Multilevel analysis of geographic variation among correlates of child undernutrition in India.
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ABSTRACT:
SUBMITTER: Jain A
PROVIDER: S-EPMC8189194 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:ObjectiveThis study aims to quantify the extent to which people's use of tobacco products varies by local areas (city ward and village) across India and the variation in this clustering by tobacco products.DesignCross-sectional study.Setting and participantsData on 73 954 adults across 2547 city wards and villages were available for analysis from 30 states and 2 union territories in India.Primary and secondary outcome measuresWe included as primary outcomes self-reported any tobacco use, current cigarette smoking, current bidi smoking, current smokeless tobacco use and a derived variable for dual use describing respondents who engaged in both smoking and smokeless tobacco use.ResultsThe median risk of an individual using tobacco was 1.64 times greater if a person hypothetically moved from an area of low to high risk of tobacco use (95% CI: 1.60 to 1.69). Area-level partitioning of variation differed by tobacco product used. Median ORs ranged from 1.77 for smokeless tobacco use to 2.53 for dual use.ConclusionsTobacco use is highly clustered geographically in India. To be effective in India, policy interventions should be directed to influence specific local contextual factors on adult tobacco use. Where people live in India influences their use of tobacco, and this association may be greater than has been observed in other settings. Tailoring tobacco control policies for local areas in India may, therefore, provide substantial public health benefits.
| S-EPMC7307551 | 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: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: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:BackgroundChild malnutrition remains a major public health issue in India. Along with myriad upstream and social determinants of these adverse outcomes, recent studies have highlighted regional differences in mean child malnutrition rates. This research helps policy makers look between urban and rural communities and states to take a population-level approach to addressing the root causes of child malnutrition. However, one gap in this between-population approach has been the omission of households as a unit of analysis. Households could represent important sources of variation in child malnutrition within communities, districts, and states.MethodsUsing the fourth round of India's National Family Health Survey from 2015 to 2016, we analyzed four and five-level multilevel models to estimate the proportion of variation in child malnutrition attributable to states, districts, communities, households, and children.ResultsOverall, we found that of the four levels that children were nested in (households, communities, districts, and states), the greatest proportion of variation in child height-for-age Z score, weight-for-age Z score, weight-for-height Z score, hemoglobin, birthweight, stunting, underweight, wasting, anemia, and low birthweight was attributable to households. Furthermore, we found that when the household level is omitted from models, the variance estimates for communities and children are overestimated.ConclusionsThese findings highlight the importance of households as an important source of clustering and variation in child malnutrition outcomes. As such, policies and interventions should address household-level social determinants, such as asset and social deprivations, in order to prevent poor child growth outcomes among the most vulnerable households in India.
| S-EPMC8507104 | biostudies-literature
Project description:In the last few decades, the prevalence of hypertension has been drastically increased in India. The present study estimates the current prevalence of hypertension and its correlates in the state of Maharashtra. The variation in the prevalence of hypertension associated with individual-level characteristics is explained at the community and district level.Data is used from the recent round of District Level Household & Facility Survey (DLHS-4), 2012-13. The DLHS-4 has used the nationally representative sample, collected through multistage stratified sampling procedure. A similar sampling frame, used in NSSO-2007-08, has been followed. The chi-square test is used to show the significance level of the association between the estimated prevalence of hypertension and its correlates. Multilevel regression analysis is carried out to investigate the effects of individual and community level factors on the prevalence of hypertension.The overall prevalence of hypertension is 25% in Maharashtra, and a huge variation in the prevalence of hypertension is found across the districts. Dhule, Gadchiroli (with a low HDI rank), Mumbai and Satara (with higher HDI rank) are the districts with the higher (above 30%) prevalence of high blood pressure. The prevalence also significantly varies according to different correlates. The prevalence of high blood pressure is higher among elderly population (40%), among males (28%), in the urban areas (27%) and in the richest wealth quintile (28%). The prevalence is also higher among cigarette smokers (31%), alcohol consumers (30%) and people with obesity (38%) as compared to their counterparts. The results of the multilevel analysis show that the older and obese persons are at four-time higher risk of hypertension. Again, age, sex, marital status, place of residence, wealth status, unhealthy habits (i.e. smoking and alcohol consumption) and BMI are significantly associated with hypertension. The results of VPC statistics show that 14% of hypertension prevalence could be attributed to differences at the community level.The prevalence of hypertension largely varies in the districts of Maharashtra irrespective of their level of socio-economic development (i.e. HDI rank). The variation in the rate of prevalence of hypertension is higher in the community (PSU) level as compared to the variation in the prevalence rate at the district level. Hypertension is attributable to the modifiable factors like risky lifestyle practices.
| S-EPMC5798824 | 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:BackgroundThe rate of caesarean delivery has increased markedly both globally and within India. However, there is considerable variation within countries. No previous studies have examined the relative importance of multiple geographic levels in shaping the distribution of caesarean delivery and to what extent they can be explained by individual-level risk factors.ObjectivesTo describe geographic variation in caesarean delivery and quantify the contribution of individual-level risk factors to the variation in India.MethodsWe conducted four-level logistic regression analysis to partition total variation in caesarean delivery to three geographic levels (states, districts and communities) and quantify the extent to which variance at each level was explained by a set of 20 sociodemographic, medical and institutional risk factors. Stratified analyses were conducted by the type of delivery facility (public/private).ResultsOverall prevalence of caesarean delivery was 19.3% in India in 2016. Most geographic variation was attributable to states (44%), followed by communities (32%), and lastly districts (24%). Adjustment for all risk factors explained 44%, 52% and 46% of variance for states, districts and communities, respectively. The proportion explained by individual risk factors was larger in public facilities than in private facilities at all three levels. A substantial proportion of between-population variation still existed even after clustering of individual risk factors was comprehensively adjusted for.ConclusionsDiverse contextual factors driving high or low rate of caesarean delivery at each geographic level should be explored in future studies so that tailored intervention can be implemented to reduce the overall variation in caesarean delivery.
| S-EPMC9292746 | biostudies-literature
Project description:ImportanceGeographic targeting of public health interventions is needed in resource-constrained developing countries.ObjectiveTo develop methods for estimating health and development indicators across micropolicy units, using assembly constituencies (ACs) in India as an example.Design, setting, and participantsThis cross-sectional study included children younger than 5 years who participated in the fourth National Family and Health Survey (NFHS-4), conducted between January 2015 and December 2016. Participants lived in 36 states and union territories and 640 districts in India. Children who had valid weight and height measures were selected for stunting, underweight, and wasting analysis, and children between age 6 and 59 months with valid blood hemoglobin concentration levels were included in the anemia analysis sample. The analysis was performed between February 1 and August 15, 2020.ExposuresA total of 3940 ACs were identified from the geographic location of primary sampling units in which the children's households were surveyed in NFHS-4.Main outcomes and measuresStunting, underweight, and wasting were defined according to the World Health Organization Child Growth Standards. Anemia was defined as blood hemoglobin concentration less than 11.0 g/dL.ResultsThe main analytic sample included 222 172 children (mean [SD] age, 30.03 [17.01] months; 114 902 [51.72%] boys) from 3940 ACs in the stunting, underweight, and wasting analysis and 215 593 children (mean [SD] age, 32.63 [15.47] months; 112 259 [52.07%] boys) from 3941 ACs in the anemia analysis. The burden of child undernutrition varied substantially across ACs: from 18.02% to 60.94% for stunting, with a median (IQR) of 35.56% (29.82%-42.42%); from 10.40% to 63.24% for underweight, with a median (IQR) of 32.82% (25.50%-40.96%); from 5.56% to 39.91% for wasting, with a median (IQR) of 19.91% (15.70%-24.27%); and from 18.63% to 83.05% for anemia, with a median (IQR) of 55.74% (48.41%-63.01%). The degree of inequality within states varied across states; those with high stunting, underweight, and wasting prevalence tended to have high levels of inequality. For example, Uttar Pradesh, Jharkhand, and Karnataka had high mean AC-level prevalence of child stunting (Uttar Pradesh, 45.29%; Jharkhand, 43.76%; Karnataka, 39.77%) and also large SDs (Uttar Pradesh, 6.90; Jharkhand, 6.02; Karnataka, 6.72). The Moran I indices ranged from 0.25 to 0.80, indicating varying levels of spatial autocorrelation in child undernutrition across the states in India. No substantial difference in AC-level child undernutrition prevalence was found after adjusting for possible random displacement of geographic location data.Conclusions and relevanceIn this cross-sectional study, substantial inequality in child undernutrition was found across ACs in India, suggesting the importance of considering local electoral units in designing targeted interventions. The methods presented in this paper can be further applied to measuring health and development indicators in small electoral units for enhanced geographic precision of public health data in developing countries.
| S-EPMC8556624 | 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