Estimating the Burden of Child Undernutrition for Smaller Electoral Units in India
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SUBMITTER: Kim J
PROVIDER: S-EPMC8556624 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Background and objectivesStudies in low-and middle-income countries where nutrition transition is underway provides mixed evidence of double burden of maternal overnutrition and child undernutrition among mother-child pairs. Shifting dietary pattern and rapid increase in overweight/obesity among adults with persistent child undernutrition indicate that India is experiencing nutrition transition and double burden of malnutrition. Hence, the study explores the presence of and the factors associated with mother-child dyads of over- and undernutrition in India.Methods and materialsThe study uses National Family Health Survey 2015-16 data. The analytic sample consists of 28,817 weighted mother-child pairs where an overweight/obese mother is paired with an undernourished child. The nutritional status of children is defined according to WHO 2006 child growth standards as underweight (i.e., low weight-for-age), stunting (i.e., low height-for-age) and wasting (i.e., low weight-for-height). Maternal overweight/obesity (i.e., BMI ≥ 25 kg/m2) is defined using adult BMI criterion. Descriptive, bivariate, and adjusted multivariable logistic regression analysis are conducted.ResultsOf the overweight/obese mothers, 21.3%, 26.5%, and 14% have underweight, stunted, and wasted children respectively. In adjusted models, maternal short stature (aOR: 2.94, 95% CI: 2.30-3.75), age of child (aOR: 3.29, 95% CI: 2.76-3.92), and poorest wealth status (aOR: 2.01, 95% CI: 1.59-2.54) are significant predictors of overweight/obese mothers and stunted child pairs. Similarly, poor wealth status (aOR: 1.68, 95% CI:1.32-2.14), maternal stature (aOR: 2.70, 95% CI: 2.08-3.52), and child aged 2-5 years (aOR: 1.77, 95% CI:1.51-2.08) are also significantly associated with higher occurrence of overweight/obese mother and-underweight child pairs.ConclusionFindings of the study are consistent with the phase of nutrition transition and double burden of malnutrition. The paper concludes with suggestions to improve the socioeconomic condition, more strategic nutrition specific investments and policy interventions to eliminate all forms of malnutrition for achieving SDGs.
| S-EPMC9205528 | biostudies-literature
Project description:In India, data on key developmental indicators used to formulate policies and interventions are routinely available for the administrative unit of districts but not for the political unit of parliamentary constituencies (PC). Recently, Swaminathan et al. proposed two methodologies to generate PC estimates using randomly displaced GPS locations of the sampling clusters ('direct') and by building a crosswalk between districts and PCs using boundary shapefiles ('indirect'). We advance these methodologies by using precision-weighted estimations based on hierarchical logistic regression modeling to account for the complex survey design and sampling variability. We exemplify this application using the latest National Family Health Survey (NFHS, 2016) to generate PC-level estimates for two important indicators of child malnutrition - stunting and low birth weight - that are being monitored by the Government of India for the National Nutrition Mission targets. Overall, we found a substantial variation in child malnutrition across 543 PCs. The different methodologies yielded highly consistent estimates with correlation ranging r = 0.92-0.99 for stunting and r = 0.81-0.98 for low birth weight. For analyses involving data with comparable nature to the NFHS (i.e., complex data structure and possibility to identify a potential PC membership), modeling for precision-weighted estimates and direct methodology are preferable. Further field work and data collection at the PC level are necessary to accurately validate our estimates. An ideal solution to overcome this gap in data for PCs would be to make PC identifiers available in routinely collected surveys and the Census.
| S-EPMC6384327 | biostudies-literature
Project description:BackgroundEconomic growth is widely perceived as a major policy instrument in reducing childhood undernutrition in India. We assessed the association between changes in state per capita income and the risk of undernutrition among children in India.Methods and findingsData for this analysis came from three cross-sectional waves of the National Family Health Survey (NFHS) conducted in 1992-93, 1998-99, and 2005-06 in India. The sample sizes in the three waves were 33,816, 30,383, and 28,876 children, respectively. After excluding observations missing on the child anthropometric measures and the independent variables included in the study, the analytic sample size was 28,066, 26,121, and 23,139, respectively, with a pooled sample size of 77,326 children. The proportion of missing data was 12%-20%. The outcomes were underweight, stunting, and wasting, defined as more than two standard deviations below the World Health Organization-determined median scores by age and gender. We also examined severe underweight, severe stunting, and severe wasting. The main exposure of interest was per capita income at the state level at each survey period measured as per capita net state domestic product measured in 2008 prices. We estimated fixed and random effects logistic models that accounted for the clustering of the data. In models that did not account for survey-period effects, there appeared to be an inverse association between state economic growth and risk of undernutrition among children. However, in models accounting for data structure related to repeated cross-sectional design through survey period effects, state economic growth was not associated with the risk of underweight (OR 1.01, 95% CI 0.98, 1.04), stunting (OR 1.02, 95% CI 0.99, 1.05), and wasting (OR 0.99, 95% CI 0.96, 1.02). Adjustment for demographic and socioeconomic covariates did not alter these estimates. Similar patterns were observed for severe undernutrition outcomes.ConclusionsWe failed to find consistent evidence that economic growth leads to reduction in childhood undernutrition in India. Direct investments in appropriate health interventions may be necessary to reduce childhood undernutrition in India. Please see later in the article for the Editors' Summary.
| S-EPMC3050933 | biostudies-literature
Project description:BackgroundWith increasing urbanization in India, child growth among urban poor has emerged as a paramount public health concern amidst the continuously growing slum population and deteriorating quality of life. This study analyses child undernutrition among urban poor and non-poor and decomposes the contribution of various factors influencing socio-economic inequality. This paper uses data from two recent rounds of National Family Health Survey (NFHS-3&4) conducted during 2005-06 and 2015-16.MethodsThe concentration index (CI) and the concentration curve (CC) measure socio-economic inequality in child growth in terms of stunting, wasting, and underweight. Wagstaff decomposition further analyses key contributors in CI by segregating significant covariates into five groups-mother's factor, health-seeking factors, environmental factors, child factors, and socio-economic factors.ResultsThe prevalence of child undernutrition was more pronounced among children from poor socio-economic strata. The concentration index decreased for stunting (-?0.186 to -?0.156), underweight (-?0.213 to -?0.162) and wasting (-?0.116 to -?0.045) from 2005 to 06 to 2015-16 respectively. The steepness in growth was more among urban poor than among urban non-poor in every age interval. Maternal education contributed about 19%, 29%, and 33% to the inequality in stunting, underweight and wasting, respectively during 2005-06. During 2005-06 as well as 2015-16, maternal factors (specifically mother's education) were the highest contributory factors in explaining rich-poor inequality in stunting as well as underweight. More than 85% of the economic inequality in stunting, underweight, and wasting among urban children were explained by maternal factors, environmental factors, and health-seeking factors.ConclusionAll the nutrition-specific and nutrition-sensitive interventions in urban areas should be prioritized, focusing on urban poor, who are often clustered in low-income slums. Rich-poor inequality in child growth calls out for integration and convergence of nutrition interventions with policy interventions aimed at poverty reduction. There is also a need to expand the scope of the Integrated Child Development Services (ICDS) program to provide mass education regarding nutrition and health by making provisions of home visits of workers primarily focusing on pregnant and lactating mothers.
| S-EPMC7713021 | biostudies-literature
Project description:There are emerging opportunities to assess health indicators at truly small areas with increasing availability of data geocoded to micro geographic units and advanced modeling techniques. The utility of such fine-grained data can be fully leveraged if linked to local governance units that are accountable for implementation of programs and interventions. We used data from the 2011 Indian Census for village-level demographic and amenities features and the 2016 Indian Demographic and Health Survey in a bias-corrected semisupervised regression framework to predict child anthropometric failures for all villages in India. Of the total geographic variation in predicted child anthropometric failure estimates, 54.2 to 72.3% were attributed to the village level followed by 20.6 to 39.5% to the state level. The mean predicted stunting was 37.9% (SD: 10.1%; IQR: 31.2 to 44.7%), and substantial variation was found across villages ranging from less than 5% for 691 villages to over 70% in 453 villages. Estimates at the village level can potentially shift the paradigm of policy discussion in India by enabling more informed prioritization and precise targeting. The proposed methodology can be adapted and applied to diverse population health indicators, and in other contexts, to reveal spatial heterogeneity at a finer geographic scale and identify local areas with the greatest needs and with direct implications for actions to take place.
| S-EPMC8106321 | biostudies-literature
Project description:Prior research has identified a number of risk factors ranging from inadequate household sanitation to maternal characteristics as important determinants of child malnutrition and health in India. What is less known is the extent to which these individual-level risk factors are geographically distributed. Assessing the geographic distribution, especially at multiple levels, matters as it can inform where, and at what level, interventions should be targeted. The three levels of significance in the Indian context are villages, districts, and states. Thus, the purpose of this paper was to (a) examine what proportion of the variation in 21 risk factors is attributable to villages, districts, and states in India and (b) elucidate the specific states where these risk factors are clustered within India. Using the fourth National Family Health Survey dataset, from 2015 to 2016, we found that the proportion of variation attributable to villages ranged from 14% to 63%, 10% to 29% for districts and 17% to 62% for states. Furthermore, we found that Bihar, Jharkhand, Madhya Pradesh, and Uttar Pradesh were in the highest risk quintile for more than 10 of the risk factors included in our study. This is an indication of geographic clustering of risk factors. The risk factors that are clustered in states such as Bihar, Jharkhand, Madhya Pradesh and Uttar Pradesh underscore the need for policies and interventions that address a broader set of child malnutrition determinants beyond those that are nutrition specific.
| S-EPMC8189194 | biostudies-literature
Project description:In India, districts serve as central policy unit for program development, administration and implementation. The one-size-fits-all approach based on average prevalence estimates at the district level fails to capture the substantial small area variation. In addition to district average, heterogeneity within districts should be considered in policy design. The objective of this study was to quantify the extent of small area variation in child stunting, underweight and wasting across 36 states/Union Territories (UTs), 640 districts (and 543 PCs), and villages/blocks in India. We utilized the 4th round of Indian National Family Health Survey (NFHS-4) conducted in 2015-2016. The study population included 225,002 children aged 0-59 months whose height and weight information were available. Stunting was defined as height-for-age z-score below 2 SD from the World Health Organization child growth reference standards. Similarly, underweight and wasting were each defined as weight-for-age < -2 SD and weight-for-height < -2 SD from the age- and sex-specific medians. We adopted a four-level logistic regression model to partition the total variation in stunting, underweight and wasting. We computed precision-weighted prevalence of child anthropometric failures across districts and PCs as well as within-district/PC variation using standard deviation (SD) measures. For stunting, 56.4% (var: 0.237; SE: 0.008) of the total variation was attributed to villages/blocks, followed by 25.8% (var: 0.109; SE: 0.030) to states/UTs, and 17.7% (Var: 0.074; SE: 0.006) to districts. For underweight and wasting, villages/blocks accounted for 38.4% (var: 0.224; SE: 0.007) and 50% (var: 0.285; SE: 0.009), respectively, of the total contextual variance in India. Similar findings were shown in multilevel models incorporating PC as a geographical unit instead of districts. We found high positive correlations between mean prevalence and SD for stunting (r = 0.780, p < 0.001), underweight (r = 0.860, p < 0.001), and wasting (r = 0.857, p < 0.001) across all districts in India. A similar pattern of correlation was found for PCs. Within-district and within-PC variation are the primary source of variation for child malnutrition in India. Our results suggest the importance of considering heterogeneity within districts and PCs when planning and administering child nutrition policies.
| S-EPMC7907088 | biostudies-literature
Project description:The public health burden of nutritional deficiency and child mortality is the major challenge India is facing upfront. In this context, using National Family Health Survey, 2015-16 data, this study estimated rate of composite index of anthropometric failure (CIAF) among Indian children by their population characteristics, across states and examined the multilevel contextual determinants. We further investigated district level burden of infant and child mortality in terms of multiple anthropometric failure prevalence across India. The multilevel analysis confirms a significant state, district and PSU level variation in the prevalence of anthropometric failures. Factors like- place of residence, household's economic wellbeing, mother's educational attainment, age, immunization status and drinking water significantly determine the different forms of multiple anthropometric failures. Wealth status of the household and mother's educational status show a clear gradient in terms of the estimated odds ratios. The district level estimation of infant and child mortality demonstrates that districts with higher burden of multiple anthropometric failures show elevated risk of infant and child mortality. Unlike previous studies, this study does not use the conventional indices, instead considered the CIAF to identify the exact and severe form of undernutrition among Indian children and the associated nexus with infant and child mortality at the district level.
| S-EPMC7710716 | biostudies-literature
Project description:In India and worldwide, there has been increased strategic focus on multisectoral convergence of nutrition-specific and nutrition-sensitive interventions to attain rapid reductions in child undernutrition. For instance, a Convergence Action Plan in India has been formed to synchronize and converge various nutrition-related interventions across ministries of union and state governments under a single umbrella. Given the large variation in number, nature and impact of these interventions, this paper aims to quantify the contribution of each intervention (proxied by relevant covariates) toward reducing child stunting and underweight in India. The interventions are classified under six sectors: (a) health, (b) women and child development, (c) education, (d) water, sanitation, and hygiene, (e) clean energy, and (f) growth sector. We estimate the potential reduction in child stunting and underweight in a counterfactual scenario of "convergence" where all the interventions across all the sectors are simultaneously and successfully implemented. The findings from our econometric analysis suggests that under this counterfactual scenario, a reduction of 18.37% points (95% CI: 16.77; 19.95) in stunting and 20.26% points (95% CI: 19.13; 21.39) in underweight can be potentially achieved. Across all the sectors, women and child development and clean energy were identified as the biggest contributors to the potential reductions in stunting and underweight, underscoring the importance of improving sanitation-related practices and clean cooking fuel. The overall impact of this convergent action was relatively stronger for less developed districts. These findings reiterate a clear role and scope of convergent action in achieving India's national nutritional goals. This warrants a complete outreach of all the interventions from different sectors.
| S-EPMC7188776 | biostudies-literature
Project description:The double burden of overnutrition and undernutrition is rapidly becoming a public health concern in low- and middle-income countries. We explored the occurrence of mother-child pairs of over- and undernutrition and the contributing factors using the 2014 Kenya Demographic and Health Survey data. A weighted sample of 7830 mother-child pairs was analysed. The children's nutritional status was determined using the WHO 2006 reference standards while maternal nutritional status was determined with BMI. Descriptive statistics, bivariate and multivariate logistic regression analysis were conducted. The proportion of overweight and obese mothers was 26 % (18·8 % overweight and 7·2 % obese). The prevalence of child stunting, underweight and wasting was 26·3, 12·8 and 5·1 %, respectively. Out of the overweight/obese mothers (weighted n 2034), 20 % had stunted children, 5·4 % underweight children and 3·1 % wasted children. Overweight/obese mother-stunted child pairs and overweight/obese mother-underweight child pairs were less likely to occur in the rural areas (adjusted OR (aOR) = 0·43; P < 0·01) in comparison with those residing in the urban areas (aOR = 0·54; P = 0·01). Children aged more than 6 months were more likely to be in the double burden dyads compared with children below 6 months of age (P < 0·01). The double burden mother-child dyads were more likely to be observed in wealthier households. Mother-child double burden is a notable public health problem in Kenya. Household wealth and urban residence are determinants of the double burden. There is need for target-specific interventions to simultaneously address child undernutrition and maternal overweight/obesity.
| S-EPMC6984123 | biostudies-literature