Semiparametric Analysis of the Socio-Demographic and Spatial Determinants of Undernutrition in Two African Countries

We estimate semiparametric regression models of chronic
undernutrition (stunting) using the 1992 Demographic and Health
Surveys (DHS) from Tanzania and Zambia. We focus particularly on
the influence of the child's age, the mother's body mass index, and
spatial influences on chronic undernutrition. Conventional
parametric regression models are not flexible enough to cope with
possibly nonlinear effects of the continuous covariates and cannot
flexibly model spatial influences. We present a Bayesian
semiparametric analysis of the effects of these two covariates on
chronic undernutrition. Moreover, we investigate spatial
determinants of undernutrition in these two countries. Compared to
previous work with a simple fixed effects approach for the
influence of provinces, we model small scale district specific
effects using flexible spatial priors. Inference is fully Bayesian
and uses recent Markov chain Monte Carlo techniques.