The impact of exposure assessment on associations between air pollution and cardiovascular mortality risks in the city of Rio de Janeiro, Brazil.

Autor: Heo S; School of the Environment, Yale University, New Haven, CT, USA. Electronic address: seulkee.heo@yale.edu., Schuch D; College of Engineering, Northeastern University, Boston, MA, USA. Electronic address: d.schuch@northeastern.edu., Junger WL; Universidade do Estado do Rio de Janeiro, Rio de Janeiro, Rio de Janeiro, Brazil. Electronic address: wjunger@ims.uerj.br., Zhang Y; College of Engineering, Northeastern University, Boston, MA, USA. Electronic address: ya.zhang@northeastern.edu., de Fatima Andrade M; Departamento de Ciências Atmosféricas, Instituto de Astronomia, Geofísica e Ciências Atmosféricas, Universidade de São Paulo, São Paulo, Brazil. Electronic address: maria.andrade@iag.usp.br., Bell ML; School of the Environment, Yale University, New Haven, CT, USA; Interdisciplinary Program in Precision Public Health, Department of Public Health Sciences, Graduate School of Korea University, Seoul, South Korea. Electronic address: Michelle.bell@yale.edu.
Jazyk: angličtina
Zdroj: Environmental research [Environ Res] 2024 Dec 15; Vol. 263 (Pt 2), pp. 120150. Date of Electronic Publication: 2024 Oct 15.
DOI: 10.1016/j.envres.2024.120150
Abstrakt: Despite a growing literature for complex air quality models, scientific evidence lacks of the influences of varying exposure assessments and air quality data sources on the estimated mortality risks. This case-crossover study estimated cardiovascular mortality risks from fine particulate matter (PM 2.5 ) and ozone (O 3 ) exposures, using varying exposure methods, to aid understanding of the impact of exposure methods in the health risk estimation. We used individual-level cardiovascular mortality data in the city of Rio de Janeiro, 2012-2016. PM 2.5 and O 3 exposure levels (from the date of death to seven prior days [lag0-7]) were estimated at the individual level or district level using either the WRF-Chem modeling data or monitoring data, resulting in a total of 10 exposure methods. The exposure-response relationships were estimated using multiple logistic regressions. The changes in cardiovascular mortality were represented as an odds ratio (OR) and 95% confidence intervals (CIs) for an interquartile range (IQR) increase in the exposures. Results showed that socioeconomically more advantaged populations had lower access to the stationary monitoring networks. Higher variance in the estimated exposure levels across the 10 exposure methods was found for PM 2.5 than O 3 . PM 2.5 exposure was not associated with mortality risk in any exposure methods. WRF-Chem-based O 3 exposure estimated for each individual of the entire population found a significant mortality risk (OR = 1.06, 95% CI: 1.01, 1.11), but not the other exposure methods. Higher risks for females and older populations were suggested for O 3 estimates estimated for each individual using the WRF-Chem data. Findings indicate that decisions on exposure methods and data sources can lead to substantially varying implications for air pollution risks and highlight the need for comprehensive exposure and health impact assessments to aid local decision-making for air pollution and public health.
Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
(Copyright © 2024 Elsevier Inc. All rights reserved.)
Databáze: MEDLINE
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