Abstract
Background. Fine particulate matter (PM(2.5)) is a leading global health risk. Latin American cities exhibit some of the world's highest urban PM(2.5) levels, yet studies of neighborhood-level PM(2.5) exposure and associated disparities in the region are limited. Methods. We conducted a cross-sectional ecological analysis of 53 041 neighborhoods across 340 cities in eight Latin American countries, leveraging the Salud Urbana en America Latina study dataset. Annual PM(2.5) concentrations were derived from satellite data and linked to socioeconomic and urban characteristics. A multilevel model analyzed associations between neighborhood PM(2.5) levels and neighborhood- and city-level characteristics. Results. The median annual neighborhood PM(2.5) concentration was 18.49 µg m(-3). Of the 256 million residents, all lived in neighborhoods with ambient PM(2.5) concentrations that exceeded the 2021 World Health Organization guidelines (5 µg m(-3)). Variability was greatest between cities (54.3% of total variance), but substantial within-city variation (26% of variance) was observed. Higher neighborhood PM(2.5) levels were associated with higher neighborhood educational attainment (mean difference [MD] comparing top to bottom tertile = 0.17 µg m(-3)), higher neighborhood intersection density (MD comparing top to bottom tertile = 0.17 µg m(-3)), and older cities (MD comparing top to bottom tertile = 1.45 µg m(-3)). Lower neighborhood PM(2.5) levels were related to higher neighborhood population density (MD comparing top to bottom tertile = - 0.55 µg m(-3)), more greenness (MD comparing top to bottom tertile = - 0.76 µg m(-3)), and larger distance from city centers (MD comparing top to bottom tertile = - 0.86 µg m(-3)). Conclusions. Neighborhoods with higher PM(2.5) concentrations tended to have higher educational attainment, more intersections, and be located in older cities, while lower concentrations were associated with denser populations, more green space, and greater distance from city centers. Our findings reveal important within-city heterogeneity in PM(2.5) and the factors associated with it, suggesting strategies to mitigate air pollution within cities.