Geo-epidemiological mapping of respiratory disease prevalence with mining dust exposure in Ogun State, Nigeria

Mining activities are significant contributors to ambient particulate matter (PM) emissions, which pose serious public health risks, especially in rapidly urbanizing regions. This study investigates the spatial correlation between PM exposure and respiratory disease prevalence in quarry-dense communities of Ogun State, Nigeria. A cross-sectional ecological design was employed, integrating gravimetric PM₁₀ and PM₂.₅ sampling, meteorological observations, and retrospective health data from 2018 to 2023. Twelve sampling sites across Ewekoro and Sagamu Local Government Areas (LGAs) were selected based on quarry proximity and population density. Spatial interpolation (Kriging), hotspot detection (Getis-Ord Gi*), Local Indicators of Spatial Association (LISA), and regression models (OLS and GWR) were applied to assess spatial patterns and exposure-response relationships. A decision tree model was also developed to predict high-risk communities. PM₁₀ and PM₂.₅ levels peaked during the dry season, with concentrations exceeding WHO guidelines across multiple sites. Respiratory diseases were most prevalent among adults aged 25–64 and children aged 5–14, with Itori, Papalanto, and Emuren communities showing the highest incidence. Significant spatial clustering of disease was confirmed through Gi* and LISA analyses. GWR outperformed OLS in modeling PM₂.₅-disease relationships (Adjusted R² = 0.74), revealing stronger associations in communities nearest to quarry operations. The decision tree identified PM₂.₅ >110 µg/m³ and residence within 2.5 km of a quarry as key predictors of elevated risk. This study demonstrates strong spatial associations between particulate pollution from mining and respiratory disease burden in quarry-adjacent communities. Findings support the implementation of spatial buffer zones, local air quality surveillance, and integrated health monitoring systems to mitigate environmental health risks in vulnerable populations.