Spatial Variability In The Association Of Ambient PM2.5 Exposure With Child Undernutrition In Sub-Saharan Africa

Abstract

Studies have associated ambient PM2.5 exposure with child undernutrition. However, the exposure–response relationship may vary across space. We therefore investigated spatial variability in ambient PM2.5 – child un dernutrition relationship in sub-Saharan Africa (SSA) merging several waves of Demographic and Health Survey data for 34 SSA countries for the period 1998 to 2022 with satellite-derived PM2.5 estimates. The study included 855,395 children with complete prenatal and postnatal PM2.5 exposure data. The prenatal and postnatal PM2.5 exposures were estimated using a weighted average of spatially-resolved annual PM2.5 estimates. We employed a Bayesian spatial model in R-INLA incorporating a spatially varying slope at the country level to investigate the variability in the exposure–response relationship. The model adjusted for individual- and area-level confounders whilst accounting for both structured and unstructured heterogeneity. A 10 µg/m3 increase in prenatal and postnatal PM2.5 exposure was associated with 11% (AOR = 1.11; 95% Credible Interval [CrI]: 1.04, 1.20) and 9% (AOR = 1.09; 95% CrI: 1.04, 1.15) increased odds of stunting in SSA, respectively. A 10 µg/m3 increase in postnatal PM2.5 was associated with 6% (AOR = 1.06; 95 % CrI:1.02, 1.11) increased odds of wasting in SSA. The PM2.5 exposure–response relationship varied widely within and between SSA countries and sub-regions with the estimates consistently higher in West Africa. The findings of the study call for tailored, region-specific interventions to help address the burden of child undernutrition attributable to air pollution in the SSA region.