61-CS CBC-60-CD B32S B32D CBC-51 PHB4 PHA4
Distance from plot B (m) 800 649 303 40 40 0 0 474 623 737
PM1 density (cells/mL) < DL < DL < DL < DL 2.2 ± 0.4 × 104 4.6 ± 0.4 × 102 3.0 ± 0.2 × 104 1.9 ± 0.2 × 105 5.7 ± 0.3 × 103 < DL
< DL, below detection limit.
==== Refs
References
Bradley PM Chapelle FH Landmeyer JE 2001a Methyl t -butyl ether mineralization in surface-water sediment microcosms under denitrifying conditions Appl Environ Microbiol 67 1975 1978 11282660
Bradley PM Landmeyer JE Chapelle FH 2001b Widespread potential for microbial MTBE degradation in surface-water sediments Environ Sci Technol 35 658 662 11349274
Bruce CL Miller KD Johnson PC 2002. Full scale bio-barrier demonstration for treatment of mixed MTBE/TBA/BTEX plume at Port Hueneme. Contam Soil Sed Water July/August: 80–84.
Bruns MA Hanson JR Mefford J Scow KM 2001 Isolate PM1 populations are dominant and novel methyl tert -butyl ether-degrading bacteria in compost biofilter enrichments Environ Microbiol 3 220 225 11321538
Clawges RM Zogorski JS Bender D 2000. Key MTBE Findings Based on National Water-Quality Monitoring. USGS Technical Report. Rapid City, SD:U.S. Geological Survey.
Deeb RA Hu HY Hanson JR Scow KM Alvarez-Cohen L 2000a Substrate interactions in BTEX and MTBE mixtures by an MTBE-degrading isolate Environ Sci Technol 35 312 317 11347603
Deeb RA Scow KM Alvarez-Cohen L 2000b Aerobic MTBE biodegradation: an examination of past studies, current challenges and future research directions Biodegradation 11 171 186 11440243
Finneran KT Lovley DR 2001 Anaerobic degradation of methyl tert -butyl ether (MTBE) and tert -butyl alcohol (TBA) Environ Sci Technol 35 1785 1790 11355193
Hanson JR Ackerman CE Scow KM 1999 Biodegradation of methyl tert -butyl ether by a bacterial pure culture Appl Environ Microbiol 65 4788 4792 10543787
Happel AM Beckenbach EH Halden RU 1998. An Evaluation of MTBE Impacts to California Groundwater Resources. UCRL-AR-130897. Livermore, CA:Environmental Protection Department, Environmental Restoration Division, Lawrence Livermore National Laboratory.
Hristova KR Gebreyesus B Mackay D Scow KM 2003 Naturally occurring bacteria similar to the MTBE-degrading strain PM1 are present in MTBE-contaminated groundwater Appl Environ Microbiol 69 2616 2623 12732529
Hristova KR Lutenegger CM Scow KM 2001 Detection and quantification of MTBE-degrading strain PM1 by real-time TaqMan PCR Appl Environ Microbiol 67 5154 5160 11679339
Kane SR Beller HR Legler TC Koester CJ Pinkart HC Halden RU 2001 Aerobic biodegradation of methyl tert -butyl ether by aquifer bacteria from leaking underground storage tank sites Appl Environ Microbiol 67 5824 5829 11722940
Landmeyer JE Chapelle FH Herlong HH Bradley PM 2001 Methyl tert -butyl ether biodegradation by indigenous aquifer microorganisms under natural and artificial ozic conditions Environ Sci Technol 35 118 1126
Salanitro JP Johnson PC Spinnler GE Maner PM Wisniewski HL Bruce C 2000 Field-scale demonstration of enhanced MTBE bioremediation through aquifer bioaugmentation and oxygenation Environ Sci Technol 34 4152 4162
Smith A 2000. Bioaugmentation of MTBE-Contaminated Groundwater with Bacterial Strain PM1 [MS Thesis]. Davis, CA:University of California, Davis.
Squillace PJ Zogorski JS Wilber WG Price CV 1996 Preliminary assessment of the occurrence and possible sources of MTBE in groundwater in the United States, 1993–1994 Environ Sci Technol 30 1721 1730
Wilson RD Mackay DM Scow KM 2002 In situ MTBE biodegradation supported by diffusive oxygen release Environ Sci Technol 36 190 199 11827053
|
15743721
|
PMC1253758
|
CC0
|
2021-01-04 23:40:57
|
no
|
Environ Health Perspect. 2005 Mar 8; 113(3):317-322
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.6939
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7347ehp0113-00032315743722ResearchArticlesAcceleration of Autoimmunity by Organochlorine Pesticides in (NZB × NZW)F1 Mice Sobel Eric S. 1Gianini John 1Butfiloski Edward J. 1Croker Byron P. 23Schiffenbauer Joel 1*Roberts Stephen M. 41Department of Medicine, and2Department of Pathology, Immunology, and Laboratory Medicine, University of Florida College of Medicine, Gainesville, Florida, USA3Northern Florida/Southern Georgia Veterans Health System and Laboratory Medicine Service, Gainesville, Florida, USA4Department of Physiological Sciences, J. Hillis Miller Health Science Center, University of Florida, Gainesville, Florida, USAAddress correspondence to E.S. Sobel, University of Florida College of Medicine, 1600 SW Archer Rd., Box 100221, Gainesville, FL 32610 USA. Telephone: (352) 392-9494. Fax. (352) 392-8483. E-mail:
[email protected]*Current address: U.S. Food and Drug Administration, Center for Drug Evaluation and Research, 9201 Corporate Blvd., Rockville, MD 20850 USA.
This work was supported in part by grants 1R21 ES10296 and 1 P42 ES07375 from the National Institute of Environmental Health Sciences.
The authors declare they have no competing financial interests.
3 2005 2 12 2004 113 3 323 328 22 6 2004 2 12 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Systemic lupus erythematosus (SLE) is an autoimmune disorder that affects women more frequently than men. In the (NZB × NZW)F1 mouse, a murine SLE model, the presence or absence of estrogen markedly influences the rate of progression of disease. Three organochlorine pesticides with estrogenic effects were administered chronically to ovariectomized female (NZB × NZW)F1 mice, and we measured the time to development of renal disease, the principal clinical manifestation of lupus in this model. Treatment with chlordecone, methoxychlor, or o,p′-dichlorodiphenyl-trichloroethane (o,p′-DDT) significantly decreased the time to onset of renal impairment, as did treatment with 17β-estradiol used as a positive control. In an expanded study of chlordecone, we found a dose-related early appearance of elevated anti–double-strand DNA autoantibody titers that corresponded with subsequent development of glomerulonephritis. Immunohistofluorescence confirmed early deposition of immune complexes in kidneys of mice treated with chlordecone. These observations are consistent with an effect of these organochlorine pesticides to accelerate the natural course of SLE in the (NZB × NZW)F1 mouse. Although we originally hypothesized that the effect on progression of autoimmunity was due to estrogenic properties of the pesticides, autoimmune effects and estrogenicity, assessed through measurement of uterine hypertrophy, were not well correlated. This may indicate that uterine hypertrophy is a poor indicator of comparative estrogenic effects of organochlorine pesticides on the immune system, or that the pesticides are influencing autoimmunity through a mode of action unrelated to their estrogenicity.
autoimmunitychlordeconeDDTestrogenicityglomerulonephritiskeponemethoxychlororganochlorine pesticidessystemic lupus erythematosus
==== Body
Systemic lupus erythematosus (SLE) is a chronic, systemic autoimmune disorder characterized by exacerbations and remissions of varying intensity and duration. Its clinical manifestations are almost invariably accompanied by the presence of autoantibodies directed at a wide array of self-components, including cell-surface structures (surface proteins and phospholipids on lymphocytes) and intracellular molecules (DNA, histones, and RNA) (von Muhlen and Tan 1995). Among its many manifestations, the presence of renal disease in the form of glomerulonephritis is used as a major predictor of morbidity and mortality (Ansell et al. 1996).
Current evidence suggests that a combination of factors plays a role in the development of autoimmunity in SLE, including genetic, environmental, hormonal, and viral influences (D’Cruz 2000; Roubinian et al. 1978). Although SLE can be seen in either sex at any age, females are at a much greater risk than are males, with the highest incidence occurring in women in their childbearing years (Lahita 1996). Although the precise factors responsible for the increased incidence of disease in women remain to be clarified, several lines of evidence suggest that sex hormones may be a predisposing factor (Cutolo et al. 1995; Rood et al. 1998; Sanchez-Guerrero et al. 1997).
An influence of estrogen status on the development of SLE is clearly demonstrated in murine SLE models, such as the (NZB × NZW)F1 mouse. Although most (NZB × NZW)F1 mice develop SLE spontaneously and experience premature mortality, females develop more severe disease and succumb at an earlier age than do males (Roubinian et al. 1978). Androgen treatment of females decreases autoantibody levels, diminishes renal disease, and improves survival (Roubinian et al. 1979). In males, castration or administration of estrogen accelerates development of SLE.
Several environmental contaminants have been found to produce estrogen-like effects, including some of the organochlorine pesticides (OCPs) (e.g., Andersen et al. 2002; Soto et al. 1994). Given the influence of estrogen on SLE in experimental models, we hypothesized that OCPs with estrogenic effects would similarly accelerate lupus development. As an initial test of this hypothesis, three different OCPs were tested for effects on the time course of development of lupus in female (NZB × NZW)F1 mice, o,p′-dichlorodiphenyltrichloroethane (o,p′-DDT), methoxychlor, and chlordecone. Each of these pesticides had been shown previously to possess estrogenic activity in vivo (e.g., Cummings 1997; Das-Sanjoy et al. 1998; Flaws et al. 1997; Morozova et al. 1997). Mice were ovariectomized to reduce the potentially confounding effects of cycling endogenous estrogen and were treated chronically with one of the pesticides or with 17β-estradiol as a positive control. Time to development of clinical SLE, manifested as terminal immune complex glomerulonephritis, was measured. In these experiments, all of the OCPs caused acceleration of time to development of SLE, with chlordecone producing the greatest response. More detailed, follow-up experiments were conducted with chlordecone to examine dose–response relationships and verify estrogenic effects. The results of these experiments, reported here, indicate an effect of the OCPs to speed progression of autoimmunity in (NZB × NZW)F1 mice.
Materials and Methods
Mice.
Female (NZB × NZW)F1 mice, 6–8 weeks of age, were obtained from the Jackson Laboratory (Bar Harbor, ME). Mice were housed in temperature-, light-, and humidity-controlled animal quarters under specific-pathogen-free conditions. Polycarbonate cages with ground corncob bedding were used, and mice had free access to food and water for the duration of the experiment. All procedures were approved by the institutional animal care and use committee of the University of Florida.
Ovariectomy.
All animals were subjected to ovariectomy or a sham-operation approximately 1 week after they were received. Surgery was performed under anesthesia with a mixture of ketamine (133 mg/kg) and xylazine (13 mg/kg) administered intraperitoneally. All procedures were identical for ovariectomized and sham-surgery mice, except that in the latter case, ovaries were exposed but not ligated and removed.
Test materials and treatments.
We purchased chlordecone (described as 99.2% pure) from Crescent Chemical (Islandia, NY). methoxychlor (95%) from Sigma Chemical Co. (St. Louis, MO), and o,p′-DDT (98%) from Chem Service (Westchester, PA). We confirmed the identity of each material as supplied by gas chromatography–mass spectrometry. Each pesticide was formulated in specified amounts into sustained-release pellets (60-day release) by Innovative Research of America (Sarasota, FL). Control pellets (matrix only), and pellets containing 17β-estradiol were also obtained from this source. One week after ovariectomy, mice were implanted subcutaneously with an OCP, 17β-estradiol, or control pellet. For implantation, mice were lightly anesthetized with methoxyflurane, and the pellet was placed beneath the skin dorsally above the shoulders. Implants were replaced every 60 days for the duration of the experiment.
Evaluation of renal function.
Once the pellets were implanted, we systematically evaluated the course of the disease. The appearance of renal disease was detected through monthly measurement of urine protein and blood urea nitrogen (BUN). Urine was collected from spontaneous expression during manual restraint. Proteinuria was measured by dipstick method using Albustix (Bayer Corp., Elkhart, IN). Blood samples were obtained from tail nicks, and BUN was measured using Azostix (Bayer Corp.). Body weights were also recorded monthly. If animals showed weight loss of ≥10% or worsening renal function by either BUN or proteinuria, they were reassessed every 2 weeks until termination. Mice were euthanized when the BUN reached or exceeded 50 mg/dL and/or proteinuria reached or exceeded 2,000 mg/dL. In the initial study of three OCPs, surviving mice were euthanized 8 months after the start of treatment. In the second study focusing on chlordecone, the experiment was ended and surviving mice euthanized after 7 months of treatment.
Histology.
At defined time points, mice from each group were euthanized, and their kidneys were preserved in 10% buffered formalin. Tissue samples were processed routinely, sectioned, mounted on glass slides, and stained with hematoxylin and eosin or periodic acid Schiff (PAS) for light microscopic examination. All kidney sections were viewed and scored by a pathologist in a blinded examination. The glomeruli were categorized using a modified World Health Organization classification (Churg et al. 1995) as having no damage, mesangiopathic damage, or proliferative damage. In addition to the severity of the glomerular damage, the amount of renal damage was quantified using the following scale: 1+, 1–9% of glomeruli affected; 2+, 10–24% of glomeruli affected; 3+,(25–49% of glomeruli affected; and 4+, ≥50% of glomeruli affected.
Autoantibody titers.
We measured auto-antibody [IgG anti–double-strand DNA (anti-dsDNA)] titers in serum in some treatment groups using indirect ELISA (enzyme-linked immunosorbent assay). Immulon 2 microtiter plates (Dynatech Laboratories, Inc., Chantilly, VA) were coated overnight at 4°C with a 1:10 (vol/vol) dilution of poly-l-lysine at 100 μL/well. Between all steps, microplates were washed three times with borate-buffered saline (25 mM Na2B4O7, 75 mM NaCl, 100 mM H3BO3, pH 8.4) containing 0.05% Tween 20. After addition of calf thymus DNA (50 μL/well at a concentration of 20 μg/mL), the plate was blocked with 100 μL/well of 3% bovine serum albumin (BSA) in phosphate-buffered saline (PBS). Dilutions (1:200) of serum samples were prepared in PBS and incubated in the appropriate wells at room temperature for 1 hr. The secondary antibody (goat anti-mouse IgG peroxidase conjugated Fc gamma specific; Jackson ImmunoResearch Laboratories, West Grove, PA) was diluted to 1:5,000 (vol/vol) in PBS and added at 50 μL/well. The developing solution consisted of o-phenylene diamine at 0.4 mg/mL PC buffer (4.7 g/L citric acid and 13.8 g/L sodium phosphate dibasic heptahydrate, pH 5.1) with 0.01% H2O2. The substrate turnover was determined by the difference between the OD450 (optical density) and OD620 on a Molecular Devices (Sunnyvale, CA) microplate reader. The concentration of antigen-specific IgG is reported in equivalent dilution factors (EDFs) of standardized reference NZB × NZW/F1 sera. This is defined by the formula EDF = (dilution of a standard reference sera that gives the equivalent OD of the test serum) × 104.
Immunohistofluorescence.
Immune complex deposition in glomeruli was visualized by immunohistofluorescence. Renal tissue sections 7 μm in thickness were mounted to glass slides (Fisher Scientific, Fairlawn, NJ). Blocking solution (1% BSA, 0.1% Tween, and 10% rat serum in PBS) was applied for 20 min. Then slides were incubated with 100 μL goat anti-mouse IgG–fluorescein isothiocyanate antibody (Southern Biotech, Birmingham, AL) diluted 1:40 in PBS with 1 mg/mL BSA for 30 min in a humidified chamber. Slides were then washed three times in PBS and once in distilled water. One drop of glycerin was placed on the sample, and the slide was coverslipped and examined by fluorescence microscopy.
Uterine hypertrophy.
We conducted a separate, short-term experiment in which we evaluated the estrogenicity of the chlorinated pesticides at various doses. Ovariectomized mice were implanted with a control pellet or a pellet containing pesticide or 17β-estradiol as in the chronic experiments. After a 4-week period, the mice were euthanized, and estrogenicity of the doses was determined by measurement of wet uterine weight. Immediately after euthanasia, the uteri were excised, trimmed free of fat, pierced, and blotted to remove excess fluid. The body of the uterus was cut just above its junction with the cervix and at the junction of the uterine horns with the ligating clips. The uterus was then weighed (wet weight). To compensate for the mass of the mouse, uterine weight was expressed as a ratio to total body weight (i.e., uterine mass/body mass × 1,000).
Statistical analysis.
We performed statistical analysis for survival using GraphPad Prism 3 software (GraphPad Software Inc., San Diego, CA). Uterine wet ratios were compared for significance using Dunnett’s procedure of one-way analysis of variance (ANOVA). Proteinuria and BUN data were tested using Dunnett’s nonparametric procedure of the Kruskal-Wallis ANOVA on ranks. The autoantibody levels were natural log-transformed before analysis in order to normalize their distribution and improve the accuracy of the analysis. After transformation, statistical significance was determined using Dunnett’s method of ANOVA. Survival data were displayed as Kaplan-Meier survival curves. We determined differences between survival curves using the log rank test. For the dose–response experiment, we also performed the log rank test for trend.
Results
We conducted an experiment in which we assessed the effects of chronic treatment with chlordecone, o,p′-DDT, or methoxychlor on time to development of lupus in ovariectomized (NZB × NZW)F1 mice. The objective of this experiment was to provide an initial test of the hypothesis that estrogenic OCPs accelerate the rate of development of disease in this lupus model. Chronic doses of these pesticides producing estrogenic effects in mice were not clearly established in the literature and were therefore estimated based upon short-term studies in the literature of potential estrogenic effects in vivo. Two doses of each OCP were tested: 1.8 and 18 mg chlordecone, 0.9 and 9 mg o,p′-DDT, and 3 and 30 mg methoxychlor. As a positive control, we also tested 0.1 mg 17β-estradiol. These doses were the amount of chemical delivered over each 60-day interval via implanted pellets. Ovariectomized females given pellets with matrix only served as controls, and an additional comparison group of untreated, ovary-intact (sham operated) females was included in the experiment. Each treatment group contained 10 animals. Within a few weeks of the start of the experiment, mice treated with the 18-mg chlordecone pellets developed tremors and were removed from the study. Overt neurotoxicity was not observed in the other treatment groups.
The primary assessment end point for this experiment was the development of severe renal disease, the hallmark of lupus in this animal model. Time to development of severe renal disease for each treatment group is shown in the form of Kaplan-Meier survival curves in Figure 1. Ovariectomy extended substantially the time to development of renal disease in this mouse strain. This is evident by comparing the time courses in Figure 1 for the ovariectomized controls with the sham-operated (i.e., ovary intact) comparison group. Replacement of estrogen with 17β-estradiol (0.1 mg/pellet) in ovariectomized mice shortened the time to appearance of renal disease such that it was not significantly different from that of sham-operated mice (Figure 1D).
Treatment of ovariectomized mice with o,p′-DDT or methoxychlor significantly shortened the time to development of renal disease compared with controls (Figure 1A,B). The survival plots for o,p′-DDT–treated and methoxychlor-treated groups were essentially the same as the plot for the sham-operated comparison group, suggesting an influence on lupus development roughly equivalent to that of endogenous estrogen. There was no significant difference in survival curves between the two doses tested for o,p′-DDT and methoxychlor, although the higher o,p′-DDT doses appeared to result in more rapid development of renal disease. The time to development of renal disease in the single chlordecone-treated group completing the study was significantly shorter than both the ovariectomized controls and the untreated, sham-surgery comparison group (Figure 1C). The difference in survival was particularly striking after 22 weeks of chlordecone treatment: 100% of the ovariectomized controls, 60% of the mice in the sham-surgery group, and none of the chlordecone-treated mice survived to this time point.
Additional mice were implanted with 1.8 mg chlordecone or control pellets and euthanized after 16 weeks of treatment. Measurement of proteinuria at this time point indicated severe renal disease in the chlordecone-treated mice but not in the ovariectomized controls. Renal sections from these mice were examined by light microscopy (Figure 2). The observations correlated well with proteinuria findings and were consistent with early appearance of immune complex glomerulonephritis in chlordecone-treated mice. All of the chlordecone-treated mice had developed significant proliferative glomerulonephritis with fibrosis, the most severe form of glomerulonephritis in lupus. The control mice, in contrast, showed only mesangial involvement, an early or mild form of renal disease. One control animal had evidence of proliferative glomerulonephritis, but only approximately 10% of glomeruli were affected.
In view of the particularly strong response to chlordecone, we conducted a follow-up experiment in which lower doses of chlordecone were tested (0.01, 0.1, 0.5, and 1.0 mg per 60-day-release pellet). The control group (matrix-only pellets) consisted of 20 animals; all other groups consisted of 10 animals each. The time course for development of severe renal disease is shown in Figure 3. Mice treated with the 1.0 or 0.5 mg chlordecone pellets developed renal disease significantly earlier than did ovariectomized controls (p < 0.05). The rate of development of lupus also appeared to be enhanced in mice treated with 0.01 and 0.1 mg chlordecone pellets, although the difference did not reach statistical significance. The log rank test for trend using all three doses was statistically significant (p < 0.03).
During the course of the follow-up experiment with chlordecone, mice were bled periodically, and the sera were tested for anti-dsDNA by ELISA. Elevated autoantibody titers appeared earlier in chlordecone-treated mice than in ovariectomized controls. The greatest difference was seen after 20 weeks of treatment, a time point in this experiment at which substantial differences in overt renal disease had not yet appeared (Figure 3). Mice treated with 1 mg chlordecone pellets had titers significantly higher than those of controls (p < 0.01) and essentially equivalent to those in the sham-operated comparison group (Figure 4). Autoantibody titers in mice treated with 0.1 mg chlordecone were also elevated compared with controls, but the difference was not statistically significant.
To verify that the earlier renal failure in chlordecone-treated mice was of autoimmune origin, a separate small cohort of (NZB × NZW)F1 female mice was ovariectomized and individual animals were implanted with a control pellet or a pellet containing chlordecone (1 mg) or estradiol (0.05 mg). Approximately 8 weeks later, at a time when some of the mice were beginning to show proteinuria, all mice were euthanized. The spleens were weighed, and the kidneys were evaluated for histopathology and immunostained for IgG. By light microscopic examination, there was a tendency toward worsened proliferative glomerulonephritis in the chlordecone- and estradiol-treated groups (Figure 5A). In contrast, less severe mesangiopathic changes were decreased, particularly in the estradiol-treated groups (Figure 5B). In general, proliferative and mesangiopathic changes were not seen on the same specimens. Proteinuria was greater in both the chlordecone- and estradiol-treated groups (Figure 5C), and both differences were statistically significant when compared to ovariectomized controls (p < 0.05). Spleen weight (Figure 5D) was clearly increased in the estradiol-treated group, and this reached statistical significance (p < 0.05). We also observed a tendency toward increased spleen weight in the chlordecone-treated group, but it did not reach statistical significance (p = 0.14). These observations were consistent with previous experiments showing similar, early development of severe renal disease in chlordecone-and estradiol-treated (NZB × NZW)F1 mice (Figure 1). Immunohistofluorescence analysis of renal sections showed enhanced deposits of IgG in the chlordecone- and estradiol-treated groups (Figure 5E). Little or no immuno-staining was observed in the control group at this time point. As indicated by previous experiments, had the control mice been observed for longer periods, they ultimately would have developed proteinuria and renal disease. For perspective on the extent of immune complex deposition in controls at these later time points, renal sections from controls from previous experiments, taken at the time of development of renal disease, were also immunostained. As shown in Figure 5E, the immune complex deposition when renal disease appeared was similar in control, chlordecone-treated, and estradiol-treated mice. These observations offer additional support for the concept that chlordecone treatment results in earlier appearance of renal disease by accelerating the course of autoimmune disease in a manner similar to estrogen.
The estrogenicity of chlordecone, methoxychlor, and o,p′-DDT in doses relevant to the autoimmunity experiments was tested using the classical end point of uterine hypertrophy. (NZB × NZW)F1 mice were ovariectomized and subsequently implanted subcutaneously with a control pellet or a pellet containing one of the pesticides. Additional mice were treated with a pellet containing 17β-estradiol as a positive control. Six weeks after implantation, mice were euthanized, and the uterine wet weight and total body weight were measured. Chlordecone and o,p′-DDT produced uterine hypertrophy (Figure 6), although, except for the highest doses of o,p′-DDT and chlordecone tested, the effects were substantially less than those produced by estradiol (0.5 mg/pellet). Chlordecone was tested over the broadest range of doses. Chlordecone doses of ≥18 mg/pellet were required to produce significant uterine hypertrophy, despite observations in previous experiments that doses as low as 1 mg/pellet were sufficient to influence the rate of development of lupus.
Discussion
It has long been hypothesized that environmental factors influence the onset and course of autoimmune diseases. Despite this, the number of chemicals clearly shown to influence autoimmunity is relatively small. Although a number of potential mechanisms can be postulated, they are thought to fall into three general categories (Rao and Richardson 1999). The first category is one in which the chemical alters self antigen such that it appears foreign to the immune system. This can occur when small molecules act as haptens or if exposure can cause novel cleavage fragments to which the immune system was ignorant. Heavy metals, such as mercury, may be an example of this pathway. The second category is one in which the chemical prevents the central tolerance of autoreactive T or B cells and is represented by pro-cainamide hydroxylamine. The third category involves alteration of gene expression. Hormones, such as estrogens, are thought to belong to this last category (Grimaldi et al. 2002). Because many of the OCPs have been shown to have estrogenic effects, we decided to test representative estrogenic OCPs in the well-characterized (NZB × NZW)F1 model of murine lupus.
The chronic administration of chlordecone, methoxychlor, or o,p′-DDT via implantable pellets significantly shortened the time to development of lupus in ovariectomized female (NZB × NZW)F1 mice. The most extensive experimentation was conducted with chlordecone and showed a dose-related, early appearance of elevated anti-dsDNA autoantibody titers and immune complex deposition in the kidneys. Doses of chlordecone that significantly elevated autoantibody titers at early time points also significantly reduced the time to subsequent development of renal disease, which was confirmed to be immune complex glomerulonephritis, the hallmark for clinical lupus in this murine model. Collectively, these observations indicate that chlordecone, and probably also methoxychlor and o,p′-DDT, acts by accelerating the natural course of development of lupus in these animals.
For chlordecone, the lowest dose per pellet found to produce a significant decrease in time to onset of renal disease was 0.5 mg. Over the course of the experiment, mice weighed on average about 42 g, resulting in a dosing rate per unit body weight of approximately 0.20 mg/kg/day. The next lower dose of chlordecone tested, 0.1 mg per pellet (or about 0.04 mg/kg/day), might be considered a no observable effect level (NOEL) from this experiment. However, there was evidence for an effect at this level and even at the lowest dose of chlordecone tested (0.01 mg/pellet). It is possible that with the use of larger treatment groups, effects from these lower doses might also reach statistical significance. Other effects of chlordecone, such as renal and liver toxicity, are generally associated with chronic chlordecone doses of 0.05 mg/kg/day or higher in rodents [Agency for Toxic Substances and Disease Registry (ATSDR) 1995].
For both methoxychlor and o,p′-DDT, doses spaced about 10-fold apart produced essentially equivalent responses. This suggests either that the effect is not dose related or that the response from the doses tested is near the maximum for these pesticides. Because the lower doses produced a significant effect, a NOEL for acceleration of autoimmunity by these pesticides cannot be determined from this study. It is worthwhile noting that the lower dose of methoxychlor tested (3 mg/pellet, or approximately 1.2 mg/kg/day) is 4-fold lower than the NOEL used by the U.S. Environmental Protection Agency (EPA) in developing an oral reference dose for methoxychlor (U.S. EPA 2004). This suggests that an effect on autoimmunity might be a sensitive toxic end point (an effect that occurs at doses lower than other adverse effects) for methoxychlor, and therefore of particular interest for risk assessment. o,p′-DDT decreased the time to development of lupus at a dosing rate of 0.9 mg/pellet (or ~ 0.35 mg/kg/day). This is similar to the lowest observable effect level for p,p′-DDT (0.25 mg/kg/day) identified by the EPA based on liver changes in rats (U.S. EPA 2004), suggesting that autoimmune effects may be a sensitive end point for this OCP as well.
Changes in the time course for development of lupus produced by the OCPs in ovariectomized mice were comparable to that produced by 17β-estradiol, used in the study as a positive control for estrogenic effects. By and large, treatment of ovariectomized mice with the OCPs resulted in a rate of progression of disease that resembled its natural course in mice with intact estrogen, represented by the sham-surgery comparison group. These observations are consistent with an estrogenic mode of action for chlordecone, methoxychlor, and o,p′-DDT effects on autoimmunity. However, estrogenicity, as measured by uterine hypertrophy in the (NZB × NZW)F1 mice, correlated poorly with effectiveness in accelerating autoimmunity. Chlordecone had a greater effect on autoimmunity than either methoxychlor or o,p′-DDT but produced the same or less uterine hypertrophy at relevant doses. At lower doses where chlordecone was still effective in significantly decreasing the time to onset of renal disease, no significant effect on uterine weight was observed. The poor correlation might be due simply to differences in responsiveness to estrogenic effects by the uterus compared with the immune system. Unfortunately, there is little information in the literature that offers insight regarding this possibility.
Alternatively, the OCPs may influence autoimmunity through a mode of action unrelated to their estrogenicity. The potential importance of alternative actions is amply demonstrated by the recent study of Sawai et al. (2003), who fed female (NZB × NZW)F1 mice a diet containing bisphenol A. Bisphenol A is produced in the manufacture of plastics and has been shown to produce estrogen-like effects both in vitro and in vivo. In contrast to expectations based on estrogenicity, bisphenol A treatment significantly delayed the appearance of renal disease relative to controls. The authors attributed the delay by bisphenol A to an observed decrease in interferon-γproduction, an effect opposite of that known to be produced by estrogen.
In the experiments reported here we used a lupus model with a high genetic predisposition for disease. With this model, it was possible to demonstrate an effect of selected OCPs to modify the rate of progression of disease but not to test whether they are capable of influencing the incidence of disease. It remains to be determined whether these or other OCPs can initiate, on a susceptible genetic background, a break in tolerance—in other words, whether they can cause SLE in a susceptible individual that might not otherwise develop it. Answering this question will require testing OCPs in mouse strains with differing genetic background with respect to SLE susceptibility genes. Several such strains are available (e.g., Wakeland et al. 2001), and their use will be important in better characterizing the autoimmune hazard associated with OCP exposure.
Correction
Values for body weight and dosing rate for chlordecone and the dosing rates for methoxychlor and o,p′-DDT were incorrect in the “Discussion” of the original manuscript published online. They have been corrected here.
Figure 1 Time to development of renal disease (plotted as a survival curve) in ovariectomized (NZB × NZW)F1 mice implanted with pellets containing (A) methoxychlor, (B) o,p′-DDT, (C) chlordecone, or (D) 17β-estradiol; ovariectomized mice implanted with control pellets and sham-operated mice are shown for comparison (n = 10/group). The time to development of renal disease was significantly decreased in all OCP-treated groups compared with ovariectomized controls (p < 0.05)
Figure 2 Representative kidney sections taken from (NZB × NZW)F1 mice after 16 weeks of treatment. (A) Sham-operated mouse. (B) Ovariectomized mouse treated with chlordecone (1.8 mg/pellet). (C and D) Two ovariectomized mice, each treated with a control pellet. (A) and (B) show enlarged, cellular, and sclerotic glomeruli (arrows) with tubular atrophy and dilation (asterisks). (C) and (D) show segmental mesangial thickening, but otherwise spared, glomeruli (arrows) with normal tubules (asterisk). Sections were stained with PAS (magnification, 400×).
Figure 3 Time to development of renal disease in ovariectomized (NZB × NZW)F1 mice (n = 20 controls; n = 10 sham operated; n = 10 for each of the chlordecone-treated groups). The time to appearance of renal disease was significantly decreased in mice treated with the 1-mg chlordecone pellets (p < 0.05).
Figure 4 Serum autoantibody titers in ovariectomized (NZB × NZW)F1 mice treated 20 weeks after treatment with chlordecone. Ovariectomized mice implanted with control pellets and sham-operated mice are shown for comparison. Antibody titers from mice treated with 1 mg chlordecone pellets were significantly higher than those of ovariectomized controls (p < 0.01).
Figure 5 Enhanced renal disease and immune complex deposition in ovariectomized, chlordecone-treated mice after 8 weeks of treatment with control pellets or pellets containing chlordecone (1 mg/pellet) or 17β-estradiol (0.05 mg/pellet; n = 6/group). Frequency of appearance of proliferative glomerulonephritis (GN; A), mesangiopathic glomerulonephritis (B), and proteinuria (C), and spleen weight. The frequency of occurrence of proteinuria was significantly increased in both chlordecone-treated and 17β-estradiol–treated mice; spleen weight (D) was significantly increased by 17β-estradiol. (E) Immunofluorescence staining (magnification, 200×) for IgG was absent in control mice, but present in mice treated with either chlordecone or 17β-estradiol after 8 weeks of treatment; later, when renal disease developed in controls, a similar extent of immunofluorescence staining was observed.
Figure 6 Uterine hypertrophy in ovariectomized (NZB × NZW)F1 mice 6 weeks after administration of pellets containing (A) methoxychlor, (B) o,p′-DDT, and (C) higher and (D) lower doses of chlordecone. Results from controls and 17β-estradiol–treated mice are reproduced in A–C to facilitate comparison with OCP-treated mice. Compared with controls, uterine weights were significantly increased in mice treated with 0.05 mg estradiol, 10 mg methoxychlor, 0.9 and 9.0 mg o,p′-DDT, and 36 mg chlordecone.
==== Refs
References
Andersen HR Vinggaard AM Rasmussen TH Gjermandsen IM Bonefeld-Jorgensen EC 2002 Effects of currently used pesticides in assays for estrogenicity, androgenicity, and aromatase activity in vitro Toxicol Appl Pharmacol 179 1 12 11884232
Ansell SM Bedhesi S Ruff B Mahomed AG Richards G Mer M 1996 Study of critically ill patients with systemic lupus erythematosus Crit Care Med 24 981 984 8681602
ATSDR 1995. Toxicological Profile for Mirex and Chlordecone. Atlanta, GA:Agency for Toxic Substances and Disease Registry.
Churg J Bernstein J Glassock RJ 1995. Lupus nephritis. In: Renal Diseases. Classification and Atlas of Glomerular Diseases (Churg J, Bernstein J, Glassock RJ, eds). New York:Igaku-Shoin, 151–169.
Cummings AM 1997 Methoxychlor as a model for environmental estrogens Crit Rev Toxicol 27 367 379 9263644
Cutolo M Sulli A Seriolo B Accardo S Masi AT 1995 Estrogens, the immune response and autoimmunity Clin Exp Rheumatol 13 217 226 7656468
Das-Sanjoy K Tan-Jian Johnson DC Dey SK 1998 Differential spatiotemporal regulation of lactoferrin and progesterone receptor genes in the mouse by primary estrogen, catechol estrogen, and xenoestrogen Endocrinology 139 2905 2915 9607801
D’Cruz D 2000 Autoimmune diseases associated with drugs chemicals and environmental factors Toxicol Lett 112–113 421 432
Flaws JA DeSanti AM Devine PJ Hirshfield AN Silbergeld EK 1997 Effect of in utero kepone exposure on the female rat urogenital tract Toxicologist 36 356
Grimaldi CM Cleary J Dagtas AS Moussai D Diamond B 2002 Estrogen alters thresholds for B cell apoptosis and activation J Clin Invest 109 1625 1633 12070310
Lahita RG 1996 The connective tissue diseases and the overall influence of gender Int J Fertil Menopausal Stud 41 156 165 8829695
Morozova OV Riboli E Turusov VS 1997 Estrogenic effect of DDT in CBA female mice Exp Toxicol Pathol 49 483 485 9495650
Rao T Richardson B 1999 Environmentally induced auto-immune diseases: potential mechanisms Environ Health Perspect 107 suppl 5 737 742 10502539
Rood MJ Van Der Velde EA Ten Cate R Breedveld FC Huizinga TW 1998 Female sex hormones at the onset of systemic lupus erythematosus affect survival Br J Rheumatol 37 1008 1010 9783768
Roubinian JR Talal N Greenspan JS Goodman JR Siiteri PK 1978 Effect of castration and sex hormone treatment on survival, anti-nucleic acid antibodies, and glomerulonephritis in NZB/NZW F1 mice J Exp Med 147 1568 1583 308087
Roubinian JR Talal N Greenspan JS Goodman JR Siiteri PK 1979 Delayed androgen treatment prolongs survival in murine lupus J Clin Invest 63 902 911 447833
Sanchez-Guerrero J Karlson EW Liang MH Hunter DJ Speizer FE Colditz GA 1997 Past use of oral contraceptives and the risk of developing systemic lupus erythematosus Arthritis Rheum 40 804 808 9153539
Sawai C Anderson K Walser-Kuntz D 2003 Effect of bisphenol A on murine immune function: modulation of interferon-γ, IgG2a, and disease symptoms in NZB × NZW F1 mice Environ Health Perspect 111 1883 1887 14644661
Soto AM Chung KL Sonnenschein C 1994 The pesticides endosulfan, toxaphene, and dieldrin have estrogenic effects on human estrogen-sensitive cells Environ Health Perspect 102 380 383 7925178
U.S. EPA 2004. Integrated Risk Information System. Washington, DC:U.S. Environmental Protection Agency. Available: http://www.epa.gov/iris [accessed 7 May 2004].
von Muhlen CA Tan EM 1995 Autoantibodies in the diagnosis of systemic rheumatic diseases Sem Arthritis Rheum 24 323 358
Wakeland EK Liu K Graham RR Behrens TW 2001 Delineating the genetic basis of systemic lupus erythematosus Immunity 15 397 408 11567630
|
15743722
|
PMC1253759
|
CC0
|
2021-01-04 23:40:57
|
no
|
Environ Health Perspect. 2005 Mar 2; 113(3):323-328
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7347
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7418ehp0113-00032915743723ResearchArticlesAssessment of Estrogenic Endocrine-Disrupting Chemical Actions in the Brain Using in Vivo Somatic Gene Transfer Trudeau Vance L. 1Turque Nathalie 2Le Mével Sébastien 2Alliot Caroline 2Gallant Natacha 1Coen Laurent 2Pakdel Farzad 3Demeneix Barbara 21Centre for Advanced Research in Environmental Genomics, Department of Biology, University of Ottawa, Ottawa, Ontario, Canada2UMR-5166, Evolution des Régulations Endocriniennes, Museum National d’Histoire Naturelle, Centre National de la Recherche Scientifique, Paris, France3UMR-6026, Equipe d’Endocrinologie Moléculaire de la Reproduction, Centre National de la Recherche Scientifique, Université de Rennes, Rennes, FranceAddress correspondence to V.L. Trudeau, Department of Biology, Third Floor, MacDonald Hall, University of Ottawa, Ottawa, Ontario K1N 6N5 Canada. Telephone: (613) 562-5800 ext. 6165. Fax: (623) 562-5486. E-mail:
[email protected]. was Professeur Invité at the Muséum National d’Histoire Naturelle, Paris, when this work was initiated.
We thank K. Palmier for performing the protein assays; G. Benisti, J.-P. Chaumeil, and E. LeGoff for animal care and technical support; and A. DeLuze for discussions and advice.
This study was supported by the Natural Sciences and Engineering Research Council of Canada, the Canadian Network of Toxicology Centres, the University of Ottawa, Museum National d’Histoire Naturelle, Paris, and Euromedex.
The authors declare they have no competing financial interests.
3 2005 2 12 2004 113 3 329 334 14 7 2004 2 12 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Estrogenic endocrine-disrupting chemicals abnormally stimulate vitellogenin gene expression and production in the liver of many male aquatic vertebrates. However, very few studies demonstrate the effects of estrogenic pollutants on brain function. We have used polyethylenimine-mediated in vivo somatic gene transfer to introduce an estrogen response element–thymidine kinase–luciferase (ERE-TK-LUC) construct into the brain. To determine if waterborne estrogenic chemicals modulate gene transcription in the brain, we injected the estrogen-sensitive construct into the brains of Nieuwkoop-Faber stage 54 Xenopus laevis tadpoles. Both ethinylestradiol (EE2; p < 0.002) and bisphenol A (BPA; p < 0.03) increased luciferase activity by 1.9- and 1.5-fold, respectively. In contrast, low physiologic levels of 17β-estradiol had no effect (p > 0.05). The mixed antagonist/agonist tamoxifen was estrogenic in vivo and increased (p < 0.003) luciferase activity in the tadpole brain by 2.3-fold. There have been no previous reports of somatic gene transfer to the fish brain; therefore, it was necessary to optimize injection and transfection conditions for the adult goldfish (Carassius auratus). Following third brain ventricle injection of cytomegalovirus (CMV)-green fluorescent protein or CMV-LUC gene constructs, we established that cells in the telencephalon and optic tectum are transfected. Optimal transfections were achieved with 1 μg DNA complexed with 18 nmol 22 kDa polyethylenimine 4 days after brain injections. Exposure to EE2 increased brain luciferase activity by 2-fold in males (p < 0.05) but not in females. Activation of an ERE-dependent luciferase reporter gene in both tadpole and fish indicates that waterborne estrogens can directly modulate transcription of estrogen-responsive genes in the brain. We provide a method adaptable to aquatic organisms to study the direct regulation of estrogen-responsive genes in vivo.
bisphenol Abrainestrogen response elementethinylestradiolgoldfishsomatic gene transferXenopus laevis
==== Body
In both female and male vertebrates, estrogens affect many aspects of development, growth, sexual differentiation, and reproductive behavior. Estrogens also exert positive and negative feedback effects on the hypothalamopituitary axis to regulate the secretion of gonadotropic and other pituitary hormones (Hess 2003; Korach et al. 2003; McLachlan 2001; Trudeau 1997). Estrogens, notably 17β-estradiol (E2), are also involved in reproductive disorders such as breast and endometrial cancers (Feigelson and Henderson 1996; Graham et al. 2000). It is now recognized that there is worldwide contamination of water systems with chemicals and pharmaceuticals that mimic or inhibit estrogen action (Kolpin et al. 2002; Metcalfe et al. 2003; Ternes et al. 1999). The contraceptive steroid ethinylestradiol (EE2) and the natural hormone E2 are among the most commonly detected hormones in surface waters and effluents from sewage treatment plants (Ternes et al. 1999). E2 and EE2 were detected in effluents of sewage treatment plants in different countries at concentrations ranging up to 64 ng/L and 42 ng/L, respectively (Yin et al. 2002). The presence of these estrogens in Canadian sewage treatment plants has been documented with median concentrations of 9 ng/L for EE2 and 6 ng/L for E2 (Ternes et al. 1999). A recent study of 139 U.S. rivers reported maximum concentrations of 830 ng/L (~ 2.8 nM) for EE2 and 200 ng/L (~ 0.7 nM) for E2 (Kolpin et al. 2002).
The xenoestrogen bisphenol A (BPA) is primarily used in the production of poly-carbonate and epoxy resins and is found in many plastic products, including food can linings and dental sealants. The widespread industrial and household use, economic importance, and near ubiquitous presence of BPA in the environment (Lee and Peart 2000; Staples et al. 1998) emphasize its risk as an endocrine disruptor. Concentrations of BPA in surface waters have been reported to be, in the most severe cases, as high as 17,200 μg/L (~ 47 μM) in leachates from hazardous waste landfill sites (Yamamoto et al. 2001), but usually concentrations have been around or below 1 μg/L (~ 2.7 nM) (Belfroid et al. 2002). However, the concentration of BPA in many polluted lakes and rivers is not known.
A host of developmental and reproductive abnormalities in many species, including humans (Guillette et al. 1995; McLachlan 2001; Tyler et al. 1998), result from exposure to estrogenic endocrine-disrupting chemicals (EDCs). For example, octylphenol, BPA, and EE2 all stimulate abnormal production of the egg yolk protein vitellogenin in male fish (Arukwe 2001; Sumpter and Jobling 1995). Moreover, BPA induced testisova in medaka exposed to a concentration of 10 μg/L (~ 27 nM) (Metcalfe et al. 2001). Other studies showed that estrogenic EDCs cause sex reversal in frogs and feminization of secondary sex characteristics in fish (Arcand-Hoy and Benson 1998; Bogi et al. 2002; Mackenzie et al. 2003).
The diversity of structure and origin of the multitude of compounds currently known to bind to estrogen receptors (ER)- αand ER-β make it difficult to predict activities in vivo in vertebrate animals (Sanchez et al. 2002; Segner et al. 2003; Yoon et al. 2001). Large-scale screening for estrogenic activities by traditional physiologic and toxicologic methods is time-consuming and costly. A variety of effective in vitro ER binding assays and estrogen-responsive reporter systems in bacterial, yeast, and vertebrate cell systems have defined much of our understanding of estrogen and EDC actions (Ackermann et al. 2002; Matthews et al. 2002; Metivier et al. 2001, 2003; Petit et al. 1997; Zacharewski 1997). However, results derived in vitro for ER binding, hepatocyte vitellogenin induction, or ER reporter gene assays often do not always accurately reflect results obtained in vivo (Andersen et al. 1999; Segner et al. 2003). When E2 or estrogenic mimics bind to ERs, receptor dimerization and recruitment of transcriptional comodulators are initiated, and the hormone–receptor complex binds to the estrogen response element (ERE) and subsequently regulates transcription in an ordered and cyclic manner (Metivier et al. 2003; Robinson-Rechavi et al. 2003). Some of the discrepancies between in vitro assays and in vivo physiologic experiments may reflect the observations that ERα and ERβ differ dramatically in tissue and cellular distributions, biologic function (Abraham et al. 2004; Hess 2003; Korach et al. 2003), and their affinities for estrogenic chemicals (Le Guevel and Pakdel 2001; Yoon et al. 2001). Moreover, the likelihood that the availability of transcriptional comodulators of the ERs in vitro and in vivo is similar is highly unlikely (Graham et al. 2000), and thus, in vitro models cannot mimic the complexities of whole animal systems with respect to estrogen-dependent processes and responses to EDCs.
To begin to overcome some of the challenges of in vivo assessment of EDC modulation of gene transcription, we have validated polyethylenimine (PEI)-mediated somatic gene transfer (Lemkine and Demeneix 2001; Ouatas et al. 1998) to introduce an estrogen response element–thymidine kinase–luciferase (ERE-TK-LUC) construct into the intact brain. The effects of environmentally relevant concentrations of estrogenic pollutants on the expression of an established ERE reporter system characterized in vitro have been studied in several cell lines (Ackermann et al. 2002; Metivier et al. 2001). We have adapted somatic gene transfer procedures previously used for the Xenopus laevis tadpole (Ouatas et al. 1998) to demonstrate that waterborne estrogenic pollutants regulate transcription in vivo, both in X. laevis tadpoles and in the adult goldfish, Carassius auratus.
Materials and Methods
Plasmid constructs.
We used a consensus ERE with a minimal thymidine kinase promoter driving firefly luciferase activity (ERE-TK-LUC) as described previously (Metivier et al. 2001). This ERE reporter system is well characterized in vitro in several cell lines (Ackermann et al. 2002; Metivier et al. 2001) and responds to both zebrafish (Menuet et al. 2002) and goldfish ER-α and ER-β subtypes (Marlatt V, Trudeau VL, Moon TW, unpublished data). cytomegalovirus (CMV)-luciferase (CMV-LUC) and CMV-green fluorescent protein (CMV-GFP) were from Vical Inc. (San Diego, CA, USA) and Invitrogen (Carlsbad, CA, USA), respectively.
Luciferase activity.
Brains from luciferase-transfected X. laevis tadpoles or goldfish were dissected and frozen in liquid nitrogen and stored at –80°C until assayed for luciferase activity [relative light units (RLUs)] according to the manufacturer’s instructions (Promega, Charbonnieres, France). Frozen brains were sonicated in ice-cold luciferase lysis buffer (200 μL for tadpoles, 500 μL for goldfish) and then centrifuged 10 min at 12,000g (4°C) to precipitate nonsoluble particles and proteins. Twenty microliters of the supernatant was mixed by vortexing with 100 μL luciferase substrate and counted immediately (10 sec) using a single-well luminometer as previously reported (Ouatas et al. 1998).
Assessment of ERE-TK-LUC activity in the brains of X. laevis tadpoles.
Previous data have demonstrated that somatic gene transfer is an effective method to study thyroid hormone (TH) responses in the X. laevis tadpole (Ouatas et al. 1998). To avoid possible TH–E2 interactions in the brain (Dellovade et al. 1999), we used Nieuwkoop-Faber (NF) stage 54 X. laevis tadpoles (Nieuwkoop and Faber 1967) in which TH synthesis was inhibited by 1 g/L sodium perchlorate to determine whether waterborne estrogenic chemicals activate ERE-TK-LUC injected into the larval brain. In all cases, we report nominal water concentrations of estrogenic chemicals. In experiment 1, tadpoles were preexposed for 48 hr to 0.5 nM EE2, 5 nM E2, 50 nM BPA (bisphenol A methylacrylate; Sigma, St. Louis, MO, USA), or ethanol vehicle (0.4 mL in 4 L water in 10-L glass tanks; 20–22°C). In experiment 2, tadpoles were similarly preexposed to 200 nM tamoxifen (TAM; Sigma), a mixed ER antagonist/agonist. After the preexposure period, tadpoles were injected with ERE-TK-LUC (200 ng in 1 μL) complexed with 6 equivalents (eq) of 22 kDa polyethylenimine (PEI; Euromedex, Souffelweyersheim, France) in a 5% glucose solution into the brain as previously described (Ouatas et al. 1998) and returned to clean water freshly treated with estrogenic chemicals and exposed a further 48 hr. Animals were then sacrificed and whole brains dissected for determination of total luciferase activities.
Development of a somatic gene transfer method for the goldfish brain.
All fish were purchased from a local supplier (Paris, France) and maintained at 20–22°C. Adult male and female goldfish were used to optimize in vivo transfer methods and to determine if water-borne estrogenic chemicals activate ERE-TK-LUC injected into the adult brain. First, we established the least intrusive method for injection into the forebrain region. Stereotaxic methods have been established for brain third ventricular injections of medium- to large-sized goldfish (25–35 g), which involved surgical opening of the cranium (Peter and Gill 1975). A modification of this method was used to inject CMV-GFP (800 ng in 2 μL; 6 eq of PEI) to determine the regions transfected by ventricular injections in adults. The skull was opened with fine scissors, and, rather than using a Hamilton syringe as originally reported (Peter and Gill 1975), we used a fine glass capillary held in a micromanipulator as reported for tadpoles (Ouatas et al. 1998). Animals were sacrificed 6 days after brain injections. Whole brain was dissected and first examined directly without fixation using epifluorescence microscopy (Olympus, Hamburg, Germany) to determine if GFP was being expressed. Some brains were fixed in 2% paraformalde-hyde in phosphate buffer and processed for standard cryostat sectioning as reported previously (Coen et al. 1999).
This surgical approach permits precise injection into the regions of interest but is slow, highly invasive, and not amenable to the treatment of large numbers of animals. We developed an alternative approach that involves only minor surgery and is more rapidly completed. Animals were anesthetized in 0.05% MS-222 and placed in a sponge holder. Under a dissection microscope and using a modeler’s drill apparatus (model 28-515; Proxxon, Niersbach, Germany) with a 0.5-mm bit attached, a small hole was made in the cranium at the midline 1–2 mm posterior to the posterior margins of the eye. In small goldfish (3–10 g), preliminary trials using 0.1% fast green dye (Sigma) established that an injection of 4 μL at an angle of approximately 45–50° relative to the top of the head and at a depth of 3–4 mm would partially fill the brain ventricle and expose cells in the forebrain and optic tectum to the injected solution. In a trial using CMV-LUC (4 μL of 500 ng DNA/μL; n = 5), approximately 80–90% of the total brain luciferase activity was found in the telencephalon and optic tectum, whereas the hypothalamus and cerebellum plus hindbrain had very low levels of transfection (data not shown).
To establish the concentration of PEI necessary for optimal transfection, small goldfish (3–10 g) were injected with 1 g CMV-LUC in 4 μL complexed with 0, 3, 6, and 9 eq of PEI in a 5% glucose solution. Briefly, as previously described for tadpoles (Ouatas et al. 1998), the required amount of PEI is calculated based on the fact that 1 μg DNA contains 3 nmol phosphate and that 1 μL 0.1 M PEI is equivalent to 100 nmol of amine nitrogen. Therefore, to condense 10 μg DNA with 6 eq of PEI, 180 nmol PEI (i.e., 1.8 μL of 0.1 M PEI) is required. We also performed a time-course study in which animals were injected with 1 μg CMV-LUC in 4 μL complexed with 6 eq of PEI, and whole brains dissected at 2, 12, 24, 48, and 96 hr. After dissection, whole brains were immediately frozen in liquid nitrogen and processed for luciferase activity as described above for tadpole brain.
Effects of estrogenic chemicals on ERE-TK-LUC in goldfish brain.
For this experiment, we used small goldfish of both sexes (in 50–70 L glass tanks). Because these animals were in the early stages of seasonal gonadal redevelopment and could not be distinguished by external secondary sex characteristics, they were randomly assigned to each of the treatment groups. To determine whether waterborne estrogenic chemicals activate ERE-TK-LUC injected into the adult brain, groups of animals were preexposed for 48 hr to 10 nM E2, 10 nM EE2, or ethanol vehicle (0.1 mL/L water). After the preexpo-sure period, ERE-TK-LUC was injected as described above, and the fish were returned to water freshly treated with estrogenic chemicals and exposed a further 48 hr, at which time the water was changed again. The injected ERE-TK-LUC (1 μg DNA in 4 μL) was complexed with 6 eq of 22 kDa PEI in a 5% glucose solution. Whole brains were dissected at 96 hr after injection. Injections, exposures, and dissections were randomized over 3 days. At the time of dissection, body weights and sex of the animals were recorded.
Statistical analysis.
The levels of luciferase activity (RLU) per whole X. laevis tadpole brain are expressed relative to mean expression levels per experiment (i.e., for the corrected RLU the mean equals 1). Goldfish injected with the ERE-TK-LUC construct varied in size (3–10 g), and therefore an additional correction was made based on milligrams of brain protein in the extracted luciferase fraction that was measured according to the manufacturer’s instructions (BioRad, Marnes-la-Coquette, France). Data were analyzed by one-way or two-way analysis of variance (ANOVA) or Student’s t-test as appropriate (SigmaStat, version 2.03; SPSS Inc., Chicago, IL, USA).
Results
Effects of estrogenic chemicals on ERE-TK-LUC activity in the brains of X. laevis tadpoles.
Figure 1A shows the effects of exposure to E2 (5 nM), EE2 (0.5 nM), and BPA (50 nM) on luciferase expression in the brains of ERE-TK-LUC–injected tadpoles. In this experiment the average activity (1 corrected RLU) represents approximately 73,000 RLU/brain. All data are expressed relative to this average. There was an effect of treatment (p < 0.004, one-way ANOVA) on luciferase activity. In the group treated with E2, mean levels were approximately 1.4-fold higher than in controls; however, this difference did not achieve statistical significance (p > 0.05). In contrast, EE2 induced a 1.9-fold increase (p < 0.002) in luciferase activity. Similarly, BPA also induced a 1.5-fold increase (p < 0.03) in luciferase activity measured in the whole brain. Figure 1B shows the effects of exposure to TAM (200 nM) on luciferase expression in the brains of ERE-TK-LUC–injected tadpoles. In this experiment the average activity (1 corrected RLU unit) represents approximately 38,000 RLU. All data are expressed relative to this average value. TAM induced a 2.3-fold increase (p < 0.003, t-test) in luciferase activity.
Somatic gene transfer in the goldfish brain.
When we injected directly into the brain third ventricle of medium sized fish, cells in the telencephalon, optic tectum, and occasionally in the hypothalamus (not shown) were trans-fected with CMV-GFP (800 ng in 2 μL). Figure 2A shows the general distribution of GFP-expressing cells in a freshly dissected whole brain. Cells in the telencephalon close to the midline and brain third ventricle, as well as some cells in the optic tectum, were visualized with epifluorescence microscopy. Examples of two neurons expressing GFP are shown in Figure 2B and C. GFP was expressed in the cell body and also extensively in neuronal processes extending laterally away from the ventricular wall (represented by the border between Figure 2B,C). Note also that synaptic boutons and dendrites are also labeled with GFP. Cells in the nucleus preopticus peri-ventricularis and nucleus preopticus (Peter and Gill 1975) also expressed GFP (not shown).
Figure 3A illustrates the effect of PEI concentrations on transfection efficiency in the goldfish brain. Whereas 3 eq of PEI was only minimally effective, 6 eq of PEI produced maximal luciferase expression at 48 hr after brain injections. There was no further enhancement of transfection using 9 eq of PEI. Using 6 eq of PEI to complex CMV-LUC, a time-course analysis (Figure 3B) was performed. The highest luciferase expression was 96 hr after brain injection.
Effects of estrogenic chemicals on ERE-TK-LUC in goldfish brain.
After having established a method for injection of DNA into the gold-fish brain (Figures 2 and 3), we examined the effects of E2, EE2, and BPA in small female and male goldfish. Figure 4 shows the effects of exposure to E2 (10 nM), EE2 (10 nM), and BPA (100 nM) on luciferase expression in the brains of ERE-TK-LUC–injected females and males. In this experiment the average activity (1 corrected unit) represents approximately 15,000 RLU/mg protein. All data are expressed relative to this average value. The effects of the various treatments on luciferase activity was dependent on the sex of the fish (two-way ANOVA: sex × treatment, p < 0.019). Basal luciferase activity was similar in control females and males (p > 0.05). In males treated with E2, mean levels were approximately 1.5-fold higher than in controls; however, this change was not statistically significant (p > 0.05). Additionally, E2 did not affect (p > 0.05) luciferase activity in females. In contrast, waterborne EE2 induced a 2-fold increase (p > 0.05) in luciferase activity in the male brain but had no effect in females (p > 0.05). Moreover, BPA did not affect (p > 0.05) luciferase activity in either sex.
Discussion
Our results indicate that waterborne estrogenic chemicals can modulate brain activity in aquatic vertebrates. Using somatic gene transfer into the brains of tadpoles and adult fish, we showed that estrogenic chemicals activate expression of an introduced ERE-TK-LUC construct. This required adaptation of somatic gene transfer methods previously used in X. laevis (Ouatas et al. 1998) and mice (Guissouma et al. 1998) to study TH-driven gene expression and in Xenopus tropicalis (Rowe et al. 2002) to analyze apoptosis during metamorphosis. To our knowledge, PEI-mediated somatic gene transfer into the fish brain has not been previously reported. Optimal transfections were achieved with 1 μg DNA complexed with 18 nmol 22 kDa PEI 4 days after brain injections. However, longer time periods were not analyzed, and it is possible that expression in the adult goldfish brain would increase after 96 hr.
The potent estrogen from female contraceptives, EE2, and the natural estrogen E2 are found at picomolar to nanomolar concentrations in both European and North American sewage effluents and surface waters (Kolpin et al. 2002; Metcalfe et al. 2003; Ternes et al. 1999). We showed that short-term exposure to 0.5 nM EE2 in tadpoles and 10 nM EE2 in male goldfish increased the activity of a known estrogen-responsive reporter gene construct by approximately 2-fold. In contrast, female goldfish were not responsive to 10 nM water-borne EE2. The plasticizing agent BPA and the mixed ER antagonist/agonist TAM were both estrogenic in tadpole brain. In both male and female goldfish, high levels (100 nM) of BPA did not activate the estrogen-responsive reporter gene construct injected into the brain.
Although we did not directly compare transfection efficiencies in tadpoles and gold-fish, there appears to be an important difference. Based on the number of GFP-positive cells and the basal levels of luciferase expression, transfection appears less efficient in adult gold-fish compared with larval tadpole brain (Ouatas et al. 1998). The maximum activity of reporter gene luciferase from a whole brain per milligram of protein showed that transfection is ~ 30-fold more efficient in the tadpole compared with the adult goldfish. The reasons for this are unknown but likely relate to differences in injection methods, ratio of brain volume to injection volume, and/or cellular characteristics of larval versus adult brain. Results in goldfish are, however, similar to those obtained with PEI-mediated transfection of hypothalamic neurons of neonatal mice with the same CMV-LUC construct (Guissouma et al. 1998). Our results showed that cells in the adult goldfish forebrain and optic tectum are transfectable in vivo. Autoradiographic (Kim et al. 1978), immunocytochemical (Navas et al. 1995), and in situ hybridization (Menuet et al. 2002) studies showed that both ER-α and ER-β are expressed in the telencephalon and hypothalamus and especially in the preoptic area of fish. Using reverse-transcriptase polymerase chain reaction (RT-PCR), Choi and Habibi (2003) also detected both ERs in goldfish brain. Our results showed that in vivo transfection in the goldfish telencephalon can be used to study the regulation of ERE-driven expression by an estrogenic pollutant.
In both animal models, there was a relatively high basal luciferase activity in controls. This is likely due to two interacting factors: high in vivo activity of the minimal thymidine kinase promoter and effects of endogenous neuroestrogen on basal expression of the ERE-TK-LUC gene construct. In X. laevis tadpoles, estrogen production in the brain has not been studied, but at NF stage 54, whole-body E2 levels are easily detectable despite having declined relative to very high levels in early stages of development (Bogi et al. 2002). Male and female gonads are distinguishable by gross morphologic characteristics at NF stage 56 (Bogi et al. 2002). Therefore, it is likely that our tadpoles were producing endogenous estrogen. Relatively high basal ERE-TK-LUC activity at this stage of tadpole development suggests that ERs are active and/or that endogenous E2 is being produced and delivered to the transfected cells. The goldfish brain has a remarkable capacity to produce E2 from testosterone because of very high aromatase activity (Callard et al. 2001; Pasmanik and Callard 1988). The dose of E2 we used is within the physiologic range and thus would be unlikely to raise brain E2 above endogenous brain E2 concentrations, especially in females. It is known that EE2 is more potent that E2 in several assay systems using the same ERE-TK-LUC reporter gene (Ackermann et al. 2002; Le Guevel and Pakdel 2001). In female goldfish, 10 nM EE2 did not affect luciferase expression, similar to what was observed with E2. This is in contrast to males where EE2 induced a 2-fold increase in activity. We have previously observed marked sex differences in gold-fish neuroendocrine responses to sex steroids (Bosma et al. 2001). For example, whereas testosterone inhibited the expression of glutamic acid decarboylases (GAD65 and GAD67) in the telencephalon of sexually mature males, it was without effect in females (Lariviere K, Trudeau VL, unpublished data).
Our results indicate that short-term exposure to environmentally relevant water levels of BPA (50 nM, ~ 18 μg/L) can activate the ERE-TK-LUC construct in the tadpole brain. In contrast to effects in fish (Metcalfe et al. 2001; Staples et al. 1998), the effects of BPA in amphibians are not well studied. Kloas et al. (1999), using a static renewal exposure protocol, reported that BPA has estrogenic activity at 2.3 μg/L (~ 6.3 nM) and induces female-biased sex reversal in X. laevis. In a second study, the same researchers found that 100 nM BPA induced female-biased sex reversal in X. laevis (Levy et al. 2004). However, in a flow-through exposure system (Pickford et al. 2003), there were no observable effects of a range of BPA concentrations (0.83–497 μg/L; ~ 2.3 nM–1.4 μM) on larval growth, development, or sexual differentiation of X. laevis tadpoles. High, nonenvironmental of BPA (10–25 μM; 3,644–9,110 μg/L) have both teratogenic and antimetamorphic actions in X. laevis (Iwamuro et al. 2003), suggesting interference with the thyroid system. It is difficult at present to reconcile the different conclusions concerning the estrogenicity of BPA in frogs. However, given that BPA is continually being added to aquatic ecosystems through industrial and sewage effluent discharges and activates a known ERE–reporter gene construct in tadpole brain, it is a contaminant of environmental concern.
Activation of an ERE-dependent luciferase reporter gene in both tadpole and fish indicates that waterborne estrogens can directly modulate transcription of estrogen-responsive genes in the brain. Previous work from our laboratory demonstrated that environmentally relevant levels of the estrogenic pollutant octylphenol modulates the expression of multiple hypothalamic genes in leopard frog tadpoles (Crump et al. 2002) and in hatchling snapping turtles (Trudeau et al. 2002). In the latter study, differential display PCR was used, and it is not known if the affected transcripts were directly or indirectly regulated by 4-t-octylphenol or E2. As quantified in these latter studies using reverse Northern blotting, changes in several hypothalamic mRNAs induced by waterborne environmentally relevant levels of octylphenol in these studies were approximately 2-fold. This level of gene expression is similar to what we observed with ERE-dependent luciferase induction after EE2, BPA, and TAM exposures.
In this article we provide a method to study the direct regulation of estrogen-responsive genes in vivo in tadpoles and fish. The power of this approach is that it is possible to determine whether an estrogenic chemical is acting on a certain tissue. The ERE-dependent luciferase reporter gene is injected at a specific site and is responsive to the known nuclear ER subtypes (Menuet et al. 2002). Moreover, because the technique is based on the transcriptional mechanism of action of estrogen, a positive effect of a given chemical can be interpreted as activation of the ER. A somatic gene transfer technique may be generalized to other aquatic species, because it is easier and less time-consuming than identifying ER-regulated genes and their promoters in each species. The main limitation of the somatic gene transfer method described is that it is unlikely to detect indirect and nongenomic effects of estrogenic chemicals.
Figure 1 Effects of estrogenic chemicals on ERE-TK-LUC activity in the brains of perchlorate-treated NF stage 54 X. laevis tadpoles. (A) Effects of exposure to ethanol control (n = 18), E2 (5 nM; n = 14), EE2 (0.5 nM; n = 20), and BPA (50 nM; n = 19) on luciferase activity in the brains of tadpoles injected with ERE-TK-LUC (200 ng/μL; 6 eq of PEI); data are presented as mean ± SEM pooled from two separate exposures. (B) Effects of exposure to ethanol control (n = 11) and TAM (200 nM; n = 12) on luciferase activity in the brains of ERE-TK-LUC–injected tadpoles; data are presented as mean ± SEM.
*p < 0.03, **p < 0.002, and #p < 0.003 compared with ethanol controls.
Figure 2 Expression of GFP in adult goldfish brain. (A) Expression of GFP in the telencephalon (TEL) and optic tectum (OT) of freshly dissected intact brain. Note the high expression around the brain third ventricle (V3); bar = 100 μm. (B) Sagittal section (25 μm) through the telencephalon of a goldfish showing a highly branching neuron expressing GFP throughout. The third ventricle is to the right; bar = 5 μm. (C) Sagittal section (25 μm) through the telencephalon of a goldfish showing a neuron extending dorsolaterally. The cell body (not easily visualized) is toward the top left corner; bar = 5 μm.
Figure 3 Optimization of PEI-based gene transfer in the goldfish brain. (A) Comparison of the efficiencies of 22 kDa linear PEI used at different ratios of PEI amines to DNA anions. Animals were injected with CMV-LUC DNA (1 μg in 4 μL) complexed with 0 (n = 9), 3 (n = 10), 6 (n = 10), and 9 (n = 10) eq of PEI; brains were dissected at 48 hr postinjection; and luciferase activity (RLU/mg protein × 10–3; mean ± SEM) was determined. (B) Time course of expression of CMV-LUC in the goldfish brain. Animals were injected with CMV-LUC DNA (1 μg in 4 μL) complexed with 6 eq of PEI; brains were dissected at 2 hr (n = 10), 12 hr (n = 10), 24 hr (n = 10), 48 hr (n = 7), and 96 hr (n = 5) postinjection, and luciferase activity (RLU/mg protein × 10–3; mean ± SEM) was determined.
Figure 4 Effects of estrogenic chemicals on ERE-TK-LUC activity in the brains of male and female goldfish preexposed for 48 hr to E2 (10 nM; n = 14 males and 14 females), EE2 (10 nM; n = 8 males and 8 females), or ethanol vehicle (0.1 mL/L water; n = 8 males and 16 females). Data are presented as mean ± SEM.
*p < 0.05 compared with the male control values. levels
==== Refs
References
Abraham IM Todman MG Korach KS Herbison AE 2004 Critical in vivo roles for classical estrogen receptors in rapid estrogen actions on intracellular signaling in mouse brain Endocrinology 145 7 3055 3061 14976146
Ackermann GE Brombacher E Fent K 2002 Development of a fish reporter gene system for the assessment of estrogenic compounds and sewage treatment plant effluents Environ Toxicol Chem 21 9 1864 1875 12206426
Andersen HR Andersson AM Arnold SF Autrup H Barfoed M Beresford NA 1999 Comparison of short-term estrogenicity tests for identification of hormone-disrupting chemicals Environ Health Perspect 107 suppl 1 89 108 10229711
Arcand-Hoy LD Benson WH 1998 Fish reproduction: an ecologically relevant indicator of endocrine disruption Environ Toxicol Chem 17 1 49 57
Arukwe A 2001 Cellular and molecular responses to endocrine-modulators and the impact on fish reproduction Mar Pollut Bull 42 8 643 655 11525282
Belfroid A van Velzen M van der Horst B Vethaak D 2002 Occurrence of bisphenol A in surface water and uptake in fish: evaluation of field measurements Chemosphere 49 1 97 103 12243336
Bogi C Levy G Lutz I Kloas W 2002 Functional genomics and sexual differentiation in amphibians Comp Biochem Physiol B Biochem Mol Biol 133 4 559 570 12470819
Bosma PT Blazquez M Fraser EJ Schulz RW Docherty K Trudeau VL 2001 Sex steroid regulation of glutamate decarboxylase mRNA expression in goldfish brain is sexually dimorphic J Neurochem 76 4 945 956 11181814
Callard GV Tchoudakova AV Kishida M Wood E 2001 Differential tissue distribution, developmental programming, estrogen regulation and promoter characteristics of cyp19 genes in teleost fish J Steroid Biochem Mol Biol 79 1–5 305 314 11850237
Choi CY Habibi HR 2003 Molecular cloning of estrogen receptor alpha and expression pattern of estrogen receptor subtypes in male and female goldfish Mol Cell Endocrinol 204 1–2 169 177 12850291
Coen L Kissa K Le Mevel S Brulet P Demeneix BA 1999 A somatic gene transfer approach using recombinant fusion proteins to map muscle-motoneuron projections in Xenopus spinal cord Int J Dev Biol 43 8 823 830 10707906
Crump D Lean D Trudeau VL 2002 Octylphenol and UV-B radiation alter larval development and hypothalamic gene expression in the leopard frog (Rana pipiens ) Environ Health Perspect 110 277 284 11882479
Dellovade TL Kia HK Zhu YS Pfaff DW 1999 Thyroid hormone coadministration inhibits the estrogen-stimulated elevation of preproenkephalin mRNA in female rat hypothalamic neurons Neuroendocrinology 70 3 168 174 10516479
Feigelson HS Henderson BE 1996 Estrogens and breast cancer Carcinogenesis 17 11 2279 2284 8968038
Graham JD Bain DL Richer JK Jackson TA Tung L Horwitz KB 2000 Thoughts on tamoxifen resistant breast cancer. Are coregulators the answer or just a red herring? J Steroid Biochem Mol Biol 74 5 255 259 11162933
Guillette LJ Jr Crain DA Rooney AA Pickford DB 1995 Organization versus activation: the role of endocrine-disrupting contaminants (EDCs) during embryonic development in wildlife Environ Health Perspect 103 suppl 7 157 164 8593864
Guissouma H Ghorbel MT Seugnet I Ouatas T Demeneix BA 1998 Physiological regulation of hypothalamic TRH transcription in vivo is T3 receptor isoform specific FASEB J 12 15 1755 1764 9837866
Hess RA 2003. Estrogen in the adult male reproductive tract: A review. Reprod Biol Endocrinol 1(1):52. Available: http://www.rbej.com/content/1/1/52 [accessed 13 January 2005].
Iwamuro S Sakakibara M Terao M Ozawa A Kurobe C Shigeura T 2003 Teratogenic and anti-metamorphic effects of bisphenol A on embryonic and larval Xenopus laevis Gen Comp Endocr 133 2 189 198 12928009
Kim YS Stumpf WE Sar M 1978 Topography of estrogen target cells in the forebrain of goldfish, Carassius auratus J Comp Neurol 182 4 611 620 721971
Kloas W Lutz I Einspanier R 1999 Amphibians as a model to study endocrine disruptors: II. Estrogenic activity of environmental chemicals in vitro and in vivo Sci Total Environ 225 1–2 59 68 10028703
Kolpin DW Furlong ET Meyer MT Thurman EM Zaugg SD Barber LB 2002 Pharmaceuticals, hormones, and other organic wastewater contaminants in U.S. streams, 1999–2000: a national reconnaissance Environ Sci Technol 36 6 1202 1211 11944670
Korach KS Emmen JM Walker VR Hewitt SC Yates M Hall JM 2003 Update on animal models developed for analyses of estrogen receptor biological activity J Steroid Biochem Mol Biol 86 3–5 387 391 14623535
Lee HB Peart TE 2000 Determination of bisphenol A in sewage effluent and sludge by solid-phase and supercritical fluid extraction and gas chromatography/mass spectrometry J AOAC Int 83 2 290 297 10772166
Le Guevel R Pakdel F 2001 Assessment of oestrogenic potency of chemicals used as growth promoter by in-vitro methods Hum Reprod 16 5 1030 1036 11331656
Lemkine GF Demeneix BA 2001 Polyethylenimines for in vivo gene delivery Curr Opin Mol Ther 3 2 178 182 11338931
Levy G Lutz I Kruger A Kloas W 2004 Bisphenol A induces feminization in Xenopus laevis tadpoles Environ Res 94 1 102 111 14643292
Mackenzie CA Berrill M Metcalfe C Pauli BD 2003 Gonadal differentiation in frogs exposed to estrogenic and antiestrogenic compounds Environ Toxicol Chem 22 10 2466 2475 14552012
Matthews JB Fertuck KC Celius T Huang YW Fong CJ Zacharewski TR 2002 Ability of structurally diverse natural products and synthetic chemicals to induce gene expression mediated by estrogen receptors from various species J Steroid Biochem Mol Biol 82 2–3 181 194 12477484
McLachlan JA 2001 Environmental signaling: what embryos and evolution teach us about endocrine disrupting chemicals Endocr Rev 22 3 319 341 11399747
Menuet A Pellegrini E Anglade I Blaise O Laudet V Kah O 2002 Molecular characterization of three estrogen receptor forms in zebrafish: binding characteristics, trans-activation properties, and tissue distributions Biol Reprod 66 6 1881 1892 12021076
Metcalfe CD Koenig BG Bennie DT Servos M Ternes TA Hirsch R 2003 Occurrence of neutral and acidic drugs in the effluents of Canadian sewage treatment plants Environ Toxicol Chem 22 12 2872 2880 14713026
Metcalfe CD Metcalfe TL Kiparissis Y Koenig BG Khan C Hughes RJ 2001 Estrogenic potency of chemicals detected in sewage treatment plant effluents as determined by in vivo assays with Japanese medaka (Oryzias latipes ) Environ Toxicol Chem 20 2 297 308 11351429
Metivier R Penot G Flouriot G Pakdel F 2001 Synergism between ERalpha transactivation function 1 (AF-1) and AF-2 mediated by steroid receptor coactivator protein-1: requirement for the AF-1 alpha-helical core and for a direct interaction between the N- and C-terminal domains Mol Endocrinol 15 11 1953 1970 11682626
Metivier R Penot G Hubner MR Reid G Brand H Kos M 2003 Estrogen receptor-alpha directs ordered, cyclical, and combinatorial recruitment of cofactors on a natural target promoter Cell 115 6 751 763 14675539
Navas JM Anglade I Bailhache T Pakdel F Breton B Jego P 1995 Do gonadotrophin-releasing hormone neurons express estrogen receptors in the rainbow trout? A double immunohistochemical study J Comp Neurol 363 3 461 474 8847411
Nieuwkoop P Faber J 1967. Normal Table of Xenopus laevis (Daudin). Amsterdam:Elsevier North Holland.
Ouatas T Le Mevel S Demeneix BA de Luze A 1998 T3-dependent physiological regulation of transcription in the Xenopus tadpole brain studied by polyethylenimine based in vivo gene transfer Int J Dev Biol 42 8 1159 1164 9879714
Pasmanik M Callard GV 1988 Changes in brain aromatase and 5 alpha-reductase activities correlate significantly with seasonal reproductive cycles in goldfish (Carassius auratus ) Endocrinology 122 4 1349 1356 3345716
Peter RE Gill VE 1975 A stereotaxic atlas and technique for forebrain nuclei of the goldfish, Carassius auratus J Comp Neurol 159 1 69 101 1088950
Petit F Le Goff P Cravedi JP Valotaire Y Pakdel F 1997 Two complementary bioassays for screening the estrogenic potency of xenobiotics: recombinant yeast for trout estrogen receptor and trout hepatocyte cultures J Mol Endocrinol 19 3 321 335 9460653
Pickford DB Hetheridge MJ Caunter JE Hall AT Hutchinson TH 2003 Assessing chronic toxicity of bisphenol A to larvae of the African clawed frog (Xenopus laevis ) in a flow-through exposure system Chemosphere 53 3 223 235 12919782
Robinson-Rechavi M Escriva Garcia H Laudet V 2003 The nuclear receptor superfamily J Cell Sci 116 Pt 4 585 586 12538758
Rowe I Coen L Le Blay K Le Mevel S Demeneix BA 2002 Autonomous regulation of muscle fibre fate during metamorphosis in Xenopus tropicalis Dev Dyn 224 4 381 390 12203730
Sanchez R Nguyen D Rocha W White JH Mader S 2002 Diversity in the mechanisms of gene regulation by estrogen receptors Bioessays 24 3 244 254 11891761
Segner H Navas JM Schafers C Wenzel A 2003 Potencies of estrogenic compounds in in vitro screening assays and in life cycle tests with zebrafish in vivo Ecotoxicol Environ Saf 54 3 315 322 12651187
Staples CA Dorn PB Klecka GM O’Block ST Harris LR 1998 A review of the environmental fate, effects, and exposures of bisphenol A Chemosphere 36 10 2149 2173 9566294
Sumpter JP Jobling S 1995 Vitellogenesis as a biomarker for estrogenic contamination of the aquatic environment Environ Health Perspect 103 suppl 7 173 178 8593867
Ternes TA Stumpf M Mueller J Haberer K Wilken RD Servos M 1999 Behavior and occurrence of estrogens in municipal sewage treatment plants—I. Investigations in Germany, Canada and Brazil Sci Total Environ 225 1–2 81 90 10028705
Trudeau VL 1997 Neuroendocrine regulation of gonadotrophin II release and gonadal growth in the goldfish, Carassius auratus Rev Reprod 2 1 55 68 9414466
Trudeau VL Chiu S Kennedy SW Brooks RJ 2002 Octylphenol (OP) alters the expression of members of the amyloid protein family in the hypothalamus of the snapping turtle, Chelydra serpentina serpentina Environ Health Perspect 110 269 275 11882478
Tyler CR Jobling S Sumpter JP 1998 Endocrine disruption in wildlife: a critical review of the evidence Crit Rev Toxicol 28 4 319 361 9711432
Yamamoto T Yasuhara A Shiraishi H Nakasugi O 2001 Bisphenol A in hazardous waste landfill leachates Chemosphere 42 4 415 418 11100793
Yin GG Kookana RS Ru YJ 2002 Occurrence and fate of hormone steroids in the environment Environ Int 28 6 545 551 12503920
Yoon K Pallaroni L Stoner M Gaido K Safe S 2001 Differential activation of wild-type and variant forms of estrogen receptor alpha by synthetic and natural estrogenic compounds using a promoter containing three estrogen-responsive elements J Steroid Biochem Mol Biol 78 1 25 32 11530281
Zacharewski T 1997 In vitro bioassays for assessing estrogenic substances Environ Sci Technol 31 3 613 623
|
15743723
|
PMC1253760
|
CC0
|
2021-01-04 23:40:57
|
no
|
Environ Health Perspect. 2005 Mar 2; 113(3):329-334
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7418
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7380ehp0113-00033515743724ResearchWorkgroup ReportSummary of a Workshop on the Development of Health Models and Scenarios: Strategies for the Future Ebi Kristie L. 1Gamble Janet L. 21Exponent Health Group, Alexandria, Virginia, USA2Global Change Research Program, Office of Research and Development, U.S. Environmental Protection Agency, Washington, DC, USAAddress correspondence to K.L. Ebi, Exponent Health Group, 1800 Diagonal Rd., Suite 300, Alexandria, VA 22314 USA. Telephone: (571) 227-7250. Fax: (571) 227-7299. E-mail:
[email protected] authors declare they have no competing financial interests.
3 2005 7 12 2004 113 3 335 338 2 7 2004 7 12 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. A workshop was convened in July 2003 by the Global Change Research Program, Office of Research and Development at the U.S. Environmental Protection Agency, to review current strategies for developing human health models and scenarios in the context of global environmental change, particularly global climate change, and to outline a research agenda that effectively characterizes the interplay of global change with the health of human populations. The research agenda developed at the workshop focused on three issues: a) the development of health models, b) the development of health scenarios, and c) the use of health models and health scenarios to inform policy. The agenda identified research gaps as well as barriers to the development and use of models and scenarios. This report summarizes the workshop findings.
climate changehealth modelshealth scenario developmentpolicy
==== Body
There is growing interest in modeling the potential health impacts of global environmental changes and in exploring, through scenario development, how current health risks could evolve with changes in environmental, technologic, economic, and societal conditions. Developing health scenarios can provide important insights into the complex relationships between humans and their environment and thus inform policy approaches to sustainable development, including intergenerational equity. Accordingly, the Global Change Research Program in the Office of Research and Development at the U.S. Environmental Protection Agency convened a workshop on 21–22 July 2003 in Washington, DC, to develop a research agenda for the development of health models and scenarios that characterize the interplay of global environmental change, particularly global climate change, with the health of human populations. Workshop participants had expertise in public health, climate change, modeling, scenario development, and policy development.
Models describe, quantitatively and/or qualitatively, relationships among various drivers of human health outcomes. For example, models can project disease burdens when input parameters change, such as the potential health consequences of changes in prevailing weather patterns. Scenarios, on the other hand, do not project whether a particular event, such as a disease outbreak, might occur. Scenarios paint pictures of possible or plausible futures and explore the different outcomes that might result when current conditions change (e.g., future socioeconomic and technologic developments, developments in medical care, population demographics, policy interventions). There is a strong interplay between models and scenarios. Scenarios can be used as inputs into models to project changes in the intensity and range of climate sensitive diseases, and models often underlie scenarios. For example, the Standardized Reference Emission Scenarios incorporate linked models of human economic activity and their resulting anthropogenic emissions with models of the earth system responses to the forcings from these emissions (Nakicenovic et al. 2000). Health models have been coupled with these scenarios to project disease burdens under different assumptions (e.g., Campbell-Lendrum et al. 2003; Hayhoe et al. 2004; Van Lieshout et al. 2004).
Both models and scenarios are needed to further our understanding of the potential impacts of climate variability and change on human health and well-being. A better understanding of the potential impacts can facilitate the development and implementation of effective and efficient adaptations that reduce negative impacts and take advantage of any opportunities that arise. In addition, this understanding can inform policy-relevant analyses of the possible consequences of mitigation policies. This is particularly critical because past scenario studies did not adequately incorporate population health issues.
Using models to project the potential health impacts of climate change poses a difficult challenge. In addition to affecting the intensity and range of climate sensitive diseases, global climate change may influence major risk factors for adverse health outcomes such as per capita income, nutrition, access to clean water, local pollution control, and large-scale migrations (McMichael et al. 2001). Another challenge to model projections arises because the sensitivity and adaptive capacity of exposed populations vary considerably depending on factors such as population density, level of economic and technologic development, local environmental conditions, preexisting health status, and the quality and availability of health care and public health infrastructure (Woodward et al. 1998). Projections of current trends into the future should not assume a future that looks like the past. Although the nature and extent of the potential health impacts of global environmental change are inherently uncertain, models can be used to explore the range of possible health burdens that could be faced by a population under a particular set of assumptions.
Scenarios are useful tools to aid assessments of the potential future impacts of global climate change. Because scenarios focus on understanding potential vulnerabilities and adaptive responses, they allow a deeper understanding of the potential health risks associated with climate and other global changes. More important, scenarios and the assessments they inform act as a bridge between science and policy. They can influence policy making by summarizing and synthesizing scientific knowledge in a form that helps policy makers visualize the dimensions of an issue and devise policies and processes to address risks and to increase future adaptive capacity (Scheraga et al. 2003).
There are many definitions of scenarios. The workshop focused on the definition used by the Intergovernmental Panel on Climate Change: scenarios are coherent, internally consistent depictions of pathways to possible futures based on assumptions about economic, ecologic, social, political, and technologic development (Nakicenovic et al. 2000). Scenarios generally include qualitative story-lines that describe assumptions about the initial state and the driving forces, events, and actions that lead to future conditions; models that quantify the storyline; outputs that explore possible future outcomes if assumptions are changed; and explicit consideration of uncertainties.
Health scenarios can be constructed by augmenting existing scenarios or by developing new scenarios. The development of new scenarios can start with current conditions and describe how driving forces could result in alternative futures, or it can start with a desirable future and describe what would need to change (and by when) to achieve it. Scenario storylines need to be grounded in an understanding of current conditions and in the factors that shape human health today. Underlying quantitative health scenarios are models of how particular sectors (e.g., technology) may change over time. Health scenarios become policy relevant as they identify and address the questions that are important to decision makers. Scenarios promise to improve our understanding of the effects of climate change and other global changes on current health policies.
Research Agenda
Efforts are just beginning to explicitly incorporate health into scenario development. To inform this process, the expert panel developed a research agenda in three related areas: development of health models, development of health scenarios, and information and approaches needed to inform related policy issues. The roadmap drawn for each area identifies critical research gaps that will be important to research and funding organizations.
Development of health models.
Modeling health end points is a complex, multideterminant process that requires attention to an array of factors across dimensions of time and space. Participants concluded that the process of model development should address the following questions:
What model(s) would be appropriate to incorporate climate change, adaptation measures, and mitigation policies?
How do we quantify uncertainty?
How do we validate the model?
Key considerations in health model development include the following:
Identifying the key proximal determinants of health and how they can be modeled to project risks and vulnerabilities. In particular, a better understanding is needed of the following:
The relationships between climate and health: A better understanding of the associations between climate and health outcomes will aid the development of appropriate adaptive responses to reduce the current and future burden of climate sensitive diseases.
The determinants of economic development: Many of the determinants of economic development are also determinants of population health.
Indirect relationships and joint effects linking climate with other important global changes in the model: Climate can affect health indirectly through other systems; for example, climate can influence ecosystems in ways that can increase or decrease the intensity of malaria transmission. Climate and land use change can independently and jointly influence the range of some disease vectors, for example, by affecting the intensity and recurrence of droughts. A better understanding is needed of the interrelationships among climate, ecosystems, land use, and health to design effective intervention measures.
Scale interactions: Population health is affected by a multitude of factors that operate at different scales, from community (e.g., whether or not there is an effective early warning system for heat waves) to individual levels (e.g., whether or not an individual spends adequate time in cooled environments during a heat wave). Climate change is a global phenomenon whose impacts will primarily be felt at regional and local scales. Local actions, such as land use change that contributes to heating or cooling of the environment, can amplify or ameliorate larger scale climate forces. Methods need to be developed for improving model accuracy by incorporating effects across multiple scales.
Methods for downscaling variables such as a country’s gross domestic product to regional and local scales: The mechanics of down-scaling national variables, particularly those that are unevenly distributed across a population, need to be understood.
Modeling, on appropriate scales, the processes of adaptation and adaptive capacity. Few models exist of either how to build public health capacity or how the implementation of specific interventions, such as development of a malaria vaccine, is likely to influence population health. Such models are necessary for estimating the potential for adaptation to reduce the projected negative consequences of climate change. Overconfidence in the effectiveness of adaptation can lead to underestimation of the future burden of disease due to climate change. In addition, models are needed of the consequences, including co-benefits, of mitigation policies at appropriate scales.
Modeling critical thresholds and nonlinearities. For example, mortality typically exhibits a curvilinear relationship with ambient temperature, with mortality rates increasing with increasing ambient temperature (above the temperature at which mortality is at a minimum) (Kovats and Koppe, in press). In some regions, there is a sharp rise in mortality at very high temperatures. Models are needed to accurately represent these thresholds.
Health models also need to explore how thresholds or nonlinearities in the climate system may affect population health. Although early climate change projections suggested that global mean surface temperature may gradually increase, there is growing concern that not only will mean temperature and precipitation change, but that changes in the variance around these variables could result in large increases in extreme events in some regions (Albritton and Meira Filho 2001). In addition, the climate record shows evidence of abrupt (on geologic scales) nonlinear changes. Research is needed to better understand the potential consequences of abrupt climate changes for population health.
Integrating top-down and bottom-up models. Top-down models are developed from an overall population health perspective that focuses on just one or a few indicators, such as life expectancy. Bottom-up models of population health aggregate individual health outcomes up to the population level. Methods are needed to merge these two approaches to improve our understanding of the key determinants of population health.
Validating models and their results. The larger and more complex a model, the more difficult validation becomes, particularly when data are limited. For example, a number of groups have developed models to project how malaria might spread under particular assumptions about changes in temperature and precipitation (e.g., Martens et al. 1999; Rogers and Randolph 2000; Tanser et al. 2003; Van Lieshout et al. 2004). Data for validation of these models are limited. Until more long-term data sets are collected, approaches need to be developed to provide policy makers with confidence that decisions based on model results will be robust.
Involving stakeholders, including representatives from multiple disciplines, in model development and validation.
Communicating model results, including underlying assumptions and the degree of uncertainty associated with the results, to all interested parties.
Development of health scenarios.
Many of the issues identified as important for model development are also important for developing scenarios to characterize possible impacts of global change. Health scenarios are particularly sensitive to time scale, level of aggregation, the validity of underlying health models, the degree of confidence in the model, and uncertainties in the scenario.
Given these sensitivities, scenario building should follow a three-step approach. The first step is to determine why the scenario is being built. Reasons generally include strategic planning, risk management, policy setting, and communication. The purpose will determine how the scenario is constructed (impact vs. vulnerability), the scope of the baseline conditions to be incorporated, and the geographic and temporal scale for the scenario. For example, if the scenario is being built to assess possible future vulnerability, then it needs to start with an understanding of regional and population vulnerabilities. For strategic planning and risk management, the scenario should help to identify future needs and priorities for research and adaptation measures to protect human health and well-being. The second step is to determine the kind of scenarios that need to be created to achieve the study purpose. The third is to select the methods and tools appropriate for generating such scenarios. The terminology used should be explicitly defined because different disciplines define the same terms differently (e.g., vulnerability relates to residual damage in natural hazards research and to the current burden of disease in public health). Multiple disciplines should be involved to develop models and scenarios that place climate change in perspective alongside other drivers of health outcomes.
Key considerations in health scenario development include the following:
Identifying key determinants of population health and how they will evolve over time. Determinants include climate change, geography (including the built environment), demographics, social behavior, medical and other technology, regional and global economics, and unforeseen events. The degree of predictability of these determinants decreases as time is projected forward, with more certainty in short-term health statistics (e.g., deaths, illnesses, and injuries), less certainty in the medium term (e.g., demographic trends), and even less certainty in long-term determinants of health (including social and economic conditions and genetic change).
Incorporating development issues. The environmental, social, economic, technologic, political, and other determinants of population health also are determinants of development. In addition, population health status is both a determinant and a consequence of development. Research is needed to understand how to incorporate the pathways to development in health scenarios.
Incorporating adaptation and adaptive capacity into scenarios. Adaptation will determine the difference between the potential and actual impacts of climate change—that is, the strategies, policies, and measures implemented to reduce the projected consequences and take advantage of the opportunities that will arise. Specific adaptations will arise from the adaptive capacity of a population. Research is needed on how to develop storylines that incorporate adaptive capacity and specific adaptation measures over time, together with the consequences on climate-related health impacts. A related issue is how to incorporate the effects of multilateral environmental agreements on vulnerability and adaptation.
Incorporating thresholds and nonlinear events into scenarios. Most scenarios assume that change, including climate change, is monotonic. However, ample evidence demonstrates that many systems have thresholds that, when crossed, produce rapid and nonlinear change. These rapid and nonlinear changes, or “surprises,” are a special and extreme sort of uncertainty that need to be explored and integrated into scenarios. Clearly, change of this magnitude and speed could have profound effects on population health.
Identifying events or processes that can change projected trends and lead to alternative futures. Uncertainties abound in the relationships among environment, human health, and society, including the constituents and boundary conditions of the problem of concern, the relationships among the system components, the relationships with the external environment, and the future evolution of external forcings.
Identifying and characterizing critical uncertainties. There are several sources of uncertainty associated with scenario development, including determining whether the full range of not-improbable futures is captured, ensuring that appropriate models are chosen, and determining whether is it appropriate to assume that associations and assumptions remain constant across geographic and temporal scales. In addition, there is uncertainty in underlying variables (e.g., the rate, speed, and regional extent of climate change; changes in economic development and technology), in response function differences across populations, and in the effectiveness of mitigation and adaptation measures.
Involving stakeholders, including decision makers and representatives from a range of pertinent disciplines, in scenario development. Developing scenarios in isolation from users of the scenarios and from other disciplines can result in improbable visions of pathways to the future. Including a range of stakeholders will inform the scenario process and can ensure broad-based support across disciplines.
Communicating to stakeholders the scenario process, including the scenario purpose, outcome, and uncertainties. This involves determining which communication methods are most effective for particular stakeholder groups.
Evaluating scenarios (including monitoring and mapping of trends).
Use of health models and scenarios to inform policy.
Carefully developed health scenarios promise to outline plausible health futures from which policy makers can develop reasoned adaptation and mitigation responses. Several issues were identified that address the particular concerns of decision makers, including the following:
Demonstrating the value of scenarios to policy makers. Climate change projections suggest that future weather patterns will be different from those experienced today. Making decisions based on current climate could decrease future adaptive capacity. Scenarios provide boundaries within which to test the consequences and robustness of policy choices.
Involving decision makers and policy makers in scenario development and eliciting information regarding the questions that are important to them.
Determining the temporal and spatial scale needed for decision making. Climate change impacts will be site specific and path dependent. For example, malaria outbreaks occur after the rainy season in some regions but occur during the dry season in other areas. Decision makers need information on the appropriate scale for the development of effective and efficient response measures.
Evaluating how current health policies may be affected by a changing climate. Current policies were designed based on recent climate conditions. Some policies will need to be modified with changing weather patterns. For example, lengthening the malaria transmission season may result in the need to treat bed nets more than once per season. Health policies (and health infrastructure) will need to be adjusted to take this change into account.
Conclusions
We identified several overarching issues that were important to both the process of model and scenario development. For example, it is critical that the purpose of the model or scenario, including the temporal, geographic, and organizational scales within which it will be built, be defined clearly during development. The terminology should be explicit because different disciplines define terms differently. Multiple disciplines should be involved in model and scenario development; in particular, the climate modeling community should be included.
More comprehensive, long-term data sets on finer scales are needed for key determinants of population health to develop models and scenarios that put climate change into perspective with other drivers of health outcomes. Health models also can be improved by better understanding of climate–health associations, better understanding and models of moderating influences (e.g., population growth and level of development), better understanding and models of adaptation measures, quantification of uncertainty, and validation.
Scenario development has moved from narrow, disciplinary-based projections to multidisciplinary integrated approaches; from solely quantitative approaches with simulation models to comprehensive approaches with detailed qualitative narratives; from expert-based approaches to processes characterized by stakeholder involvement; and from a focus on likely futures to a focus on lessons that can be learned. The comprehensive inclusion of health issues in narrative scenarios with the involvement of stakeholders can now be achieved.
The workshop concluded that research on the development of health models and scenarios for global environmental change is of critical importance.
Workshop Participants
Carlos Corvalan Maud Huynen Joel Scheraga
World Health Organization Maastricht University U.S. Environmental Protection Agency
Kristie Ebi Rik Leemans Jacinthe Sequin
Exponent Health Group Wageningen University Health Canada
Paul Epstein Bettina Menne Michael Slimak
Harvard Medical School World Health Organization U.S. Environmental Protection Agency
Majid Ezzati Antonio Navarra Roger Street
Harvard School of Public Health Instituto Nazionale di Geofisica e Vulcanologia Meteorological Service of Canada
Janet Gamble Hugh Pitcher Brian Thomas
U.S. Environmental Protection Agency University of Maryland Swiss Re America
Martha Garrett John Reilly Ferenc Toth
Uppsala University Massachusetts Institute of Technology International Atomic Energy Agency
Anne Grambsch Dieter Riedel Mary Wilson
U.S. Environmental Protection Agency Health Canada Harvard School of Public Health
==== Refs
References
Albritton DL Meira Filho LG Cubasch U Dai X Ding Y Griggs DJ 2001. Technical Summary. Working Group 1, Intergovernmental Panel on Climate Change. Cambridge, UK:Cambridge University Press.
Campbell-Lendrum DH Corvalan CF Pruss-Ustun A 2003. How much disease could climate change cause? In: Climate Change and Human Health: Risks and Responses (McMichael AJ, Campbell-Lendrum D, Corvalan CF, Ebi KL, Githeko A, Scheraga JD, Woodward A, eds). Geneva:World Health Organization/World Meterological Organization/United Nations Environmental Programme, 133–158.
Hayhoe K Cayan D Field CB Frumhoff PC Maurer EP Miller NL 2004 Emission pathways, climate change, and impacts on California Proc Natl Acad Sci USA 101 12422 12427 15314227
Kovats RS Koppe C In press. Heat waves past and future impacts on health. In: Integration of Public Health with Adaptation to Climate Change: Lessons Learned and New Directions (Ebi K, Smith J, Burton I, eds). Lisse, the Netherlands:Taylor & Francis.
Martens P Kovats RS Nijhof S deVries P Livermore MTJ Bradley DJ 1999 Climate change and future populations at risk of malaria Global Environ Change 9 S89 S107
McMichael AJ Githeko A Akhtar R Carcavallo R Gubler G Haines A 2001. Human Health. In: The Third Assessment Report of the Intergovernmental Panel on Climate Change (McCarthy JJ, Canziani OF, Leary NA, Dokken DJ, White KS, eds). Cambridge, UK:Cambridge University Press, 451–486.
Nakicenovic N Davidson O Davis G Grubler A Kram T La Rovere EL 2000. IPCC Special Report on Emission Scenarios. A Special Report of Working Group III of the Intergovernmental Panel on Climate Change. Cambridge, UK:Cambridge University Press.
Rogers DJ Randolph SE 2000 The global spread of malaria in a future, warmer world Science 289 1763 1769 10976072
Scheraga J Ebi K Moreno AR Furlow J 2003. From science to policy: developing responses to climate change. In: Climate Change and Human Health: Risks and Responses (McMichael AJ, Campbell-Lendrum D, Corvalan CF, Ebi KL, Githeko A, Scheraga JD, Woodward A, eds). Geneva:World Health Organization/World Meterological Organization/United Nations Environmental Programme, 237–266.
Tanser F Sharp B leSueur D 2003 Potential effect of climate change on malaria transmission in Africa Lancet 362 1792 1798 14654317
Van Lieshout M Kovats RS Livermore MTJ Martens P 2004 Climate change and malaria: analysis of the SRES climate and socio-economic scenarios Global Environ Change 14 87 99
Woodward A Hales S Weinstein P 1998 Climate change and human health in the Asia Pacific region: who will be the most vulnerable? Clim Res 11 31 38
|
15743724
|
PMC1253761
|
CC0
|
2021-01-04 23:40:57
|
no
|
Environ Health Perspect. 2005 Mar 7; 113(3):335-338
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7380
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7471ehp0113-00033915743725Environmental MedicineArticleVascular Dysfunction in Patients with Chronic Arsenosis Can Be Reversed by Reduction of Arsenic Exposure Pi Jingbo 12Yamauchi Hiroshi 3Sun Guifan 4Yoshida Takahiko 5Aikawa Hiroyuki 6Fujimoto Wataru 7Iso Hiroyasu 8Cui Renzhe 8Waalkes Michael P. 2Kumagai Yoshito 91Graduate School of Medical Sciences, University of Tsukuba, Tsukuba, Japan2Laboratory of Comparative Carcinogenesis, National Cancer Institute, National Institutes of Health, Department of Health and Human Services, Research Triangle Park, North Carolina, USA3Department of Preventive Medicine, St. Marianna University School of Medicine, Kawasaki, Japan4Department of Labor Hygiene and Occupational Health, School of Public Health, China Medical University, Shenyang, China5Department of Public Health, Asahikawa Medical College, Asahikawa, Japan6Department of Environmental Health, Tokai University School of Medicine, Isehara, Japan7Department of Dermatology, Kawasaki Medical School, Kurashiki, Japan8Department of Public Health, and9Department of Environmental Medicine, Graduate School of Comprehensive Human Sciences, University of Tsukuba, Tsukuba, JapanAddress correspondence to Y. Kumagai, Department of Environmental Medicine, Doctoral Programs in Medical Sciences, Graduate School of Comprehensive Human Sciences, University of Tsukuba, 1-1-1 Tennodai, Tsukuba, Ibaraki 305-8575, Japan. Telephone/Fax: 81-29-853-3133. E-mail:
[email protected] thank N. Shimojo (Institute of Community Medicine, University of Tsukuba) for his encouragement on this project; B. Li, C. Qian, S.T. Shi, S. Liu, X. Li, and S.T. Ben (School of Public Health, China Medical University) and C.Z. Zhang (Erdeng E Health Department of Baotou, Inner Mongolia, China) for their excellent contributions to this work. We also thank L.K. Keefer, J. Liu, and E. Leslie for their critical reviews of the manuscript.
This work was supported in part by funding from the Japan-China Medical Association to Y.K. by a China Nature Science Foundation grant (no. 30000142 to J.P.), and by Grants-in-Aids (nos. 15406004 and 13576029 to Y.K. and no. 13576018 to H.Y.) for scientific research from the Ministry of Education, Science and Culture of Japan.
The authors declare they have no competing financial interests.
3 2005 9 12 2004 113 3 339 341 2 8 2004 9 12 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Chronic arsenic exposure causes vascular diseases associated with systematic dysfunction of endogenous nitric oxide. Replacement of heavily arsenic-contaminated drinking water with low-arsenic water is a potential intervention strategy for arsenosis, although the reversibility of arsenic intoxication has not established. In the present study, we examined urinary excretion of cyclic guanosine 3′,5′-monophosphate (cGMP), a second messenger of the vasoactive effects of nitric oxide, and signs and symptoms for peripheral vascular function in 54 arsenosis patients before and after they were supplied with low-arsenic drinking water in an endemic area of chronic arsenic poisoning in Inner Mongolia, China. The arsenosis patients showed a marked decrease in urinary excretion of cGMP (mean ± SEM: male, 37.0 ± 6.1; female, 37.2 ± 5.4 nmol/mmol creatinine), and a 13-month period of consuming low-arsenic drinking water reversed this trend (male, 68.0 ± 5.6; female, 70.6 ± 3.0 nmol/mmol creatinine) and improved peripheral vascular response to cold stress. Our intervention study indicates that peripheral vascular disease in arsenosis patients can be reversed by exposure cessation and has important implications for the public health approach to arsenic exposure.
arseniccGMPendothelial dysfunctionintervention studynitric oxide
==== Body
The consumption of water contaminated by naturally occurring arsenic poses a serious threat to human health worldwide (Gebel 1999; Nickson et al. 1998). Arsenic causes a wide range of human ailments, including cancer, and vascular diseases such as peripheral and cardiovascular disease, arteriosclerosis, Raynaud’s syndrome, and hypertension (Chen 1990; Engel et al. 1994; Rahman et al. 1999; Wang et al. 2002; Yu et al. 2002). Because the precise mechanisms of arsenic toxicity are still largely undefined, a potentially important remedial action is the termination of further exposure by providing safe drinking water. However, limited data are available on the reversibility of chronic arsenosis in humans.
Our previous studies indicated that chronic exposure to arsenic through drinking water can induce systematic nitric oxide dysfunction, and the impaired NO signaling or bioactivity contributes to arsenic-associated vascular diseases (Pi et al. 2000, 2003; Kumagai and Pi 2004). NO bioactivity is a critical factor in vascular tone, and its impairment can lead to vaso-occlusive diseases (Ganz and Vita 2003). Impaired NO bioactivity contributes, at least in part, to vascular diseases in chronic arsenosis patients (Pi et al. 2000). NO produced endogenously from l-arginine by NO synthases is involved in many physiologic and pathophysiologic processes (Ganz and Vita 2003), and reduced NO production in turn is related to vascular endothelial cell dysfunction (Gewaltig and Kojda 2002). Among the multiple activities of NO, the homeostatic control of the vascular endothelium is directly connected with the activation of soluble guanylate cyclase and the production of cyclic 3′,5′-guanosine monophosphate (cGMP), a critical second messenger of the NO system (Gewaltig and Kojda 2002). Urinary excretion cGMP has been used as a reliable biomarker for endogenous NO production and endothelial cell function (Boger et al. 1997; Cui et al. 2004), and reduced cGMP production is thought to be a biochemical indicator of impaired NO production and peripheral vascular disease (Boger et al. 1997). Therefore, in this follow-up study, we evaluated the impact of intake reduction on chronic arsenic intoxication by investigating urinary excretion of cGMP and peripheral vascular function in arsenosis patients before and after they were supplied with low-arsenic drinking water.
Methods
Subjects.
This study was carried out in Gangfangying village, Baotou, Inner Mongolia, China, where high concentrations of arsenic (up to 1,790 μg/L) were present in tube-well water from the end of the 1970s to August 1999. At this point, an alternative community water supply with a drastically lower arsenic level (37 μg/L) was installed. The investigations were conducted in August 1999, just before the new water system was installed, and again in September 2000, 13 months after the switch to less-contaminated drinking water. We obtained informed consent from all participants. Two certified dermatologists and two trained physicians performed physical examinations and administered a standardized questionnaire interview at both time points. A total of 54 volunteer residents (24 males and 30 females, 8–65 years of age; mean age, 36.2 years) who participated in the two surveys in 1999 and 2000 and provided urine samples were enrolled in the present study. Some patients were excluded from this study because of unclear exposure history (14 cases) or because they provided no urine samples in 2000 (10 cases). Before arsenic remediation, 29 of the subjects were identified as having skin lesions typical of arsenosis, which include verrucous hyperkeratoses of the palms and soles of the feet and hypo- and hyperpigmentation in the trunk area (Pi et al. 2002). These symptoms were predominantly found in males (18/29 cases; 62%). In addition, there were 16 reports of cold-weather–associated pain and coldness in the extremities of the feet and hands and/or white fingers, which are regarded as indicators of arsenic-induced peripheral vascular dysfunction. There were no cases of hypertension or overt cardiac dysfunction. We collected fasting peripheral venous blood and morning urine samples for arsenic and/or cGMP analysis. Additionally, for a reference control, we collected 1,132 urine samples from a general population of Japanese men and women (40–65 years of age), living in the two farming communities of Ikawa and Kyowa, known to have minimal exposure to environmental inorganic arsenic.
Evaluation of arsenic poisoning.
We evaluated peripheral vascular response to cold stress by the difference of finger systolic blood pressure before and after ice-water immersion, which made the surface temperature of the finger decrease by 10ºC. Finger systolic blood pressure was determined by a finger blood pressure monitor (HEM-808F; Omron, Matsusaka, Japan). We measured skin temperature using a Tele-thermometer (WMZ-03, Shanghai Instruments, Shanghai, China).
Arsenic content in biological samples.
We determined arsenic levels in water and biological samples by atomic absorption spectrophotometry (AA-6800G-ASA-2sp; Shimadzu, Kyoto, Japan) according to our previously reported method (Pi et al. 2003). The detection limit of this method was 1 ng, and the coefficient of variation was < 5%. For standard reference material, we used oyster tissue (no. 1566) from the National Institute of Standards and Technology (Gaithersburg, MD, USA).
Urinary cGMP level.
We used an 125I-labeled cGMP radioimmunoassay kit (Amersham, Buckinghamshire, UK) with a detection limit of 256 fmol/ml to measure urinary cGMP. The interassay coefficient of variation was 3.2% (n = 8). To control the differences in renal function, we divided the urinary excretion of cGMP by the urinary creatinine concentration (expressed in nanomoles cGMP per millimoles of creatinine) (Boger et al. 1997). Urinary creatinine levels were determined using a creatinine test kit (Wako Pure Chemical Industries, Osaka, Japan). For each subject, we determined the urinary cGMP excretion level and creatinine twice and used the average value as the final measurement. In the present study, we investigated the effects of arsenic exposure reduction among chronic arsenosis patients based on urinary excretion of cGMP as an indicator of vascular dysfunction. We did not determine the levels of nitrite/nitrate, which are stable NO metabolites, as an alternative index of NO function because several of the tube-wells were contaminated with high levels of nitrite and/or nitrate, which would have distorted these data.
Statistical analysis.
Data are expressed as mean ± SEM in all cases. Comparisons between data obtained before and after the water switch were performed with a two-tailed, paired Student’s t-test. A value of p = 0.05 was considered statistically significant.
Results and Discussion
Table 1 shows that the mean arsenic level in the well water consumed by the 54 subjects from the end of the 1970s to August 1999 (before remediation) was 180 μg/L. In the nearly 20 years of exposure, all of the households enrolled in this study had shared between two and six of these water sources. The arsenic level of the new water supply was 37 μg/L, lower than the World Health Organization (WHO) maximum permissible limit of 50 μg/L for drinking water (WHO 1984). The 13-month exposure reduction markedly decreased the arsenic levels in biological samples, including urine and blood samples, in a sex-independent fashion (Table 1), showing that the new low-arsenic water supply effectively reduced the body burden of arsenic.
As shown in Table 2 and Figure 1, the urinary cGMP levels in all age groups of both sexes were significantly depressed before remediation when high levels of arsenic were consumed. This finding was supported by the work of Lee et al. (2003), who reported that arsenite can dramatically inhibit cGMP accumulation in isolated aortic rings of rats. After the 13-month arsenic exposure reduction, urinary cGMP levels increased to normal, as compared to the Japanese general population-based control values of 57.3 ± 2.1 nmol cGMP/mmol of creatinine in males (n = 510; 40–65 years of age) and 70.6 ± 3.0 in females (n = 622; 40–65 years of age) (Cui et al. 2004).
In agreement with the recovery of the arsenic-induced dysfunction of the NO/cGMP system, as indicated by the increase in urinary cGMP excretion, peripheral vascular response to cold stress, measured as the difference in finger systolic blood pressure before and after ice-water immersion, was significantly improved in male arsenosis patients (Table 3). In female arsenosis patients, although some improvement in finger blood pressure response occurred, it was not statistically significant (Table 3). The difference between peripheral vascular response to cold stress between male and female patients before remediation was also significant (Table 3), which is consistent with more severe exposure in males as evidenced by blood and urinary arsenic (Table 1) and skin lesions. In addition, 3 of the 16 patients reporting cold-weather–associated pain and coldness and/or white fingers showed improvement, although 12 patients had no significant change, and 1 patient became worse (data not shown).
Replacement of drinking water heavily contaminated with arsenic with low-arsenic water is a potential intervention strategy to minimize or reverse the adverse health effects of this toxic inorganic element. Consistent with our previous results (Pi et al. 2000), male and female arsenosis patients in the present study showed a marked depression in urinary excretion of cGMP, and a 13-month period of consuming low-arsenic drinking water reversed this depression. In addition, improved peripheral vascular response to cold stress was clearly observed in male arsenosis patients after consuming low-arsenic water and tended to improve in females. Together, these data suggest that long-term arsenic exposure induces biochemical changes in the vascular system and causes functional vascular damage, which, at least in males, can be reversed by limiting further arsenic intake. Although cGMP production improved, it is possible that females may need a longer period of reduced arsenic exposure for vascular function to be completely restored. In addition, before remediation, males had much higher blood and urinary arsenic levels and showed a higher rate of arsenic-induced skin lesions, indicating more severe intoxication. Thus, improvement of the symptoms of arsenic poisoning may be more readily observed in males.
In conclusion, a 13-month arsenic exposure reduction effectively reverses the arsenic-induced impairment of the NO/cGMP pathway in both males and females and improves peripheral vascular function in males. Additional comprehensive follow-up studies are necessary to document the long-term health benefits of arsenic exposure reduction, but the present results indicate the reduction of arsenic exposure could be an important public health strategy.
Figure 1 Urinary cGMP excretion in male (n = 24) and female (n = 30) untreated chronic arsenosis patients before and after the switch to low-arsenic drinking water. Water remediation reversed the arsenic-induced suppression of cGMP production in both males (p = 0.0012) and females (p < 0.0001).
Table 1 Arsenic levels in drinking water and biological samples before and after drinking water remediation.
Before remediation
After remediation
Males Females Males Females
Biological samples
Blood (μg/L)a 9.89 ± 0.21 (n = 22) 6.10 ± 0.79 (n = 23) 2.52 ± 0.23* (n = 22) 1.83 ± 0.19* (n = 23)
Urine (μg/g Cr) 424.5 ± 122.9 (n = 24) 292.5 ± 66.6 (n = 30) 177.2 ± 37.7* (n = 24) 161.5 ± 32.7* (n = 30)
Drinking water (μg/L) 180 ± 60 38
Cr, creatinine. Data expressed as mean ± SEM. Before remediation, n = 37 community wells; after remediation, n = 1 low-arsenic community well.
a Nine blood samples were not available.
* Significantly reduced (p < 0.05) compared with appropriate sex-matched population values from before remediation.
Table 2 Urinary cGMP excretion (nmol/mmol creatinine) before and after switching to low-arsenic drinking water.
Before remediation
After remediation
Age (years)a Males Females Males Females
8–13 22.1 ± 3.0 (n = 3) 27.2 ± 1.7 (n = 4) 73.7 ± 19.8* (n = 3) 66.8 ± 22.4* (n = 4)
21–40 29.6 ± 3.6 (n = 6) 33.3 ± 5.5 (n = 15) 60.1 ± 3.1* (n = 6) 76.8 ± 7.8* (n = 15)
41–65 45.1 ± 10.2 (n = 15) 42.9 ± 11.1 (n = 11) 67.2 ± 6.5* (n = 15) 69.9 ± 8.5* (n = 11)
Data expressed as mean ± SEM.
a Age in August 1999.
* Significantly different (p < 0.05) from measurement taken in August 1999, immediately before the introduction of low-arsenic drinking water.
Table 3 Peripheral vascular response to cold stress before and after switching to low-arsenic drinking water.
Sex No. Before remediation After remediation
Males 15 41.5 ± 5.8 26.0 ± 4.8*
Females 16 28.6 ± 3.4** 22.6 ± 4.3
Data expressed as mean ± SEM (mmHg).
* Significantly different (p < 0.05) from measurement taken before remediation.
** Significantly different (p < 0.05) from males before remediation.
==== Refs
References
Boger RH Bode-Boger SM Thiele W Junker W Alexander K Frolich JC 1997 Biochemical evidence for impaired nitric oxide synthesis in patients with peripheral arterial occlusive disease Circulation 95 2068 2074 9133517
Chen CJ 1990 Blackfoot disease [Letter] Lancet 336 442 1974970
Cui R Iso H Pi J Kumagai Y Yamagishi K Tanigawa T 2004 Urinary cyclic GMP excretion and blood pressure levels in a general population Atherosclerosis 172 161 166 14709371
Engel RR Hopenhayn-Rich C Receveur O Smith AH 1994 Vascular effects of chronic arsenic exposure: a review Epidemiol Rev 16 184 209 7713176
Ganz P Vita JA 2003 Testing endothelial vasomotor function: nitric oxide, a multipotent molecule Circulation 108 2049 2053 14581383
Gebel TW 1999 Arsenic and drinking water contamination Science 283 1458 1459 10206874
Gewaltig MT Kojda G 2002 Vasoprotection by nitric oxide: mechanisms and therapeutic potential Cardiovasc Res 55 250 260 12123764
Kumagai Y Pi J 2004 Molecular basis for arsenic-induced alteration in nitric oxide production and oxidative stress: implication of endothelial dysfunction Toxicol Appl Pharmacol 198 450 457 15276426
Lee MY Jung BI Chung SM Bae ON Lee JY Park JD 2003 Arsenic-induced dysfunction in relaxation of blood vessels Environ Health Perspect 111 513 517 12676608
Nickson R McArthur J Burgess W Ahmed KM Ravenscroft P Rahman M 1998 Arsenic poisoning of Bangladesh groundwater [Letter] Nature 395 338 9759723
Pi J Horiguchi S Sun Y Nikaido M Shimojo N Hayashi T 2003 A potential mechanism for the impairment of nitric oxide formation caused by prolonged oral exposure to arsenate in rabbits Free Radic Biol Med 35 102 113 12826260
Pi J Kumagai Y Sun G Yamauchi H Yoshida T Iso H 2000 Decreased serum concentrations of nitric oxide metabolites among Chinese in an endemic area of chronic arsenic poisoning in inner Mongolia Free Radic Biol Med 28 1137 1142 10832076
Pi J Yamauchi H Kumagai Y Sun G Yoshida T Aikawa H 2002 Evidence for induction of oxidative stress caused by chronic exposure of Chinese residents to arsenic contained in drinking water Environ Health Perspect 110 331 336 11940449
Rahman M Tondel M Ahmad SA Chowdhury IA Faruquee MH Axelson O 1999 Hypertension and arsenic exposure in Bangladesh Hypertension 33 74 78 9931084
Wang CH Jeng JS Yip PK Chen CL Hsu LI Hsueh YM 2002 Biological gradient between long-term arsenic exposure and carotid atherosclerosis Circulation 105 1804 1809 11956123
WHO 1984. Guidelines for Drinking Water Quality. Geneva:World Health Organization.
Yu HS Lee CH Chen GS 2002 Peripheral vascular diseases resulting from chronic arsenical poisoning J Dermatol 29 123 130 11990246
|
15743725
|
PMC1253762
|
CC0
|
2021-01-04 23:40:58
|
no
|
Environ Health Perspect. 2005 Mar 9; 113(3):339-341
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7471
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7412ehp0113-00034215743726Children's HealthArticlesChildren’s Exposure to Volatile Organic Compounds as Determined by Longitudinal Measurements in Blood Sexton Ken 1Adgate John L. 2Church Timothy R. 2Ashley David L. 3Needham Larry L. 3Ramachandran Gurumurthy 2Fredrickson Ann L. 2Ryan Andrew D. 21University of Texas School of Public Health, Brownsville Regional Campus, Brownsville, Texas, USA2Division of Environmental Health Sciences, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA3Division of Laboratory Sciences, National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, Georgia, USAAddress correspondence to K. Sexton, University of Texas School of Public Health, Brownsville Regional Campus, 80 Fort Brown, RAHC Building, Brownsville, TX 78520-4956 USA. Telephone: (956) 554-5168. Fax: (956) 554-5152. E-mail
[email protected] measurements were performed by S.S. Hecht and S.G. Carmella (University of Minnesota), and volatile organic compound badge analyses were performed by T.H. Stock and M.T. Morandi (University of Texas School of Public Health). We are especially grateful to personnel at the Minneapolis Public Schools, including principals, teachers, and nurses, and to the students and parents who participated in the study. Without them, this project would not have been possible. At the time the study was conducted, K.S. was a member of the Division of Environmental and Occupational Health, School of Public Health, University of Minnesota.
This research was funded by Science to Achieve Results (STAR) grants R825813 and R826789 from the U.S. Environmental Protection Agency, the National Center for Environmental Research, and a grant from the Legislative Commission on Minnesota Resources.
The authors declare they have no competing financial interests.
3 2005 22 11 2004 113 3 342 349 13 7 2004 22 11 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Blood concentrations of 11 volatile organic compounds (VOCs) were measured up to four times over 2 years in a probability sample of more than 150 children from two poor, minority neighborhoods in Minneapolis, Minnesota. Blood levels of benzene, carbon tetrachloride, trichloroethene, and m-/p-xylene were comparable with those measured in selected adults from the Third National Health and Nutrition Examination Survey (NHANES III), whereas concentrations of ethylbenzene, tetrachloroethylene, toluene, 1,1,1-trichloroethane, and o-xylene were two or more times lower in the children. Blood levels of styrene were more than twice as high, and for about 10% of the children 1,4-dichlorobenzene levels were ≥10 times higher compared with NHANES III subjects. We observed strong statistical associations between numerous pairwise combinations of individual VOCs in blood (e.g., benzene and m-/p-xylene, m-/p-xylene and o-xylene, 1,1,1-trichloroethane and m-/p-xylene, and 1,1,1-trichloroethane and trichloroethene). Between-child variability was higher than within-child variability for 1,4-dichlorobenzene and tetrachloroethylene. Between- and within-child variability were approximately the same for ethylbenzene and 1,1,1-trichloroethane, and between-child was lower than within-child variability for the other seven compounds. Two-day, integrated personal air measurements explained almost 79% of the variance in blood levels for 1,4-dichlorobenzene and approximately 20% for tetrachloroethylene, toluene, m-/p-xylene, and o-xylene. Personal air measurements explained much less of the variance (between 0.5 and 8%) for trichloroethene, styrene, benzene, and ethylbenzene. We observed no significant statistical associations between total urinary cotinine (a biomarker for exposure to environmental tobacco smoke) and blood VOC concentrations. For siblings living in the same household, we found strong statistical associations between measured blood VOC concentrations.
biomarkersblood concentrationschildren’s healthcotinineenvironmental justiceenvironmental tobacco smokeexposure assessmentinterchild variabilityintrachild variabilitypersonal exposurevolatile organic compounds
==== Body
Volatile organic compounds (VOCs), many of which exhibit acute and chronic toxicity in people, are common constituents of cleaning and degreasing agents, deodorizers, dry-cleaning processes, paints, pesticides, personal care products, and solvents. Numerous VOCs are also components of automotive exhaust, industrial emissions, and environmental tobacco smoke (ETS), and they can be released into the air during showering or bathing in chlorinated water. Airborne VOCs are therefore ubiquitous in urban and nonurban environments, in indoor and outdoor settings, and in occupational and nonoccupational situations (Adgate et al. 2004a, 2004b; Edwards et al. 2001b; Kim et al. 2002; Sexton et al. 2004a, 2004b, 2004c; Wallace et al. 1985, 1987, 1988).
Although data on nonoccupational exposures to VOCs are scarce, it is apparent that concentrations of many VOCs tend to be higher indoors than outdoors and that personal (breathing zone) exposures are likely to be higher than matched in-home concentrations (Adgate et al. 2004a, 2004b; Edwards et al. 2001b; Kim et al. 2002; Sexton et al. 2004b, 2004c; Wallace et al. 1985, 1987, 1988). Research also demonstrates that nonoccupational exposures can produce corresponding blood VOC concentrations in the parts-per-trillion to parts-per-billion range (Ashley et al. 1992, 1994, 1996, 1997; Brugnone et al. 1989, 1992, 1995; Churchill et al. 2001). Children are a potentially at-risk population because they may be both more exposed to VOCs and more susceptible to adverse effects than adults. It is well established, for example, that children can be affected by different sources, pathways, and routes of exposure than adults; that children often have greater intake of air, food, beverages, soil, and dust per unit body weight and surface area; and that children differ from adults in terms of important pharmacokinetic and pharmacodymanic parameters (Aprea et al. 2000; Bearer 1995; Guzelian et al. 1992; Needham and Sexton 2000). Yet despite these concerns, it is difficult to estimate VOC-related health effects accurately because there is a paucity of information on childhood VOC exposures (Adgate et al. 2004a, 2004b; Morello-Frosch et al. 2000; Sexton et al. 2004a; Wallace 2001; Woodruff et al. 1998). In this study, we examined longitudinal measurements of blood VOC concentrations for a probability sample of elementary school–age children from two economically disadvantaged neighborhoods in Minneapolis and explored correlations with matched measurements of personal exposure to airborne VOCs and total urinary cotinine levels.
Materials and Methods
The School Health Initiative: Environment, Learning, Disease (SHIELD) study examined children’s exposure over time to complex mixtures of environmental agents, including VOCs, ETS, metals, pesticides, and allergens.
Subjects.
The children and families participating in the SHIELD study were from two of the most disadvantaged and ethnically diverse neighborhoods in Minneapolis: Lyndale and Whittier. For the 150 children/families in the study, total annual household income was < $9,999 for 27% of the households, between $10,000 and $19,999 for 30%, and between $20,000 and $29,999 for 21%. Just 3% of the households earned > $50,000 annually. Forty-four percent of the participating households had no occupant with a high school degree or equivalent, 32% had at least one occupant with a high school degree or equivalent, and 23% had at least one occupant who was a college graduate or technical certificate holder. In fall 1999, of the 558 children enrolled in either the Lyndale or Whittier elementary schools, 43% were African American, 20% were recent immigrants from Somalia, 20% were Hispanic (primarily Mexican American), 7% were white, 6% were Asian, and 3% were Native American. Just over half of the children (54% at Lyndale and 52% at Whittier) lived in a household where English was the primary language. As a further indicator of poverty, > 75% of the children attending each school received either free or reduced-cost meals through the National School Lunch/Breakfast Program.
Data collection.
This study was approved by the University of Minnesota Research Subjects’ Protection Program Institutional Review Board: Human Subjects Committee. Only a brief synopsis is provided here because details of the study design (Sexton et al. 2000) and recruitment, retention, and compliance results (Sexton et al. 2003) have been published previously. A stratified random sampling strategy was used to select SHIELD participants from students in grades 2–5 (age range, 6–10 years) at either the Lyndale or Whittier elementary schools in south Minneapolis, and age-eligible siblings were also allowed to participate. In fall 1999, children and their families selected for SHIELD were contacted based on enrollment information provided by the Student Accounting Department, Minneapolis Public Schools. After successful contact, recruiters met with children and caregivers in their homes to explain the study and answer any questions. Recruiters obtained verbal and written consent/assent and administered the baseline questionnaire (which asked questions about demographic, socioeconomic, and housing attributes) to the 152 children/families who agreed to be in the study, plus 51 siblings. At enrollment the primary caregiver was asked a series of questions about smoking status and behavior, as well as questions about socioeconomic status, residential characteristics, and the child’s health.
During winter (January–February) and spring (April–May) of both 2000 and 2001, children were asked to give blood samples, which were collected at school by a trained phlebotomist. The phlebotomist attempted to obtain a 33-mL venipuncture blood sample from each child during each of the four monitoring sessions. Urine samples were also collected at the same time.
For the 2 days preceding collection of a blood sample, children, with the help of care-givers, interviews/translators, and field technicians, were asked to maintain a time–activity log, which recorded the location and approximate time they spent in seven different micro-environments. They also were asked to answer questions about the location and approximate time they spent in the presence of an active smoker. During winter and spring 2000, children also were asked to wear or carry a small passive sampler throughout the same 2-day period to measure airborne VOC concentrations. At times when it was impractical to wear or carry the monitor, such as while sleeping, children/families were instructed to place the monitor as near as possible to the child’s head (e.g., on a nightstand next to the bed). For year 1 of SHIELD, the enrollment rate was 57%, the retention rate was 85%, and > 80% of children provided requested blood and urine samples.
Laboratory analyses.
Determination of selected VOCs in whole blood was performed by the Division of Laboratory Science, National Center for Environmental Health, Centers for Disease Control and Prevention (Atlanta, GA), using an established gas chromatography/mass spectrometry method (Ashley et al. 1992). The analytical limit of detection (nanograms per milliliter) for individual compounds was 0.010 for benzene, 0.005 for carbon tetrachloride, 0.040 for 1,4-dichlorobenzene, 0.031 for ethyl-benzene, 0.008 for styrene, 0.022 for tetra-chloroethylene, 0.016 for toluene, 0.010 for trichloroethene, 0.024 for 1,1,1-trichloroethane, 0.020 for m-/p-xylene, and 0.050 for o-xylene. Quality control was established by using two separate quality control materials, of which at least one was analyzed daily. Blood levels for the control pools were compared with previously established 99% confidence limits. Among the additional data validity checks were examination of gas chromatography retention time, analyte accurate mass, and instrument sensitivity, as well as comparison of mass ratios with known standards.
We obtained airborne VOC concentrations (48-hr integrated samples) with 3M model 3500 organic vapor monitors (3M Corporation, St. Paul, MN), which are charcoal-based passive air samplers. Evidence of the suitability of these monitors for personal air sampling, as well as determination of extraction efficiencies and calculation of method detection limits, has been published previously (Chung et al. 1999a, 1999b). Laboratory measurements of individual VOCs were done by T.H. Stock and M.T. Morandi at the University of Texas School of Public Health. The extraction solvent consisted of 2:1 vol:vol mix of acetone and carbon disulfide, which provided a low background for target analytes. All extracts were analyzed by gas chromatography/ mass spectrometry. Analytical and internal standards were prepared, and VOC concentrations were calculated as described previously (Chung et al. 1999b).
Total cotinine in urine samples was measured by gas chromatography–mass spectrometry in the laboratory of S.S. Hecht at the University of Minnesota, as described in previous publications (Hecht et al. 1993, 2001).
Statistical analysis and related considerations.
Index children were sampled with selection probabilities designed to equally represent strata defined by school, grade, English-speaking versus non-English-speaking homes, and sex. Analyses were weighted to account for selection and response probabilities. Race/ethnicity was further broken down for analysis, and groups with fewer than 15 children were aggregated into a category designated “other.” Statistical analyses were performed using SAS (version 8.0; SAS Institute, Cary, NC) and S-Plus (S-Plus 2001; Insightful Corp., Seattle, WA). Analyses were performed on log-transformed laboratory values to normalize the distributions and to equalize variances, and transformed means were exponentiated to obtain geometric means. Concentrations below analytical detection limits that produced a laboratory value > 0 were included in the analyses.
We analyzed the effects of study design variables and personal exposure factors (from the time–activity logs) on blood VOC concentrations using weighted linear regression models, which included variables for season (spring compared with winter), school (Lyndale compared with Whittier), sex (male compared with female), race/ethnicity [African American, Somali immigrant, Hispanic, and Southeast Asian compared with white/Native American (“other”)], and VOC source variables (travel: ≥ 1.5 hr in a motorized vehicle over 48 hr vs. < 1.5 hr; cleaners: > 0 hr using cleaning supplies over 48 hr vs. 0 hr; cigarettes: > 0 hr spent in close proximity to a smoker over 48 hr vs. 0 hr; room deodorizers: > 0 hr using deodorizers over the past 6 months vs. 0 hr; ventilation: > 0 hr doors and/or windows were open for ventilation over 48 hr vs. 0 hr). Two-way interactions between design, source, and ventilation variables were also tested, and only significant associations are reported. This modeling of blood VOC concentrations used only results from the year 2000 because data from the time–activity logs were available only during this time.
To estimate within-child and between-child variability, blood VOC concentrations were log-transformed to make the variances homogeneous across different levels of exposure. The geometric mean for the population was designated μ, and a components-of-variance analysis was used to estimate a) the overall mean of the log-transformed values, log(μ); b) the between-child variance of log-transformed child-specific mean values, σP; and c) the within-child variance of log-transformed levels, σI. Assuming a normal distribution of individual log-transformed measurements, 95% tolerance limits (limits within which 95% of the measurements would be expected to fall) for the log-transformed values would be between x ± 1.96σI for a child with a mean log-concentration level of x. To translate the results to actual concentrations, rather than simply presenting the results in the log-transformed scale, we back-transformed these values to give corresponding intervals in the original concentration scale (nanograms per milliliter). Results in the log scale are interpreted as relative changes in concentration, so intervals in the log scale cannot be directly translated to a fixed interval in the concentration scale. Thus, we give intervals for selected individuals based on whether their mean level is an average concentration or at one or the other extreme of the distribution. Analogously, assuming they are also approximately normal, 95% tolerance limits for the distribution of mean log-transformed values among all children were computed as log(μ) ± 1.96σP and similarly back-transformed.
Results
Over the 2-year, four–monitoring-session study, 134 index (randomly selected) children provided 416 blood samples. Sixty-nine children provided 4 samples, 18 provided 3 samples, 39 provided 2 samples, and 8 provided 1 sample. The number of valid samples varied by VOC and by monitoring session for two reasons. First, some samples were deemed invalid by the laboratory because of condition (e.g., clotting), failure to meet acceptability standards (e.g., insufficient blood), instrument problems, or failure of quality control parameters to be within acceptable limits. Second, the number of children providing samples changed from session to session. The distributions of blood concentrations for 11 VOCs measured during each of the four monitoring periods are summarized numerically in Table 1 and displayed graphically in Figure 1 using box and whisker plots.
During all four monitoring sessions > 50% of the samples were above the detection limit for benzene (66–97%), ethylbenzene (61–99%), styrene (57–99%), and m-/p-xylene (66–99%), whereas > 30% were above the detection limit for 1,4-dichlorobenzene (41–89%), tetrachloroethylene (37–63%), toluene (45–75%), and o-xylene (32–73%). The percentage of samples above the detection limit was substantially less for carbon tetrachloride (5–23%), trichloroethene (3–7%), and 1,1,1-trichloroethane (0–2%), although the percentage above zero was considerably higher (carbon tetrachloride > 38%, trichloroethene > 62%, 1,1,1-trichloroethane > 66%). Distributions of blood VOC concentrations were relatively stable over the four monitoring sessions, although median values for benzene, toluene, m-/p-xylene, and o-xylene were comparatively higher in May 2001. Also, in both February and May 2000, 99th-percentile values for 1,4-dichlorobenzene and styrene were comparatively higher, whereas 99th-percentile values for tetrachloroethylene and o-xylene were comparatively higher in February 2000.
Relationships between all 55 pairwise combinations of individual VOC concentrations are portrayed in Figure 2 on a log scale using a scatterplot matrix. Matched data from all four monitoring sessions are included, and the matched number of samples varies from 261 for carbon tetrachloride and ethylbenzene to 378 for m-/p-xylene and o-xylene. Note that the data indicate a shift in analytical detection limits over the course of the 2-year study for three VOCs (carbon tetrachloride, trichloroethene, 1,1,1-trichloroethane), which tended to be at or near the limit of detection. Results indicate that significant correlations existed between many of the pairwise combinations. Adjusted R2 values were greater than 0.50 for four pairwise combinations [1,1,1-trichloroethane and m-/p-xylene (0.52), benzene and m-/p-xylene (0.55), m-/p-xylene and o-xylene (0.67), and trichloroethene and 1,1,1-trichloroethane (0.84)], and between 0.40 and 0.50 for five others [1,1,1-trichloroethane and carbon tetrachloride (0.42), benzene and 1,1,1-trichloroethane (0.43), trichloroethene and m-/p-xylene (0.46), m-/p-xylene and ethylbenzene (0.46), and o-xylene and ethylbenzene (0.47)]. Twelve pairwise combinations had adjusted R
2 values between 0.20 and 0.40, and four were between 0.10 and 0.20. Adjusted R2 values were less than 0.05 for all 30 of the remaining 55 pairwise combinations.
The results of the components-of-variance analysis for the 11 blood VOCs measured in this study are summarized in Table 2. For each VOC, we first provide an estimate of the overall population geometric mean (column 2) and associated population 95% tolerance limits (columns 3 and 4). Next, to illustrate the spread of within-child variance, we estimate individual 95% tolerance limits for a child with a mean blood VOC level a) at the lower 95% tolerance limit (LP) for the overall population (columns 5 and 6), b) at the geometric mean (μ) for the overall population (columns 7 and 8), and c) at the upper 95% tolerance limit (UP) for the overall population (columns 9 and 10).
The overall population 95% tolerance interval (columns 3 and 4) provides a measure of between-child variability. For 8 of 11 compounds, the ratio of UP to LP ranged from 2.2 (trichloroethene) to 7.3, whereas it exceeded 10 for 1,4-dichlorobenzene (> 56,000 because a few children had elevated values), tetrachloroethylene (28.8), and styrene (16.7). Similarly, within-child variability can be estimated using the tolerance interval (columns 7 and 8) for a child with a blood level equal to the population mean [or equal to the lower or upper population 95% confidence interval (CI)]. The ratio of the Uμ to Lμ ranged from 2.5 (1,1,1-trichloroethane) to 9.8 (m-/p-xylene) for 7 of 11 compounds, and exceeded 10 for 1,4-dichlorobenzene (130), styrene (30), tetrachloroethylene (14), and benzene (14). The within-child variance can also be examined by comparing the individual 95% CI (LIL − UIL) for a child with a mean blood concentration at the lower population 95% CI (columns 5 and 6) with the individual 95% CI (LIU − UIU) for a child with a mean blood concentration at the upper population 95% CI (columns 9 and 10). For 9 of 11 VOCs, all except 1,4-dichlorobenzene and tetrachloroethylene, these individual 95% tolerance intervals overlap.
The ratio of (UP − LP):(Uμ − Lμ) provides a comparison of the between-child and within-child variability, where a ratio > 1 indicates between > within and a ratio < 1 indicates between < within. The between-child variability exceeded the within-child variability for 1,4-dichlorobenzene (ratio = 434) and tetra-chloroethylene (ratio = 2), and it was approximately the same (ratio ~ 1) for ethylbenzene and 1,1,1-trichloroethane. Within-child variability exceeded between-child variability for benzene, carbon tetrachloride, styrene, toluene, trichloroethene, m-/p-xylene, and o-xylene.
In addition to index (randomly selected) children, siblings were eligible to participate in the study provided they were also enrolled in grades 2–5 at either the Lyndale or Whittier elementary schools. Thirty-five households had an index child plus one sibling, and four households had an index child plus two siblings, for which matched blood VOC samples were available. A single matched-blood VOC sample was obtained from the index child and the sibling(s) in 7 households, two matched samples in 11 households, three in 14 households, and four in 7 households, for a total of 109 matched index–sibling blood samples. We observed moderately strong statistical associations between measured VOC concentrations in index children and their siblings for all 11 individual compounds: benzene, R2 = 0.54; carbon tetrachloride, R2 = 0.48; 1,4-dichlorobenzene, R2 = 0.82; ethylbenzene, R
2 = 0.32; styrene, R
2 = 0.69; tetrachloroethylene, R2 = 0.43; toluene, R2 = 0.56; 1,1,1-trichloroethane, R2 = 0.37; trichloroethene, R
2 = 0.44; m-/p-xylene, R
2 = 0.69; and o-xylene, R2 = 0.51.
Total urinary cotinine, a well-established biomarker for exposure to ETS, was measured in the children’s urine during both monitoring sessions in 2000, and results have been published previously (Hecht et al. 2001; Sexton et al. 2004a). Because exposure to ETS is a possible source of blood VOCs in nonsmokers (Ashley et al. 1996, Churchill et al. 2001), we examined the relationship between matched (within-index child) total urinary cotinine levels and concentrations of individual VOCs in blood. The total number of matched pairs ranged from 75 for ethyl-benzene to 86 for m-/p-xylene. Results indicated a lack of statistical association between cotinine and all 11 individual VOCs, with adjusted R2 values ranging from 0.0001 for o-xylene to 0.05 for 1,1,1-trichloroethane.
During winter and spring 2000, the children wore a small, charcoal-based passive air sampler for the 2 days preceding collection of blood samples (n = 93 in winter 2000, n = 88 in spring 2000). Measurements provide an estimate of the child’s 2-day, integrated, personal exposure (across all indoor and outdoor microenvironments) to airborne VOCs. The relationships between matched (within-index child) personal VOC exposures and blood VOC concentrations are shown in Figure 3. There was a strong statistical association for 1,4-dichlorobenzene (R2 = 0.79) and a moderate association for m-/p-xylene (R2 = 0.22), o-xylene (R
2 = 0.19), tetrachloroethylene (R2 = 0.19), and toluene (R2 = 0.26). Little or no statistical association was observed for trichloroethene (R
2 = 0.01), styrene (R
2 = 0.005), benzene (R2 = 0.033), or ethylbenzene (R2 = 0.08).
Each data point in Figure 4 represents the estimated main effect of the variable or two-way interaction compared with the designated referent category in terms of relative VOC concentration (nanograms per milliliter). The 100% line indicates that blood VOC concentrations are approximately the same relative to the referent value—suggesting that there is no discernible effect on blood VOC concentrations. The variation about the mean is represented by 95% CI, which is calculated from the standard error of the parameter estimate from each regression model. Results were considered to be statistically significant when the CI did not include 100%. For example, the model indicates that mean blood benzene levels in spring 2000 were 22% higher than winter 2000 levels, and because the CI does not include the 100% line, this result is considered significant.
Results suggest that mean blood concentrations were significantly higher in spring than winter 2000 for benzene (22% higher), tetrachloroethylene (77%), m-/p-xylene (27%), and o-xylene (25%). Blood VOC concentrations were similar for children enrolled at the Whittier and Lyndale schools, except for benzene (14%), tetrachloroethylene (37%), and trichloroethene (7%), which were higher in children attending Lyndale. We observed no significant differences in blood VOC concentrations between males and females, but mean levels of 1,4-dichlorobenzene were 262% higher in African-American, 310% higher in Hispanic, 97% higher in Somali immigrant, and 419% higher in Southeast-Asian children compared with a group designated “other,” which included white and Native American children. Ethylbenzene concentrations in blood were 34% higher for children whose caregiver reported using home deodorizers during the 6 months preceding the study. Although benzene blood concentrations were not significantly increased by smokers in the home and were slightly decreased by ventilation, ventilation in homes with smokers was associated with 34% higher levels than would be expected by the product of the two effects. Conversely, for carbon tetrachloride there was a 30% increase in blood concentrations for children from homes with smokers, but the interaction effect made concentrations 24% lower in children who reported both exposure to ETS and windows or doors open for ventilation than would be expected by the product of the two effects. Styrene levels in blood were significantly lower (50%) for ventilated homes but were 284% higher than expected in children living in homes where cleaners were used and windows or doors were also open for ventilation. As always, one must interpret these with results with caution because of the issues raised by multiple comparison.
Discussion
Several studies have shown that internal doses of some VOCs, including benzene, styrene, and toluene, are elevated in smokers (Ashley et al. 1996; Churchill et al. 2001; Wallace et al. 1987). For nonsmokers, exposure to VOCs can be elevated in a variety of ways, including carrying out routine cooking and cleaning activities, being in close proximity to a smoker, riding inside a car in heavy traffic, refueling a vehicle, conducting hobby-related activities indoors, coming into contact with dry-cleaning processes or products, using cosmetics, and applying paints, paint thinners, furniture strippers, stains, and varnishes (Adgate et al. 2004a, 2004b; Ashley et al. 1992, 1994, 1996; Edwards et al. 2001a, 2001b; Kim et al. 2002; Sexton et al. 2004a, 2004b, 2004c; Wallace et al. 1985, 1987, 1988). Overall, available studies indicate that blood VOC levels are in the parts-per-trillion to parts-per-billion range for most people with no known occupational exposure, and that smoking is the largest confounder in discerning the influence of other environmental exposures (Ashley et al. 1996; Brugnone et al. 1989; Churchill et al. 2001; Wallace et al. 1987).
The internal doses that result from environmental exposures to VOCs are a function of complicated biologic, chemical, and physical processes. The evidence on the pharmacokinetics of VOCs suggests that a series of dynamic mechanisms control the uptake, deposition in body stores, metabolism, and elimination of these chemicals. Most of the internal dose of VOCs is eliminated in a matter of hours. However, a portion is removed over a much longer time period, and it is possible that VOCs may bioaccumulate with repeated exposures of sufficient duration. The half-life of VOCs in blood is short (hours), intermediate (days) in muscle tissue, and longer (months, years) in adipose tissue. The fraction of deposition at different sites in the body depends on two key factors: the length of exposure and the lipid solubility of the VOC (Ashley et al. 1996; Ashley and Prah 1997).
None of the children in this study were active smokers, nor were any of the children exposed in an occupational setting. Their VOC exposures and related blood levels are the product of concentrations in the air, water, soil, dust, food, beverages, and consumer products with which they came into contact through everyday activities and behaviors. Data from the time–activity logs indicate that in winter and spring 2000 the children spent most of their time indoors at home or at school and that they had relatively little exposure to ETS. On average, the children spent 65% (SD = 6.6) of each day inside at home, 25% (SD = 4.4) inside at school, 3.2% (SD = 5.4) inside in other locations, 1.2% (SD = 2.0) outside at home, 1.3% (SD = 1.0) outside at school, 0.7% (SD = 0.7) outside in other locations, and 3.6% (SD = 1.9) traveling in a vehicle. They were in close proximity to a smoker inside a building for an average of 1.3% (SD = 3.8) of each day and in close proximity to a smoker inside a vehicle for 0.1% (SD = 0.2) (Adgate et al. 2004a).
To put measured blood concentrations in perspective, Table 3 provides a comparison of results (arithmetic mean, median, and 95th percentile) from 134 SHIELD children between 6 and 10 years of age (one to four samples collected over 2 years), with findings from one-time measurements in more than 550 adults (≥18 years, including smokers) with no known occupational exposure who participated in the Third National Health and Nutrition Examination Survey (NHANES III) (Ashley et al. 1994). Blood concentrations of carbon tetrachloride and trichloroethene were near limits of detection in both studies. Mean and median levels of benzene and m-/p-xylene were comparable in both studies, although 95th percentile values were substantially higher in NHANES III (0.14 vs. 0.48 ng/mL for benzene and 0.32 vs. 0.78 ng/mL for m-/p-xylene). It is worth noting that for benzene and m-/p-xylene highest 95th percentile SHIELD values in specific seasons were comparable with NHANES III values: 0.40 in spring 2001 versus 0.48 ng/mL in NHANES III for benzene and 0.60 in spring 2001 versus 0.78 ng/mL in NHANES III for m-/p-xylene. Mean, median, and 95th percentile concentrations were two or more times higher in NHANES III for ethylbenzene, tetrachloroethylene, toluene, 1,1,1-trichloroethane, and o-xylene. Mean and 95th percentile blood levels of 1,4-dichlorobenzene and mean, median, and 95th percentile levels of styrene were more than twice as high in SHIELD children compared with NHANES III.
Because the NHANES III sample included smokers, it is not surprising that many blood VOCs were higher compared with SHIELD children. The fact that styrene concentrations were substantially higher in the children is unexpected, particularly because styrene is one of several VOCs known to be elevated in smokers’ blood (Ashley et al. 1996; Churchill et al. 2001; Wallace et al. 1987). The source of the children’s exposure to styrene is not known, and related health risks (e.g., effects on the central nervous system, liver, and red blood cells) are uncertain. Further research is needed to elucidate the sources, pathways, and routes of exposure to styrene for children in general and poor minority children in particular.
The blood concentrations of 1,4-dichloro-benzene in some SHIELD children were among the highest ever measured by the National Center for Environmental Health, Centers for Disease Control and Prevention. Thirteen of the 134 index children with at least one blood sample had 1,4-dichlorobenzene concentrations > 10 ng/mL (a total of 26 samples exceeded 10 ng/mL). For two of these children all four blood values were > 10 ng/mL, and for seven, two values were > 10 ng/mL. Although the SHIELD study was not designed to identify specific VOC sources, the evidence suggests that children were typically exposed inside their homes (R2 = 0.77 for indoor residential vs. blood concentrations). Because 1,4-dichlorobenzene is a common constituent of air fresheners and deodorizers, and because field staff reported the pervasive odor of these products in some households, we speculate that elevated blood levels in this population may be caused by frequent use of these kinds of consumer products. Additional research is needed to determine the sources and pathways for children’s exposure to 1,4-dichlorobenzene, and to better ascertain related health risks (e.g., cancer, central nervous system, respiratory system, kidney).
Because longitudinal measurements of blood VOC concentrations were made in the same children over time, the SHIELD data provide one of the first opportunities to estimate interchild and intrachild variability. For 2 of 11 VOCs (1,4-dichlorobenzene and tetrachloroethylene), between-child variability was greater than within-child variability, a condition that tends to complicate efforts to distinguish differences between individuals with a limited number of measurements and a constrained sample size. Between-child variability was less than within-child variability for seven VOCs (benzene, carbon tetrachloride, styrene, toluene, trichloroethene, m-/p-xylene, o-xylene) and approximately the same for ethylbenzene and 1,1,1-trichloroethane. The ratio of between-child to within-child variability is important because it can affect determinations of the minimum sample size and number of measurements needed to detect differences between groups of individuals (e.g., power calculations). In this study, children’s blood samples were drawn during the school day at convenient times. Future research should examine whether the timing of blood collection (e.g., early morning vs. end of day) has an effect on within- and between-child variability.
Because they have many common sources, numerous individual blood VOCs were highly correlated (e.g., R2 = 0.84 for trichloroethene and 1,1,1-trichloroethane, R2 = 0.67 for m-/p-xylenes and o-xylene, R2 = 0.55 for benzene and m-/p-xylenes, R
2 = 0.52 for 1,1,1-trichloroethane and m-/p-xylenes). Although we expected that airborne VOC levels would be the major determinant of blood VOC concentrations, 2-day, integrated personal air samples explained < 10% of the variance in blood levels for four of nine VOCs (benzene, ethylbenzene, styrene, trichloroethene) for which matched air–blood samples were available, and between 19 and 26% for four others (tetrachloroethylene, toluene, m-/p-xylenes, o-xylene). Personal air levels explained most of the variance in matched blood concentrations only for 1,4-dichlorobenzene (R2 = 0.79).
A previous study (Mannino et al. 1995) in adults known to be occupationally exposed to gasoline fumes and automotive exhaust found substantially higher correlations in nonsmokers between personal air measurements (5–8 hr integrated occupational samples) and blood concentrations for several VOCs (ethylbenzene, R = 0.82; toluene, R = 0.88; m-/p-xylenes, R = 0.94; o-xylene, R = 0.90). The relatively low correlations in SHIELD children could be explained by one or more of several possible reasons: the longer averaging time for personal air samples (48 hr vs. 5–8 hr); different exposure magnitudes, durations, and frequencies (e.g., longer-term, relatively lower community exposures for the children vs. shorter-term, relatively higher occupational exposures); differences in pharmacokinetics (e.g., absorption, deposition, metabolism, elimination) between children and adults; and the contribution of other routes of exposure (e.g., ingestion of VOCs in food or beverages, absorption through the skin during bathing or showering).
Although smoking is known to be an important determinant of blood VOC concentrations (Ashley et al. 1996; Churchill et al. 2001; Wallace et al. 1987), evidence of a link between ETS exposure and blood VOC levels in nonsmokers is scarce. We have previously reported results of total urinary cotinine measurements, a biomarker for nicotine and hence ETS exposure in nonsmokers, for SHIELD children. Findings indicated that measured concentrations in the children’s urine were comparable with other ETS studies in non-smoking adults (Hecht et al. 2001) and that concentrations varied by ethnicity/race, with highest levels observed in African-American children and lowest levels in Hispanic and Somali immigrant children (Sexton et al. 2004a). When we examined matched (within-child) measurements of total urinary cotinine and blood VOC levels in winter and spring 2000, we found virtually no correlation between ETS exposure and any of the 11 measured blood VOCs (0.0001 ≤R
2 ≤0.05), despite the fact that some children were exposed to relatively high levels of ETS (Hecht et al. 2001; Sexton et al. 2004a) that might reasonably be expected to influence blood VOC concentrations, particularly levels of benzene, styrene, and toluene (Ashley et al. 1996; Churchill et al. 2001; Wallace et al. 1987). One possible explanation for the lack of statistical association is the relatively stable levels of total urinary cotinine measured over time for each child, which meant that within-child variability was comparatively low (Sexton et al. 2004a). On the other hand, these results are consistent with relatively low correlations observed between personal air exposure and most blood VOC concentrations, which suggests that, except for 1,4-dichlorobenzene, airborne levels may not have been the dominant factor influencing children’s blood VOC concentrations.
Conclusions
The SHIELD study is one of the first to measure, over time, blood concentrations of VOCs in a probability sample of children. Results indicate that childhood exposures to some compounds equaled or exceeded VOC exposures of adults, including smokers, in an earlier national survey, and that within-child variability was greater than between-child variability for 7 of 11 individual VOCs. Matched personal exposure (breathing zone) measurements explained ≤25% of the variance in blood concentrations for 10 of 11 compounds, whereas matched urinary cotinine measurements (an ETS exposure biomarker) explained ≤5% of the variance in blood VOC levels for each of the 11 compounds. Further research is needed to better understand the sources, pathways, and routes of children’s exposure to VOCs.
Figure 1 Box and whisker plots of blood VOC concentrations (ng/mL) measured in SHIELD children. Each box and whisker plot shows the median and the interquartile range (25th–75th percentile; box) and the minimum and maximum concentrations (whiskers) at a specific sampling session.
Figure 2 Scatterplot matrix showing relationships between blood concentrations (log10 ng/mL) for all pairwise combinations of individual VOCs over all sampling sessions.
Figure 3 Blood VOC concentrations versus personal exposure concentrations.
Figure 4 Estimated mean relative blood VOC concentration for each variable in the regression model. Vent, ventilation. Each point represents the estimated mean effect and the deviation from the mean using the 95% CI (calculated as the anti-log of the parameter estimates from each regression model). Season, winter 2000 versus spring 2000; school, Whittier versus Lyndale; sex, female versus male; African American versus other (including whites); Somali immigrant versus other (including whites); Hispanic versus other (including whites); Southeast Asian versus other (including whites); travel, > 1.5 hr on highway or road today; cleaners, > 0 hr spent using cleaning supplies today; cigarettes, > 0 cigarettes smoking in your presence today; vent, > 0 hr door and windows open for ventilation today; cigarettes × vent; cleaners × vent.
Table 1 Distribution of blood VOC concentrations (ng/mL) among SHIELD children.
Percentile
VOC Month/year No. % > DL 10th 25th 50th 75th 90th 95th 99th
Benzene Feb 2000 112 97.4 0.03 0.04 0.06 0.07 0.08 0.09 0.16
May 2000 113 94.0 0.03 0.04 0.04 0.06 0.07 0.08 0.10
Feb 2001 63 66.3 0.05 0.06 0.07 0.08 0.10 0.10 0.11
May 2001 72 80.9 0.10 0.14 0.18 0.22 0.28 0.40 0.41
Carbon tetrachloride Feb 2000 106 5.2 0.00 0.00 0.00 0.00 0.00 0.01 0.04
May 2000 110 9.4 0.00 0.00 0.00 0.00 0.00 0.01 0.01
Feb 2001 60 22.1 0.01 0.01 0.01 0.01 0.01 0.02 0.02
May 2001 34 22.5 0.01 0.01 0.01 0.01 0.02 0.03 0.14
1,4-Dichlorobenzene Feb 2000 112 88.7 0.04 0.06 0.14 0.38 6.00 12.00 470.0
May 2000 114 79.5 0.04 0.05 0.12 0.96 5.50 27.00 140.0
Feb 2001 56 41.1 0.05 0.06 0.22 2.80 13.00 22.00 24.00
May 2001 86 65.2 0.05 0.05 0.15 1.10 2.20 18.00 34.00
Ethylbenzene Feb 2000 92 79.1 0.02 0.02 0.03 0.05 0.07 0.08 0.12
May 2000 86 66.7 0.01 0.02 0.03 0.04 0.05 0.07 0.17
Feb 2001 63 61.1 0.02 0.02 0.02 0.03 0.03 0.03 0.04
May 2001 88 98.9 0.03 0.04 0.05 0.06 0.08 0.09 0.10
Styrene Feb 2000 103 89.6 0.04 0.05 0.07 0.18 0.74 0.85 1.00
May 2000 108 92.3 0.05 0.07 0.09 0.18 0.54 0.68 2.00
Feb 2001 54 56.8 0.06 0.07 0.09 0.10 0.11 0.11 0.54
May 2001 88 98.9 0.08 0.09 0.11 0.12 0.17 0.21 0.27
Tetrachloroethylene Feb 2000 108 62.6 0.02 0.02 0.03 0.05 0.11 0.65 0.82
May 2000 113 43.6 0.02 0.02 0.02 0.03 0.05 0.09 0.21
Feb 2001 60 46.3 0.03 0.03 0.03 0.04 0.06 0.09 0.19
May 2001 79 37.1 0.03 0.03 0.03 0.04 0.09 0.10 0.69
Toluene Feb 2000 106 73.9 0.06 0.07 0.10 0.13 0.20 0.25 0.49
May 2000 102 55.6 0.07 0.07 0.08 0.11 0.19 0.20 0.55
Feb 2001 60 45.3 0.09 0.10 0.11 0.14 0.16 0.19 0.38
May 2001 79 75.3 0.10 0.12 0.17 0.25 0.34 0.37 0.61
Trichloroethene Feb 2000 100 7.0 0.01 0.01 0.01 0.01 0.01 0.01 0.01
May 2000 115 5.1 0.01 0.01 0.01 0.01 0.01 0.01 0.01
Feb 2001 59 3.2 0.01 0.01 0.01 0.01 0.01 0.01 0.02
May 2001 88 6.7 0.01 0.01 0.01 0.01 0.01 0.02 0.02
1,1,1-Trichloroethane Feb 2000 108 0.0 0.02 0.02 0.02 0.02 0.02 0.03 0.03
May 2000 114 0.0 0.02 0.02 0.02 0.02 0.02 0.02 0.03
Feb 2001 63 1.1 0.03 0.03 0.03 0.03 0.04 0.04 0.04
May 2001 78 2.2 0.03 0.03 0.03 0.04 0.04 0.06 0.07
m-/p-Xylene Feb 2000 113 98.3 0.10 0.11 0.13 0.17 0.21 0.22 0.74
May 2000 115 98.3 0.09 0.10 0.11 0.13 0.17 0.17 0.20
Feb 2001 63 66.3 0.15 0.16 0.19 0.23 0.31 0.31 0.32
May 2001 88 98.9 0.23 0.30 0.37 0.47 0.57 0.60 0.66
o-Xylene Feb 2000 113 73.0 0.02 0.02 0.03 0.05 0.06 0.08 0.30
May 2000 114 44.4 0.02 0.02 0.02 0.03 0.04 0.05 0.07
Feb 2001 63 31.6 0.03 0.03 0.03 0.04 0.05 0.06 0.11
May 2001 88 66.3 0.03 0.04 0.07 0.11 0.13 0.14 0.16
DL, detection limit.
Table 2 Summary of intrachild and interchild variability for blood VOC concentrations (ng/mL).
Intrachild tolerance interval for
Interchild tolerance interval for populationb Individual with mean of Lpc Individual with mean of μd Individual with mean of Upe
Compound Overall population geometric meana (μ) LP UP LIL UIL Lμ Uμ LIU UIU
Benzene 0.063 0.026 0.152 0.007 0.097 0.017 0.233 0.042 0.559
Carbon tetrachloride 0.005 0.002 0.011 0.001 0.006 0.002 0.014 0.004 0.030
1,4-Dichlorobenzene 0.242 0.001 56.436 0.000 0.012 0.021 2.728 5.009 635.803
Ethylbenzene 0.033 0.012 0.087 0.004 0.035 0.012 0.092 0.031 0.244
Styrene 0.110 0.027 0.450 0.005 0.149 0.020 0.608 0.082 2.487
Tetrachloroethylene 0.033 0.006 0.173 0.002 0.024 0.009 0.127 0.045 0.661
Toluene 0.117 0.045 0.306 0.017 0.121 0.043 0.315 0.114 0.824
Trichloroethene 0.007 0.005 0.011 0.003 0.008 0.004 0.012 0.007 0.018
1,1,1-Trichloroethane 0.027 0.018 0.041 0.012 0.029 0.017 0.043 0.026 0.064
m-/p-Xylene 0.172 0.074 0.401 0.024 0.230 0.055 0.536 0.129 1.249
o-Xylene 0.039 0.015 0.100 0.006 0.041 0.014 0.105 0.037 0.271
a μ = 10mean[log(x)], the estimated geometric mean, calculated by back-transforming the average of within-child mean log concentrations.
b (LP, UP) = 95% tolerance interval for the population of individual mean serum levels, calculated using between-child SD, σP, for the log-transformed data and back-transforming: log(μ) ± 1.96σP.
c (L
IL, U
IL) = Tolerance interval for an individual with mean serum level equal to the lower tolerance limit of the population, LP, and calculated using within-child SD, σI, and back-transforming: log(LP) ± 1.96σI.
d (L
μ, U
μ) = Tolerance interval for an individual with mean serum level equal to the estimated geometric mean of the population, μ, and calculated using within-child SD, σI, and back-transforming: log(μ) ± 1.96σI.
e (L
IU, U
IU) = Tolerance interval for an individual with mean level equal to the upper tolerance limit of the population, UP, calculated using within-child SD, σI, and back-transforming: log(UP) ± 1.96σI.
Table 3 Comparison of blood VOC concentrations (ng/mL) for SHIELD children and selected adult participants (including smokers) in NHANES III.
Meana Median
95th Percentile
Compound SHIELDb NHANESc SHIELD NHANES SHIELD NHANES
Benzene 0.08 0.13 0.08 0.06 0.14 0.48
Carbon tetrachloride 0.01 ND 0.01 ND 0.01 ND
1,4-Dichlorobenzene 4.22 1.9 0.21 0.33 24.5 9.2
Ethylbenzene 0.04 0.11 0.03 0.06 0.07 0.25
Styrene 0.17 0.07 0.12 0.04 0.50 0.18
Tetrachloroethylene 0.06 0.19 0.03 0.06 0.22 0.62
Toluene 0.14 0.52 0.11 0.28 0.27 1.5
Trichloroethene 0.01 0.02 0.01 ND 0.01 0.02
1,1,1-Trichloroethane 0.03 0.34 0.03 0.13 0.03 0.80
m-/p-Xylene 0.21 0.37 0.19 0.19 0.32 0.78
o-Xylene 0.05 0.14 0.04 0.11 0.09 0.30
ND, below limit of detection.
a Arithmetic mean.
b Participants included 134 children with at least one blood sample in 2000 or 2001 (average values were used for children with more than one blood sample).
c Between 574 and 1,037 participants, depending on the VOC (from Ashley et al. 1994).
==== Refs
References
Adgate JL Church TR Ryan AD Ramachandran G Fredrickson AL Stock TH 2004a Outdoor, indoor, and personal exposure to VOCs in children Environ Health Perspect 112 1386 1392 15471730
Adgate JL Eberly LE Stroebel C Pellizzari ED Sexton K 2004b Personal, indoor, and outdoor VOC exposures in a probability sample of children J Expo Anal Environ Epidemiol 14 suppl 1 S4 S13 15118740
Aprea C Strambi M Novelli MT Lunghini L Bozzi N 2000 Biologic monitoring of exposure to organophosphate pesticides in 195 Italian children Environ Health Perspect 108 521 525 10856025
Ashley DL Bonin MA Cardinali FL McCraw JM Holler JS Needham LL 1992 Determining volatile organic compounds in human blood from a large sample population using purge and trap gas chromatography/mass spectrometry Anal Chem 64 1021 1029 1590585
Ashley DL Bonin MA Cardinali FI McCraw JM Wooten JV 1994 Blood concentrations of volatile organic compounds in a nonoccupationally exposed U.S. population and in groups with suspected exposure Clin Chem 40 7 1401 1404 8013127
Ashley DL Bonin MA Cardinali FL McCraw JM Wooten JV 1996 Measurement of volatile organic compounds in human blood Environ Health Perspect 104 suppl 5 871 877 8933028
Ashley DL Prah JD 1997 Time dependence of blood concentrations during and after exposure to a mixture of volatile organic compounds Arch Environ Health 52 1 26 33 9039854
Bearer CF 1995 Environmental health hazards: how children are different from adults Future Child Crit Issues Child Youths 5 2 11 26
Brugnone F Gobbi M Ayyad K Giuliari C Cerpelloni M Perbellini L 1995 Blood toluene as a biological index of environmental toluene in the “normal” population and in occupationally exposed workers immediately after exposure and 16 hours later Int Arch Occup Environ Health 6 421 425 7782127
Brugnone F Perbellini L Faccini GB Pasini F Danzi B Maranelli G 1989 Benzene in the blood and breath of normal people and occupationally exposed workers Am J Ind Med 16 385 399 2610211
Brugnone F Perbellini L Maranelli G Romeo L Guglielmi G Lombardini F 1992 Reference values for blood benzene in the occupationally unexposed general population Int Arch Occup Environ Health 64 179 184 1399030
Chung CW Morandi MT Stock TH Afshar M 1999a Evaluation of a passive sampler for volatile organic compounds at ppb concentrations, varying temperatures, and humidities with 24-h exposures. 1. Description and characterization of exposure chamber system Environ Sci Technol 33 20 3661 3665
Chung CW Morandi MT Stock TH Afshar M 1999b Evaluation of a passive sampler for volatile organic compounds at ppb concentrations, varying temperatures, and humidities with 24-h exposures. 2. Sampler performance Environ Sci Technol 33 20 3666 3671
Churchill JE Ashley DL Kaye WE 2001 Recent chemical exposures and blood volatile organic compound levels in a large population-based sample Arch Environ Health 56 2 157 166 11339680
Edwards RD Jurvelin J Koistinen K Saarela K Jantunen M 2001a VOC source identification from personal and residential indoor, outdoor and workplace microenvironment samples in EXPOLIS-Helsinki, Finland Atmos Environ 35 4829 4841
Edwards RD Jurvelin J Saarela K Jantunen M 2001b VOC concentrations measured in personal samples and residential indoor, outdoor and workplace microenvironments in EXPOLIS-Helsinki, Finland Atmos Environ 35 4531 4543
Guzelian PS Henry CJ Olin SS 1992. Similarities and Differences between Children and Adults: Implications for Risk Assessment. Washington, DC:ILSI Press.
Hecht SS Carmella SG Murphy SE Akerkar S Brunnemann KD Hoffman D 1993 A tobacco-specific lung carcinogen in the urine of men exposed to cigarette smoke N Engl J Med 329 1543 1546 8413477
Hecht SS Ye M Carmella SG Fredrickson A Adgate JL Greaves IA 2001 Metabolites of a tobacco-specific lung carcinogen in the urine of elementary school-aged children Cancer Epidemiol Biomarkers Prev 10 1109 1116 11700257
Kim YM Harrad S Harrison RM 2002 Levels and sources of personal inhalation exposure to volatile organic compounds Environ Sci Technol 36 24 5405 5410 12521168
Mannino DM Schreiber J Aldous K Ashley D Moolenaar R Almaguer D 1995 Human exposure to volatile organic compounds: a comparison of organic vapor monitoring badge levels and blood levels Int Arch Occup Environ Health 67 59 64 7622282
Morello-Frosch RA Woodruff TJ Axelrad DA Caldwell JC 2000 Air toxics and health risks in California: the public health implications of outdoor concentrations Risk Anal 20 2 273 291 10859786
Needham LL Sexton K 2000 Assessing children’s exposure to hazardous environmental chemicals: an overview of selected research challenges and complexities J Expo Anal Environ Epidemiol 10 611 629 11138654
Sexton K Adgate JL Church TR Greaves IA Ramachandran G Fredrickson AL 2003 Recruitment, retention, and compliance results from a probability study of children’s environmental health in economically disadvantaged neighborhoods Environ Health Perspect 111 731 736 12727602
Sexton K Adgate JL Church TR Hecht SS Ramachandran G Greaves IA 2004a Children’s exposure to environmental tobacco smoke: using diverse exposure metrics to document ethnic/racial differences Environ Health Perspect 112 392 397 14998759
Sexton K Adgate JL Mongin SJ Pratt GC Ramachandran G Stock TH 2004b Estimating personal exposure to volatile organic compounds based on measured concentrations in outdoor and indoor air Environ Sci Technol 38 9 2593 2602 15180055
Sexton K Adgate JL Ramachandran R Pratt GC Mongin SJ Stock TH 2004c Comparison of personal, indoor, and outdoor exposures to hazardous air pollutants in three urban communities Environ Sci Technol 38 2 423 430 14750716
Sexton K Greaves IA Church TR Adgate JL Ramachandran G Tweedie R 2000 A school-based strategy to assess children’s environmental exposures and related health effects in economically disadvantaged urban communities J Expo Anal Environ Epi 10 6 682 694
Wallace LA 2001 Human exposure to volatile organic compounds: implications for indoor air studies Annu Rev Energy Environ 26 269 301
Wallace L Pellizzari E Hartwell TD Perritt R Ziegenfus R 1987 Exposures to benzene and other volatile organic compounds from active and passive smoking Arch Environ Health 42 5 272 279 3452294
Wallace LA Pellizzari ED Hartwell TD Sparacino CM Sheldon LS Zelon H 1985 Personal exposures, indoor-outdoor relationships, and breath levels of toxic air pollutants measured for 355 persons in New Jersey Atmo Environ 19 10 1651 1661
Wallace LA Pellizzari ED Hartwell TD Whitmore R Zelon H Perritt R 1988 The California TEAM study: breath concentrations and personal exposures to 26 volatile organic compounds in air and drinking water of 188 residents of Los Angeles, Antioch, and Pittsburg, CA Atmos Environ 22 10 2141 2161
Woodruff TJ Axelrad DA Caldwell J Morello-Frosch R Rosenbaum A 1998 Public health implications of 1990 air toxics concentrations across the United States Environ Health Perspect 106 245 251 9518474
|
15743726
|
PMC1253763
|
CC0
|
2021-01-04 23:40:57
|
no
|
Environ Health Perspect. 2005 Mar 22; 113(3):342-349
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7412
|
oa_comm
|
==== Front
Environ Health PerspectEnviron. Health PerspectEnvironmental Health Perspectives0091-67651552-9924National Institue of Environmental Health Sciences 10.1289/ehp.7240ehp0113-00035015743727Children's HealthArticlesAsthma and Farm Exposures in a Cohort of Rural Iowa Children Merchant James A. 1Naleway Allison L. 2Svendsen Erik R. 3Kelly Kevin M. 1Burmeister Leon F. 4Stromquist Ann M. 1Taylor Craig D. 1Thorne Peter S. 1Reynolds Stephen J. 5Sanderson Wayne T. 1Chrischilles Elizabeth A. 61Department of Occupational and Environmental Health, University of Iowa College of Public Health, Iowa City, Iowa, USA2Center for Health Research, Kaiser Permanente Northwest, Portland, Oregon, USA3National Health and Environmental Effects Research Laboratory, Human Studies Division, Epidemiology and Biomarkers Branch, U.S. Environmental Protection Agency, Research Triangle Park, North Carolina, USA4Department of Biostatistics, University of Iowa College of Public Health, Iowa City, Iowa, USA5Department of Environmental and Radiological Health Sciences, Colorado State University College of Veterinary Medicine and Biomedical Sciences, Fort Collins, Colorado, USA6Department of Epidemiology, University of Iowa College of Public Health, Iowa City, Iowa, USAAddress correspondence to J.A. Merchant, University of Iowa College of Public Health, E220H1 General Hospital, Iowa City, IA 52242 USA. Telephone: (319) 384-5452. Fax: (319) 384-5455. E-mail:
[email protected] authors acknowledge the many contributions of the Keokuk County Rural Health Study staff.
This work was supported by National Institute for Occupational Safety and Health (NIOSH) grant 5 R01/CCR714364 and NIOSH-funded grant U07/CCU706145 to the Great Plains Center for Agricultural Health. These findings do not necessarily represent the U.S. Environmental Protection Agency.
The authors declare they have no competing financial interests.
3 2005 7 12 2004 113 3 350 356 6 5 2004 7 12 2004 Publication of EHP lies in the public domain and is therefore without copyright. All text from EHP may be reprinted freely. Use of materials published in EHP should be acknowledged (for example, ?Reproduced with permission from Environmental Health Perspectives?); pertinent reference information should be provided for the article from which the material was reproduced. Articles from EHP, especially the News section, may contain photographs or illustrations copyrighted by other commercial organizations or individuals that may not be used without obtaining prior approval from the holder of the copyright. Epidemiologic studies of farm children are of international interest because farm children are less often atopic, have less allergic disease, and often have less asthma than do nonfarm children—findings consistent with the hygiene hypothesis. We studied a cohort of rural Iowa children to determine the association between farm and other environmental risk factors with four asthma outcomes: doctor-diagnosed asthma, doctor-diagnosed asthma/medication for wheeze, current wheeze, and cough with exercise. Doctor-diagnosed asthma prevalence was 12%, but at least one of these four health outcomes was found in more than a third of the cohort. Multivariable models of the four health outcomes found independent associations between male sex (three asthma outcomes), age (three asthma outcomes), a personal history of allergies (four asthma outcomes), family history of allergic disease (two asthma outcomes), premature birth (one asthma outcome), early respiratory infection (three asthma outcomes), high-risk birth (two asthma outcomes), and farm exposure to raising swine and adding antibiotics to feed (two asthma outcomes). The high prevalence of rural childhood asthma and asthma symptoms underscores the need for asthma screening programs and improved asthma diagnosis and treatment. The high prevalence of asthma health outcomes among farm children living on farms that raise swine (44.1%, p = 0.01) and raise swine and add antibiotics to feed (55.8%, p = 0.013), despite lower rates of atopy and personal histories of allergy, suggests the need for awareness and prevention measures and more population-based studies to further assess environmental and genetic determinants of asthma among farm children.
agricultural occupational exposuresammoniaanimal feeding operationsasthmaasthma diagnosis and treatmentasthma health care policyasthma school screeningasthma underdiagnosisasthma undertreatmentchildrenchronic wheezecough with exercisefarminggenetic selectionhydrogen sulfidehygiene hypothesisodorrural
==== Body
Most epidemiologic studies of childhood asthma have been conducted among inner-city or urban populations and have found asthma prevalence to vary by location, likely attributable to differing environmental exposures [International Study of Asthma and Allergies in Children (ISAAC) Steering Committee 1998]. Studies of rural childhood asthma are of particular interest because they have consistently reported that farm children are less often atopic (Braun-Fahrlander et al. 1999; Downs et al. 2001; Riedler et al. 2000, 2001), have lower rates of allergic diseases (Braun-Fahrlander et al. 1999; Kilpelainen et al. 2000; Riedler et al. 2000, 2001; Von Ehrenstein et al. 2000; Wickens et al. 2002), and in several reports also have lower rates of asthma (Ernst and Cormier 2000; Kilpelainen et al. 2000; Riedler et al. 2000, 2001; Von Ehrenstein et al. 2000). These findings are consistent with the hygiene hypothesis, which posits that childhood allergy risk is immunologically modulated in early life by exposure to infectious agents. However, several studies have not found positive associations between asthma and asthma symptoms among children and farm exposures, raising questions regarding the influence of unmeasured risk factors and/or selection in these cross-sectional studies (Chrischilles et al. 2004; Downs et al. 2001; Salam et al. 2004; Wickens et al. 2002).
It is recognized that asthma risk is conveyed by a complex interaction of genetic and environmental determinants, which makes the epidemiologic investigation of farm-related asthma difficult (Douwes et al. 2001; Niven 2003; Schwartz 2001). International studies of childhood asthma among farm children have typically measured atopy to gauge genetic predisposition to asthma but have less consistently described and measured farm environment risk factors, often using endotoxin as an indicator of exposure to infectious agents early in life. Although endotoxin is a ubiquitous exposure in agriculture, its concentration varies within and between farm types, and it is but one of many agricultural respiratory exposures children may encounter (Douwes et al. 2003; Reynolds et al. 1996; Schenker et al. 1998).
Over the last three decades, the development of a vertically integrated livestock industry has significantly reduced the number of U.S. family farms raising hogs, poultry, and cattle but has rapidly increased the number of large animal-feeding operations (AFOs) (National Academy of Sciences 2003). Although inflammatory airway diseases, including asthma, chronic bronchitis, organic dust toxic syndrome, and progressive airway obstruction, are now well documented among AFO workers (Schenker et al. 1998), there has been much less research regarding exposures and health outcomes among AFO-exposed children and community-based residents (Reynolds et al. 1997a; Salam et al. 2004; Thu et al. 1997; Wing and Wolf 2000).
The Keokuk County Rural Health Study (KCRHS) is a large, population-based study of a cohort of rural families living in an intensely agricultural region of southeastern Iowa (Merchant et al. 2002). The aim of the present study was to estimate asthma prevalence and assess whether farm exposures result in less atopy, less allergic disease, and less asthma, while taking into account multiple personal and other environmental risk factors, among this cohort of farm children.
Materials and Methods
The study population.
This study reports data on children from birth through 17 years of age collected in round 1 of the KCRHS, which began in 1994 and ended in 1998. Keokuk County was chosen because it is intensely agricultural and entirely rural. A stratified, random sample that identified households from farm, town, and rural nonfarm locations was used. A total of 2,496 eligible households were identified. Details regarding the sampling methodology and survey methods have been reported previously (Merchant et al. 2002). All members of enrolled households were invited to a centrally located research facility for interviews, and all adults and children ≥8 years of age were invited for medical examinations. One adult per household was interviewed by a trained interviewer about the health of all of the children (from birth but < 18 years of age) living in the household.
Questionnaire.
The childhood respiratory questionnaire chosen for this study was that used in University of Southern California studies of childhood asthma in Los Angeles (Peters et al. 1999). We used four asthma outcomes to estimate asthma prevalence—doctor-diagnosed asthma, asthma/medication for wheeze (doctor-diagnosed asthma and/or medication for wheeze in the last 12 months), current wheeze, and cough with exercise. These four asthma outcomes, severe symptoms consistent with asthma, atopy, an early respiratory illness, and a high-risk birth are fully defined in the definition section of the online version this article. The parent’s response to the questionnaire also provided information regarding parental farm exposures, maternal smoking during pregnancy, household exposure to tobacco smoke, parental education, and household income.
Clinical assessment.
Children ≥8 years of age were invited to complete a medical examination that included skin prick testing (SPT), spirometry, methacholine challenge testing, and height and weight measurements to calculate 95th percentile body mass index (kilograms per square meter) (Must et al. 1991). A total of 18 aeroallergens common to the Midwest, a histamine-positive and normal saline-negative control, were used for SPTs. Common rural aeroallergens included tree pollen mix, grass pollen mix, ragweed pollen, weed pollen mix, cockroach mix, mold mix, insect mix, caddis fly/moth/mayfly mix, cat pelt, dog hair, mouse and rat mix, and dust mite Der f and Der p mix. Farm aeroallergens included grain dust mix or grain smut mix, soybean dust or soybean whole grain, cattle hair, horse hair, chicken feathers, and turkey feathers. Children taking antihistamines and other medications known to affect skin test results, those with histories of past systemic reactions to allergy skin testing, and any participant who might have been pregnant were excluded from skin testing. A wheal ≥3 mm in diameter was defined as a positive reaction; subjects were considered atopic by SPT if they had a positive reaction to any two of the allergens tested. Spirometry was completed on a rolling-seal spirometer that conformed to American Thoracic Society (1995) guidelines. Contraindications to methacholine testing included participants with a baseline forced expiratory volume in 1 sec (FEV1) of < 70% of predicted or FEV1 < 1.5 L, pregnancy or suspected pregnancy, lactation, current use of a β-adrenergic blocking agent, and a decline in FEV1 of ≥15% to the diluent. Methacholine was administered by dosimeter in five serial doses of 0.025, 0.25, 2.5, 10.0, and 25.0 mg/mL, with 3 min between doses (Crapo et al. 2000). Bronchial hyperresponsiveness was defined as having a drop in FEV1 of ≥20% from the postsaline control (PC20), following inhalation of ≤8 mg/mL of methacholine (Anto 1998; Crapo et al. 2000).
Serum analysis.
Sera were collected from subjects (n = 217) at the time of SPT and analyzed for total and specific IgE. Total IgE was measured by immunoassay using murine monoclonal anti-human IgE as the capture antibody (CLB, Sanguin Blood Supply Foundation, Amsterdam, the Netherlands), rabbit anti-human IgE as the second antibody (Dako, Corp., Carpinteria, CA), and peroxidase-conjugated donkey anti-rabbit IgG as the labeling antibody (Research Diagnostics, Inc., Flanders, NJ) in a TMB substrate system (Pierce Endogen, Rockford, IL). Standard curves were generated using an IgE CAP system standards (Pharmacia Diagnostics, Uppsala, Sweden) with the standard curve from 0.02 to 10 kU/L. Sera were studied at initial dilutions of 1:20, 1:40, 1:80, and 1:160, with higher dilutions run for high IgE sera. Individuals were considered to be atopic by IgE if their total IgE was ≥60 kU/L (Contreras et al. 2003).
Environmental assessment.
An industrial hygienist visited each household shortly after the clinic visit and completed a home environmental questionnaire and checklist, when applicable a farm environmental questionnaire and farm environmental checklist, and measurement of a limited number of environmental parameters. Details of these environmental assessments have been published previously (Park et al. 2003; Reynolds et al. 1997b). Assessments of specific environmental exposures were taken from these instruments, including several farm operation questions, livestock and antibiotics in animal feed questions, and questions regarding gas stoves, heating with wood, exposure to pesticides, exposure to cats and dogs as pets, and dehumidifier use.
Household type was determined at the time of the child’s birth from the biologic mother’s reproductive history questionnaire and through follow-up phone interviews with the biologic mother regarding residence type (farm, rural nonfarm, or home) at the time of birth. Children’s various farm tasks and the age each task was first performed were determined from a questionnaire on childhood tasks from available KCRHS round 2 data and from follow-up phone administration of this questionnaire to round 1 participants who had not participated in round 2.
Statistical analysis.
Chi-squared tests and analysis of variance were used to evaluate any differences among demographic, personal, and environmental risk factors for farm, rural non-farm, and town households. Univariable logistic regression was used to identify variables that were significant (p < 0.1) for doctor-diagnosed asthma, asthma/medication for wheeze, chronic wheeze, and cough with exercise. Multivariable logistic regression was then used to identify significant (p < 0.05) variables in the final models.
Initial data analyses was performed with SAS (version 8; SAS Institute, Inc., Cary, NC) software. SUDAAN software (Research Triangle Institute, Research Triangle Park, NC) was then used to adjust variance estimates for potential intrahousehold correlation resulting from the inclusion of more than one child per household.
The study was approved annually by The University of Iowa institutional review board. A parent or legally authorized representative of each child participant provided written informed consent. Children 8–17 years of age gave their assent.
Results
Cohort description.
Of the 2,496 Keokuk County households eligible for this study, 1,675 households (67.1%) initially contacted by letter and telephone agreed to participate immediately or to be contacted at a later date. Enrollment stopped when the goal of 1,000 households was reached. A total of 1,004 households (336 farm, 206 rural non-farm, 462 town households) enrolled and participated in round 1 of the study.
The cohort, which consisted of 644 children (224 farm, 155 rural nonfarm, and 265 town), did not differ in age among household types, was somewhat overrepresented by boys in farm and rural nonfarm households, and was 97.7% Caucasian. Of the 336 farms in the cohort, 109 had children. Complete data on all farming characteristics were available on 89 farms with children and on 172 farms without children. These farms produced primarily corn, soybeans, and hogs but very few other livestock. Farms with children were somewhat smaller (434 total acres in production) than farms without children (468 total acres in production) but were otherwise similar, except that farms with children on average raised more hogs (298 vs. 141, p = 0.03). Fifty percent of farm children were reported by a parent to perform tasks around hogs, compared with ≤16% for rural non-farm or town children, whereas 40% of farm children were reported to perform tasks around cows compared with ≤13% for rural nonfarm or town children.
Health outcomes.
Ninety-five percent of the children’s data were provided by the child’s biologic mother or female guardian. Complete data on asthma outcomes were available on 610 children. Concordance between the four asthma outcomes varied from strong to weak: doctor-diagnosed asthma (asthma/medication for wheeze κ = 0.81, p < 0.0001; current wheeze κ = 0.31, p < 0.0001; cough with exercise κ = 0.26, p < 0.0001), asthma/medication for wheeze (current wheeze κ = 0.53, p < 0.0001; cough with exercise κ = 0.39, p = 0.11; current wheeze and cough with exercise κ = 0.27, p = 0.73). Only 4.4% of participants were captured by all four asthma outcomes, whereas 33.6% of all 610 participants were captured by at least one asthma outcome. Children with doctor-diagnosed asthma included only a third (8 of 24) of the children with severe symptoms consistent with asthma, whereas children with any one of the four asthma outcomes captured 23 of 24 children with severe symptoms. Of the 394 children 8–17 years of age, 351 (89.1%) had SPT, 347 (88.1%) had pulmonary function tests, and 215 (61.2%) agreed to have blood drawn for sera. Agreement between total individual IgE and SPT results (Aspergillus, cat hair, cockroach, weed mix, tree pollen, Der p, and Der f) ranged from 72.8 to 89.1%.
Children who were born on a farm had a lower prevalence of atopy (IgE), a lower prevalence of diagnosed allergies and a higher forced vital capacity (likely attributable to hyperinflation) (Table 1). Children who currently lived on a farm were somewhat more likely to be boys and somewhat less likely to have diagnosed allergies (Table 1).
A very high proportion of children who lived on a farm at the time of study (currently lives on a farm) were born when their parents lived on a farm (born on a farm) and continued to live on a farm (data for those who lived on a farm during the first year of life or through age 5, or had a parent who continued to work on a farm, were also analyzed but not reported). Because univariable associations were similar for all farm versus nonfarm groups, only comparisons of born on a farm and currently living on a farm exposure results are presented (Table 2). Farm children were consistently exposed to less tobacco smoke but were more often exposed to wood stoves, conditions resulting in dehumidifier use, cats as pets, and application of pesticides outside the home. Farm children’s parents were more often better educated and had a household annual income of ≥$20,000 (Table 2).
Univariable associations among the four asthma outcomes and environmental risk factors are presented in Tables 3 and 4. A weak association was observed between doctor-diagnosed asthma and less parental education. A near significant association was observed between doctor-diagnosed asthma/medication for wheeze and living on a farm raising swine and a significant association with living on a farm that adds antibiotics to feed. No significant association was observed with environmental exposures and current wheeze, but significant negative associations were observed between cough with exercise and exposure to wood smoke and applied pesticides outside home in the last year, significant positive associations were observed with dogs as household pets, and near significant positive associations were observed with living on a swine farm and living on a farm that added antibiotics to feed. Tables 5 and 6 present univariable associations among the four asthma health outcomes and personal and clinical risk factors and health measures, which reveal similar association patterns but a few significant differences.
Multivariable models that included personal or environmental risk factors with univariable significance of p < 0.1 for any of the four asthma outcomes are presented in Table 7. In addition to sex, age, history of allergies, family history of allergies, premature birth, early respiratory infection, and high-risk birth, an interaction term (living on a farm that raised swine and added antibiotics to feed) was independently associated with asthma/medication for wheeze, current wheeze (p = 0.06), and cough with exercise. Of farms that raised swine, 24 of 43 (55.8%) added antibiotics to feed. Of livestock farms that add antibiotics to feed, 24 of 31 farms or 77.4% raise swine. Those farms that add antibiotics to feed were found to have larger mean numbers of livestock than those that did not add antibiotics to feed (750 vs. 392 animals; p = 0.0002). Examination of children who lived on farms raising swine and adding antibiotics to feed found that 55.8% (p = 0.013) reported at least one of the four asthma outcomes (Figure 1).
Discussion
This study reports uniformly high-prevalence estimates of asthma and asthma-related symptoms that are consistent with asthma prevalence observed in studies of U.S. urban populations (Bauer et al. 1999; ISAAC Steering Committee 1998). These high asthma prevalence estimates, and our finding of a high proportion (two-thirds) of children with severe symptoms consistent with asthma but without a doctor diagnosis of asthma, are consistent with the findings of our Rural Childhood Asthma Study (Chrischilles et al. 2004) and underscore the need for asthma screening programs, for improved rural health care provider asthma diagnostic and management skills, and for health policies that would improve access and insurance coverage for rural children.
A history of diagnosed allergies was found to be less common among children who lived on a farm in the first year of life, a finding consistent with many other studies of farm children (Braun-Fahrlander et al. 1999; Kilpelainen et al. 2000; Riedler et al. 2000, 2001; Von Ehrenstein et al. 2000). The three estimates of atopy also tended to be lower among children who lived on a farm in the first year of life, as reported by others (Braun-Fahrlander et al. 1999; Riedler et al. 2000, 2001). However, asthma and asthmalike symptom prevalences were found to be high and to not differ between children with farm exposures and those without farm exposures, unlike the findings of others (Ernst and Cormier 2000; Kilpelainen et al. 2000; Riedler et al. 2000, 2001; Von Ehrenstein et al. 2000), despite lower rates of allergic disease and atopy and a significantly lower exposure to household tobacco smoke among farm children. However, as depicted in Figure 1, these excesses are found only among children living on farms raising swine, whereas a lower prevalence of asthma was observed among farm children not raising swine compared with nonfarm children, which is consistent with the aforementioned studies.
Farms in Northern Europe tend to be smaller than Iowa farms and to have livestock that are often housed in immediate proximity to living quarters, and these farm families have been described as more traditional in their way of life. Farms in Canada, Australia, and New Zealand are described as larger but typically not as livestock intensive as Iowa farms (Downs et al. 2001; Ernst and Cormier 2000; Wickens et al. 2002). Keokuk County farm families do not live in immediate proximity to livestock buildings but do usually live on the same acreage, typically with many farm family members participating in the farm operation. It is common for young children to be exposed to farming operations, including AFOs, as they accompany a parent or sibling in assisting with farm tasks (Park et al. 2003). Farm children in Keokuk County were reported by their parents to be exposed as bystanders to farm tasks around livestock as early as 1 year of age; however, such tasks around livestock were typically done by male adolescents. Although no environmental measurements of farm task exposures were made, several studies conducted in Iowa document high levels of occupational exposures to respirable and total dust, endotoxin, hydrogen sulfide, and ammonia, which have been associated with asthma, chronic bronchitis, cross-shift declines in lung function, and progressive declines in lung function over time among those working in AFOs (Reynolds et al. 1996; Schenker et al. 1998; Schwartz et al. 1995). It is therefore probable that some swine-farm–exposed children had high exposures to endotoxin and other AFO exposures and that some of the asthma and asthma symptoms observed among these farm youth are attributable to occupational exposures.
Multivariable models for doctor-diagnosed asthma/medication for wheeze and cough with exercise found that raising swine and adding antibiotics to feed were independently associated with these health outcomes. Because farms that add antibiotics to feed were much larger than those that did not add antibiotics to feed, adding antibiotics to feed may serve as an indicator of larger swine operations. However, it is plausible that antibiotic exposures may be playing some causal role because antibiotics have been documented to be components of emissions from AFOs (Hamscher et al. 2003; Svendsen et al. 2003) and, when consumed for medical purposes, have been associated with childhood asthma (Wickens et al. 1999). These high asthma estimates make clear that on-farm exposure to swine production is associated with asthma among children living on these farms and that swine production contributes to the higher prevalence of asthma outcomes in this livestock-intensive rural community. More detailed assessment of the temporal relationships between childhood farm exposures, including measurements of endotoxin-laden dust, irritant gases, and antibiotics in relation to asthma estimates, is needed to further our understanding of these relationships.
Other events early in life, apart from farm exposures, including premature birth, a respiratory infection at ≤3 years of age, and high-risk birth, were independently associated with asthma outcomes in this study, also consistent with other studies of childhood asthma (Farooqi and Hopkin 1998; Von Mutius et al. 1993). These early-life risk factors, which did not differ between farm and nonfarm participants in this study, may confound assessment of farm exposures in populations where farm families are poorer and have less adequate prenatal health care.
Two studies of nonfarm infants have evaluated the role of endotoxin exposures early in life and have reported no relationship between endotoxin levels and atopy, allergic disease, and asthma (Bolte et al. 2003; Park et al. 2001), findings inconsistent with the hygiene hypothesis. Another contributing explanation, which has been recognized, but only indirectly assessed (Braun-Fahrlander et al. 1999; Downs et al. 2001; Ernst and Cormier 2000; Leynaert et al. 2001), is the potential unmeasured effect of systematic genetic selection of those susceptible to farm-related respiratory disease away from farming over successive generations. It is common for farm youth to leave the farm in Keokuk County, so much so that we have reported a significant deficit of asthma among adult farm men compared with other men in Keokuk County (Merchant et al. 2002).
Because indicators of asthma associated with common farm exposures are influenced by genotypic patterns (Arbour et al. 2000; Gilliland et al. 2004), epidemiologic studies of genotype among farm family generations could help define patterns of differential selection of atopic, allergic, and asthmatic members of farm families away from farming.
Limitations of this study include the relatively small numbers of children with clinical data. Also, this study was not designed to address the question of whether exposures to dust, irritant gases, and odors arising from AFOs may be associated with respiratory symptoms or health conditions among rural residents living in proximity to farms with AFOs. However, the few community-based studies of AFO exposures have reported higher rates of airway symptoms (Reynolds et al. 1997a; Thu et al. 1997; Wing and Wolf 2000), and significant peaks in asthma hospital visits have been observed following peak exposures to total reduced sulfur (for children) and to hydrogen sulfide (for adults) from a large animal waste treatment complex (Campagna et al. 2004). As the result of these findings and community complaints about odor, several states now regulate some combination of hydrogen sulfide, total reduced sulfur, ammonia, and odor. Given our finding of a high prevalence of asthma outcomes among farm children living on swine farms, it is clear that farm parents should be aware of this risk and take precautions to reduce childhood respiratory exposures from AFOs. Evaluation of asthma outcomes and environmental exposures among school children and rural residents living proximate to AFOs remains an important research priority.
Figure 1 Prevalence of one or more asthma outcomes in rural Iowa children.
Table 1 Farm exposures for living on a farm [% (no./total) or mean ± SD], personal and family risk factors, and asthma outcomes.
Variable Born on a farm Not born on a farm OR (95% CI) p-Value Currently lives on a farm Does not currently live on a farm OR (95% CI) p-Value
Male sex 56.2 (122/217) 52.0 (196/377) 1.19 (0.84–1.67) 0.3277 58.5 (131/224) 51.0 (214/420) 1.36 (0.98–1.88) 0.0654
Age (years) 9.6 ± 5.0 (n = 217) 9.6 ± 4.9 (n = 377) 1.00 (0.96–1.04) 1.00 10.0 ± 4.9 (n = 224) 9.5 ± 4.9 (n = 420) 1.02 (0.98–1.06) 0.36
No. of siblings < 18 years of age 1.6 ± 1.2 (n = 217) 1.4 ± 1.0 (n = 377) 1.15 (0.87–1.53) 0.33 1.5 ± 1.2 (n = 224) 1.5 ± 1.0 (n = 420) 1.04 (0.77–1.40) 0.79
Atopy (IgE) 29.3 (24/82) 42.0 (50/119) 0.57 (0.31–1.04) 0.0661 32.5 (27/83) 38.8% (52/134) 0.76 (0.43–1.36) 0.3477
Atopy (SPT) 13.6 (15/110) 18.7 (34/182) 0.69 (0.34–1.40) 0.2926 18.6 (21/113) 17.5 (36/206) 1.08 (0.57–2.06) 0.8196
Atopy (by questionnaire) 21.2 (46/217) 22.8 (86/377) 0.91 (0.53–1.57) 0.7333 24.1 (54/224) 22.9 (96/420) 1.07 (0.61–1.90) 0.8122
Diagnosed allergies 10.8 (23/212) 17.7 (64/362) 0.57 (0.32–0.99) 0.0324 11.0 (24/218) 16.9 (66/402) 0.61 (0.35–1.06) 0.0612
Overweight (BMI/95th percentile) 8.1 (10/123) 5.5 (11/201) 1.53 (0.63–3.71) 0.3661 4.8 (6/124) 8.3 (19/228) 0.56 (0.22–1.43) 0.1836
Low birth weight (< 2,500 g) 3.8 (8/211) 5.0 (18/357) 0.74 (0.31–1.78) 0.4804 2.8 (6/214) 5.3 (21/399) 0.52 (0.19–1.40) 0.1793
Premature birth 10.4 (22/212) 12.2 (44/362) 0.84 (0.44–1.57) 0.5749 8.7 (19/218) 11.9 (48/402) 0.70 (0.34–1.44) 0.3216
Early respiratory infection 13.7 (29/212) 9.9 (36/362) 1.44 (0.80–2.57) 0.2446 12.8 (28/218) 10.7 (43/402) 1.23 (0.68–2.23) 0.5049
NICU admission 9.0 (19/212) 12.2 (44/362) 0.71 (0.38–1.33) 0.2660 11.5 (25/218) 11.7 (47/402) 0.98 (0.54–1.76) 0.9418
High-risk birtha 17.0 (36/212) 22.4 (81/362) 0.71 (0.44–1.15) 0.1545 19.3 (42/218) 20.9 (84/402) 0.90 (0.56–1.45) 0.6730
Doctor-diagnosed asthma 13.2 (28/212) 10.5 (38/362) 1.30 (0.69–2.43) 0.4234 11.9 (26/218) 11.7 (47/402) 1.02 (0.55–1.91) 0.9433
Asthma/medications for wheezing 17.0 (36/212) 15.2 (55/362) 1.14 (0.67–1.95) 0.6301 17.9 (39/218) 15.7 (63/402) 1.17 (0.71–1.95) 0.5427
Current wheeze 19.3 (41/212) 18.2 (66/362) 1.08 (0.65–1.77) 0.7769 19.3 (42/218) 20.2 (81/402) 0.95 (0.58–1.53) 0.8194
Cough with exercise 18.4 (39/212) 19.3 (70/362) 0.94 (0.58–1.53) 0.8022 19.7 (43/218) 18.9 (76/402) 1.05 (0.65–1.72) 0.8331
FVCb 3.38 ± 1.20 3.34 ± 1.11 1.96 (1.07–3.58) 0.03 3.47 ± 1.18 3.25 ± 1.09 1.64 (0.90–3.01) 0.11
FEV1b 2.88 ± 0.96 2.88 ± 0.97 1.30 (0.67–2.52) 0.44 2.98 ± 0.95 2.78 ± 0.94 1.54 (0.77–3.08) 0.22
FEV1/FVCb 86.20 ± 7.09 86.48 ± 7.11 0.97 (0.93–1.02) 0.26 86.47 ± 6.99 86.88 ± 6.24 1.02 (0.97–1.06) 0.52
FEF 25th–75th percentileb 3.20 ± 1.12 3.23 ± 1.12 0.91 (0.64–1.29) 0.60 3.32 ± 1.10 3.07 ± 1.20 1.19 (0.84–1.68) 0.33
Positive methacholine challenge 49.2 (64/130) 52.0 (120/231) 0.90 (0.57–1.40) 0.6308 49.6 (69/139) 53.9 (137/254) 0.84 (0.54–1.31) 0.4445
Abbreviations: CI, confidence interval; BMI, body mass index; FEF, forced expiratory flow; NICU, neonatal intensive care unit; OR, odds ratio.
a High-risk birth is defined as premature birth, hospitalization in an NICU, use of oxygen following birth (not including resuscitation at birth), or use of oxygen at home after leaving the hospital.
b Adjusted for age, height, and sex.
Table 2 Farm exposures and environmental risk factors for living on a farm [% (no./total)].
Variable Born on a farm Not born on a farm OR (95% CI) p-Value Currently lives on a farm Does not currently live on a farm OR (95% CI) p-Value
Born on a farm — — — — 80.3 (171/213) 12.1 (46/381) 29.65 (16.63–52.86) < 0.0001
Lived on farm for at least 3 months before 1 year of age 98.1 (212/216) 4.0 (15/375) 1,272 (342.50–4724.07) < 0.0001 82.1 (174/212) 14.0 (53/379) 28.16 (15.90–49.88) < 0.0001
Lived on farm for at least 3 months before 5 years of age 99.1 (214/216) 11.2 (42/375) 848.36 (203.16–3542.64) < 0.0001 87.7 (186/212) 18.5 (70/379) 31.58 (16.95–58.84) < 0.0001
Farm residence 78.8 (171/217) 11.1 (42/377) 29.65 (16.63–52.86) < 0.0001 — — — —
Parent does farm work 79.3 (172/217) 27.8 (105/377) 9.90 (5.80–16.90) < 0.0001 95.1 (213/224) 20.2 (85/420) 76.32 (27.42–212.41) < 0.0001
Maternal smoking during pregnancy 21.2 (45/212) 29.0 (105/362) 0.66 (0.36–1.20) 0.1467 18.4 (40/218) 31.6 (127/402) 0.49 (0.25–0.93) 0.0161
Current household exposure to tobacco smoke 13.5 (28/208) 26.1 (94/360) 0.44 (0.23–0.83) 0.0057 10.8 (23/214) 30.8 (123/400) 0.27 (0.13–0.54) 0.0001
Ever household exposure to tobacco smoke 20.7 (43/208) 42.3 (153/362) 0.36 (0.21–0.62) 0.0001 13.1 (28/214) 47.5 (191/402) 0.17 (0.09–0.32) < 0.0001
Gas stove in home for cooking 48.7 (95/195) 46.4 (161/347) 1.10 (0.66–1.84) 0.7232 46.8 (95/203) 46.6 (176/378) 1.01 (0.58–1.75) 0.9730
Burn wood for fuel 31.3 (61/195) 20.8 (72/347) 1.74 (0.97–3.11) 0.0728 32.0 (65/203) 20.9 (79/378) 1.78 (0.97–3.28) 0.0680
Current dehumidifier use in home 54.4 (106/195) 30.8 (107/347) 2.67 (1.59–4.49) 0.0003 55.2 (112/203) 29.6 (112/378) 2.92 (1.66–5.15) 0.0002
Parent education (highest years of school)a 14.2 ± 2.1 (n = 215) 13.5 ± 2.0 (n = 377) 1.17 (1.04–1.32) 0.01 14.3 ± 2.0 (n = 222) 13.5 ± 1.9 (n = 412) 1.22 (1.07–1.39) < 0.01
Household income (< $20,000) 2.4 (5/204) 10.6 (38/360) 0.21 (0.04–1.16) 0.0068 2.8 (6/211) 11.3 (45/399) 0.23 (0.05–1.03) 0.0084
Household pets: cats 66.7 (130/195) 49.0 (170/347) 2.08 (1.25–3.48) 0.0045 66.5 (135/203) 49.2 (186/378) 2.05 (1.19–3.54) 0.0092
Household pets: dogs 69.2 (135/195) 64.8 (225/347) 1.22 (0.69–2.16) 0.4869 70.9 (144/203) 65.3 (247/378) 1.29 (0.71–2.37) 0.3898
Applied pesticides in home during past year 57.4 (112/195) 58.2 (202/347) 0.97 (0.58–1.62) 0.9035 58.6 (119/203) 58.7 (222/378) 1.00 (0.57–1.74) 0.9873
Applied pesticides outside home during past year 49.7 (97/195) 33.4 (116/347) 1.97 (1.17–3.33) 0.0130 49.8 (101/203) 33.6 (127/378) 1.96 (1.12–23.43) 0.0220
Raise swine 40.4 (76/188) 3.8 (14/366) 17.06 (7.55–38.58) < 0.0001 52.5 (96/183) 0.0 (0/420) NA < 0.0001
Raise livestock 68.6 (129/188) 7.4 (27/366) 27.45 (14.66–51.40) < 0.0001 89.6 (164/183) 0.0 (0/420) NA < 0.0001
Add antibiotics in feed 27.1 (51/188) 3.6 (13/366) 10.11 (4.24–24.08) < 0.0001 37.7 (69/183) 0.0 (0/420) NA < 0.0001
Abbreviations: CI, confidence interval; NA, not applicable; OR, odds ratio.
a Mean ± SD (no./total).
Table 3 Outcomes and environmental risk factors [% (no./total) or mean ± SD] for doctor-diagnosed asthma and asthma medications for wheeze.
Variable Doctor-diagnosed asthma (n = 72) Nonasthmatic (n = 538) OR (95% CI) p-Value Asthma/medications for wheeze (n = 101) Nonasthmatic (n = 509) OR (95% CI) p-Value
Parent education (highest years of school) 13.2 ± 1.9 (n = 71) 13.9 ± 2.0 (n = 533) 0.90 (0.80–1.02) 0.08 13.5 ± 1.9 (n = 99) 13.9 ± 2.0 (n = 505) 0.86 (0.73–1.02) 0.10
Raise swine 23.6 (17/72) 15.0 (76/507) 1.75 (0.85–3.63) 0.1861 24.0 (24/100) 14.4 (69/479) 1.88 (1.02–3.45) 0.0762
Add antibiotics in feed 15.3 (11/72) 10.8 (55/507) 1.48 (0.68–3.24) 0.3707 19.0 (19/100) 9.8 (47/479) 2.16 (1.15–4.04) 0.0407
Abbreviations: CI, confidence interval; OR, odds ratio. No significant association (p < 0.1) was observed for any asthma outcome for the following variables: farm residence, born on a farm, lived on a farm for at least 3 months while < 1 year of age, lived on farm for at least 3 months while < 5 years of age, parent does farm work, maternal smoking during pregnancy, current household exposure to tobacco smoke, ever household exposure to tobacco smoke, gas stove in home for cooking, burn wood for fuel, current dehumidifier use in home, household income (< $20,000), household pets: cats, household pets: dogs, applied pesticides in home during past year, applied pesticides outside home during past year, or raise livestock.
Table 4 Outcomes and environmental risk factors [% (no./total)] for current wheeze and cough with exercise.
Variable Current wheeze (n = 120) None (n = 490) OR (95% CI) p-Value Cough with exercise (n = 117) None (n = 493) OR (95% CI) p-Value
Burn wood for fuel 21.6 (24/111) 25.8 (117/454) 0.79 (0.46–1.37) 0.3896 16.8 (18/107) 26.9 (123/458) 0.55 (0.31–0.97) 0.0255
Household pets: dogs 67.6 (75/111) 67.6 (307/454) 1.00 (0.62–1.62) 0.9921 76.6 (82/107) 65.5 (300/458) 1.73 (1.01–2.94) 0.0350
Applied pesticides outside home during past year 33.3 (37/111) 41.8 (190/454) 0.69 (0.43–1.11) 0.1255 29.9 (32/107) 42.6 (195/458) 0.58 (0.35–0.96) 0.0282
Raise swine 20.3 (24/118) 15.0 (69/461) 1.45 (0.79–2.65) 0.2636 22.8 (26/114) 14.4 (67/465) 1.76 (0.97–3.19) 0.0970
Add antibiotics in feed 14.4 (17/118) 10.6 (49/461) 1.42 (0.74–2.71) 0.3328 17.5 (20/114) 9.9 (46/465) 1.94 (1.00–3.77) 0.0917
Abbreviations: CI, confidence interval; OR, odds ratio. No significant association (p < 0.1) was observed for any asthma outcome for the following variables: farm residence, born on a farm, lived on farm for at least 3 months while < 1 year of age, lived on farm for at least 3 months while < 5 years of age, parent does farm work, maternal smoking during pregnancy, current household exposure to tobacco smoke, ever household exposure to tobacco smoke, gas stove in home for cooking, current dehumidifier use in home, parent education (highest years of school), household income (< $20,000), household pets: cats, applied pesticides in home during past year, and raise livestock.
Table 5 Doctor-diagnosed asthma and asthma/medication for wheeze, family and personal risk factors, and respiratory symptoms and function [% (no./total) or mean ± SD].
Variable Doctor-diagnosed asthmatic (n = 73) Nonasthmatic (n = 538) OR (95% CI) p-Value Asthma/medication for wheeze (n = 101) Nonasthmatic (n = 509) OR (95% CI) p-Value
Male sex 72.6 (53/73) 51.6 (282/547) 2.49 (1.31–4.72) 0.0021 71.6 (73/102) 50.6 (262/518) 2.46 (1.46–4.13) 0.0003
Age (years) 11.0 ± 4.4 9.3 ± 4.9 1.1 (1.03–1.13) < 0.01 9.5 ± 4.8 9.5 ± 4.9 1.0 (0.96–1.04) 0.96
No. of siblings < 18 years of age 1.5 ± 1.0 1.5 ± 1.1 0.97 (0.75–1.26) 0.81 1.4 ± 1.0 1.5 ± 1.1 0.93 (0.74–1.16) 0.52
Atopy (IgE) 56.7 (17/30) 32.6 (58/178) 2.71 (1.22–6.00) 0.0235 54.3 (19/35) 32.4 (56/173) 2.86 (1.35–6.05) 0.0208
Atopy (SPT) 30.8 (12/39) 16.2 (43/266) 2.30 (1.03–5.18) 0.0824 34.1 (15/44) 15.3 (40/261) 1.61 (0.83–3.15) 0.1671
SPT (mean positive) 1.46 0.98 0.0493 1.45 0.67 0.0286
Atopy (by questionnaire) 43.8 (32/73) 21.6% (118/547) 2.84 (1.43–5.62) 0.0172 41.2 (42/102) 20.8 (108/518) 2.66 (1.49–4.74) 0.0063
Diagnosed allergies 39.7 (29/73) 11.5 (63/547) 5.06 (2.92–8.77) < 0.0001 39.2 (40/102) 10.0 (52/518) 5.78 (3.46–9.66) < 0.0001
Overweight (BMI > 95th percentile) 9.6 (5/52) 6.7 (19/285) 1.49 (0.54–4.14) 0.4927 8.8 (5/57) 6.8 (19/280) 1.32 (0.48–3.66) 0.6183
Low birth weight (< 2,500 g) 6.8 (5/73) 4.1 (22/540) 1.73 (0.60–5.02) 0.3798 4.9 (5/102) 4.3 (22/511) 1.15 (0.40–3.31) 0.8066
Premature birth 20.6 (15/73) 9.5 (52/547) 2.46 (1.21–5.00) 0.0513 21.6 (22/102) 8.7 (45/518) 2.89 (1.60–5.23) 0.0066
NICU admission 19.2 (14/73) 10.6 (58/547) 2.00 (0.98–4.10) 0.1128 18.6 (19/102) 10.2 (53/518) 2.01 (1.07–3.78) 0.0603
High-risk birtha 34.2 (25/73) 18.5 (101/547) 2.30 (1.33–3.97) 0.0145 35.3 (36/102) 17.4 (90/518) 2.59 (1.61–4.19) 0.0011
Early respiratory infection 21.9 (16/73) 10.0 (55/547) 2.51 (1.23–5.14) 0.0463 21.6 (22/102) 9.5 (49/518) 2.63 (1.42–4.88) 0.0124
FVCb 3.45 ± 1.18 3.32 ± 1.13 0.69 (0.27–1.77) 0.44 3.42 ± 1.17 3.31 ± 1.13 0.63 (0.25–1.58) 0.32
FEV1b 2.87 ± 1.00 2.84 ± 0.94 0.43 (0.15–1.27) 0.13 2.84 ± 0.97 2.85 ± 0.95 0.37 (0.13–1.06) 0.07
FEV1/FVC b 83.55 ± 7.29 86.40 ± 6.38 0.95 (0.90–1.01) 0.08 83.40 ± 7.57 86.48 ± 6.27 0.95 (0.90–1.00) 0.07
FEF 25th–75th percentileb 2.99 ± 1.21 3.18 ± 1.15 0.66 (0.39–1.10) 0.11 2.93 ± 1.18 3.19 ± 1.16 0.62 (0.37–1.02) 0.06
Positive methacholine challenge 63.6 (35/55) 51.4 (164/319) 1.65 (0.91–3.02) 0.0960 65.6 (40/61) 50.8 (159/313) 1.84 (1.03–3.30) 0.0343
Abbreviations: BMI, body mass index; CI, confidence interval; FEF, forced expiratory flow; NICU, neonatal intensive care unit; OR, odds ratio.
a High-risk birth is defined as premature birth, hospitalization in an NICU, use of oxygen following birth (not including resuscitation at birth), or use of oxygen at home after leaving the hospital.
b Adjusted for age, height, and sex.
Table 6 Current wheeze and chronic cough, family and personal risk factors, and respiratory symptoms and function [% (no./total) or mean ± SD].
Variable Current wheeze (n = 120) None (n = 490) OR (95% CI) p-Value Cough with exercise (n = 117) No cough (n = 493) OR (95% CI) p-Value
Male sex 56.9 (70/123) 53.3 (265/497) 1.16 (0.77–1.74) 0.4839 66.4 (79/119) 51.1 (256/501) 1.89 (1.22–2.93) 0.0046
Age (years) 8.0 ± 4.9 9.9 ± 4.8 0.93 (0.89–0.97) < 0.01 10.7 ± 4.5 9.2 ± 5.0 1.06 (1.02–1.11) < 0.01
No. of siblings < 18 years of age 1.4 ± 1.0 1.5 ± 1.1 0.89 (0.72–1.11) 0.30 1.4 ± 0.9 1.6 ± 1.1 0.85 (0.69–1.05) 0.13
Atopy (IgE) 45.4 (15/33) 34.3 (60/177) 1.60 (0.80–3.19) 0.2030 35.3 (18/51) 36.3 (57/157) 0.96 (0.48–1.91) 0.9000
Atopy (SPT) 45.4 (20/44) 13.4 (35/261) 5.38 (2.68–10.79) 0.0004 29.7 (19/64) 14.9 (36/241) 2.40 (1.29–4.49) 0.0145
SPT (mean positive) 1.95 0.58 0.0005 1.38 0.62 0.0097
Atopy (by questionnaire) 26.0 (32/123) 23.7 (118/497) 1.13 (0.66–1.95) 0.6676 26.0 (31/119) 23.8 (119/501) 1.13 (0.66–1.94) 0.6593
Diagnosed allergies 30.9 (38/123) 10.9 (54/497) 3.67 (2.25–5.97) < 0.0001 30.2 (36/119) 11.2 (56/501) 3.45 (2.16–5.49) < 0.0001
Overweight (BMI > 95th percentile) 13.0 (7/54) 6.0 (17/283) 2.33 (0.92–5.92) 0.1509 12.0 (9/75) 5.7 (15/262) 2.25 (0.96–5.25) 0.1143
Low birth weight (< 2,500 g) 6.5 (8/123) 3.9 (19/490) 1.72 (0.75–3.95) 0.2752 6.0 (7/117) 4.0 (20/496) 1.51 (0.60–3.85) 0.4182
Premature birth 17.1 (21/123) 9.3 (46/497) 2.02 (1.14–3.59) 0.0399 18.5 (22/119) 8.9 (45/501) 2.30 (1.23–4.31) 0.0243
NICU admission 15.4 (19/123) 10.7 (53/497) 1.53 (0.85–2.76) 0.1892 18.5 (22/119) 9.9 (50/501) 2.05 (1.14–3.67) 0.0395
High-risk birtha 27.6 (34/123) 18.5 (92/497) 1.68 (1.05–2.68) 0.0413 31.9 (38/119) 17.6 (88/501) 2.20 (1.38–3.51) 0.0033
Early respiratory infection 17.9 (22/123) 9.9 (49/497) 1.99 (1.10–3.60) 0.0487 18.5 (22/119) 9.8 (49/501) 2.09 (1.20–3.64) 0.0232
FVCb 3.35 ± 1.10 3.33 ± 1.14 0.94 (0.41–2.15) 0.88 3.47 ± 1.08 3.29 ± 1.15 0.90 (0.46–1.73) 0.74
FEV1b 2.81 ± 0.89 2.85 ± 0.96 0.60 (0.27–1.33) 0.21 2.90 ± 0.89 2.83 ± 0.97 0.57 (0.29–1.14) 0.11
FEV1/FVCb 84.27 ± 6.87 86.26 ± 6.52 0.95 (0.91–1.00) 0.06 83.94 ± 7.02 86.51 ± 6.38 0.95 (0.91–0.99) 0.01
FEF 25th–75th percentileb 2.98 ± 1.13 3.18 ± 1.17 0.69 (0.47–1.02) 0.06 3.05 ± 1.16 3.17 ± 1.17 0.69 (0.49–0.99) 0.04
Positive methacholine challenge 60.7 (34/56) 51.9 (165/318) 1.43 (0.81–2.54) 0.2160 61.0 (50/82) 51.0 (149/292) 1.50 (0.89–2.52) 0.1214
Abbreviations: BMI, body mass index; CI, confidence interval; FEF, forced expiratory flow; NICU, neonatal intensive care unit; OR, odds ratio.
a High-risk birth is defined as premature birth, hospitalization in an NICU, use of oxygen following birth (not including resuscitation at birth), or use of oxygen at home after leaving the hospital.
b Adjusted for age, height, and sex.
Table 7 Multivariable models for asthma outcomes.
Doctor-diagnosed asthma
Asthma/medication for wheeze
Current wheeze
Cough with exercise
Parameter OR (95% CI) p-Value OR (95% CI) p-Value OR (95% CI) p-Value OR (95% CI) p-Value
Male sex 2.62 (1.38–4.95) < 0.01 2.41 (1.38–4.22) < 0.01 — — 1.75 (1.07–2.86) 0.03
Child’s age 1.09 (1.03–1.15) 0.01 — — 0.93 (0.88–.097) < 0.01 1.07 (1.02–1.13) 0.01
Ever been diagnosed with allergies 4.60 (2.56–8.25) < 0.01 5.48 (3.10–9.70) < 0.01 3.88 (2.26–6.66) < 0.01 3.34 (1.97–5.67) < 0.01
Atopy (by questionnaire) 2.58 (1.22–5.45) 0.01 2.40 (1.24–4.65) 0.01 — — — —
Premature birth 2.43 (1.16–5.12) 0.02 — — — — — —
Early respiratory infection — — 1.92 (0.87–4.23) 0.10 1.84 (0.92–3.70) 0.09 1.91 (1.01–3.62) 0.05
High-risk birth — — 2.08 (1.23–3.52) 0.01 — — 2.13 (1.30–3.48) < 0.01
Add antibiotics to feed and raise swine — — 2.47 (1.29–4.74) 0.01 1.91 (0.98–3.73) 0.06 2.72 (1.34–5.52) 0.01
Household pets: dogs — — — — — — 1.73 (0.98–3.06) 0.06
Abbreviations: —, risk factors not selected in the stepwise logistic regression; OR, odds ratio.
==== Refs
References
Anto JM 1998. Methods to assess and quantify BHR (bronchial hyperresponsiveness) in epidemiological studies. Clin Exp Allergy 28(1):13–14, 32–36.
Arbour NC Lorenz E Schutte BC Zabner J Kline JN Jones M 2000 TLR4 mutations are associated with endotoxin hyporesponsiveness in humans Nat Genet 25 2 187 191 10835634
American Thoracic Society 1995 Standardization of spirometry, 1994 Update Am J Respir Crit Care Med 152 3 1107 1136 7663792
Bauer EJ Lurie N Yeh C Grant EN 1999 Screening for asthma in an inner-city elementary school in Minneapolis, Minnesota J Sch Health 69 1 12 16 10098113
Bolte G Bischof W Borte M Lehmann I Wichmann HE Heinrich J 2003 Early endotoxin exposure and atopy development in infants: results of a birth cohort study Clin Exp Allergy 33 6 770 776 12801311
Braun-Fahrlander C Gassner M Grize L Neu U Sennhauser FH Varonier HS 1999 Prevalence of hay fever and allergic sensitization in farmer’s children and their peers living in the same rural community. SCARPOL team. Swiss Study on Childhood Allergy and Respiratory Symptoms with Respect to Air Pollution Clin Exp Allergy 29 1 28 34 10051699
Campagna D Kathman SJ Pierson R Inserra SG Phifer BL Middleton DC 2004 Ambient hydrogen sulfide, total reduced sulfur, and hospital visits for respiratory diseases in northeast Nebraska, 1998–2000 J Expo Anal Environ Epidemiol 14 180 187 15014549
Chrischilles E Ahrens R Kuehl A Kelly K Thorne P Burmeister L 2004 Asthma prevalence and morbidity among rural Iowa schoolchildren J Allergy Clin Immunol 113 66 71 14713909
Contreras JP Ly NP Gold DR He H Wand M Weiss ST 2003 Allergen-induced cytokine production, atopic disease, IgE, and wheeze in children J Allergy Clin Immunol 112 6 1072 1077 14657861
Crapo RO Casaburi R Coates AL Enright PL Hankinson JL Irvin CG 2000 Guidelines for methacholine and exercise challenge testing—1999 Am J Respir Crit Care Med 161 1 309 329 10619836
Douwes J McLean D Slater T Pearce N 2001 Asthma and other respiratory symptoms in New Zealand pine processing sawmill workers Am J Ind Med 39 6 608 615 11385645
Douwes J Thorne PS Pearce N Heederik D 2003. Biological agents—recognition. In: Modern Industrial Hygiene (Perkins J, ed). Vol. 2. Cincinnati, OH:American Conference of Governmental Industrial Hygienists, 219–292.
Downs SH Marks GB Mitakakis TZ Leuppi JD Car NG Peat PK 2001 Having lived on a farm and protection against allergic diseases in Australia Clin Exp Allergy 31 4 570 575 11359424
Ernst P Cormier Y 2000 Relative scarcity of asthma and atopy among rural adolescents raised on a farm Am J Respir Crit Care Med 161 5 1563 1566 10806155
Farooqi IS Hopkin JM 1998 Early childhood infection and atopic disorder Thorax 53 11 927 932 10193389
Gilliland FD Li Y Saxon A Diaz-Sanchez D 2004 Effect of glutathione-S -transferase M1 and P1 genotypes on xenobiotic enhancement of allergic responses: randomised, placebo-controlled crossover study Lancet 363 9403 119 125 14726165
Hamscher G Pawelzick HT Sczesny S Nau H Hartung J 2003 Antibiotics in dust originating from a pig-fattening farm: a new source of health hazard for farmers? Environ Health Perspect 111 1590 1594 14527837
ISAAC Steering Committee 1998 Worldwide variations in the prevalence of asthma symptoms: the International Study of Asthma and Allergies in Childhood (ISAAC) Eur Respir J 12 2 315 335 9727780
Kilpelainen M Terho EO Helenius H Koskenvuo M 2000 Farm environment in childhood prevents the development of allergies Clin Exp Allergy 30 2 201 208 10651772
Leynaert B Neukirch C Jarvis D Chinn S Burney P Neukirch F 2001 Does living on a farm during childhood protect against asthma, allergic rhinitis, and atopy in adulthood? Am J Respir Crit Care Med 164 10 pt 1 1829 1834 11734431
Merchant JA Stromquist AM Kelly KM Zwerling C Reynolds SJ Burmeister LF 2002 Chronic disease and injury in an agricultural county: the Keokuk County Rural Health Cohort Study J Rural Health 18 4 521 535 12380895
Must A Dallal GE Dietz WH 1991 Reference data for obesity: 85th and 95th percentiles of body mass index (wt/ht2) and triceps skinfold thickness Am J Clin Nutr 53 4 839 846 2008861
National Academy of Sciences 2003. Air Emissions from Animal Feeding Operations: Current Knowledge, Future Needs. Washington, DC:National Academies Press.
Niven R 2003 The endotoxin paradigm: a note of caution Clin Exp Allergy 33 3 273 276 12614436
Park H Reynolds SJ Kelly KM Stromquist AM Burmeister LF Zwerling C 2003 Characterization of agricultural tasks performed by youth in the Keokuk County Rural Health Study Appl Occup Environ Hyg 18 6 418 429 12746065
Park JH Gold DR Spiegelman DL Burge HA Milton DK 2001 House dust endotoxin and wheeze in the first year of life Am J Respir Crit Care Med 163 2 322 328 11179100
Peters JM Avol E Navidi W London SJ Gauderman WJ Lurmann F 1999 A study of twelve Southern California communities with differing levels and types of air pollution. I. Prevalence of respiratory morbidity Am J Respir Crit Care Med 159 3 760 767 10051248
Reynolds SJ Donham KJ Stookesberry J Thorne PS Subramanian P Thu K 1997a Air quality assessments in the vicinity of swine production facilities J Agromed 4 37 45
Reynolds SJ Donham KJ Whitten P Merchant JA Burmeister LF Popendorf WJ 1996 Longitudinal evaluation of dose-response relationships for environmental exposures and pulmonary function in swine production workers Am J Ind Med 29 1 33 40 8808040
Reynolds SJ Merchant JA Zwerling C Stromquist AM Burmeister LF 1997b The Keokuk County Rural Health Study: preliminary results of environmental exposure assessments J Agromed 4 1/2 55 62
Riedler J Braun-Fahrlander C Eder W Schreuer M Waser M Maisch S 2001 Exposure to farming in early life and development of asthma and allergy: a cross-sectional survey Lancet 358 9288 1129 1133 11597666
Riedler J Eder W Oberfeld G Schreuer M 2000 Austrian children living on a farm have less hay fever, asthma and allergic sensitization Clin Exp Allergy 30 2 194 200 10651771
Salam MT Li YF Langholz B Gilliland FD 2004 Early-life environmental risk factors for asthma: findings from the Children’s Health Study Environ Health Perspect 112 760 765 15121522
Schenker MB Christiani D Cormier Y Dimich-Ward H Doekes G Dosman J 1998 Respiratory health hazards in agriculture Am J Respir Crit Care Med 158 5 pt 2 S1 S76 9817727
Schwartz DA 2001 Does inhalation of endotoxin cause asthma? Am J Respir Crit Care Med 163 2 305 306 11179094
Schwartz DA Donham KJ Olenchock SA Popendorf WJ Van Fossen DS Burmeister LF 1995 Determinants of longitudinal changes in spirometric function among swine confinement operators and farmers Am J Respir Crit Care Med 151 1 47 53 7812571
Svendsen ER Naleway AL Reynolds SJ Taylor CD Thorne PS Stromquist AM 2003 Exposure to antibiotic feed additives and asthma in U.S. farm children Am J Respir Crit Care Med 167 7 A155
Thu K Donham KJ Ziegenhorm R Reynolds S Thorne PS Subramanian P 1997 A control study of the physical and mental health of residents living near a large-scale swine operation J Agric Safety Health 3 13 26
Von Ehrenstein OS Von Mutius E Illi S Baumann L Bohm O von Kries R 2000 Reduced risk of hay fever and asthma among children of farmers Clin Exp Allergy 30 2 187 193 10651770
Von Mutius E Nicolai T Martinez FD 1993 Prematurity as a risk factor for asthma in preadolescent children J Pediatr 123 223 229 8345417
Wickens K Lane JM Fitzharris P Siebers R Riley G Douwes J 2002 Farm residence and exposures and the risk of allergic diseases in New Zealand children Allergy 57 12 1171 1179 12464046
Wickens K Pearce N Crane J Beasley R 1999 Antibiotic use in early childhood and the development of asthma Clin Exp Allergy 29 6 766 771 10336592
Wing S Wolf S 2000 Intensive livestock operations, health, and quality of life among eastern North Carolina residents Environ Health Perspect 108 233 238 10706529
|
15743727
|
PMC1253764
|
CC0
|
2021-01-04 23:40:58
|
no
|
Environ Health Perspect. 2005 Mar 7; 113(3):350-356
|
utf-8
|
Environ Health Perspect
| 2,004 |
10.1289/ehp.7240
|
oa_comm
|
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.