Identifying climatic and non-climatic determinants of malnutrition prevalence in Bangladesh: A country-wide cross-sectional spatial analysis

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 arc seconds (∼ 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.