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Mapping the long-term associations between air pollutants and COVID-19 risks and the attributable burdens in the continental United States()
Numerous studies have investigated the associations between COVID-19 risks and long-term exposure to air pollutants, revealing considerable heterogeneity and even contradictory regional results. Studying the spatial heterogeneity of the associations is essential for developing region-specific and co...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd.
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9994533/ https://www.ncbi.nlm.nih.gov/pubmed/36898647 http://dx.doi.org/10.1016/j.envpol.2023.121418 |
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author | Feng, Benying Wang, Wei Zhou, Bo Zhou, Ying Wang, Jinyu Liao, Fang |
author_facet | Feng, Benying Wang, Wei Zhou, Bo Zhou, Ying Wang, Jinyu Liao, Fang |
author_sort | Feng, Benying |
collection | PubMed |
description | Numerous studies have investigated the associations between COVID-19 risks and long-term exposure to air pollutants, revealing considerable heterogeneity and even contradictory regional results. Studying the spatial heterogeneity of the associations is essential for developing region-specific and cost-effective air-pollutant-related public health policies for the prevention and control of COVID-19. However, few studies have investigated this issue. Using the USA as an example, we constructed single/two-pollutant conditional autoregressions with random coefficients and random intercepts to map the associations between five air pollutants (PM(2.5), O(3), SO(2), NO(2), and CO) and two COVID-19 outcomes (incidence and mortality) at the state level. The attributed cases and deaths were then mapped at the county level. This study included 3108 counties from 49 states within the continental USA. The county-level air pollutant concentrations from 2017 to 2019 were used as long-term exposures, and the county-level cumulative COVID-19 cases and deaths through May 13, 2022, were used as outcomes. Results showed that considerably heterogeneous associations and attributable COVID-19 burdens were found in the USA. The COVID-19 outcomes in the western and northeastern states appeared to be unaffected by any of the five pollutants. The east of the USA bore the greatest COVID-19 burdens attributable to air pollution because of its high pollutant concentrations and significantly positive associations. PM(2.5) and CO were significantly positively associated with COVID-19 incidence in 49 states on average, whereas NO(2) and SO(2) were significantly positively associated with COVID-19 mortality. The remaining associations between air pollutants and COVID-19 outcomes were not statistically significant. Our study provided implications regarding where a major concern should be placed on a specific air pollutant for COVID-19 control and prevention, as well as where and how to conduct additional individual-based validation research in a cost-effective manner. |
format | Online Article Text |
id | pubmed-9994533 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Elsevier Ltd. |
record_format | MEDLINE/PubMed |
spelling | pubmed-99945332023-03-09 Mapping the long-term associations between air pollutants and COVID-19 risks and the attributable burdens in the continental United States() Feng, Benying Wang, Wei Zhou, Bo Zhou, Ying Wang, Jinyu Liao, Fang Environ Pollut Article Numerous studies have investigated the associations between COVID-19 risks and long-term exposure to air pollutants, revealing considerable heterogeneity and even contradictory regional results. Studying the spatial heterogeneity of the associations is essential for developing region-specific and cost-effective air-pollutant-related public health policies for the prevention and control of COVID-19. However, few studies have investigated this issue. Using the USA as an example, we constructed single/two-pollutant conditional autoregressions with random coefficients and random intercepts to map the associations between five air pollutants (PM(2.5), O(3), SO(2), NO(2), and CO) and two COVID-19 outcomes (incidence and mortality) at the state level. The attributed cases and deaths were then mapped at the county level. This study included 3108 counties from 49 states within the continental USA. The county-level air pollutant concentrations from 2017 to 2019 were used as long-term exposures, and the county-level cumulative COVID-19 cases and deaths through May 13, 2022, were used as outcomes. Results showed that considerably heterogeneous associations and attributable COVID-19 burdens were found in the USA. The COVID-19 outcomes in the western and northeastern states appeared to be unaffected by any of the five pollutants. The east of the USA bore the greatest COVID-19 burdens attributable to air pollution because of its high pollutant concentrations and significantly positive associations. PM(2.5) and CO were significantly positively associated with COVID-19 incidence in 49 states on average, whereas NO(2) and SO(2) were significantly positively associated with COVID-19 mortality. The remaining associations between air pollutants and COVID-19 outcomes were not statistically significant. Our study provided implications regarding where a major concern should be placed on a specific air pollutant for COVID-19 control and prevention, as well as where and how to conduct additional individual-based validation research in a cost-effective manner. Elsevier Ltd. 2023-05-01 2023-03-08 /pmc/articles/PMC9994533/ /pubmed/36898647 http://dx.doi.org/10.1016/j.envpol.2023.121418 Text en © 2023 Elsevier Ltd. All rights reserved. Since January 2020 Elsevier has created a COVID-19 resource centre with free information in English and Mandarin on the novel coronavirus COVID-19. The COVID-19 resource centre is hosted on Elsevier Connect, the company's public news and information website. Elsevier hereby grants permission to make all its COVID-19-related research that is available on the COVID-19 resource centre - including this research content - immediately available in PubMed Central and other publicly funded repositories, such as the WHO COVID database with rights for unrestricted research re-use and analyses in any form or by any means with acknowledgement of the original source. These permissions are granted for free by Elsevier for as long as the COVID-19 resource centre remains active. |
spellingShingle | Article Feng, Benying Wang, Wei Zhou, Bo Zhou, Ying Wang, Jinyu Liao, Fang Mapping the long-term associations between air pollutants and COVID-19 risks and the attributable burdens in the continental United States() |
title | Mapping the long-term associations between air pollutants and COVID-19 risks and the attributable burdens in the continental United States() |
title_full | Mapping the long-term associations between air pollutants and COVID-19 risks and the attributable burdens in the continental United States() |
title_fullStr | Mapping the long-term associations between air pollutants and COVID-19 risks and the attributable burdens in the continental United States() |
title_full_unstemmed | Mapping the long-term associations between air pollutants and COVID-19 risks and the attributable burdens in the continental United States() |
title_short | Mapping the long-term associations between air pollutants and COVID-19 risks and the attributable burdens in the continental United States() |
title_sort | mapping the long-term associations between air pollutants and covid-19 risks and the attributable burdens in the continental united states() |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9994533/ https://www.ncbi.nlm.nih.gov/pubmed/36898647 http://dx.doi.org/10.1016/j.envpol.2023.121418 |
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