Abstract
The established evidence associating air pollution with health is limited to populations from specific regions. Further large-scale studies in several regions worldwide are needed to support the literature to date and encourage national governments to act. Brazil is an example of these regions where little research has been performed on a large scale. To address this gap, we conducted a study looking at the relationship between daily PM2.5, NO2, and O3, and hospital admissions for circulatory and respiratory diseases across Brazil between 2008 and 2018. A time-series analytic approach was applied with a distributed lag modeling framework. We used a generalized conditional quasi-Poisson regression model to estimate relative risks (RRs) of the association of each air pollutant with the hospitalization for circulatory and respiratory diseases by sex, age group, and Brazilian regions. Our study population includes 23, 791, 093 hospital admissions for cardiorespiratory diseases in Brazil between 2008 and 2018. Among those, 53.1% are respiratory diseases, and 46.9% are circulatory diseases. Our findings suggest significant associations of ambient air pollution (PM2.5, NO2, and O3) with respiratory and circulatory hospital admissions in Brazil. The national meta-analysis for the whole population showed that for every increase of PM2.5 by 10 μg/m3, there is a 3.28% (95%CI: 2.61; 3.94) increase in the risk of hospital admission for respiratory diseases. For O3, we found positive associations only for some sub-group analyses by age and sex. For NO2, our findings suggest that a 10 ppb increase in this pollutant, there was a 35.26% (95%CI: 24.07; 46.44) increase in the risk of hospital admission for respiratory diseases. This study may better support policymakers to improve the air quality and public health in Brazil
Originalsprog | Engelsk |
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Artikelnummer | 114794 |
Tidsskrift | Environmental Research |
Vol/bind | 217 |
Antal sider | 9 |
ISSN | 0013-9351 |
DOI | |
Status | Udgivet - 2023 |
Bibliografisk note
Funding Information:This work was supported by the Brazilian Agencies National Council for Scientific and Technological Development ( CNPq ) and by the Ministry of Science, Technology and Innovation ( MCTI ).
Publisher Copyright:
© 2022 Elsevier Inc.