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The association between opioids, environmental, demographic, and socioeconomic indicators and COVID-19 mortality rates in the United States: an ecological study at the county level
BACKGROUND: The spread of the COVID-19 pandemic throughout the world presents an unprecedented challenge to public health inequities. People who use opioids may be a vulnerable group disproportionately impacted by the current pandemic, however, the limited prior research in this area makes it unclea...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8204068/ https://www.ncbi.nlm.nih.gov/pubmed/34130741 http://dx.doi.org/10.1186/s13690-021-00626-z |
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author | Qeadan, Fares Mensah, Nana Akofua Tingey, Benjamin Bern, Rona Rees, Tracy Madden, Erin Fanning Porucznik, Christina A. English, Kevin Honda, Trenton |
author_facet | Qeadan, Fares Mensah, Nana Akofua Tingey, Benjamin Bern, Rona Rees, Tracy Madden, Erin Fanning Porucznik, Christina A. English, Kevin Honda, Trenton |
author_sort | Qeadan, Fares |
collection | PubMed |
description | BACKGROUND: The spread of the COVID-19 pandemic throughout the world presents an unprecedented challenge to public health inequities. People who use opioids may be a vulnerable group disproportionately impacted by the current pandemic, however, the limited prior research in this area makes it unclear whether COVID-19 and opioid use outcomes may be related, and whether other environmental and socioeconomic factors might play a role in explaining COVID-19 mortality. The objective of this study is to evaluate the association between opioid-related mortality and COVID-19 mortality across U.S. counties. METHODS: Data from 3142 counties across the U.S. were used to model the cumulative count of deaths due to COVID-19 up to June 2, 2020. A multivariable negative-binomial regression model was employed to evaluate the adjusted COVID-19 mortality rate ratios (aMRR). RESULTS: After controlling for covariates, counties with higher rates of opioid-related mortality per 100,000 persons were found to be significantly associated with higher rates of COVID-19 mortality (aMRR: 1.0134; 95% CI [1.0054, 1.0214]; P = 0.001). Counties with higher average daily Particulate Matter (PM2.5) exposure also saw significantly higher rates of COVID-19 mortality. Analyses revealed rural counties, counties with higher percentages of non-Hispanic whites, and counties with increased average maximum temperatures are significantly associated with lower mortality rates from COVID-19. CONCLUSIONS: This study indicates need for public health efforts in hard hit COVID-19 regions to also focus prevention efforts on overdose risk among people who use opioids. Future studies using individual-level data are needed to allow for detailed inferences. |
format | Online Article Text |
id | pubmed-8204068 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-82040682021-06-15 The association between opioids, environmental, demographic, and socioeconomic indicators and COVID-19 mortality rates in the United States: an ecological study at the county level Qeadan, Fares Mensah, Nana Akofua Tingey, Benjamin Bern, Rona Rees, Tracy Madden, Erin Fanning Porucznik, Christina A. English, Kevin Honda, Trenton Arch Public Health Research BACKGROUND: The spread of the COVID-19 pandemic throughout the world presents an unprecedented challenge to public health inequities. People who use opioids may be a vulnerable group disproportionately impacted by the current pandemic, however, the limited prior research in this area makes it unclear whether COVID-19 and opioid use outcomes may be related, and whether other environmental and socioeconomic factors might play a role in explaining COVID-19 mortality. The objective of this study is to evaluate the association between opioid-related mortality and COVID-19 mortality across U.S. counties. METHODS: Data from 3142 counties across the U.S. were used to model the cumulative count of deaths due to COVID-19 up to June 2, 2020. A multivariable negative-binomial regression model was employed to evaluate the adjusted COVID-19 mortality rate ratios (aMRR). RESULTS: After controlling for covariates, counties with higher rates of opioid-related mortality per 100,000 persons were found to be significantly associated with higher rates of COVID-19 mortality (aMRR: 1.0134; 95% CI [1.0054, 1.0214]; P = 0.001). Counties with higher average daily Particulate Matter (PM2.5) exposure also saw significantly higher rates of COVID-19 mortality. Analyses revealed rural counties, counties with higher percentages of non-Hispanic whites, and counties with increased average maximum temperatures are significantly associated with lower mortality rates from COVID-19. CONCLUSIONS: This study indicates need for public health efforts in hard hit COVID-19 regions to also focus prevention efforts on overdose risk among people who use opioids. Future studies using individual-level data are needed to allow for detailed inferences. BioMed Central 2021-06-15 /pmc/articles/PMC8204068/ /pubmed/34130741 http://dx.doi.org/10.1186/s13690-021-00626-z Text en © The Author(s) 2021 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data. |
spellingShingle | Research Qeadan, Fares Mensah, Nana Akofua Tingey, Benjamin Bern, Rona Rees, Tracy Madden, Erin Fanning Porucznik, Christina A. English, Kevin Honda, Trenton The association between opioids, environmental, demographic, and socioeconomic indicators and COVID-19 mortality rates in the United States: an ecological study at the county level |
title | The association between opioids, environmental, demographic, and socioeconomic indicators and COVID-19 mortality rates in the United States: an ecological study at the county level |
title_full | The association between opioids, environmental, demographic, and socioeconomic indicators and COVID-19 mortality rates in the United States: an ecological study at the county level |
title_fullStr | The association between opioids, environmental, demographic, and socioeconomic indicators and COVID-19 mortality rates in the United States: an ecological study at the county level |
title_full_unstemmed | The association between opioids, environmental, demographic, and socioeconomic indicators and COVID-19 mortality rates in the United States: an ecological study at the county level |
title_short | The association between opioids, environmental, demographic, and socioeconomic indicators and COVID-19 mortality rates in the United States: an ecological study at the county level |
title_sort | association between opioids, environmental, demographic, and socioeconomic indicators and covid-19 mortality rates in the united states: an ecological study at the county level |
topic | Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8204068/ https://www.ncbi.nlm.nih.gov/pubmed/34130741 http://dx.doi.org/10.1186/s13690-021-00626-z |
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