Analysis of the spatial patterns of malnutrition among women in Nigeria with a Bayesian structured additive model

Malnutrition among women has severe consequences on their health, households and national development. The different forms of malnutrition among adult individuals are severe thinness, underweight, overweight and obesity which are usually assessed using height and weight indices calculated as body mass index (BMI). In this study, the spatial distributions of the various forms of malnutrition measured at the upper and lower tails of the BMI were accessed among women of reproductive age in Nigeria after accounting for the influence of socio-economic factors. Bayesian quantile regression that permits for inference on conditional quantiles, yielding a complete description of the functional changes among covariates at different quantiles of the response variable was adopted. Markov random field and Bayesian P-splines were used as prior distributions for the spatial and nonlinear effects respectively, while computation was based on MCMC approach. Data were derived from the 2013 Nigeria Demographic and Health Survey. Findings indicate the existence of spatial structure in the various forms of malnutrition with neighbouring states sharing similar patterns and that the socio-economic variables exact dissimilar influence on the various forms of malnutrition. The study provides valuable insights for policy makers in the quest for halting all forms of malnutrition among Nigerian women.