Spatial modeling of child malnutrition attributable to drought in India.

OBJECTIVES: Indian agriculture is mostly dependent on monsoon. Poor and irregular rainfall may result in crop failure and food shortage among the vulnerable population. This study examined the variations in drought condition and its association with under age 5 child malnutrition across the districts of India. METHODS: Using remote sensing and National Family Health Survey (NFHS-4) data, univariate Moran's I and bivariate local indicator of spatial autocorrelation (LISA) maps were generated to assess the spatial autocorrelation and clustering. To empirically check the association, we applied multivariate ordinary least square and spatial autoregressive models. RESULTS: The study identified highly significant spatial dependence of drought followed by underweight, stunting, and wasting. Bivariate LISA maps showed negative spatial autocorrelation between drought and child malnutrition. Regression results suggest agricultural drought is substantially associated with stunting. An increasing value of drought showed statistical association with the decreasing (beta = - 8.251; p value < 0.05) prevalence rate of child stunting across India. CONCLUSIONS: This study provides evidence of child undernutrition attributable to drought condition, which will further improve the knowledge of human vulnerability and adaptability in the climatic context.