Peer-reviewed article
Understanding the geographical burden of stunting in India: A regression‐decomposition analysis of district‐level data from 2015–16
Purnima Menon, Derek Headey, Rasmi Avula, Phuong Hong Nguyen ·
Summary
Written by AI, not yet AICS's view · claude-sonnet-5-5The study uses district-level data from India's 2015-16 National Family Health Survey, covering 601,509 households in 640 districts, to map stunting among young children and identify what explains differences between districts. Stunting prevalence was 38.4% nationally and ranged widely across districts, with high-stunting districts clustered in the north and centre. The gap between high- and low-stunting districts was explained by several factors, including women's low body mass index, education, children's diet, household assets, open defecation, age at marriage, antenatal care and household size. The authors conclude that stunting needs a nationwide focus, with district-specific attention to key determinants.
Key points
- India accounts for approximately one third of the world's stunted preschoolers.
- National stunting prevalence was 38.4%, ranging from 12.4% to 65.1% across districts.
- 239 of 640 districts had stunting above 40%, and 202 had prevalence of 30-40%.
- Women's low BMI explained 19% of the difference between high- and low-stunting districts, education 12%, and children's adequate diet 9%.
- The decomposition models explained 71% of the observed difference in stunting prevalence.
Limitations
The analysis uses district-level aggregate data from a single survey round, so it describes associations between districts and cannot show that any factor causes stunting or that changing it would reduce stunting. The abstract does not describe how well the data capture individual children or how the remaining 29% of the difference is explained.
Abstract
AbstractIndia 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.