A spatial analysis of childhood stunting and its contextual correlates in India

Autor: Pralip Kumar Narzary, Preeti Dhillon, Rupam Bharti
Rok vydání: 2019
Předmět:
Zdroj: Clinical Epidemiology and Global Health. 7:488-495
ISSN: 2213-3984
DOI: 10.1016/j.cegh.2019.04.005
Popis: Introduction Despite various programmes aiming to improve the nutritional status of children, nearly 38% of children under age five are still stunted in India, and there is huge spatial variation across the states. Objectives The present study first examines the spatial clustering of childhood stunting and then investigates the contextual determinants including meteorological factors, poverty and crop production affecting childhood stunting. Methods The percentage of stunted children under 5 years of age is taken from the district factsheets of National Family Health Survey 2015–16 (NFHS-4). Other data are taken from Census of India (2011) and Ministry of Agriculture and Farmers Welfare. To fulfil the set objectives, the spatial analysis including Moran-I index and spatial regressions models are used. Results The spatial analysis shows a high degree of clustering (Moran's I: 0.65) in childhood stunting in districts of India. Extreme temperature of districts reveals a positive association with childhood stunting as nearly 40% of children from districts with maximum temperature above 40 °C were stunting. After controlling for socioeconomic factors, spatial regression reveals that a 1 °C increase in average annual temperature would lead to 0.134 increase in the percentage of stunted children. The study reveals a negative effect of district-level per-capita crop production, wealth and education levels on the childhood stunting. Conclusion The paper manifests the gigantic variations and clustering in the childhood malnutrition across districts of India. The study recommends to target the districts in hot spot areas, districts with extreme temperature and with low levels of crop production to fight against malnutrition under the umbrella of sustainable development goals.
Databáze: OpenAIRE