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+{"metadata":{"id":"0218e311aeb86da4e427f8f1af47c5f9","source":"gardian_index","url":"https://cgspace.cgiar.org/rest/bitstreams/50193398-b9a9-4504-ae4b-3e7a5eca144a/retrieve"},"pageCount":59,"title":"","keywords":[],"chapters":[{"head":"Summary of key findings","index":1,"paragraphs":[{"index":1,"size":10,"text":"The main findings of the study are summarized below: i."},{"index":2,"size":53,"text":"The survey results indicate the Global Acute Malnutrition (GAM) rate (weight for height <-2 Z score or oedema) was 12.5 % [CI: 10. 7 -14.6] and the prevalence of severe acute malnutrition (SAM) in the study sample was 2.2 % [CI: 1.4 -3.4] which slightly exceeded the 2. 0 % WHO cut-off point."},{"index":3,"size":1,"text":"ii."},{"index":4,"size":19,"text":"The overall prevalence of chronic malnutrition (HAZ < -2 SD) among children aged  and the prevalence increased with age."},{"index":5,"size":1,"text":"iii."},{"index":6,"size":15,"text":"The prevalence of wasting stunting and underweight was significantly higher among boys compared to girls."},{"index":7,"size":1,"text":"iv."},{"index":8,"size":11,"text":"The prevalence of underweight was 21.1% [CI: 18.0 - 24.4] v."},{"index":9,"size":19,"text":"There was no significant difference in the general levels of malnutrition between intervention and comparison communities (P > 0.05)."}]},{"head":"vi.","index":2,"paragraphs":[{"index":1,"size":77,"text":"The prevalence of GAM in Wa West and Tolon districts were above the normal 15 % level recommended by the WHO and can be described as critical/ very high. The highest prevalence of chronic malnutrition was in the Tolon and Savelugu Districts located in the Northern Region and the malnutrition situation is serious according to the WHO cut-off for public health significance. The lowest prevalence of chronic malnutrition was in Kassena-Nankana/Bongo District of the Upper East Region."},{"index":2,"size":82,"text":"vii. Consumption of rich protein foods among the children remains poor as most children (90.8 %) were fed on cereal-based foods. However, the consumption of foods known to have a good content of micronutrients and protein was less than satisfactory. For example, less than 10 % of children were fed on vitamin A rich fruits and vegetables. Overall, consumption of flesh meat and eggs was reported in less than 12 %. Legumes consumption was reported in 45.7 % of the households interviewed."},{"index":3,"size":1,"text":"viii."},{"index":4,"size":29,"text":"Generally, the infant and young child feeding (IYCF) practices were sub-optimal and need to be improved. Timely complementary feeding rate was only 41.5 % among children aged 6-8 months."},{"index":5,"size":1,"text":"ix."},{"index":6,"size":34,"text":"Of the 778 children aged 6-23 months; 57.3 % met the minimum meal frequency, 61.8 % received the minimum dietary diversity (≥ 4 food groups), and only 44.1 % had received an acceptable diet."},{"index":7,"size":1,"text":"x."},{"index":8,"size":85,"text":"The most consistent determinants of minimum acceptable diet across all the districts were age of the child, whether or not child was breast feeding and maternal age. Children aged 9-23 months were 4.2 times more likely to meet minimum acceptable diet compared to children aged 6-8 months (AOR = 4.2, 95% CI: 2.5, 6.9, p < 0.001]. The data showed that children not breastfeeding were 7 times more likely [AOR 7.4;, p < 0.001] to meet minimum acceptable diet, compared to children who were breastfeeding."},{"index":9,"size":37,"text":"xi. None of the World Health Organization (WHO) recommended complementary feeding indicators (Minimum meal frequency, minimum dietary diversity, and minimum acceptable diet) was associated with any of child growth indicators among children aged 6-23 months. vii xii."},{"index":10,"size":103,"text":"Multiple logistic regression analysis revealed that children's age, maternal age, gender of child, and geographical location were significantly related to stunting. Compared to the Kasena-Nankana District in the Upper East Region, children in the Tolon District were 3.6 times more likely (AOR= 2.0, CI= 1.59-2.53, p < 0.001) and those in Savelugu were 3.4 times more likely (AOR= 3.57, CI= 2.18-5.84, p < 0.001) of becoming stunted. It was found that children whose mothers were less than 18 years were 5 times more likely [AOR 5.75; 95% CI (1.62-20.42)] of becoming stunted compared to children born to mothers aged more than 35 years."},{"index":11,"size":1,"text":"xiii."},{"index":12,"size":81,"text":"The prevalence of diarrhoea in the two weeks prior to the survey was 33.7 % among children aged 6-36 months. The proportion of mothers who gave ORS/other rehydration therapy if her child had diarrhoea was less than 20 % and the proportion of children with sickness who received less breast milk or solid/semi-solid foods, because the child did not want it was over 60 % in both intervention and comparison communities. This is a dangerous situation and needs to be addressed."}]},{"head":"Conclusion and recommendations","index":3,"paragraphs":[{"index":1,"size":84,"text":"Young children aged less than two years in Northern Ghana are at risk of not meeting the WHO recommended infant feeding standards given that less than 50 % were on minimum acceptable diet. This finding suggests that the majority of children are at risk of under nutrition. It is thus recommended that a massive community-based nutrition education in combination with homebased dietary counselling be launched with a focus on utilizing locally available nutrient dense foods with messages developed that are nutritionally and culturally appropriate. "}]},{"head":"INTRODUCTION","index":4,"paragraphs":[{"index":1,"size":60,"text":"It is well-established that optimal nutrition is critical for human development and economic growth. However, many countries including Ghana continue to face unacceptable high levels of food insecurity and malnutrition (United Nations Standing Committee on Nutrition (UNSCN) 2010) and most of these countries are less likely to meet the Millennium Development Goal of eradicating extreme poverty and hunger by 2015."},{"index":2,"size":123,"text":"Poor quality of complementary foods and suboptimal infant feeding practices are among the major determinants that contribute to the high mortality among infants and young children (Lartey 2008). Food insecurity, poverty and malnutrition continue to be overwhelming in many households especially in Northern Ghana. The estimated prevalence of chronic malnutrition for example, in Upper East Region is 36 % compared with a national average of 28 % (GDHS, 2008). According to the Ghana Demography and Health Survey (GDHS) of 2008, 78 % of children age 6-59 months in Ghana had some level of anaemia and the prevalence was as high as 89 % in the Upper East and Upper West regions (Ghana Statistical Service (GSS), Ghana Health Service (GHS), and ICF Macro 2009)."},{"index":3,"size":83,"text":"The programme area is characterized by high poverty and recurrent droughts and floods which predispose communities to increased vulnerability to food insecurity and malnutrition. For example, seventy percent (70%) of Ghana's poor reside in the three regions of Northern Ghana, namely Northern, Upper East and Upper West Regions (Ghana Statistical Service, 2006). The national average of poverty is estimated as 39 % while in the Northern Region it is 69 %, Upper East Region 88 % and the Upper West Region 84 %."},{"index":4,"size":104,"text":"Effective research capacity is crucial for addressing emerging challenges and designing appropriate mitigation strategies in sub-Saharan Africa (Sawyerr 2004). Despite the clear potential for agricultural change to improve nutrition in low and middle income countries, the evidence base for this relationship is poor. Against this background, the International Institute of Tropical Agriculture (IITA) in collaboration with the Ghana Health Service (GHS) and the University for Development Studies (UDS) has initiated a new project which seeks to identify and promote the consumption of locally available micronutrient-rich foods including vegetables, fruits, and animal-source foods (ASF) to improve dietary diversity and nutritional outcomes of children 6-36 months."},{"index":5,"size":152,"text":"The high economic and social costs associated with malnutrition (general under-nutrition and micronutrient deficiencies) can be avoided if there is concerted and coordinated multi-sectoral approach that should necessarily involve food and agriculture sectors together with complementary interventions such as public health nutrition and education. Efforts at increasing productivity of staple foods especially nutrient-dense foods in a more sustainable production system will ensure the availability of a variety of nutritious foods. Addressing malnutrition requires interventions not only in the food system, but also in the health, sanitation, education and other sectors. By providing clear, accurate information to the population groups, an opportunity is provided for consumers to choose diverse and nutritious foods, thereby ensuring healthier diets that will promote good health and wellbeing. A lot more evidence is needed on how to design, implement, evaluate, and scale up successful, integrated agriculture-nutrition-health program models for improved nutrition outcomes (von Braun, Ruel, and Gillespie 2011)."},{"index":6,"size":114,"text":"The promotion of dietary diversity using locally available nutritious foods is an effective approach to improve the quality of young children's diet and, hence, their growth and development. A key strategy of ensuring diverse diet reaches the target population is to increase consumer demand for nutritional products through behavior change communication. Strategies/Innovations will be driven by action research and evaluation. This will allow for implementation of interventions based on empirical evidence, effective monitoring and evaluation of programmes. There is currently little empirical evidence on how agriculture-nutrition linkages work. One crucial task of this project then, is to document the evidence base on the nutritional impacts emanating from the implementation of planned joint agricultural-nutrition interventions."},{"index":7,"size":33,"text":"The research component of the project is to be managed by the University for Development Studies (UDS) and it aims at providing knowledge and evidence for improved programme implementation, policymaking and investment decisions."}]},{"head":"Research Problem and Justification","index":5,"paragraphs":[{"index":1,"size":15,"text":"The prevalence of food and nutrition insecurity continues to be unacceptably high in Northern Ghana."},{"index":2,"size":63,"text":"Children are often fed on complementary foods consisting mainly of watery cereal porridges made from maize, sorghum or millet. Most of the time, dietary quality and diversity of these foods remain unsatisfactory in households. Any attempt to reverse the high rates of chronic malnutrition in Northern Ghana will have to address the constraints to providing sufficiently nutrient-rich diet needed for rapidly growing children."},{"index":3,"size":73,"text":"For better nutrition and health for the poor, agricultural, nutrition and public health interventions will need to be implemented together. Evidence on the joint effect of such interventions on nutritional status are rare. To fill this knowledge gap, a community intervention trial will be carried out to evaluate the impact of crop diversification, livestock ownership coupled with public health behavior change communication strategies on nutritional status, household food security, and child care practices."},{"index":4,"size":68,"text":"The main aim of the research is to develop, test and evaluate the effectiveness of combining behaviour change communication for complementary feeding developed using \"trials of improved practices\" (TIPs) with nutrition sensitive agriculture interventions oriented toward promoting diverse locally available, nutrient-rich and affordable foods (such as dark green leafy vegetables, orangefleshed vegetables and fruit, nuts and legumes, fruits and small fish and livestock). The specific objectives are to:"},{"index":5,"size":27,"text":"i. Characterize diet of children under three years of age and determine the adequacy of current caregiver feeding practices by comparing them with the ideal practices ii."},{"index":6,"size":13,"text":"Develop acceptable and nutritionally balanced (energy-and nutrient-dense) recipes from locally available foods. iii."},{"index":7,"size":25,"text":"Assess the effect of promoting the utilization of available bio-fortified foods as appropriate complementary foods for children on the nutritional status of children 6-36 months"},{"index":8,"size":11,"text":"The specific research questions to be answered in the study are: "}]},{"head":"Aim and Objectives of the Survey","index":6,"paragraphs":[{"index":1,"size":75,"text":"Prior to the commencement of the project, an inception baseline survey was conducted in November 2013 to assess the level of malnutrition and Infant and Young Child Feeding (IYCF) practices in the beneficiary districts. The overall aim of the survey was to collect information on knowledge and practices related to IYCF practices which will serve as a baseline for future comparison after the implementation of the project. The specific objectives of the survey were to:"},{"index":2,"size":14,"text":"i. Identify baseline indicators for comparison of outcome indicators in follow up surveys. ii."},{"index":3,"size":16,"text":"Estimate the level of acute malnutrition (wasting), stunting and underweight among children aged 6-36 months. iii."},{"index":4,"size":13,"text":"Assess the infant and young child feeding (IYCF) practices in beneficiary communities iv."},{"index":5,"size":12,"text":"Understand the living conditions, socioeconomic indicators and dietary diversity of households v."},{"index":6,"size":13,"text":"Assess the morbidity of under-fives in the two weeks prior to the survey."}]},{"head":"SURVEY METHODOLOGY","index":7,"paragraphs":[]},{"head":"Study Design","index":8,"paragraphs":[{"index":1,"size":16,"text":"A cross-sectional nutrition baseline survey in intervention and comparison communities was carried out in November, 2013."}]},{"head":"Study Population, Sample Size and Sampling","index":9,"paragraphs":[{"index":1,"size":29,"text":"The study population comprised mothers/primary caregivers and children aged 6-35 months, selected using a 25 by 24 two-stage cluster sampling procedure. The primary sampling units (PSUs) will be communities."},{"index":2,"size":173,"text":"The required sample size for this population-based survey was calculated based on the standard formula for one point sample estimation: The primary outcome variable used to estimate the sample size is the population proportion of chronic malnutrition (25.0 %) in the study area (UNICEF, 2013). A sample size of 288 is required to ensure that the estimated prevalence of the main outcome variable was within plus or minus 5 % of the true prevalence at 95% confidence level. Assuming a correction factor of 2 (the \"design effect\") for cluster sampling the sample size was increased to 576. A non response rate of 5 % and other unexpected events (e.g. damaged/incomplete questionnaire) was factored in the sample size determination and so the sample size is adjusted to 600. To determine the number of observations per cluster, the sample size was divided by the 25 programme communities (clusters) to be surveyed. This yielded a sample size of 24 per cluster. The same number of comparison communities was selected from each of the five programme district."},{"index":3,"size":26,"text":"Details of the 50 clusters are shown in Appendix A. Probability proportionate to size (PPS) was used to select the comparison clusters from the programme districts."},{"index":4,"size":50,"text":"In each cluster, a complete list of all households was compiled and systematic random sampling used in selecting study households. All the households in each cluster were serially numbered. To get the sampling interval, the total number of households in a cluster was divided by the sample size of 24."},{"index":5,"size":104,"text":"The first household was then randomly selected by picking any number within the sample interval. Subsequent selections were made by adding the sampling interval to the selected number in order to locate the next household to visit. If the selected household does not have a target respondent, then next household was selected using the systematic sampling procedure. This process continued until the required sample size was obtained. A minimum of 24 mother/child pairs were randomly selected from a cluster giving a total of 600 respondents per study arm. Only one eligible participant was selected from each household for household interview, using simple random sampling."}]},{"head":"Procedure for selecting individual survey subjects","index":10,"paragraphs":[{"index":1,"size":58,"text":"Women of reproductive age and their children under 36 months old in the sampled households were included in the study (that is, eligible for interview). Only one eligible mother was randomly selected for interview in any particular sampled household. If more than one eligible woman was available within one household, the mother of the youngest child was interviewed."}]},{"head":"Main Outcome Measures","index":11,"paragraphs":[{"index":1,"size":23,"text":"The key outcome indicators included the nutritional status of children, minimum dietary diversity, minimum meal frequency, complementary feeding rate, initiation of breastfeeding rate"}]},{"head":"Data Collection Methods","index":12,"paragraphs":[{"index":1,"size":69,"text":"Face-to-face interviews were conducted using pre-tested and validated structured questionnaires to collect representative data of socio-demographic characteristics, infant feeding practices & nutritional status. Additionally qualitative data using focus group discussions (FGD's) was collected to complement the quantitative data. During FGD's, information was collected on locally available and affordable nutritious foods (e.g. bio-fortified foods). The barriers that mothers faced toward feeding their children with nutritious food were also be discussed."}]},{"head":"Nutritional Status Assessment","index":13,"paragraphs":[{"index":1,"size":8,"text":"The details of anthropometric measurement are described below:"},{"index":2,"size":25,"text":"Age: The exact age of the child was recorded in months, based on information contained in child health records booklets, birth certificates and baptismal cards."},{"index":3,"size":57,"text":"Weight: The weight of children was assessed with Seca Electronic UNISCALE (SECA 890). The batteries were replaced after every cluster (minimum of 80 readings). This was done to ensure weak batteries do not affect the readings on the scales. All children in the selected households aged 6 to 36 months were weighed to the nearest 0.1 kg."}]},{"head":"Height:","index":14,"paragraphs":[{"index":1,"size":141,"text":"The term length is used for children who cannot walk yet. Their height is measured lying down. One generally refers to stature from when children can and will stand alone, i.e. around 2 years of age onward. The length of children less than two years of age (i.e. up to and including 23 months) was thus measured in a lying position. A specialized wooden device (that is, an infantometer) was used. The child was placed on its back between the slanting sides. The head was placed so that it is against the top end. The knees were gently pushed down by a helper. The foot-piece is then moved toward the child until it presses softly against the soles of the child's feet and the feet are at right angles to the legs. The length/height was measured to the nearest 0.1 cm."},{"index":2,"size":76,"text":"For children aged 24-59 months and adults, stature was measured in a standing position. The child stood without shoes on a level floor. The legs were placed against each other, as also were the heels. The buttocks, shoulder blades and head rested against the measuring board. The child looked straight ahead so that an imaginary plane that would connect the eyes and ears were parallel to the floor and the arms hanged loosely by the sides."},{"index":3,"size":40,"text":"Body Mass Index (BMI): is a simple index of weight-to-height commonly used to classify underweight, overweight and obesity in adults. It is defined as the weight in kilograms divided by the square of the height in metres (kg/m 2 )."},{"index":4,"size":67,"text":"Mid Upper Arm Circumference (MUAC): MUAC was measured in centimeters, to the nearest 0.1cm, using standard MUAC measuring tapes. The data collectors were trained to locate the mid-point between the shoulder and the tip of the elbow on the left arm with the arm bent at a right angle and to note the mid-point. The measurement was taken at this mid-point with the arm extended and relaxed."},{"index":5,"size":39,"text":"Bilateral Edema: This was diagnosed by placing both thumbs on the upper side of the feet and applying pressure for about three seconds. Oedema was considered to be present if a skin depression remained after the pressure was released."}]},{"head":"Assessment of Infant and Young Child Feeding (IYCF) Practices","index":15,"paragraphs":[{"index":1,"size":117,"text":"Infant and young child feeding indicators including minimum meal frequency, minimum dietary diversity and minimum acceptable diet were estimated by recall of food and liquid consumption during the previous day of the survey using a semi-quantitative food frequency dietary diversity questionnaire (FFQ) developed and validated by the FAO (Barker 2001;FAO 2011). The dietary diversity score ranged from 0-16 with minimum of 0 if none of the food groups was consumed to 16 if all the food groups were consumed. From the dietary diversity score, the minimum dietary diversity indicator was constructed using the WHO recommended cut-off point with a value of \"1\" if the child had consumed four or more groups of foods and \"0\" if less."},{"index":2,"size":61,"text":"Minimum meal frequency is the proportion of children who received complementary foods the minimum recommended number of times in the past 24-hours. For breastfed children, the frequency should be at least 2 times for 6-8 months, and at least 3 times for 9 -23 months of age. For nonbreastfed children, it should be at least 4 times in last 24 hours."},{"index":3,"size":72,"text":"Minimum dietary diversity is the proportion of children who ate at least four or more varieties of foods from the seven food groups in a 24 hour time period. Minimum acceptable diet is a composite indicator of minimum dietary diversity and minimum meal frequency. When a currently breastfed child meets both the minimum diversity and the minimum meal frequency, the child is considered to have met the WHO recommended minimum acceptable diet."}]},{"head":"Data Quality Control Measures","index":16,"paragraphs":[{"index":1,"size":97,"text":"In an effort to collect quality data, a number of strategies were applied. A two-day training training session aimed at ensuring the reliability and validity of data collected was organized for data collectors. The training ensured a good understanding and acquisition of skills for effective and efficient administration of the data collection tools. The content of the training included the aim of study, survey methodology including selection of eligible participants, data recording, administration of questionnaires and supervision. In addition, the training also focused on the art of interviewing and clarifying questions that were unclear to the respondents."},{"index":2,"size":52,"text":"The final stage in the training of data collectors involved field-testing of data collection tools. The main aim here was to refine the tools and to ensure the competence of the data collectors. The Focus Group Discussion (FGD) guide and household questionnaires were pre-tested and revised before the main field work commenced."},{"index":3,"size":97,"text":"In each team, there was a supervisor who ensured that all the methodological issues were being adhered to. Furthermore, field supervisors checked all data collected in a given day and made sure that all field challenges are attended to immediately in the field. Any errors noted were discussed with the concerned enumerators. Briefing meetings took place every day where teams shared their experiences in the field and necessary corrections and recommendations made to ensure smooth implementation of the survey. In addition, the Principal Investigator visited teams in the communities at random to observe how interviews were conducted."}]},{"head":"Data Management and analyses plan","index":17,"paragraphs":[{"index":1,"size":68,"text":"Data analyses were performed using procedures in SPSS complex samples module, version 18.0 for Windows. Design weights were added to each district (that is, total population divided by number of respondents) to perform weighted analysis. This module of SPSS takes into account the complex nature of the cluster sample design. This was done in order to make statistically valid population inferences and computed standard errors from sample data."},{"index":2,"size":138,"text":"The ENA software (2013 Version) was used in the analysis of anthropometric data and to check the plausibility of the data. Anthropometric measurements such as height, weight and age of children were converted into Z-scores using the 2006 WHO reference growth curves. The Z-scores were then transported to SPSS for further analyses. Before performing the anthropometric calculations for weight-for-height (WH), height-for-age (HA) and weight-for-age (WA), the data was cleaned and outliers removed. Exclusion of z-scores which were outside the WHO flags: WHZ -5 to 5; HAZ -6 to 6; WAZ -6 to 5 were excluded from the data set. In all, 5 (0.4 %) of the WAZ scores, and 12 (1.0 %) each of WHZ/HAZ outliers were removed from that data set. The SMART methodology recommends that the percentage of outliers should not exceed 2% of the sample."},{"index":3,"size":69,"text":"Children from project and non-project households were compared on descriptive statistics using Chisquare test (χ 2 ) for proportions, independent sample t-test for means. Both bivariate and multivariate analyses were performed to identify predictors of feeding practices and nutritional status of children whilst controlling for potential confounding variables. The stepwise backward elimination procedure was used in the multiple logistic regression. All associations will be considered statistically significant at p<0.05."}]},{"head":"Cut -off Points used to define Acute and Chronic Malnutrition among children","index":18,"paragraphs":[{"index":1,"size":24,"text":"Different threshold exist to interpret the public health significance of the main nutritional indicators. The thresholds currently in use are shown in Table 2.1. "}]},{"head":"Ethics and informed consent","index":19,"paragraphs":[{"index":1,"size":63,"text":"Informed verbal consent was sought through communication with community representatives and on individual household level, with accompanying clarification on purpose and nature of the study. There was also briefing of households selected for questionnaire administration, weight and height measurement. All records collected during the survey were considered as confidential and stored with the name of the respondent and community to identify the data."}]},{"head":"RESULTS","index":20,"paragraphs":[]},{"head":"Study sample characteristics","index":21,"paragraphs":[{"index":1,"size":73,"text":"A total of 1200 mothers/caretakers were interviewed at the household level; 600 each from intervention and comparison communities. There were missing values on a number of variables for two respondents. This gave a response rate of 99.8 %. The mean age of the respondents was 29.2±6.7 years with the minimum and maximum ages of 15 and 60 years respectively and majority of them (81.8 %) were in the age group of 18-35 years."},{"index":2,"size":62,"text":"The mean number of children under five years of age living a household was 2.0± 1.3 with a range of 1-10. Majority 70.4 % (843) of the respondents were Dagomba and Dagao by ethnicity and most of them 70.5 % (845) had no formal education at all. Table 3.1a displays a comparison of the sociodemographic characteristics in the intervention and comparison communities."},{"index":3,"size":24,"text":"The age group composition and sex distribution of children in the study samples were not significantly different, indicating a well balanced situation (Table 3.1b).   "}]},{"head":"Household decision making and care of the child","index":22,"paragraphs":[{"index":1,"size":40,"text":"In most households 49.7 (595), the husband or other man in the household usually makes decisions about purchasing food or taking child for health services. Grandmothers and siblings take care of children when mother is not at home (Table 3.2). "}]},{"head":"Utilization of Maternal Care Services","index":23,"paragraphs":[{"index":1,"size":120,"text":"Of the women interviewed, 99.2 % (1176/1186) had attended antenatal clinic (ANC) at least once during the last pregnancy. For those who attended, the minimum number of antenatal care (ANC) visits was 1 whilst the maximum number was 14. Majority of the ANC attendees 85.0 % (8008/1186) made at least four prenatal visits during the last pregnancy as recommended by the World Health Organization. Table 3.3 shows the frequency of ANC attendance and place of delivery. A significant number of women 45.0 % (536/1191) delivered at home. At baseline, there was a significant difference in the uptake of ANC services between the study groups but there was no significant difference in institutional delivery services between the programme and non-programme communities. "}]},{"head":"Household Food Production and Access","index":24,"paragraphs":[{"index":1,"size":75,"text":"The primary source of obtaining food for 92.5 % of households was their own production (e.g. farming). Less than 1 % (0.3) of the households did not grow any kind of crops. Most households (98.0 %) reported cultivating grains, roots, tubers but less than 5 % in both intervention and comparison communities grow orange or yellow fruits and vegetables. The cultivation of leafy green vegetables was reported in only 30 % of households (Table 3.4a)."},{"index":2,"size":128,"text":"With respect to household livestock and poultry keeping, 4.9 % of the sampled households did not keep any animal or bird. Table 3.4b shows the types of animals and poultry owned by households. Whereas, over 80 % of households keep chickens, ducks, or other birds; for the meat/sale, only 23.0 % do so for their eggs in the comparison communities and 33.0 % in the intervention communities. In both the intervention and comparison communities, cows, goats, sheep, or dogs are kept mainly for sale but 56.4 % of households reported keeping these animals for the sake of meat in the intervention communities. Keeping rabbits, guinea pigs, or other small mammals was practiced by less than 5 % of households. Fish farming was rarely practiced in the study population. "}]},{"head":"Plausibility Checks for Anthropometric Data","index":25,"paragraphs":[{"index":1,"size":128,"text":"Data quality was validated using the plausibility check function of the SMART for Emergency Nutrition Assessment (ENA) software. The overall scoring of the plausibility check of the follow-up survey data was 10 % and this is acceptable. The validity (plausibility) checks showed for example that the values for standard deviation (SD) of the z-scores for Weight for Height Z-score (WHZ) was 0.99, Height for Age Z-score (HAZ) was 1.06 and weight for age Z-score (WAZ) was 0.98, all within acceptable limits (that is less than 1.2) as shown in Appendix E. The SD of WHZ should not exceed 1.2 in a good survey. The weight, height and MUAC measurements were without digit preference. All these suggest that the data have been well taken and were of good quality."}]},{"head":"Nutritional Status of Children 6-36 Months","index":26,"paragraphs":[{"index":1,"size":24,"text":"Anthropometric indicators of Height-for-age (HAZ), weight-for-age (WAZ), weight-for-height (WHZ) and MUAC z-scores (MUACZ) were determined as recommended by the World Health Organization (WHO, 2006)."},{"index":2,"size":80,"text":"Malnutrition is generally classified into acute malnutrition (wasting) or chronic malnutrition (stunting). Stunting (HAZ < -2 SD) is generally the result of inadequate nutrition and/or infectious diseases over prolong period of time which results in depletion of critical nutrients. It can be seen as a failure to grow adequately in height or length. Wasting (WHZ < -2 SD) which reflects more recent undernutrition or illness manifests in failure to gain sufficient weight relative to height or length, or weight loss."},{"index":3,"size":17,"text":"Tables 3.5 shows the prevalence of acute, chronic and underweight malnutrition among index children aged 6-36 months.  "}]},{"head":"Prevalence of Malnutrition by Sex","index":27,"paragraphs":[{"index":1,"size":17,"text":"The prevalence of wasting stunting and underweight was significantly higher among boys compared to girls (Table 3.8). "}]},{"head":"Prevalence of Child Malnutrition by Age Categories","index":28,"paragraphs":[{"index":1,"size":51,"text":"The proportion of children suffering from acute, chronic malnutrition and underweight vary according to age group (Table 3.9). The GAM levels were highest and critical in the age group 9-23 months. For chronic under-nutrition, the highest levels were found among children aged 24-36 months. ) = 14.9 , p = 0.003"}]},{"head":"Distribution of Mean Z-scores and Design Effect","index":29,"paragraphs":[{"index":1,"size":76,"text":"Table 3.10 shows the weighted mean z-scores of the anthropometric indices used in the study and the design effects. The mean height-for-age and weight-for-age z-scores at baseline indicate that the distribution of these anthropometric indicators in the study sample was shifted significantly below zero, the expected value of the WHO 2006 reference distribution. There was an overall shift to the left of the study population when compared with the reference population, implied the presence of malnutrition."},{"index":2,"size":220,"text":"The design effect (DEFF) is the ratio of the true variance of a statistic when cluster sampling is used to the variance of the statistic for a simple random sample with the same number of cases. A design effect of 1.0 therefore means the sampling design is equivalent to simple random sampling. A design effect greater than 1.0 means the sampling design reduces precision of estimate compared to simple random sampling (e.g. cluster sampling reduces precision). A design effect less than 1.0 means the sampling design increases precision compared to simple random sampling (stratified sampling, for instance, increases precision). The distribution of the z-scores according to age, sex and cluster (combined) were compared to the WHO 2006 child growth standards (Figs. 3.1 to 3.3). All the z-scores distribution curves of the sample population for the main indicators were skewed towards the left as compared to the WHO standards. This implies that the prevalence of wasting, stunting and the underweight was higher in our survey population than in the WHO reference population. Majority of the newborns 91.9 % (1099) were given first yellowish milk (colostrum) as the first feed after delivery, though some mothers 8.1 % (97) practice prelacteal feeding. Table 3.11 shows the types of prelacteal feeds given to children. Plain water was the most cited prelacteal given to children. "}]},{"head":"Food Consumption","index":30,"paragraphs":[{"index":1,"size":121,"text":"Table 3.12 shows the types of food that were fed to children in the past 24 hours prior to the study. Most children (90.8 %) were fed on cereal-based foods. However, the consumption of foods known to have a good content of micronutrients and protein was less than satisfactory. For example, less than 10 % of children were fed on vitamin A rich fruits and vegetables. Consumption of flesh meat and eggs was reported in less than 12 %. Legumes consumption was reported in 45.7 % of the households interviewed. Continued breastfeeding rate at one year (that is, among children 12-15 months) was 99.3 % but it slightly reduced to 93.3 % by year two (that is, among children 20-23 months)."},{"index":2,"size":163,"text":"Timely initiation of breastfeeding (TIBF) rate (that is, proportion of children born in the last 24 months who were put to the breast within one hour of birth) was 46.6 %. Timely complementary feeding rate was 41.5 % among children aged 6-8 months. The proportion of children 6-23 months who met the minimum dietary diversity (≥ 4 food groups) was 61.8 %. Though a significant proportion of the children met the dietary diversity requirement, only 57.3 % met the minimum meal frequency, resulting in less than 50.0 % (44.1 %) of the children aged 6-23 months meeting the minimum acceptable diet. The proportion of children 6-23 months of age who receive an iron-rich food or ironfortified food in the past 24 hours prior to the study was less than 10 %. Table 3.13 shows weighted comparison of the core IYCF indicators in the intervention and comparison communities. There was no significant difference between the study groups with respect to the core IYCF indicators.  "}]},{"head":"Determinants of Minimum Acceptable Diet","index":31,"paragraphs":[{"index":1,"size":38,"text":"Knowledge on the predictors of appropriate complementary feeding practices or the risk factors is necessary to develop policies and programmes to improve the situation. Factors associated with minimum acceptable diet were assessed using both bivariate and multivariate analyses."},{"index":2,"size":62,"text":"Table 3.15a shows bivariate analyses of the predictors of minimum acceptable diet. The most consistent determinants of minimum acceptable diet across all the districts were age of the child, whether or not child was breast feeding and maternal age. Children of elderly mothers (35 + ) were more likely to meet the acceptable diet, compared to young mothers (less than 18 years)."},{"index":3,"size":117,"text":"The proportion of children aged 6 -8 months who received minimum acceptable diet was significantly lower than that of children aged 9 -23 months. This trend is similar for minimum meal frequency and minimum dietary diversity, suggesting younger children (6-8 months) were the most vulnerable for not meeting these recommended infant feeding practices. Children who were currently breast feeding at the time of the study were less likely of not meeting a diversified diet compared to their non-breast feeding counterparts.  (1.7-33.1), p < 0.001] to meet minimum acceptable diet, compared to children who were breastfeeding. Women who delivered in health facilities were more likely to feed their children acceptable diets compared to women who delivered at home. "}]},{"head":"Determinants of Undernutrition among Children aged 6-36 months","index":32,"paragraphs":[{"index":1,"size":41,"text":"Table 3.16a shows bivariate analyses of predictors of chronic malnutrition among children aged 6-36 months. Chronic malnutrition (stunting) was most prevalent in the Northern Region especially among children aged 24-36 months. The prevalence of stunting was significantly higher among male children."},{"index":2,"size":77,"text":"Complementary feeding indicators were also assessed as predictors of nutritional adequacy in the programme communities. Surprisingly, none of the World Health Organization (WHO) recommended complementary feeding indicators (Minimum meal frequency, minimum dietary diversity, and minimum acceptable diet) was associated with any of child growth indicators among children aged 6-23 months. However, among children aged 6-36 months, bivariate analyses showed that minimum dietary diversity was associated with chronic under nutrition (Table 3.16a). * 95 % confidence level (CI)"}]},{"head":"Multivariate analyses","index":33,"paragraphs":[{"index":1,"size":68,"text":"Multivariate analysis revealed that children's breast feeding status and gender of child were significant predictors of wasting (acute malnutrition) (Table 3.17b). Risk of wasting was 4.8 times among children were breast feeding compared, to children who were not breast feeding (AOR= 4.78, CI: 2.50-9.14, p < 0.001). Male children were 1.4 times more likely of becoming wasted, compared to female children (AOR= 1.37, CI: 1.04-1.79, p = 0.024). "}]},{"head":"10 Childhood Morbidity and Vitamin A supplementation","index":34,"paragraphs":[{"index":1,"size":104,"text":"Table 3.18 shows access to growth monitoring services and vitamin A supplementation. The proportion of children aged 6-36 months who received a dose of vitamin A in the last six months prior to the study was 93.1 % in the intervention communities. Most families went to public health facility to seek health care assistance when child was sick. The proportion of children aged 6-36 months who received a dose of vitamin A in the last six months prior to the study was 93.1 % in the intervention communities. Most families went to public health facility to seek health care assistance when child was sick."}]},{"head":"Prevalence and Management of Childhood Diarrhoea","index":35,"paragraphs":[{"index":1,"size":90,"text":"Table 3.19 shows the incidence and management practices of diarrhoea. The incidence of diarrhoea in the two weeks prior to the survey was above 30 % in both intervention and comparison communities. The proportion of mothers who gave ORS/other rehydration therapy if her child had diarrhoea was less than 20 %. The proportion of children with sickness who received less breast milk or solid/semisolid foods, because the child did not want it was over 60 % in both intervention and comparison communities and needs to be addressed  DISCUSSION OF RESULTS"}]},{"head":"Nutritional Status of Children","index":36,"paragraphs":[{"index":1,"size":117,"text":"The results of the nutrition survey indicate there was no significant difference in child growth indicators between intervention and comparison communities. Global acute malnutrition (GAM) levels were below WHO emergency threshold of 15 %. According to the WHO classification system, a prevalence between 5 and 9 % is considered poor (World Health Organization (WHO) 1996). According to the findings of the survey, the prevalence of global stunting was medium in terms of public health significance. The findings of this study are consistent with results of a recent Multi Cluster Indicator Survey (MICS) of 2011 conducted in the three regions of Northern Ghana, in which prevalence of chronic malnutrition was in the range of 23.1-37.4 % (UNICEF 2011)."},{"index":2,"size":145,"text":"The predominance of stunting in older children indicates failure in growth and development during the first two years of life. The findings of the study suggest that tackling childhood stunting through preventive activities targeting the period of pregnancy and the first two years of life should be a high priority. A chronic situation of hunger (due to food availability and/or food access problems) has long been identified as the major cause of stunting. However, more and more evidence now suggests that chronic malnutrition continues to exist even in food-secure households or with supplementary feeding programmes (Das Gupta et al. 2005), suggesting that food utilization and other child care factors play a significant role in children's nutritional status. The high prevalence of chronic malnutrition in the survey area therefore points to the fact that non-food aspects of food security need to be addressed alongside food-based interventions."}]},{"head":"Factors Contributing to Poor Nutritional Status of Children","index":37,"paragraphs":[{"index":1,"size":82,"text":"The findings of this study indicated that the risk of stunting increases with age, consistent with other studies (Apkota and Gurung 2009;Sah 2004). Children in the youngest age group 6-11 months had a significantly lower risk of stunting than children in the older age groups. It is likely that breast feeding during early life is protective and that stunting becomes more likely as the child becomes more dependent on foods that are of poor quality and exposure to non-food factors including infections."},{"index":2,"size":40,"text":"The fact that the highest prevalence of stunting was seen in children aged 24 -36 months suggest poor nutrition in utero and feeding practices in earlier stages of life may play a significant role in the aetiology of chronic malnutrition."},{"index":3,"size":91,"text":"The provision of adequate, safe and acceptable complementary food is essential in order to reduce child under nutrition. It is for this reason, WHO and UNICEF have recommended eight core infant feeding practices to be adopted (World Health Organization 2007). To better promote these recommended practices, it is essential to demonstrate the evidence on the existing proportion of mothers who are adopting these dietary practices and the effect they have on growth. Findings from this survey showed the proportion of children aged 6-23 months receiving the recommended diets was below expectations."},{"index":4,"size":82,"text":"Poor complementary feeding practices contribute to inadequate energy and protein intake (Fikree et al. 2005). The analysis of data collected on feeding practices point to poor diet quality in the programme communities. The survey findings showed that all children in the 6-23 month group were unlikely of meeting the recommended feeding practices but the 6-8 months aged children, were the most vulnerable. Therefore, the impact of inadequate feeding practices in the younger children will have a cumulative effect as the child grows."},{"index":5,"size":58,"text":"Interestingly, none of the World Health Organization (WHO) recommended complementary feeding indicators (Minimum meal frequency, minimum dietary diversity, and minimum acceptable diet) were associated with child growth indicators among children aged 6-23 months. The apparent lack of association may be due to the fact there was very little variation in the study population with respect to these indicators."},{"index":6,"size":68,"text":"In bivariate analyses, it was only minimum dietary diversity that associated negatively with acute under-nutrition among children aged 24-36 months but that association was not maintained in multivariable analyses. The lack of association may be explained partly by the fact that the feeding indicators may not be sensitive to chronic under-nutrition because they are assessed based on 24 hour recall which may not give the usual dietary intake."},{"index":7,"size":142,"text":"Factors other than the World Health Organization (WHO) recommended complementary feeding indicators were associated with child growth indicators among children aged 6-23 months. For example, gender of child, age of the child, maternal age, district of residence and whether or not the child was breast feeding were significantly related to stunting in the study sample. Other factors that were associated with stunting in bivariate analysis but failed to reach significance level in multivariable regression analyses included household rears chickens, ducks, or other birds for the eggs mothers' educational level, the number of children less than 59 months living in the household . Improving the nutritional knowledge of the mother on key nutrition issues may contribute to the reduction of chronic under-nutrition. The results showed that mothers were not adequately informed in some basic nutrition issues that are potential determinants of child growth."},{"index":8,"size":110,"text":"Findings about the relationship between feeding practices and growth have been mixed. A survey conducted in Mexico found that measures of recommended breastfeeding and complementary feeding practices were not associated with growth when family economics and other factors were included in logistic regression models (Gonzalez-Cossio et al. 2006). In seven Latin American countries, it was reported that recommended child feeding practices were positively associated with height-forage with a stronger effect for children of lower socio-economic status (Ruel and Menon 2002). Dietary diversity among 6-23-month-old children was found to be positively associated with height-for-age in seven of 11 countries when other variables were included in the models (Arimond and Ruel 2004)."},{"index":9,"size":118,"text":"Under-nutrition and childhood morbidity have a synergistic relationship. The two conditions act in such a way that illness can suppress appetite precipitating under nutrition of a child while, on the other hand, nutritional deficiencies increase the susceptibility of the child to infectious diseases (Yadav 2007). Children who suffer frequent bouts of disease (such as tuberculosis, malaria and diarrhoea) are more prone to malnutrition. The prevalence of illness with a cough that comes from the chest among children in the programme communities was quite high and was contributing to acute malnutrition. Generally, improving dietary intake to recommended levels together with the elimination of diarrhoea and febrile illness at the same time would be necessary to achieve optimal child growth."},{"index":10,"size":61,"text":"Other important factors likely to be associated with the prevalence of malnutrition in the programme communities may include foetal growth restriction leading to low birth weight, maternal nutritional status at conception and during pregnancy, environmental hygiene and inadequate caring practices. Acute malnutrition in particular, is caused by a decrease in food consumption and/or illness resulting in sudden weight loss or oedema."}]},{"head":"Infant and Young Child Feeding (IYCF) practices","index":38,"paragraphs":[{"index":1,"size":71,"text":"Information on IYCF was collected in every household that had a child less than 24 months of age. Most of the IYCF practices were sub-optimal and need to be improved. For example, in 41.5 % of cases, mothers introduced complementary food at 6 months of age. Going by WHO criteria, it is a serious situation if the proportion of introducing complementary food at 6 months is in the range of 60-79%."},{"index":2,"size":114,"text":"Inadequate dietary intake due to lack of food variety as most children were fed on monotonous cereal-based diets with very low foods rich in proteins such as milk, eggs or meat being consumed. Consumption of rich protein foods among the children remains poor as most children (90.8 %) were fed on cereal-based foods. However, the consumption of foods known to have a good content of micronutrients and protein was less than satisfactory. For example, less than 10 % of children were fed on vitamin A rich fruits and vegetables. Overall, consumption of flesh meat and eggs was reported in less than 12 %. Legumes consumption was reported in 45.7 % of the households interviewed."},{"index":3,"size":88,"text":"The proportion of children 6-23 months who met the minimum dietary diversity (≥ 4 food groups) was 61.8 %. Though a significant proportion of the children met the dietary diversity requirement, only 57.3 % met the minimum meal frequency, resulting in less than 50.0 % (44.1 %) of the children aged 6-23 months meeting the minimum acceptable diet. The proportion of children 6-23 months of age who receive an iron-rich food or iron-fortified food in the past 24 hours prior to the study was less than 10 %."},{"index":4,"size":80,"text":"The rate of minimum dietary diversity, minimum meal frequency and minimal acceptable diet for the breastfed were less than satisfactory especially in the Northern Region. The recommended dietary diversity for young children 6 to 23.9 months old is a minimum of four different food groups daily. Dietary diversity at the individual level is measure of quality of the diet. The more diversified a child's diet is, the larger the variety of nutrients he/she receives which enhance his/her health and nutrition."},{"index":5,"size":36,"text":"The number of different food groups consumed therefore better reflects a quality diet. Children who consume, for example, an average of four different food groups implies that their diets offer some diversity in both macro-and micronutrients."},{"index":6,"size":68,"text":"An acceptable diet for children 6-23 months consists of a child being fed at least three times a day and receiving four of the food groups. In all districts it was identified that a large percentage of children were not receiving what is considered to be an acceptable diet for this age group. Unacceptable child feeding practices add to increased rates of malnutrition both acute and chronic malnutrition."},{"index":7,"size":18,"text":"A lot more needs to be done to improve the diet quality of children in the programme communities."},{"index":8,"size":178,"text":"To address the issue of low dietary diversity, health and nutrition education and behavior change communication need to be strengthened and focused on improving child feeding practices with foods rich in macro and micro nutrients. It is also important to build a synergy between the agriculture and health activities in the program district so that families can gain access to more diverse array of foods especially animal-based foods. In promoting food diversity, change agents in the field should develop a list of locally available foods, their corresponding food group, and seasonal availability in order to better focus the health and agriculture messages related to dietary diversity. Another important step towards having more diversified meals is to improve the livelihood of families through sustainable income generating activities. Along with this is the need to address household behavior in respect of food purchasing choices once household income starts to increase. It will be important to promote families spending more on priority foods including fruits and vegetables and flesh foods such as meat from animals and poultry if income levels increase."}]},{"head":"Prevalence and Management of Childhood Diarrhoea","index":39,"paragraphs":[{"index":1,"size":212,"text":"The prevalence of diarrhoea in the two weeks prior to the survey was 33.7 % among children aged 6-36 months. The proportion of mothers who gave ORS/other rehydration therapy if her child had diarrhoea was less than 20 % and the proportion of children with sickness who received less breast milk or solid/semi-solid foods, because the child did not want it was over 60 % in both intervention and comparison communities. This is a dangerous situation and needs to be addressed. Diarrhoea can cause the growth of a child to falter, due to the child's impaired ability to absorb and utilize nutrients. This makes it very important that mothers are able to manage diarrhoea effectively, especially feeding appropriately during diarrhoea. The recommended treatment for diarrhoea involves three aspects namely: providing ORS for the child during diarrhoea, providing increased fluids to the child during diarrhoea and providing the same or more quantity of food to the child during diarrhoea. Making easy access to ORS and Zinc tablets in line with current protocols will further facilitate in the effective management of diarrhoea. Results of an earlier study of infants aged 6-12 months showed that children who were fed more frequently during illnesses were better-off than those fed less frequently (World Health Organization (WHO) 2006)."}]},{"head":"Patronage/uptake of Maternal and Child Health Services","index":40,"paragraphs":[{"index":1,"size":42,"text":"Less than 60 % of children aged 6-36 were weighed 3-4 times at child welfare clinic (CWC) in the past 4 months. Regular attendance at growth monitoring sessions will enable health workers detect growth failure early enough for the necessary attention. xiii."},{"index":2,"size":81,"text":"The prevalence of diarrhoea in the two weeks prior to the survey was 33.7 % among children aged 6-36 months. The proportion of mothers who gave ORS/other rehydration therapy if her child had diarrhoea was less than 20 % and the proportion of children with sickness who received less breast milk or solid/semi-solid foods, because the child did not want it was over 60 % in both intervention and comparison communities. This is a dangerous situation and needs to be addressed."}]},{"head":"Conclusion and Recommendations","index":41,"paragraphs":[{"index":1,"size":33,"text":"Young children aged less than two years in Northern Ghana are at risk of not meeting the WHO recommended infant feeding standards given that less than 50 % were on minimum acceptable diet."},{"index":2,"size":29,"text":"The findings showed that all children in the 6-23 month group were unlikely of meeting the recommended feeding practices but the 6-8 months aged children, were the most vulnerable."},{"index":3,"size":45,"text":"None of the World Health Organization (WHO) recommended complementary feeding indicators (Minimum meal frequency, minimum dietary diversity, and minimum acceptable diet) were associated with child growth indicators among children aged 6-23 months, perhaps due to the little variation of the indicators in the study population."},{"index":4,"size":38,"text":"This finding suggests that the majority of children are at risk of under nutrition. An appropriate mix of health education and food supplements could be a feasible option to improve the dietary and nutritional status of young children."},{"index":5,"size":8,"text":"From the findings the following recommendations are made:"},{"index":6,"size":1,"text":"i."},{"index":7,"size":17,"text":"Children at risk of having inadequate complementary feeding should be specifically targeted by those policies and programmes."},{"index":8,"size":44,"text":"ii. Focus health and nutrition education and behavior change communication should be strengthened and sustained at all health facilities, out-reach points within communities focusing on hygienic practices for caregivers, appropriate timing of complementary feeding, dietary diversity, the management of common childhood illnesses, particularly diarrhoea."},{"index":9,"size":1,"text":"iii."},{"index":10,"size":29,"text":"Additionally, the provision of sufficiently nutrient-rich diet (through enriched complementary foods, community based food fortification) for children aged 6 -23 months will contribute to reducing rates of chronic malnutrition."},{"index":11,"size":1,"text":"iv."},{"index":12,"size":42,"text":"Results from the baseline survey should be used to guide in improving IYCF practices through household trials and behaviour change communication strategies including trials of improved practices (TIPs) and focused educational campaigns at the community level. Milk (other than breast milk) iii."},{"index":13,"size":3,"text":"Plain water iv."},{"index":14,"size":5,"text":"Sugar or glucose water v."},{"index":15,"size":3,"text":"Gripe water vi."},{"index":16,"size":3,"text":"Sugar-salt-water solution vii."},{"index":17,"size":3,"text":"Fruit juice viii."},{"index":18,"size":3,"text":"Infant formula ix."},{"index":19,"size":6,"text":"Tea / infusions x. Honey xi."},{"index":20,"size":6,"text":"Other (specify) _____________ Breast milk iii."},{"index":21,"size":3,"text":"Plain water iv."},{"index":22,"size":9,"text":"Commercially produced infant formula (e.g. Lactogen or SMA) v."},{"index":23,"size":14,"text":"Any other milk such as evaporated/sweetened condensed milk, powdered, or fresh animal milk vi."},{"index":24,"size":12,"text":"Sugar water, coconut, palm juice, other fruit juice or canned drink vii."},{"index":25,"size":6,"text":"Tea or coffee or infusions viii."},{"index":26,"size":6,"text":"Liquid or semi-liquid traditional medicine ix."},{"index":27,"size":7,"text":"Other liquid (specify) ____________________________________ A grandparent iii."},{"index":28,"size":3,"text":"A sibling iv."},{"index":29,"size":3,"text":"An aunt/uncle v."},{"index":30,"size":3,"text":"A neighbor/friend vi."},{"index":31,"size":3,"text":"The father vii."},{"index":32,"size":8,"text":"Other, (specify): …………………………………………. Less, because mother's decision iii."},{"index":33,"size":2,"text":"More iv."},{"index":34,"size":3,"text":"The same v."},{"index":35,"size":10,"text":"Child never breastfed or child breastfeeding before last illness vi."},{"index":36,"size":6,"text":"Child has never been sick vii."},{"index":37,"size":37,"text":"Does not know 5. The last time [child's name] was sick, did you offer less, more or the same amount of solid/semi-solid foods as when [child's name] is healthy? IF THEY RESPOND \"LESS\" THEN PROBE \"WHY?\") i."},{"index":38,"size":11,"text":"Less than usual, because the child did not want it ii."},{"index":39,"size":7,"text":"Less than usual, because mother's decision iii."},{"index":40,"size":4,"text":"More than usual iv."},{"index":41,"size":5,"text":"The same as usual v."},{"index":42,"size":3,"text":"Stopped completely vi."},{"index":43,"size":6,"text":"Child has never been sick vii."},{"index":44,"size":15,"text":"Does not know 6. Where did you seek health care assistance when child was sick?"},{"index":45,"size":1,"text":"i."},{"index":46,"size":6,"text":"Child has never been sick ii."},{"index":47,"size":4,"text":"No assistance sought iii."},{"index":48,"size":3,"text":"Own medication iv."},{"index":49,"size":1,"text":"Traditional "}]}],"figures":[{"text":" a) Can the prevalence of child malnutrition be decreased if messages and recipes generated from TIPs are locally available and accepted? b) Is focused behaviour change communication combined with nutrition-sensitive agriculture interventions to improve complementary feeding practices more effective than stand alone health and agricultural interventions in reducing malnutrition among children aged 6-36 months? "},{"text":" sample size t = confidence level at 95% (standard value of 1.96) p = estimated prevalence of malnutrition in the project area (25.0 %) m = margin of error at 5% (standard value of 0.05) "},{"text":"Fig. 3 . 1 Fig. 3.1 Weight-for-length/ height z-scores distribution curves "},{"text":"5 . 8 . When you delivered (Name of child) what did you do with the first yellowish breast milk? i) Give it to the baby ii) Discard it/spill it iii) Other (Specify)_______________ 6a. Is child currently breastfeeding? (a) Yes (b) No (If yes, skip to question 7) 6b. If your child is not currently breastfeeding, how many months did you breastfeed him/her? i) Less than six months ii) 6-12 months iii) 13-24 months iv) More than 24 months 7. Yesterday, was [child's name] breastfed? Yesterday did [child's name] have anything to drink from a bottle with a nipple during the day or night? (a) Yes (b) No 9. Kindly mention all liquids (Name of child) drank yesterday during the day or at night ( "},{"text":" 10. Is child currently eating other foods apart from breast milk? (a) Yes (b) No 11. Who mainly decides what [child's name] should and should not eat? i. The mother ii. "},{"text":"  "},{"text":"Table 2 .  Indicator Normal/ Poor/ Serious/ Critical/ IndicatorNormal/Poor/Serious/Critical/  Low Medium High Very high LowMediumHighVery high Wasting (GAM) <5% 5-9.9% 10-14.9% >15% Wasting (GAM)<5%5-9.9%10-14.9%>15% Stunting <20% 20-29.9% 30-39.9% >40% Stunting<20%20-29.9%30-39.9%>40% Underweight <10% 10-19.9% 20-29.9% >30% Underweight<10%10-19.9%20-29.9%>30%  "},{"text":"Table 3 . 1a: Comparison of socio-demographic characteristics of respondents Characteristic N   Test statistic  CharacteristicNTest statistic   Study Arm    Study Arm   Intervention Comparison   InterventionComparison   Communities Communities   CommunitiesCommunities   n (%) n (%)   n (%)n (%) Age Groups (years)      Age Groups (years) Under 18 13 5 (38.3) 8 (61.7) Chi-square (χ 2 ) = Under 18135 (38.3)8 (61.7)Chi-square (χ2 ) = 18-35 979 484 (49.2) 495 (50.8) 1.6 , p = 0.5  18-35979484 (49.2)495 (50.8)1.6 , p = 0.5 35 + 205 105 (52.6) 100 (47.4)   35 +205105 (52.6)100 (47.4) Total 1197 597 (49.9) 600 (50.1)   Total1197597 (49.9)600 (50.1) Educational level      Educational level None 845 416 (49.2) 429 (50.8) χ 2 = 7.3 , p = 0.12 None845416 (49.2)429 (50.8)χ 2 = 7.3 , p = 0.12 Primary 189 86 (45.5) 103 (54.5)   Primary18986 (45.5)103 (54.5) Basic (JSS/Middle) 133 78 (58.6) 55 (41.4)   Basic (JSS/Middle)13378 (58.6)55 (41.4) Senior High School (SHS) 28 17 (60.7) 11 (39.3)   Senior High School (SHS) 2817 (60.7)11 (39.3) Tertiary 3 1 (33.3) 2 (66.7)   Tertiary31 (33.3)2 (66.7) (College/university)      (College/university) Total 1198 598 (49.9) 600 (50.1)   Total1198598 (49.9)600 (50.1) Religion      Religion Christianity 558 278 (49.8) 280 (50.2) χ 2 = 13.8 , p = 0.003 Christianity558278 (49.8)280 (50.2)χ 2 = 13.8 , p = 0.003 Islam 574 301 (52.4) 273 (47.6)   Islam574301 (52.4)273 (47.6) African Traditional 56 15 (26.8) 41 (73.2)   African Traditional5615 (26.8)41 (73.2) Religion (ATR)      Religion (ATR) Other 10 4 (40.0) 6 (60.0)   Other104 (40.0)6 (60.0) Total 1198 598 (49.9) 600 (50.1)   Total1198598 (49.9)600 (50.1)  "},{"text":"Table 3 . 1a: Comparison of socio-demographic characteristics of respondents Characteristic N   Test statistic CharacteristicNTest statistic   Study Arm   Study Arm   Intervention Comparison  InterventionComparison   Communities Communities  CommunitiesCommunities   n (%) n (%)  n (%)n (%) Ethnicity     Ethnicity Dagomba 460 233 (50.7) 227 (49.3) χ 2 = 173.4 , p < Dagomba460233 (50.7)227 (49.3)χ 2 = 173.4 , p < Dagao 383 175 (45.7) 208 (54.3) 0.001 Dagao383175 (45.7)208 (54.3)0.001 Wala 85 57 (67.1) 28 (32.9)  Wala8557 (67.1)28 (32.9) Frafra 32 14 (43.8) 18 (56.3)  Frafra3214 (43.8)18 (56.3) Kasena 93 89 (95.7) 4 (4.3)  Kasena9389 (95.7)4 (4.3) Nankana 90 2 (2.2) 88 (97.8)  Nankana902 (2.2)88 (97.8) Builsa 8 5 (62.5) 3 (37.5)  Builsa85 (62.5)3 (37.5) Other 47 23 (48.9) 24 (51.1)  Other4723 (48.9)24 (51.1) Total 1198 598 (49.9) 600 (50.1)  Total1198598 (49.9)600 (50.1) Main Source of Income     Main Source of Income Trader/vendor 294 176 (59.9) 118 (40.1) χ 2 = 19.8 , p = 0.006 Trader/vendor294176 (59.9)118 (40.1)χ 2 = 19.8 , p = 0.006 Agricultural worker 754 357 (47.3) 397 (52.7)  Agricultural worker754357 (47.3)397 (52.7) Office worker (Civil 1 1 (100.0) 0 (0.0)  Office worker (Civil11 (100.0)0 (0.0) Servant     Servant Service worker (e.g. 60 26 (43.3) 34 (56.7)  Service worker (e.g.6026 (43.3)34 (56.7) Hair-dresser,     Hair-dresser, seamstress)     seamstress) Healthcare (e.g. Nurse ) 2 1 (50.0) 1 (50.0)  Healthcare (e.g. Nurse )21 (50.0)1 (50.0) Education/research 4 3 (75.0) 1 (25.0)  Education/research43 (75.0)1 (25.0) (Teacher)     (Teacher) Nothing 44 21 (47.7) 23 (52.3)  Nothing4421 (47.7)23 (52.3) Other 39 14 (35.9) 25 (64.1)  Other3914 (35.9)25 (64.1) Total 1198 598 (49.9) 600 (50.1)  Total1198598 (49.9)600 (50.1)  "},{"text":"Table 3  Characteristic N   Test statistic CharacteristicNTest statistic   Study Arm   Study Arm   Comparison Intervention  ComparisonIntervention   Communities Communities  CommunitiesCommunities   n (%) n (%)  n (%)n (%) Gender of youngest     Gender of youngest child     child Male 594 306 (51.5) 288 (48.5) Chi-square (χ 2 ) = Male594306 (51.5)288 (48.5)Chi-square (χ 2 ) =     0.9 , p = 0.3 0.9 , p = 0.3 Female 601 293 (48.8) 308 (51.2)  Female601293 (48.8)308 (51.2) Total 1195 599 (50.1) 596 (49.9)  Total1195599 (50.1)596 (49.9)  "},{"text":"Table 3 . 2: Household decision making and care of the child Characteristic N   Test statistic CharacteristicNTest statistic   Study Arm   Study Arm   Comparison Communities Intervention  Comparison CommunitiesIntervention   n (%) Communities  n (%)Communities    n (%)  n (%) Who usually makes     Who usually makes decisions about     decisions about purchasing food or     purchasing food or taking child for health     taking child for health services?     services? Mother/caretaker 256 118 (46.1) 138 (53.9) χ 2 = 8.9 , p = 0.2 Mother/caretaker256118 (46.1)138 (53.9)χ 2 = 8.9 , p = 0.2 Husband/partner or 595 319 (53.6) 276 (46.4)  Husband/partner or595319 (53.6)276 (46.4) other man in the     other man in the household     household Mother/caregiver and 253 124 (49.0) 129 (51.0)  Mother/caregiver and253124 (49.0)129 (51.0) father together     father together Elder person in 80 33 (41.3) 47 (58.8)  Elder person in8033 (41.3)47 (58.8) household/family     household/family Mother/caregiver 8 3 (37.5) 5 (62.5)  Mother/caregiver83 (37.5)5 (62.5) together with the elder     together with the elder person     person Other Person 5 2 (40.0) 3 (60.0)  Other Person52 (40.0)3 (60.0) Does not know 1 1 (100.0) 0 (0.0)  Does not know11 (100.0)0 (0.0) Total 1198 600 (50.1) 598 (49.9)  Total1198600 (50.1)598 (49.9) Care of your child when     Care of your child when mother is not at home     mother is not at home Sibling 215 100 (46.5) 115 (53.5) χ 2 = 8.9 , p = 0.2 Sibling215100 (46.5)115 (53.5)χ 2 = 8.9 , p = 0.2 Auntie 76 33 (43.4) 43 (56.6)  Auntie7633 (43.4)43 (56.6)  "},{"text":"Table 3 . 3: Uptake of maternal care services Factor N FactorN  Study Arm Study Arm  "},{"text":"Table 3 . 4a: Types of crops grown by households Types of crops  Types of crops grown by  grown by households Study Arm householdsStudy Arm  "},{"text":"Table 3 . 5: Nutritional status of children aged 6-36 months (Sexes and ages combined)  N Mean ±SD Prevalence of Moderate Acute Severe Acute NMean ±SDPrevalence ofModerate AcuteSevere Acute Variable   <-2 z-score and / or edema Malnutrition <-2 Z-score and> = -3 z- Malnutrition (<-3 z-score Variable<-2 z-score and / or edemaMalnutrition <-2 Z-score and> = -3 z-Malnutrition (<-3 z-score     score and/or oedema scoreand/or oedema WAZ * 1195 -1.12±1.06 21.1 [CI: 18.0 -24.4] 17.6 [CI: 15.1 -20.5] 3.4 [CI: 2.3 -5.0] WAZ *1195-1.12±1.0621.1 [CI: 18.0 -24.4]17.6 [CI: 15.1 -20.5]3.4 [CI: 2.3 -5.0] HAZ* 1188 -1.06±1.33 23.2 [CI: 19.6 -27.1] 16.4 [CI: 13.7 -19.6] 6.8 [CI: 5.0 -9.2] HAZ*1188-1.06±1.3323.2 [CI: 19.6 -27.1]16.4 [CI: 13.7 -19.6]6.8 [CI: 5.0 -9.2] WHZ* 1188 -0.77±1.11 12.5 [CI: 10.7 -14.6] 10.3 [CI: 8.4 -12.6] 2.2 [CI: 1.4 -3.4] WHZ*1188-0.77±1.1112.5 [CI: 10.7 -14.6]10.3 [CI: 8.4 -12.6]2.2 [CI: 1.4 -3.4]  "},{"text":"Table 3 . 6 shows the geographical distribution of prevalence of acute, chronic and underweight malnutrition among index children. The prevalence of global acute malnutrition in Wa West and Tolon districts were above the normal 15 % level recommended by the WHO. The level in the two districts can be described as critical/ very high. The highest prevalence of chronic malnutrition was in the Tolon and Savelugu Districts located in the Northern Region and the malnutrition situation is serious according to the WHO cut-off for public health significance.  "},{"text":"Table 3 . 6: Geographical distribution of wasting, stunting and underweight among children 6-36 months (weighted analysis by districts)  N Wasting Stunting H/A < -2 z Underweight W/A< - NWastingStunting H/A < -2 zUnderweight W/A< - District  <-2 z-score and / or edema  2 z District<-2 z-score and / or edema2 z Tolon 239 15.5 *[CI: 11.3 -20.8] 31.8) 26.4 Tolon23915.5 *[CI: 11.3 -20.8]31.8)26.4    *[CI: 24.4 -41.6] *[CI: 19.3 -34.9] *[CI: 24.4 -41.6]*[CI: 19.3 -34.9] Salvelugu 238 10.5 *[CI: 7.1 -15.3] 31.1 *[CI: 27.3 -35.2] 26.5*[CI: 22.4 -30.9] Salvelugu23810.5 *[CI: 7.1 -15.3]31.1 *[CI: 27.3 -35.2]26.5*[CI: 22.4 -30.9] Nadowli 238 3.8 *[CI: 2.5 -5.6] 17.2 *[CI: 12.8 -22.8] 12.6 *[CI: 9.0 -17.3] Nadowli2383.8 *[CI: 2.5 -5.6]17.2 *[CI: 12.8 -22.8]12.6 *[CI: 9.0 -17.3]  "},{"text":"Table 3 . 7 shows the weighted analysis of acute, chronic and underweight by intervention and comparison communities. There was no significant difference in child growth indicators between intervention and comparison communities. Table 3.7 : Weighted analysis of wasting, stunting and underweight by intervention and comparison Table 3.7 : Weighted analysis of wasting, stunting and underweight by intervention and comparison communities      communities Indicator N Comparison Communities Communities Intervention Test Statistic  IndicatorNComparison CommunitiesCommunities InterventionTest Statistic Wasting 1188 13.6*[CI: 11.0 -16.7] 11.4 *[CI: 8.9 -14.5] Chi-square (χ 2 ) = Wasting118813.6*[CI: 11.0 -16.7]11.4 *[CI: 8.9 -14.5]Chi-square (χ2 ) = <-2 z-score and / or    1.3 , p = 0.3  <-2 z-score and / or1.3 , p = 0.3 edema      edema Stunting H/A < -2 z 1188 20.6*[CI: 16.6 -26.0] 25.8 *[CI: 19.8 -32.8] Chi-square (χ 2 ) = Stunting H/A < -2 z118820.6*[CI: 16.6 -26.0]25.8 *[CI: 19.8 -32.8]Chi-square (χ2 ) =     4.5 , p = 0.25 4.5 , p = 0.25 Underweight W/A< 1195 21.6*[CI: 17.8 -25.9] 20.5*[CI: 15.6 -26.4] Chi-square (χ 2 ) = Underweight W/A<119521.6*[CI: 17.8 -25.9]20.5*[CI: 15.6 -26.4]Chi-square (χ2 ) = -2 z    0.2 , p = 0.8  -2 z0.2 , p = 0.8 *95% Confidence Interval     *95% Confidence Interval  "},{"text":"Table 3 . 8 : Weighted analysis of the prevalence of wasting, stunting and underweight by gender Gender Gender  "},{"text":"Table 3 . 9 : Weighted analysis of the prevalence of wasting, stunting and underweight by age classification (sexes combined)  N Wasting  Stunting H/A < -2 z Underweight W/A< - NWastingStunting H/A < -2 zUnderweight W/A< - Age Group  <-2 z-score and / or edema   2 z Age Group<-2 z-score and / or edema2 z (months)       (months) 6-8 135 11.1 *[CI: 6.2 -18.9] 6.7 *[CI: 3.0 -14.5] 12.8 6-813511.1 *[CI: 6.2 -18.9]6.7 *[CI: 3.0 -14.5]12.8       *[CI: 7.7 -20.6] *[CI: 7.7 -20.6] 9-23 643 17.2 *[CI: 14.9 -19.8] 21.9 *[CI: 17.8 -26.5] 25.2 *[CI: 21.2 -29.7] 9-2364317.2 *[CI: 14.9 -19.8]21.9 *[CI: 17.8 -26.5]25.2 *[CI: 21.2 -29.7] 24-36 401 5.7 *[CI: 3.9 -8.3] 30.8 *[CI: 24.2 -38.2] 17.7 *[CI: 14.0 -22.2] 24-364015.7 *[CI: 3.9 -8.3]30.8 *[CI: 24.2 -38.2]17.7 *[CI: 14.0 -22.2] Test Statistic  0.001 Chi-square (χ 2 ) = 29.2 , p < < 0.001 Chi-square (χ 2 ) = 34.1 , p Chi-square (χ 2 Test Statistic0.001 Chi-square (χ2 ) = 29.2 , p << 0.001 Chi-square (χ2 ) = 34.1 , pChi-square (χ2  "},{"text":"Table 3 . 10: Weighted Mean z-scores and design effects Indicator Mean z-scores Error Standard 95% Confidence Interval Design Effect IndicatorMean z-scoresError Standard95% Confidence IntervalDesign Effect    Lower Upper  LowerUpper Weight-for-Age -1.15 0.05 -1.26 -1.05 3.30 Weight-for-Age -1.150.05-1.26-1.053.30 Height-for-Age -1.12 0.07 -1.25 -0.98 3.85 Height-for-Age -1.120.07-1.25-0.983.85 Weight-for- -0.78 0.05 -0.88 -0.684 2.81 Weight-for--0.780.05-0.88-0.6842.81 Height      Height  "},{"text":"Table 3 . 11: Types of prelacteals given to children (Multiple responses) Types of Prelacteals Given Frequency (n) Percentage (n) Types of Prelacteals GivenFrequency (n)Percentage (n) Milk (other than breastmilk)   Milk (other than breastmilk) No 1187 98.9 No118798.9 Yes 9 0.8 Yes90.8 Total 1196 100.0 Total1196100.0 Plain water   Plain water No 1173 98.0 No117398.0 Yes 24 2.0 Yes242.0 Total 1197 100.0 Total1197100.0 Sugar or glucose water   Sugar or glucose water No 1196 99.9 No119699.9 Yes 1 0.1 Yes10.1 Total 1197 100.0 Total1197100.0 Gripe water   Gripe water No 1194 99.7 No119499.7 Yes 3 0.3 Yes30.3 Total 1197 100.0 Total1197100.0 Tea/infusion   Tea/infusion No 1191 99.5 No119199.5 Yes 6 0.5 Yes60.5 Total 1197 100.0 Total1197100.0  "},{"text":"Table 3 . 12: Types of food fed to children in the past 24 hours (Multiple responses) Types of foods Frequency (n) Percentage (%) Types of foodsFrequency (n)Percentage (%) Cereals   Cereals No 110 9.2 No1109.2 Yes 1085 90.8 Yes108590.8 Total 1195 100.0 Total1195100.0 Roots and tubers   Roots and tubers No 936 78.3 No93678.3 Yes 259 21.7 Yes25921.7 Total 1195 100.0 Total1195100.0 Vitamin A rich vegetables and   Vitamin A rich vegetables and fruits   fruits No 1022 85.7 No102285.7 Yes 171 14.3 Yes17114.3 Total 1193 100.0 Total1193100.0 Green leafy vegetables   Green leafy vegetables No 740 61.9 No74061.9 Yes 455 38.1 Yes45538.1 Total 1195 100.0 Total1195100.0 Vitamin A rich fruits   Vitamin A rich fruits No 1084 90.9 No108490.9 Yes 109 9.1 Yes1099.1 Total 1193 100.0 Total1193100.0 Dried fruits vegetables (e.g. okro,   Dried fruits vegetables (e.g. okro, pumpkin,baoba, wild leaves)   pumpkin,baoba, wild leaves) No 676 56.6 No67656.6 Yes 518 43.4 Yes51843.4 Total 1194 100.0 Total1194100.0  "},{"text":"Table 3 . 12: Types of food fed to children in the past 24 hours (Multiple responses) Types of foods Given Frequency (n) Percentage (n) Types of foods GivenFrequency (n)Percentage (n) Organ meat   Organ meat No 1133 94.9 No113394.9 Yes 61 5.1 Yes615.1 Total 1194 100.0 Total1194100.0 Flesh meat   Flesh meat No 1053 88.2 No105388.2 Yes 141 11.8 Yes14111.8 Total 1194 100.0 Total1194100.0 Eggs   Eggs No 1052 88.5 No105288.5 Yes 137 11.5 Yes13711.5 Total 1189 100.0 Total1189100.0  "},{"text":"Table 3 . 12: Types of food fed to children in the past 24 hours (Multiple responses) Types of foods Given Frequency (n) Percentage (n) Types of foods GivenFrequency (n)Percentage (n) Milk   Milk No 902 75.5 No90275.5 Yes 293 24.5 Yes29324.5 Total 1195 100.0 Total1195100.0 Fats and oils   Fats and oils No 520 43.5 No52043.5 Yes 675 56.3 Yes67556.3 Total 1195 100.0 Total1195100.0 Spices and condiments   Spices and condiments No 385 32.2 No38532.2 Yes 810 67.8 Yes81067.8 Total 1195 100.0 Total1195100.0  "},{"text":"Table 3 . 13 Summary of core IYCF indicators among children 6-23 monthsThere was a significant difference in the proportion of children on minimum acceptable diet in the districts. The highest proportion of breastfed children aged 6-23 months on minimum acceptable diet was 54.7 % in Kassena-Nankana/Bongo whereas the lowest proportion of 31.3 % was reported from the Savelugu District. The mean dietary diversity score of children in the Wa West District was significantly higher compared to Tolon District (Table3.14).    Test statistic Test statistic Indicator    Indicator  Study Arm   Study Arm  Comparison Intervention Communities  ComparisonIntervention Communities  Communities   Communities Timely initiation of breastfeeding (TIBF) rate 50.5 *[CI: 43.0 -58.0] 46.4*[CI: 40.9 -52.0] Chi-square (χ 2 ) = 1.3 , p = Timely initiation of breastfeeding (TIBF) rate50.5 *[CI: 43.0 -58.0]46.4*[CI: 40.9 -52.0]Chi-square (χ 2 ) = 1.3 , p =    0.4 0.4 Timely Complementary 38.7 *[CI: 25.9 -53.3] 31.4 *[CI: 19.5 -46.4]  Timely Complementary38.7 *[CI: 25.9 -53.3]31.4 *[CI: 19.5 -46.4]  "},{"text":"Table 3  .14: Dietary diversity of children 6-23 months by districts  .14: Dietary diversity of children 6-23 months by districts     95% Confidence Interval  95% Confidence Interval     for Mean   for Mean     Lower   Lower  N Mean Std. Deviation Bound Upper Bound Test Statistic NMeanStd. DeviationBoundUpper BoundTest Statistic Tolon 153 3.6 2.9 3.2 4.1 F (4, 763) = 6.1, p < 0.001 Tolon1533.62.93.24.1F (4, 763) = 6.1, p < 0.001 Savelugu 147 4.6 3.4 4.0 5.1  Savelugu1474.63.44.05.1 Nadowli 147 3.9 2.2 3.5 4.2  Nadowli1473.92.23.54.2 Wa west 162 5.0 2.9 4.6 5.5  Wa west1625.02.94.65.5 Kassena- 155 4.5 2.5 4.1 4.9  Kassena-1554.52.54.14.9 Nankana/Bongo       Nankana/Bongo Total 764 4.3 2.8 4.1 4.5  Total7644.32.84.14.5  "},{"text":"Table 3 . 15a: Bivariate analysis of the predictors of minimum acceptable diet among children6-23 months (N = 778)      Met Minimum acceptable diet   Met Minimum acceptable diet Indicator No Yes Test-statistic IndicatorNoYesTest-statistic Maternal age group    Maternal age group Less than 18 years 75.6 *[CI: 50.6 -90.4] 24.4 *[CI: 9.6 -49.4] χ 2 = 6.7, p = Less than 18 years75.6 *[CI: 50.6 -90.4]24.4 *[CI: 9.6 -49.4]χ 2 = 6.7, p = 18-35 years 56.2 *[CI: 50.5 -61.7] 43.8 *[CI: 38.3 -49.5] 0.045 18-35 years56.2 *[CI: 50.5 -61.7]43.8 *[CI: 38.3 -49.5]0.045 More than 35 years 43.9 *[CI: 38.8 -54.5] 56.1 *[CI: 45.5 -66.2]  More than 35 years43.9 *[CI: 38.8 -54.5]56.1 *[CI: 45.5 -66.2] Total 54.9 *[CI: 50.1 -59.6] 45.1 *[CI: 40.4 -49.9]  Total54.9 *[CI: 50.1 -59.6]45.1 *[CI: 40.4 -49.9] 6-8 months 85.6 *[CI: 79.8 -90.0] 14.4 *[CI: 10.0 -20.2] χ 2 = 52.1, p < 6-8 months85.6 *[CI: 79.8 -90.0]14.4 *[CI: 10.0 -20.2]χ 2 = 52.1, p < 9-23 months 49.3 *[CI: 43.7 -55.0] 50.7*[CI: 45.0 -56.3] 0.001 9-23 months49.3 *[CI: 43.7 -55.0]50.7*[CI: 45.0 -56.3]0.001 Total 55.0 *[CI: 50.2 -59.7] 45.0 *[CI: 40.3 -49.8]  Total55.0 *[CI: 50.2 -59.7]45.0 *[CI: 40.3 -49.8] Currently breastfeeding?    Currently breastfeeding? Yes 56.2 *[CI: 51.2 -61.0] 43.8 *[CI: 39.0 -48.8] χ 2 = 15.1, p < Yes56.2 *[CI: 51.2 -61.0]43.8 *[CI: 39.0 -48.8]χ 2 = 15.1, p < No 8.6 *[CI: 2.6 -24.5] 91.4 *[CI: 75.5 -97.4] 0.001 No8.6 *[CI: 2.6 -24.5]91.4 *[CI: 75.5 -97.4]0.001 Total 55.1 *[CI: 50.2 -59.8] 44.9 *[CI: 40.2 -49.8]  Total55.1 *[CI: 50.2 -59.8]44.9 *[CI: 40.2 -49.8] Geographical location    Geographical location Northern Region 58.4 *[CI: 50.2 -66.2] 41.6 *[CI: 33.8 -49.8] χ 2 = 8.1, p = Northern Region58.4 *[CI: 50.2 -66.2]41.6 *[CI: 33.8 -49.8]χ 2 = 8.1, p = Upper West Region 56.6 *[CI: 50.3 -62.6] 43.4 *[CI: 37.4 -49.7] 0.048 Upper West Region56.6 *[CI: 50.3 -62.6]43.4 *[CI: 37.4 -49.7]0.048 Upper East Region 45.6 *[CI: 38.3 -53.0] 54.4 *[CI: 47.0 -61.7]  Upper East Region45.6 *[CI: 38.3 -53.0]54.4 *[CI: 47.0 -61.7] Place of delivery    Place of delivery Home 60.2 *[CI: 52.7 -67.3] 39.8 *[CI: 32.7 -47.3] χ 2 = 7.0, p = Home60.2 *[CI: 52.7 -67.3]39.8 *[CI: 32.7 -47.3]χ 2 = 7.0, p = Health facility 50.5 *[CI: 45.0 -55.9] 49.5 *[CI: 44.1 -55.0] 0.02 Health facility50.5 *[CI: 45.0 -55.9]49.5 *[CI: 44.1 -55.0]0.02 As shown in Table 3.15b, age of child remained a strong predictor of minimum acceptable diet after As shown in Table 3.15b, age of child remained a strong predictor of minimum acceptable diet after adjusting for confounding variables. Children aged 9-23 months were 4.2 times more likely to meet adjusting for confounding variables. Children aged 9-23 months were 4.2 times more likely to meet minimum acceptable diet compared to children aged 6-8 months (AOR = 4.2, 95% CI: 2.5, 6.9, p < minimum acceptable diet compared to children aged 6-8 months (AOR = 4.2, 95% CI: 2.5, 6.9, p < 0.001]. The data showed that children not breastfeeding were 7 times more likely [AOR 7.4; 95% CI 0.001]. The data showed that children not breastfeeding were 7 times more likely [AOR 7.4; 95% CI  "},{"text":"Table 3 . 15b: Multivariate analysis of the predictors of minimum acceptable diet among children 6-23 months     95% C.I.for EXP(B) 95% C.I.for EXP(B)  Wald Sig. Exp(B) Lower Upper WaldSig.Exp(B)LowerUpper Age group 9-23 months 30.95 <0.001 4.2 2.5 6.9 Age group 9-23 months30.95<0.0014.22.56.9 Non-breastfeeding 6.89 0.009 7.4 1.7 33.1 Non-breastfeeding6.890.0097.41.733.1 Facility delivery 4.84 0.028 1.4 1.04 1.9 Facility delivery4.840.0281.41.041.9 Household wealth index 5.49 0.019 1.1 1.01 1.1 Household wealth index5.490.0191.11.011.1 Constant 45.69 0.000 0.122   Constant45.690.0000.122  "},{"text":"Table 3 . 16a: Bivariate Analysis of predictors of chronic malnutrition among children aged 6-36 months Multiple logistic regression analysis revealed that children's age, maternal age, gender of child, and geographical location were significantly related to stunting (Table3.16b). Compared to the Kasena-Nankana District in the Upper East Region, children in the Tolon District were 3.6 times more likely (AOR= 2.0, CI= 1.59-2.53, p < 0.001) and those in Savelugu were 3.4 times more likely (AOR= 3.57, CI= 2.18-5.84, p < 0.001) of becoming stunted. It was found that children whose mothers were less than 18 years were 5 times more likely[AOR 5.75;] of becoming stunted compared to children born to mothers aged more than 35 years.  Classification of chronic malnutrition  Classification of chronic malnutrition Characteristic Normal Stunted  CharacteristicNormalStunted    Test statistic Test statistic Region    Region Northern 68.4 *[CI: 61.2 -74.8] 31.6 *[CI: 25.2 -38.8] χ 2 = 53.4 p < Northern68.4 *[CI: 61.2 -74.8]31.6 *[CI: 25.2 -38.8]χ 2 = 53.4 p < Upper East 87.8 *[CI: 83.7 -91.0] 12.2 *[CI: 9.0 -16.3] 0.001 Upper East87.8 *[CI: 83.7 -91.0]12.2 *[CI: 9.0 -16.3]0.001 Upper West 84.5 *[CI: 81.1 -87.4] 15.5 *[CI: 12.6 -18.9]  Upper West84.5 *[CI: 81.1 -87.4]15.5 *[CI: 12.6 -18.9] Age of child (months)    Age of child (months) 6-8 93.3 *[CI: 85.5-97.0] 6.7 *[CI: 3.0 -14.5] χ 2 = 35.1 p 6-893.3 *[CI: 85.5-97.0]6.7 *[CI: 3.0 -14.5]χ 2 = 35.1 p 9-23 78.1 *[CI: 73.5-82.2] 21.9 *[CI: 17.8 -26.5] <0.001 9-2378.1 *[CI: 73.5-82.2]21.9 *[CI: 17.8 -26.5]<0.001 24-36 69.2 *[CI: 61.8-75.8] 30.8 *[CI: 24.2 -38.2]  24-3669.2 *[CI: 61.8-75.8]30.8 *[CI: 24.2 -38.2] Gender of child    Gender of child Male 73.6 *[CI: 68.7 -78.1] 26.4 *[CI: 21.9 -31.3] χ 2 = 6.5 , p = 0.02 Male73.6 *[CI: 68.7 -78.1]26.4 *[CI: 21.9 -31.3]χ 2 = 6.5 , p = 0.02 Female 79.9 *[CI: 75.1 -83.9] 20.1 *[CI: 16.1 -24.9]  Female79.9 *[CI: 75.1 -83.9]20.1 *[CI: 16.1 -24.9] * 95 % confidence level (CI)   * 95 % confidence level (CI) Table 3. 16a: Bivariate Analysis of predictors of chronic malnutrition among children aged 6-36 Table 3. 16a: Bivariate Analysis of predictors of chronic malnutrition among children aged 6-36 months    months  Classification of chronic malnutrition  Classification of chronic malnutrition Characteristic Normal Stunted Test CharacteristicNormalStuntedTest  n (%) n (%) statistic n (%)n (%)statistic Household rears livestock?    Household rears livestock? Yes 77.6 *[CI: 73.8 -81.1] 22.4 *[CI: 18.9 -26.2] χ 2 = 7.1 , p Yes77.6 *[CI: 73.8 -81.1]22.4 *[CI: 18.9 -26.2]χ 2 = 7.1 , p No 62.9 *[CI: 47.5 -76.1] 37.1 *[CI: 23.9 -52.5] = 0.03 No62.9 *[CI: 47.5 -76.1]37.1 *[CI: 23.9 -52.5]= 0.03 Household rears chickens,    Household rears chickens, ducks, or other birds; for    ducks, or other birds; for the eggs    the eggs Yes 81.4 *[CI: 76.8 -85.3] 18.6 *[CI: 14.7 -23.2] χ 2 = 5.6 , p Yes81.4 *[CI: 76.8 -85.3]18.6 *[CI: 14.7 -23.2]χ 2 = 5.6 , p No 75.0 *[CI: 70.3 -79.2] 25.0 *[CI: 20.8 -29.7] = 0.02 No75.0 *[CI: 70.3 -79.2]25.0 *[CI: 20.8 -29.7]= 0.02 No. of children U-5    No. of children U-5  "},{"text":"Table 3 . 16b: Multivariate analysis of the determinants of chronic under nutrition     95% C.I.for EXP(B) 95% C.I.for EXP(B)  Wald Sig. Exp(B) Lower Upper WaldSig.Exp(B)LowerUpper Age of child (months) 38.99 0.000    Age of child (months)38.990.000 6-8 Reference     6-8Reference 9-23 15.51 <0.001 4.55 2.14 9.67 9-2315.51<0.0014.552.149.67 24-36 33.88 <0.001 11.10 4.93 24.95 24-3633.88<0.00111.104.9324.95 Breastfeeding (Yes) 4.33 0.04 1.61 1.03 2.51 Breastfeeding (Yes)4.330.041.611.032.51 Maternal Age (years) 7.33 0.03    Maternal Age (years)7.330.03 Under 18 7.33 0.01 5.75 1.62 20.42 Under 187.330.015.751.6220.42 18-35 0.446 0.50 1.15 0.77 1.73 18-350.4460.501.150.771.73 35+ Reference     35+Reference District 55.30 0.000    District55.300.000 Tolon District 25.75 <0.001 3.57 2.18 5.84 Tolon District25.75<0.0013.572.185.84 Savelugu District 23.84 <0.001 3.39 2.08 5.53 Savelugu District23.84<0.0013.392.085.53 Nadowli District(3) 1.40 0.24 1.38 0.81 2.34 Nadowli District(3)1.400.241.380.812.34 Wa West District 0.000 0.99 1.01 0.58 1.76 Wa West District0.0000.991.010.581.76 Kasena-Nankana/Bongo Reference     Kasena-Nankana/BongoReference Gender (male) 11.91 0.001 1.70 1.26 2.30 Gender (male)11.910.0011.701.262.30 Constant 75.42 0.000 0.011   Constant75.420.0000.011  "},{"text":"Table 3 . 17a: Bivariate analysis of core infant and young child feeding indicators and acute malnutrition among children aged6-36 months      Classification of acute malnutrition  Classification of acute malnutrition Characteristic Normal Wasted  CharacteristicNormalWasted  n (%) n (%) Test statistic n (%)n (%)Test statistic Region    Region Northern 85.6 *[CI: 81.7 -88.7] 14.4 *[CI: 11.3 -18.3] χ 2 = 4.9 p = 0.013 Northern85.6 *[CI: 81.7 -88.7]14.4 *[CI: 11.3 -18.3]χ 2 = 4.9 p = 0.013 Upper West 90.9 *[CI: 89.2 -92.5] 9.1 *[CI: 7.5 -10.8]  Upper West90.9 *[CI: 89.2 -92.5]9.1 *[CI: 7.5 -10.8] Upper East 87.4 *[CI: 85.7 -88.9] 12.6 *[CI: 11.1 -14.3]  Upper East87.4 *[CI: 85.7 -88.9]12.6 *[CI: 11.1 -14.3] Gender of child    Gender of child Male 85.6 *[CI: 83.2 -87.6] 14.4 *[CI: 12.4 -16.8] χ 2 = 2.9 p = 0.022 Male85.6 *[CI: 83.2 -87.6]14.4 *[CI: 12.4 -16.8]χ 2 = 2.9 p = 0.022 Female 88.9 *[CI: 86.1 -91.2] 11.1 *[CI: 8.8 -13.9]  Female88.9 *[CI: 86.1 -91.2]11.1 *[CI: 8.8 -13.9] Age of child (months)    Age of child (months) 6-8 88.9 *[CI: 81.1 -93.8] 11.1*[CI: 6.2 -18.9]  6-888.9 *[CI: 81.1 -93.8]11.1*[CI: 6.2 -18.9] 9-23 82.8 *[CI: 80.2 -85.1] 17.2 *[CI: 14.9 -19.8] χ 2 = 29.1 , p < 0.001 9-2382.8 *[CI: 80.2 -85.1]17.2 *[CI: 14.9 -19.8]χ 2 = 29.1 , p < 0.001 24-36 94.3 *[CI: 91.7 -96.1] 5.7 *[CI: 3.9 -8.3]  24-3694.3 *[CI: 91.7 -96.1]5.7 *[CI: 3.9 -8.3] Currently breastfeeding?    Currently breastfeeding? Yes 84.6 *[CI: 82.1 -86.8] 15.4 *[CI: 13.2 -17.9] χ 2 = 24.7 , p < 0.001 Yes84.6 *[CI: 82.1 -86.8]15.4 *[CI: 13.2 -17.9]χ 2 = 24.7 , p < 0.001 No 96.3 *[CI: 93.4 -97.9] 3.7 *[CI: 2.1 -6.6]  No96.3 *[CI: 93.4 -97.9]3.7 *[CI: 2.1 -6.6] Child had an illness with a    Child had an illness with a cough that comes from the    cough that comes from the chest at any time in the    chest at any time in the last two weeks?    last two weeks? Yes 83.9 *[CI: 80.8 -86.6] 16.1 *[CI: 13.4 -19.2] χ 2 = 9.4 , p = 0.004 Yes83.9 *[CI: 80.8 -86.6]16.1 *[CI: 13.4 -19.2]χ 2 = 9.4 , p = 0.004 No 89.9 *[CI: 87.0 -92.3] 10.1 *[CI: 7.7 -13.0]  No89.9 *[CI: 87.0 -92.3]10.1 *[CI: 7.7 -13.0]  "},{"text":"Table 3 . 17b: Multivariate analysis of the determinants of acute under nutrition     95% C.I.for EXP(B) 95% C.I.for EXP(B)  Wald Sig. Exp(B) Lower Upper WaldSig.Exp(B)LowerUpper Breastfeeding currently 23.639 <0.001 4.78 2.50 9.14 Breastfeeding currently23.639<0.0014.782.509.14 Child had an illness with a cough that 10.848 0.002 1.82 1.26 2.62 Child had an illness with a cough that10.8480.0021.821.262.62 comes from the chest in the last two      comes from the chest in the last two weeks?      weeks? Gender(male) 5.453 0.024 1.37 1.04 1.79 Gender(male)5.4530.0241.371.041.79 Constant 17.948 0.000    Constant17.9480.000  "},{"text":"Table 3 . 18: Access to growth monitoring services and vitamin A supplementation Frequency n (%) Test statistic Frequency n (%)Test statistic  "},{"text":"Table 3 . 19 Prevalence and management of childhood sickness Frequency n (%) Test statistic Frequency n (%)Test statistic  "},{"text":"Table 3 . 19 Prevalence and management of childhood sickness Frequency n (%) Test statistic Frequency n (%)Test statistic  "},{"text":" The proportion of children aged 6-59 months reported to have received vitamin A supplementation in last 6 months was well over 90 % and this should be maintained. xi. None of the World Health Organization (WHO) recommended complementary feeding indicators (Minimum meal frequency, minimum dietary diversity, and minimum acceptable diet) was associated with any of child growth indicators among children aged 6-23 months. xii. Multiple logistic regression analysis revealed that children's age, maternal age, gender of child, and geographical location were significantly related to stunting. Compared to the Kasena-Nankana District in the Upper East Region, children in the Tolon District were 3.6 times more likely (AOR= 2.0, CI= 1.59-2.53, p < 0.001) and those in Savelugu were 3.4 times more likely (AOR= 3.57, CI= 2.18-5.84, p < 0.001) of becoming stunted. It was found that children whose mothers were less than 18 years were 5 times more likely [AOR 5.75; 95% CI (1.62-20.42)] of becoming stunted compared to children born to mothers aged more than 35 years.  "},{"text":" Does this household own livestock, herds, other farm animals, poultry or fish? If yes, tell me about all the types of animals that you have. (CHECK ALL THAT APPLY) INFANT AND CHILD FEEDING PRACTICES (Administer to the mother on behalf of child) 1. During the pregnancy with [child's name], how many times did you visit a health care center for a prenatal care services? (Verify from the antenatal card) …………………………………………….. 2. Where did you deliver (Name of child)? After delivery of the index child, how long did it take you to breastfeed him/her for the first time? v. Mother/caregiver together with the elder person v.Mother/caregiver together with the elder person vi. Other person, specify ________________ vi.Other person, specify ________________ vii. 3. i. Does not know Within first hour of delivery vii. 3. i.Does not know Within first hour of delivery 9. Who usually takes care of your child when you are not at home? ii. 2 to 23 hours after delivery 9. Who usually takes care of your child when you are not at home? ii. 2 to 23 hours after delivery i. iii. Sibling The next day (More than 24 hours) i. iii.Sibling The next day (More than 24 hours) ii. iv. Auntie Do not remember ii. iv.Auntie Do not remember iii. Uncle iii.Uncle iv. 4. Before putting child to the breast for the first time after delivery, what was child given to drink? (Multiple Grandmother iv. 4. Before putting child to the breast for the first time after delivery, what was child given to drink? (Multiple Grandmother v. responses possible) Grandfather/Father v. responses possible) Grandfather/Father vi. Not Applicable (Always takes child along) vi.Not Applicable (Always takes child along) vii. i. Others (Specify) __________________________________________ Nothing vii. i.Others (Specify) __________________________________________ Nothing ii.  ii. 10. Does anyone in your household grow food? If yes, tell me about all the types of food that are grown. (CHECK 10. Does anyone in your household grow food? If yes, tell me about all the types of food that are grown. (CHECK ALL THAT APPLY) ALL THAT APPLY) i. Yes (grains, roots, tubers) i.Yes (grains, roots, tubers) ii. Yes (legumes, nuts) ii.Yes (legumes, nuts) iii. Yes (orange or yellow fruits & vegetables) iii.Yes (orange or yellow fruits & vegetables) iv. Yes (green leafy vegetables) iv.Yes (green leafy vegetables) v. Yes (any other fruits & vegetables) v.Yes (any other fruits & vegetables) vi. Yes (other: specify________________ vi.Yes (other: specify________________ vii. No vii.No viii. Does not know viii.Does not know 11. i. Yes (chickens, ducks, or other birds: for the meat/sale) 11. i.Yes (chickens, ducks, or other birds: for the meat/sale) ii. Yes (chickens, ducks, or other birds: for the eggs) ii.Yes (chickens, ducks, or other birds: for the eggs) iii. Yes (cows, goats, sheep, pigs, dogs or other large mammals for the meat) iii.Yes (cows, goats, sheep, pigs, dogs or other large mammals for the meat) iv. Yes (cows, goats, sheep, or dogs for sale) iv.Yes (cows, goats, sheep, or dogs for sale) v. Yes (rabbits, guinea pigs, or other small mammals) v.Yes (rabbits, guinea pigs, or other small mammals) vi. Yes (fish) vi.Yes (fish) vii. No vii.No viii. Does not know viii.Does not know 12. What is the primary source of obtaining food for the household? 12. What is the primary source of obtaining food for the household? i. Own production (e.g. farming) i.Own production (e.g. farming) ii. Purchases ii.Purchases iii. Food aid iii.Food aid iv. Borrowing, gift, barter iv.Borrowing, gift, barter v. Other (specify) ___________________________________________ v.Other (specify) ___________________________________________ SECTION B: i. At home SECTION B: i. At home ii. CHPS Compound ii.CHPS Compound iii. Clinic iii.Clinic iv. Maternity home iv.Maternity home v. Health centre v.Health centre vi. Hospital vi.Hospital  "},{"text":" 12.At what age did you first give solid or semisolid food to [child's name]? What kind of solid or semi-solid food was given to (Child's Name) in the last 24 hours? (e.g. kenkey, banku, koko, tuo zaafi, akple, rice, mashed yam, weanimix)…………………… 15. How many times did (Name of child) eat solid or semi-solid food or soft foods other than liquids yesterday during the day or at night? …………………………….16. Please, indicate whether your CHILD ate from the following food groups during the past 24 hours whether at home or outside the home. , or butter added to food or used for cooking SPICES CONDIMENTS, BEVERAGES Spices (black pepper, salt), condiments(soy sauce, hot sauce),coffee, tea, alcoholic beverages OR LOCAL examples 17. What do you consider as the major constraint to feeding your child so that he/she grows well? Reliance of firewood and time demands reduces the frequency of cooking.SECTION C: CHILD MORBIDITY AND UTILIZATION OF HEALTH SERVICES1. Has (Name of child) had an illness with a cough that comes from the chest at any time in the last two weeks? Name of child) had Fever/Malaria: High temperature with shivering/ suspected malaria in the last two weeks?i.Yes ii. No iii. Don't know 4. The last time [child's name] was sick, did you offer less, more or the same amount of breast milk as when [child's name] is healthy? (If response is \"less\", ask additional questions to determine why.) i. Less, because the child did not want it ii. iv. Infusion at the hospital leaves etc. iv.Infusion at the hospitalleaves etc. v. Other (specify)………………………………………………………………………… v.Other (specify)………………………………………………………………………… VITAMIN A RICH FRUITS vi. Not Applicable (Child had no diarrhoea) Ripe mangoes, papayas + other locally available vitamin- VITAMIN A RICH FRUITS vi. Not Applicable (Child had no diarrhoea) Ripe mangoes, papayas + other locally available vitamin-   A rich fruits A rich fruits 3. Has (   3. Has ( DRIED FRUITS AND VEGETABLES Any form of dried vegetables (okro, pumpkin,baoba, DRIED FRUITS AND VEGETABLESAny form of dried vegetables (okro, pumpkin,baoba,   wild types wild types ORGAN MEAT (IRON-RICH) Liver, kidney or other organ meats or blood-based foods ORGAN MEAT (IRON-RICH)Liver, kidney or other organ meats or blood-based foods FLESH MEATS Beef, pork, lamb, goat, rabbit, wild game, chicken, duck, FLESH MEATSBeef, pork, lamb, goat, rabbit, wild game, chicken, duck, i. Before 6 months or other birds i.Before 6 monthsor other birds ii. EGGS At Six months  ii. EGGSAt Six months iii. FISH Seven to 9 months Fried, or dried, or shellfish iii. FISHSeven to 9 monthsFried, or dried, or shellfish iv. LEGUMES, NUTS, AND SEEDS After nine months Beans, peas, lentils, nuts, seeds, or foods made from iv. LEGUMES, NUTS, AND SEEDS After nine monthsBeans, peas, lentils, nuts, seeds, or foods made from   these these v. Yet to start  v.Yet to start MILK AND MILK PRODUCTS Milk, cheese, yogurt or other milk products MILK AND MILK PRODUCTSMilk, cheese, yogurt or other milk products vi. Don't know  vi.Don't know 13. Yesterday did [child's name] eat any solid or semi-solid foods? i. Yes ii. No iii. Does not apply (child does not eat solid foods) iv. Does not know Examples OILS AND FATS Oils, fatsi. Poor access (e.g. poverty) to nutritious foods ii. Lack of time iii. Lack of access to clean water iv. Low crop production yields 14.Food group v. YES/NO 13. Yesterday did [child's name] eat any solid or semi-solid foods? i. Yes ii. No iii. Does not apply (child does not eat solid foods) iv. Does not know Examples OILS AND FATS Oils, fatsi. Poor access (e.g. poverty) to nutritious foods ii. Lack of time iii. Lack of access to clean water iv. Low crop production yields 14.Food group v.YES/NO CEREALS  Bread, noodles, biscuits, any other food made from CEREALSBread, noodles, biscuits, any other food made from   millet, sorghum, maize, rice, wheat. millet, sorghum, maize, rice, wheat. VIITAMIN A RICH VEGETABLES i.Yes ii. No iii. Don't know Pumpkin, carrots, squash, or sweet potatoes that are VIITAMIN A RICH VEGETABLES i.Yes ii. No iii. Don't knowPumpkin, carrots, squash, or sweet potatoes that are AND TUBERS 2a. Have the child had diarrhoea in the past two weeks? orange inside + other locally available vitamin -A rich vegetables (e.g. Sweet pepper) i.Yes ii. No iii. Don't know AND TUBERS 2a. Have the child had diarrhoea in the past two weeks? orange inside + other locally available vitamin -A rich vegetables (e.g. Sweet pepper) i.Yes ii. No iii. Don't know WHITE TUBERS AND ROOTS 2b. When (name of child) had diarrhoea, what treatment, if any, did you give? White potatoes, white yam, cassava, or food made from WHITE TUBERS AND ROOTS 2b. When (name of child) had diarrhoea, what treatment, if any, did you give? White potatoes, white yam, cassava, or food made from i. Nothing roots. i.Nothingroots. DARK GREEN LEAFY VEGETABLES ii. ORS iii. Sugar-salt solution Dark green leafy vegetables, including wild ones + other locally available vitamin-A rich leaves such as cassava DARK GREEN LEAFY VEGETABLES ii. ORS iii. Sugar-salt solutionDark green leafy vegetables, including wild ones + other locally available vitamin-A rich leaves such as cassava  "},{"text":" Record from the Child Health Record Card the number of times in the last 4 months (Name of child) was weighed:.................................. SECTION D: SOCIO-ECONOMIC STATUS ASSESSMENT 1. What type of house do members of the household dwell in?  healer healer v. Private Clinic v.Private Clinic vi. Public health facility/ PHC vi.Public health facility/ PHC vii. Drug Peddler vii.Drug Peddler viii. Chemical Store viii.Chemical Store 7. During the past 6 months, did [child's name] ever take a vitamin A capsule, supplement or syrup? 7. During the past 6 months, did [child's name] ever take a vitamin A capsule, supplement or syrup? i. Yes i.Yes ii. No ii.No iii. Does not know iii.Does not know 8.  8.  "}],"sieverID":"c2da6d99-d1b3-4c42-bd05-f970d4711d9b","abstract":""}
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