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Ambient fine particulate matter in Latin American cities: Levels, population exposure, and associated urban factors

BACKGROUND: Exposure to particulate matter (PM(2.5)) is a major risk factor for morbidity and mortality. Yet few studies have examined patterns of population exposure and investigated the predictors of PM(2.5) across the rapidly growing cities in lower- and middle-income countries. OBJECTIVES: Chara...

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Detalles Bibliográficos
Autores principales: Gouveia, Nelson, Kephart, Josiah L., Dronova, Iryna, McClure, Leslie, Granados, José Tapia, Betancourt, Ricardo Morales, O'Ryan, Andrea Cortínez, Texcalac-Sangrador, José Luis, Martinez-Folgar, Kevin, Rodriguez, Daniel, Diez-Roux, Ana V.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8024944/
https://www.ncbi.nlm.nih.gov/pubmed/33581538
http://dx.doi.org/10.1016/j.scitotenv.2021.145035
Descripción
Sumario:BACKGROUND: Exposure to particulate matter (PM(2.5)) is a major risk factor for morbidity and mortality. Yet few studies have examined patterns of population exposure and investigated the predictors of PM(2.5) across the rapidly growing cities in lower- and middle-income countries. OBJECTIVES: Characterize PM(2.5) levels, describe patterns of population exposure, and investigate urban factors as predictors of PM(2.5) levels. METHODS: We used data from the Salud Urbana en America Latina/Urban Health in Latin America (SALURBAL) study, a multi-country assessment of the determinants of urban health in Latin America, to characterize PM(2.5) levels in 366 cities comprising over 100,000 residents using satellite-derived estimates. Factors related to urban form and transportation were explored. RESULTS: We found that about 172 million or 58% of the population studied lived in areas with air pollution levels above the defined WHO-AQG of 10 μg/m(3) annual average. We also found that larger cities, cities with higher GDP, higher motorization rate and higher congestion tended to have higher PM(2.5). In contrast cities with higher population density had lower levels of PM(2.5). In addition, at the sub-city level, higher intersection density was associated with higher PM(2.5) and more green space was associated with lower PM(2.5). When all exposures were examined adjusted for each other, higher city per capita GDP and higher sub-city intersection density remained associated with higher PM(2.5) levels, while higher city population density remained associated with lower levels. The presence of mass transit was also associated with lower PM(2.5) after adjustment. The motorization rate also remained associated with PM(2.5) and its inclusion attenuated the effect of population density. DISCUSSION: These results show that PM(2.5) exposures remain a major health risk in Latin American cities and suggest that urban planning and transportation policies could have a major impact on ambient levels.