Spatial variability in the association of ambient PM2.5 exposure with acute respiratory infection among children in Sub-Saharan Africa.
Does breathing dirty air raise a child's chances of getting a serious respiratory infection — and if so, does that risk play out the same way everywhere across sub-Saharan Africa?
College of Health researcher(s)
Highlights
- Prenatal and postnatal PM2.5 exposure is associated with an increased risk of acute respiratory infections (ARI) in sub-Saharan Africa (SSA).
- The effects of PM2.5 on ARI in SSA vary significantly by region with the strongest exposure health effects observed in Eastern and Central Africa.
- A Bayesian spatial model reveals that the risk of ARI is more clustered geographically
- The study findings underscore the need for tailored country-specific interventions for reducing the burden of childhood ARIs in SSA attributable to air pollution
Abstract
Ambient PM2.5 exposure has been associated with an increased risk of acute respiratory infections (ARIs). However, the magnitude and direction of this association may vary across geographical settings, both within and between countries, underscoring the need for context-specific investigation. We combined Demographic and Health Surveys (DHS) data from 1998 to 2022 across 34 SSA countries with satellite-derived geospatial PM2.5 data from the V5.GL.02 product (ACAG). The DHS GPS coordinates allowed us to extract PM2.5 exposure data within a 2km buffer for urban areas and 5km buffer for rural areas to help account for geographic coordinate displacement. This study used Bayesian multilevel spatial logistic regression model under the Integrated Nested Laplace Approximations (INLA) framework for the analysis across 34 SSA countries. Of the 129,769 children included in this study, 22.7% experienced ARI in SSA. Higher ambient PM2.5 exposure was consistently associated with increased odds of ARI in SSA. In the country level analysis, postnatal exposure showed a clear positive association with ARI (AOR = 1.14; 95% CrI: 1.07–1.21), while prenatal exposure showed no meaningful relationship. In the Sub-national level analysis, the strength of association increased: prenatal exposure indicated a modest elevated risk but remained statistically non-significant, and postnatal exposure remained the strongest predictor (AOR = 1.22; 95% CrI: 1.07–1.38). Geographical differences were evident, with East and Central Africa demonstrating the most pronounced associations across both modelling frameworks. The study findings underscore the need for tailored country-specific interventions for reducing the burden of childhood ARIs in SSA attributable to air pollution. Spatial variations in air pollution health effects need to be taken into consideration whenever policymakers are developing and implementing air pollution control policies.