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Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis
Assessing whether long-term exposure to air pollution increases the severity of COVID-19 health outcomes, including death, is an important public health objective. Limitations in COVID-19 data availability and quality remain obstacles to conducting conclusive studies on this topic. At present, publi...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Association for the Advancement of Science
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7673673/ https://www.ncbi.nlm.nih.gov/pubmed/33148655 http://dx.doi.org/10.1126/sciadv.abd4049 |
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author | Wu, X. Nethery, R. C. Sabath, M. B. Braun, D. Dominici, F. |
author_facet | Wu, X. Nethery, R. C. Sabath, M. B. Braun, D. Dominici, F. |
author_sort | Wu, X. |
collection | PubMed |
description | Assessing whether long-term exposure to air pollution increases the severity of COVID-19 health outcomes, including death, is an important public health objective. Limitations in COVID-19 data availability and quality remain obstacles to conducting conclusive studies on this topic. At present, publicly available COVID-19 outcome data for representative populations are available only as area-level counts. Therefore, studies of long-term exposure to air pollution and COVID-19 outcomes using these data must use an ecological regression analysis, which precludes controlling for individual-level COVID-19 risk factors. We describe these challenges in the context of one of the first preliminary investigations of this question in the United States, where we found that higher historical PM(2.5) exposures are positively associated with higher county-level COVID-19 mortality rates after accounting for many area-level confounders. Motivated by this study, we lay the groundwork for future research on this important topic, describe the challenges, and outline promising directions and opportunities. |
format | Online Article Text |
id | pubmed-7673673 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | American Association for the Advancement of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-76736732020-11-24 Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis Wu, X. Nethery, R. C. Sabath, M. B. Braun, D. Dominici, F. Sci Adv Research Articles Assessing whether long-term exposure to air pollution increases the severity of COVID-19 health outcomes, including death, is an important public health objective. Limitations in COVID-19 data availability and quality remain obstacles to conducting conclusive studies on this topic. At present, publicly available COVID-19 outcome data for representative populations are available only as area-level counts. Therefore, studies of long-term exposure to air pollution and COVID-19 outcomes using these data must use an ecological regression analysis, which precludes controlling for individual-level COVID-19 risk factors. We describe these challenges in the context of one of the first preliminary investigations of this question in the United States, where we found that higher historical PM(2.5) exposures are positively associated with higher county-level COVID-19 mortality rates after accounting for many area-level confounders. Motivated by this study, we lay the groundwork for future research on this important topic, describe the challenges, and outline promising directions and opportunities. American Association for the Advancement of Science 2020-11-04 /pmc/articles/PMC7673673/ /pubmed/33148655 http://dx.doi.org/10.1126/sciadv.abd4049 Text en Copyright © 2020 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/ https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited. |
spellingShingle | Research Articles Wu, X. Nethery, R. C. Sabath, M. B. Braun, D. Dominici, F. Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis |
title | Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis |
title_full | Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis |
title_fullStr | Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis |
title_full_unstemmed | Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis |
title_short | Air pollution and COVID-19 mortality in the United States: Strengths and limitations of an ecological regression analysis |
title_sort | air pollution and covid-19 mortality in the united states: strengths and limitations of an ecological regression analysis |
topic | Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7673673/ https://www.ncbi.nlm.nih.gov/pubmed/33148655 http://dx.doi.org/10.1126/sciadv.abd4049 |
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