Identifying climatic and non-climatic determinants of malnutrition prevalence in Bangladesh: A country-wide cross-sectional spatial analysis. (June 2021)

• Record Type: Journal Article
• Authors: Rabbi, Sifat E; Ali, Mohammad; Costa, Luis C.; Pradhan, Prajal; Rahman, Atiya; Yunus, Fakir Md; Kropp, Jürgen P.
• Is Part Of: Spatial and spatio-temporal epidemiology. Volume 37(2021)
• Publication Date: 2021-06
• Subjects: Malnutrition -- Under-five children -- Spatial variation determinants -- Socioeconomic -- Temperature -- Precipitation -- Bangladesh; Epidemiology -- Statistical methods -- Periodicals; Epidemiology -- Periodicals; 614.4072
• DOI: 10.1016/j.sste.2021.100422
• Languages: English
• ISSNs: 1877-5845

Abstract

Highlights: Malnutrition is multi-faceted in Bangladesh where climate plays a hidden role on its spatial distribution. Higher summer temperature or lower monsoon rainfall in a district is associated with lower malnutrition prevalence that linked with higher staple food production. Stunting prevalence was lower in districts with increased literacy, improved sanitation, greater road density and higher GDP per capita. Underweight prevalence was higher in districts with higher access to water, suggestive of unsafe water sources and use. Both climate and non-climate perspectives is important to understand spatial variations of malnutrition. Abstract: Child malnutrition is indisputably a multi-faceted phenomenon. Comprehending the aforesaid crucial issue this paper intended to identify climatic and non-climatic factors for the spatial variation of malnutrition prevalence in Bangladesh. The climatic data on temperature and rainfall are obtained from the WorldClim dataset. We obtained a set of global climate layers that included monthly data on minimum temperature, maximum temperature, mean temperature, and rainfall for the period 1960–1990, at a spatial resolution up to 30 ′onds (~ 1 × 1 km at the equator). The data are extracted at the district level using the zonal-statistics in QGIS. This study performed a spatial lag regression to evaluate association of malnutrition with climate characteristics and other factors. The prevalence of malnutrition exhibited substantial association with temperature and precipitation. Food production, water access, improved sanitation, literacy, road density, solvency ratio and GDP had a significant association with the spatial variation of malnutrition in Bangladesh.