@LancetGH features a Bayesian analysis of nutrition survey data in #Afghanistan

Thursday, March 15, 2018

The current edition of Lancet Global Health features an analysis of health survey data using Bayesian modeling techniques to map nutritional status in the country:
The 2013 Afghanistan NNS is the largest, most comprehensive nutrition assessment of its kind to be done in the country. Designed to be representative at the national and provincial levels, the survey's aim was to provide estimates on various nutritional indicators, including anthropometry, infant and young child feeding, and micronutrient deficiencies, for women, children, adolescent girls, and the elderly in Afghanistan.
The specific objectives of our study were to estimate the district-level prevalence of nutritional status indicators among children (stunting, underweight, or wasting) and women of reproductive age (underweight or short stature) and to understand the major causes of undernutrition in women and children in Afghanistan through exploring a range of individual, household, community, and environmental risk factors.
What was interesting to me about this particular analysis (besides the maps) was the use of Bayesian modeling, which I now understand better after designing this visualization on county-level estimates of teen birth rates based on a Bayesian analysis. In addition to identifying socioeconomic factors correlated with the various nutritional variables of interest, the authors used the Bayesian model to populate a series of chloropleth maps on said variables:

Figure 2: Prevalence of child stunting, wasting, and underweight in districts of Afghanistan

Figure 3: Prevalence of underweight, obese, and overweight in women of reproductive age in districts of Afghanistan

Not surprisingly, nutritional indicators in children were directly related to things like household wealth, food insecurity, and maternal education and literacy. "Linear growth and weight of children younger than 5 years old were independently associated with household wealth, maternal literacy, maternal anthropometry, child age, food security, geography, and improved hygiene and sanitation conditions" - i.e., "children from richer households were taller, weighed more, and were less emaciated." Also not surprisingly, child malnutrition is at "alarming" levels in many areas, particularly those experiencing active conflict:
Districts with alarmingly high wasting prevalence (some exceeded 20%) were in central regions and regions bordering Pakistan, including the east, southeast, and south. The concurrent conflict and insecurity in these regions could be one explanation, particularly since a gradient of child emaciation across wealth status and maternal education was not evident.

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