Analysis of Childhood Morbidity with Geoadditive Probit and Latent Variable Model: A case study for Egypt

Childhood diseases are a major cause of death of children in the developing world. In developing countries a quarter of infant and childhood mortality is related to childhood disease particularly to diarrhea. Our case study is based on the 2003 Demographic and Health Survey for Egypt(EDHS). It provided data on the prevalence and treatment of common childhood disease such as diarrhea, cough and fever which are seen as symptoms or indicators of children’s health status, causing increased morbidity and mortality. These causes are often associated with a number of risk factors, including inadequate antenatal care, lack of or inadequate vaccination and environmental factors which affected the health of child in early years, various bio-demographic and socio-economic variables. In this paper we investigate the impact of such factors on childhood disease with flexible geaodditive models. These models allow to analyze usual linear effects of covariates, nonlinear effects of continuous covariates, and small-area regional effects within a unified, semi-parametric Bayesian framework for modelling and inference. As a first step we employ separate geoadditive probit models to the binary target variables for diarrhea, cough and fever using covariate information from the EDHS. Based on these results, we then apply recently developed geoadditive latent variable models where the three observable disease variables are taken as indicators for the latent individual variable "health status" or "frailty" of a child. This modelling approach allows to study the common influence of risk factors on individual frailties of children, thereby automatically accounting for association between diseases as indicators for health status.