PloS one
Child malnutrition in the Democratic Republic of the Congo: A Bayesian Gaussian regression analysis using the 2023-24 demographic and health survey
By Tsala Dimbuene Z and Sampasa-Kanyinga H.
Abstract
Background
Child stunting remains a major public health challenge in the Democratic Republic of the Congo (DRC), reflecting persistent inequalities in child nutrition and health outcomes. This study examines the distribution and spatial variation of height-for-age z-scores (HAZ) among children under five, while also assessing the influence of selected demographic and socioeconomic factors.
Methods
Data were obtained from the 2023-2024 Demographic and Health Survey (DHS-8). A structured additive regression model was then applied to assess the effects of child age and maternal education, allowing for nonlinear relationships through smooth functions. To capture geographic heterogeneity, spatial effects were decomposed into structured (spatially correlated) and unstructured (area-specific random) components, enabling the identification of regional clustering and residual province-level variation in stunting.