Abstract
Air pollution has been one of the major threats to public health. The study aimed to determine latent patterns of geographical distribution of health-related air pollutants across the USA and to evaluate real-world cumulative effects of these patterns on public health metrics. It was an ecological study using county-level data on the concentrations of 12 air pollutants over 20 years. Latent class analysis was used to identify the common clusters of life expectancy-associated air pollutants based on their concentration characteristics in the final counties studied (n = 699). Multivariate linear regression analyses were then applied to assess the relationship between the LCA-derived clusters and health measurements with confounding adjustment. We found that PM2.5 mass, PM10 speciation, and NONOxNOy (the reactive nitrogen species) were associated with life expectancy and thus were included in LCA. Among five identified clusters, the one with a more severe pollutant profile was associated with a decreasing life expectancy, an increasing mortality risk among middle-aged and elderly populations (≥45 years), and an increasing mortality rate caused by chronic respiratory conditions, cardiovascular diseases, and neoplasms. Our study brings new perspectives on real-world geographical patterns of air pollution to explain health disparities across the USA.
| Original language | English |
|---|---|
| Article number | 177 |
| Journal | Life |
| Volume | 16 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - Jan 2026 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- air pollution
- epidemiology
- geographical pattern
- health inequality
- latent class analysis
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