| Understanding the geographical burden of stunting in India: A regression-decomposition analysis of district-level data from 2015–16 |
| Authors: |
Purnima Menon, Derek Headey, Rasmi Avula, and Phuong Hong Nguyen |
| Source: |
Maternal and Child Nutrition, e12620; DOI: 10.1111/mcn.12620 |
| Topic(s): |
Child health
GIS/GPS
Nutrition
Spatial analysis
|
| Country: |
Asia
India
|
| Published: |
APR 2018 |
| 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 highand
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.
KEYWORDS
child undernutrition, decomposition analysis, determinants, India, spatial analysis, stunting |
| Web: |
https://www.researchgate.net/publication/325337138_Understanding_the_geographical_burden_of_stunting_in_India_A_regression-decomposition_analysis_of_district-level_data_from_the_2015-16/fulltext/5b06a |
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