Geospatial inequalities and determinants of nutritional status among women and children in Afghanistan: an...

Undernutrition is a pervasive condition in Afghanistan, and prevalence is among the highest in the world. We aimed to comprehensively assess district-level geographical disparities and determinants of nutritional status (stunting, wasting, or underweight) among women and children in Afghanistan.

The study used individualised data from the recent Afghanistan National Nutrition Survey 2013. Outcome variables were based on growth and weight anthropometry data, which we analysed linearly as Z scores and as dichotomous categories. We analysed data from a total of almost 14 000 index mother-child pairs using Bayesian spatial and generalised least squares regression models accounting for the complex survey design.

We noted that childhood stunting, underweight, and combined stunting and wasting were consistently highest in districts in Farah, Nangarhar, Nuristan, Kunar, Paktia, and Badakhshan provinces. District prevalence ranged from 4% to 84% for childhood stunting and 5% to 66% for underweight. Child wasting exceeded 20% in central and high-conflict regions that bordered Pakistan including east, southeast, and south. Among mothers, dual burden of underweight and overweight or obesity existed in districts of north, northeast, central, and central highlands (prevalence of 15-20%). Linear growth and weight of children were independently associated with household wealth, maternal literacy, maternal anthropometry, child age, food security, geography, and improved hygiene and sanitation conditions. The mother's body-mass index was determined by many of the same factors, in addition to ethnolinguistic status and parity. Younger mothers (<20 years old) were more underweight and shorter than older mothers (aged 20-49 years).

Afghanistan's rapidly changing political, socioeconomic, and insecurity landscape has both direct and indirect implications on population nutrition. Novel evidence from our study can be used to understand these multifactorial determinants and to identify granular disparities for local level tracking, planning, and implementation of nutritional interventions.

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