ArticleMaternal & child nutrition2018
Understanding the geographical burden of stunting in India: A regression-decomposition analysis of district-level data from 2015-16.
Article in Maternal & child nutrition, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 57 papers.
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Who cites it
57 citing papers in PubMed.
- A river, frontline families, and the double-edged sword of community participation: how nutrition interventions are shaped at the village level in Dhubri, India.Health policy and planning · 2026Article
- Small area geographic variation in girl and boy child marriage in India: a district-level longitudinal analysis, 2016 and 2021.Journal of global health · 2025Article
- Progress in child nutrition outcomes: insights from India's recent experience.BMC public health · 2025Article
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- M-SAKHI - Mobile health solutions to help community providers promote maternal and infant nutrition and health: a description of development of the Program Impact Pathway using Theory of Change.Public health nutrition · 2024Article
- Open Defecation, Livestock Ownership, and Child Nutritional Status in India.The American journal of tropical medicine and hygiene · 2024Article
- The role of dairy consumption in the relationship between wealth and early life physical growth in India: evidence from multiple national surveys.BMC public health · 2024Article
- Ethnicity/caste and child anthropometric outcomes in India using the National Family Heath Survey 2015-16 and 2019-21.PloS one · 2024Article
- Trends and long-term variation explaining nutritional determinants of child linear growth: analysis of Bangladesh Demographic and Health Surveys 1996-2018.Public health nutrition · 2023Article
- Small area variations in four measures of poverty among Indian households: Econometric analysis of National Family Health Survey 2019-2021.Humanities & social sciences communications · 2023Article
- Trends in the prevalence and social determinants of stunting in India, 2005-2021: findings from three rounds of the National Family Health Survey.BMJ nutrition, prevention & health · 2023Article
- Article
- The Effects of Financial Stress and Household Socio-Economic Deprivation on the Malnutrition Statuses of Children under Five during the COVID-19 Lockdown in a Marginalized Region of South Punjab, Pakistan.Children (Basel, Switzerland) · 2022Article
- Birth length is the strongest predictor of linear growth status and stunting in the first 2 years of life after a preconception maternal nutrition intervention: the children of the Women First trial.The American journal of clinical nutrition · 2022Article
- Small area variations in low birth weight and small size of births in India.Maternal & child nutrition · 2022Article
- Predictive algorithm to stratify newborns at-risk for child undernutrition in India: Secondary analysis of the National Family Health Survey-4.Journal of global health · 2022Article
- Inequalities in childhood stunting: evidence from Sudan multiple indicator cluster surveys (2010-2014).BMC public health · 2022Article
- Modeling the potential impacts of improved monthly income on child stunting in India: a subnational geospatial perspective.BMJ open · 2022Article
- Socio-Economic and Environmental Determinants of Malnutrition in under Three Children: Evidence from PDHS-2018.Children (Basel, Switzerland) · 2022Article
- Region matters: Mapping the contours of undernourishment among children in Odisha, India.PloS one · 2022Article
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Abstract
India accounts for approximately one third of the world's total population of stunted preschoolers. Addressing global undernutrition, therefore, requires an understanding of the determinants of stunting across India's diverse states and districts. We created a district-level aggregate data set from the recently released 2015-2016 National and Family Health Survey, which covered 601,509 households in 640 districts. We used mapping and descriptive analyses to understand spatial differences in distribution of stunting. We then used population-weighted regressions to identify stunting determinants and regression-based decompositions to explain differences between high- and low-stunting districts across India. Stunting prevalence is high (38.4%) and varies considerably across districts (range: 12.4% to 65.1%), with 239 of the 640 districts have stunting levels above 40% and 202 have prevalence of 30-40%. High-stunting districts are heavily clustered in the north and centre of the country. Differences in stunting prevalence between low and high burden districts were explained by differences in women's low body mass index (19% of the difference), education (12%), children's adequate diet (9%), assets (7%), open defecation (7%), age at marriage (7%), antenatal care (6%), and household size (5%). The decomposition models explained 71% of the observed difference in stunting prevalence. Our findings emphasize the variability in stunting across India, reinforce the multifactorial determinants of stunting, and highlight that interdistrict differences in stunting are strongly explained by a multitude of economic, health, hygiene, and demographic factors. A nationwide focus for stunting prevention is required, while addressing critical determinants district-by-district to reduce inequalities and prevalence of childhood stunting.
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