Joint modelling of child poverty and malnutrition in children aged 6 to 59 months in Malawi.

Abstract

The objective of this study was to identify risk factors associated with poverty and malnutrition of children among the ages 6-to-59 months in the country of Malawi, making use of the joint model. By joint modelling, we refer to simultaneously analysing two or more response variables emanating from the same individual. Using the 2015/2016 Malawi Demographic and Health Survey, we jointly examine the relationship that exists between poverty and malnutrition of children among 6-to-59 months in Malawi. Jointly modelling these two outcome variables is appropriate since it is expected that people that live under poverty would have a poor nutrition system, and if a child is malnourished, the likelihood that they come from a poor family is greatly enhanced. Jointly modelling correlated outcomes can improve the efficiency of parameter estimates compared to fitting separate models for each outcome, as joint models have better control over type I error rates in multiple tests. A generalized linear mixed model (GLMM) was adopted and a Bayesian approach was used for parameter estimation. The potential risk factors considered in this study comprised of the childs age in months, gender of child, birth weight, birth order, mothers education level, head of household sex, language, household smoking habit, anaemic level, type of residence (urban or rural), region, toilet facility, source of drinking water, and multiple births. Each response was modelled separately as well as jointly and the results compared. The R package MCMCglmm was used in the analyses. The joint model revealed a positive association between malnutrition of children and poverty in the household.