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This study aimed to identify the spatial patterns of lower respiratory tract infections (LRIs) and their association with fine particulate matter (PM 2.5 ). The disability-adjusted life year (DALY) database was used to represent the burden each country experiences as a result of LRIs. PM 2.5  data obtained from the Atmosphere Composition Analysis Group was assessed as the source for main exposure. Global Moran’s I and Getis-Ord Gi* were applied to identify the spatial patterns and for hotspots analysis of LRIs. A generalized linear mixed model was coupled with a sensitivity test after controlling for covariates to estimate the association between LRIs and PM 2.5 . Subgroup analyses were performed to determine whether LRIs and PM 2.5  are correlated for various ages and geographic regions. A significant spatial auto-correlated pattern was identified for global LRIs with Moran’s Index 0.79, and the hotspots of LRIs were clustered in 35 African and 4 Eastern Mediterranean countries. A consistent significant positive association between LRIs and PM 2.5  with a coefficient of 0.21 (95% CI 0.06–0.36) was identified. Furthermore, subgroup analysis revealed a significant effect of PM 2.5  on LRI for children (0–14 years) and the elderly (≥ 70 years), and this effect was confirmed to be significant in all regions except for those comprised of Eastern Mediterranean countries.

Spatial patterns of lower respiratory tract infections and their association with fine particulate matter