Child Malnutrition in the Democratic Republic of the Congo: A Bayesian Gaussian Regression Analysis Using the 2023–24 Demographic and Health Survey

This repository contains the code and documentation for a Bayesian Gaussian regression analysis of child malnutrition in the Democratic Republic of the Congo (DRC). The analysis uses the 2023–24 Demographic and Health Survey (DHS) to examine how child, maternal, household and geographic factors relate to nutritional status in children under five years. The outcome is [height-for-age / weight-for-age / weight-for-height z-scores], modelled as continuous variables with Gaussian likelihoods. The deposit includes: analysis scripts in R, with the model specification, priors, sampling settings and convergence and posterior checks; the Quarto source for the manuscript, tables and figures; a README with the software versions, the run order and the random seed. The survey data are not included, because DHS data cannot be redistributed. They can be requested free of charge from the DHS Program (dhsprogram.com) by registering and applying for the DRC 2023–24 dataset. The README lists the file names and variables used, so that the analysis can be reproduced. Keywords: child malnutrition; stunting; Democratic Republic of the Congo; Demographic and Health Survey; Bayesian regression; Gaussian regression; reproducibility.