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A model of disparities: risk factors associated with COVID-19 infection

BACKGROUND: By mid-May 2020, there were over 1.5 million cases of (SARS-CoV-2) or COVID-19 across the U.S. with new confirmed cases continuing to rise following the re-opening of most states. Prior studies have focused mainly on clinical risk factors associated with serious illness and mortality of...

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Autores principales: Rozenfeld, Yelena, Beam, Jennifer, Maier, Haley, Haggerson, Whitney, Boudreau, Karen, Carlson, Jamie, Medows, Rhonda
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7387879/
https://www.ncbi.nlm.nih.gov/pubmed/32727486
http://dx.doi.org/10.1186/s12939-020-01242-z
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author Rozenfeld, Yelena
Beam, Jennifer
Maier, Haley
Haggerson, Whitney
Boudreau, Karen
Carlson, Jamie
Medows, Rhonda
author_facet Rozenfeld, Yelena
Beam, Jennifer
Maier, Haley
Haggerson, Whitney
Boudreau, Karen
Carlson, Jamie
Medows, Rhonda
author_sort Rozenfeld, Yelena
collection PubMed
description BACKGROUND: By mid-May 2020, there were over 1.5 million cases of (SARS-CoV-2) or COVID-19 across the U.S. with new confirmed cases continuing to rise following the re-opening of most states. Prior studies have focused mainly on clinical risk factors associated with serious illness and mortality of COVID-19. Less analysis has been conducted on the clinical, sociodemographic, and environmental variables associated with initial infection of COVID-19. METHODS: A multivariable statistical model was used to characterize risk factors in 34,503cases of laboratory-confirmed positive or negative COVID-19 infection in the Providence Health System (U.S.) between February 28 and April 27, 2020. Publicly available data were utilized as approximations for social determinants of health, and patient-level clinical and sociodemographic factors were extracted from the electronic medical record. RESULTS: Higher risk of COVID-19 infection was associated with older age (OR 1.69; 95% CI 1.41–2.02, p < 0.0001), male gender (OR 1.32; 95% CI 1.21–1.44, p < 0.0001), Asian race (OR 1.43; 95% CI 1.18–1.72, p = 0.0002), Black/African American race (OR 1.51; 95% CI 1.25–1.83, p < 0.0001), Latino ethnicity (OR 2.07; 95% CI 1.77–2.41, p < 0.0001), non-English language (OR 2.09; 95% CI 1.7–2.57, p < 0.0001), residing in a neighborhood with financial insecurity (OR 1.10; 95% CI 1.01–1.25, p = 0.04), low air quality (OR 1.01; 95% CI 1.0–1.04, p = 0.05), housing insecurity (OR 1.32; 95% CI 1.16–1.5, p < 0.0001) or transportation insecurity (OR 1.11; 95% CI 1.02–1.23, p = 0.03), and living in senior living communities (OR 1.69; 95% CI 1.23–2.32, p = 0.001). CONCLUSION: sisk of COVID-19 infection is higher among groups already affected by health disparities across age, race, ethnicity, language, income, and living conditions. Health promotion and disease prevention strategies should prioritize groups most vulnerable to infection and address structural inequities that contribute to risk through social and economic policy.
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spelling pubmed-73878792020-07-29 A model of disparities: risk factors associated with COVID-19 infection Rozenfeld, Yelena Beam, Jennifer Maier, Haley Haggerson, Whitney Boudreau, Karen Carlson, Jamie Medows, Rhonda Int J Equity Health Research BACKGROUND: By mid-May 2020, there were over 1.5 million cases of (SARS-CoV-2) or COVID-19 across the U.S. with new confirmed cases continuing to rise following the re-opening of most states. Prior studies have focused mainly on clinical risk factors associated with serious illness and mortality of COVID-19. Less analysis has been conducted on the clinical, sociodemographic, and environmental variables associated with initial infection of COVID-19. METHODS: A multivariable statistical model was used to characterize risk factors in 34,503cases of laboratory-confirmed positive or negative COVID-19 infection in the Providence Health System (U.S.) between February 28 and April 27, 2020. Publicly available data were utilized as approximations for social determinants of health, and patient-level clinical and sociodemographic factors were extracted from the electronic medical record. RESULTS: Higher risk of COVID-19 infection was associated with older age (OR 1.69; 95% CI 1.41–2.02, p < 0.0001), male gender (OR 1.32; 95% CI 1.21–1.44, p < 0.0001), Asian race (OR 1.43; 95% CI 1.18–1.72, p = 0.0002), Black/African American race (OR 1.51; 95% CI 1.25–1.83, p < 0.0001), Latino ethnicity (OR 2.07; 95% CI 1.77–2.41, p < 0.0001), non-English language (OR 2.09; 95% CI 1.7–2.57, p < 0.0001), residing in a neighborhood with financial insecurity (OR 1.10; 95% CI 1.01–1.25, p = 0.04), low air quality (OR 1.01; 95% CI 1.0–1.04, p = 0.05), housing insecurity (OR 1.32; 95% CI 1.16–1.5, p < 0.0001) or transportation insecurity (OR 1.11; 95% CI 1.02–1.23, p = 0.03), and living in senior living communities (OR 1.69; 95% CI 1.23–2.32, p = 0.001). CONCLUSION: sisk of COVID-19 infection is higher among groups already affected by health disparities across age, race, ethnicity, language, income, and living conditions. Health promotion and disease prevention strategies should prioritize groups most vulnerable to infection and address structural inequities that contribute to risk through social and economic policy. BioMed Central 2020-07-29 /pmc/articles/PMC7387879/ /pubmed/32727486 http://dx.doi.org/10.1186/s12939-020-01242-z Text en © The Author(s) 2020 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/. The Creative Commons Public Domain Dedication waiver (http://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
Rozenfeld, Yelena
Beam, Jennifer
Maier, Haley
Haggerson, Whitney
Boudreau, Karen
Carlson, Jamie
Medows, Rhonda
A model of disparities: risk factors associated with COVID-19 infection
title A model of disparities: risk factors associated with COVID-19 infection
title_full A model of disparities: risk factors associated with COVID-19 infection
title_fullStr A model of disparities: risk factors associated with COVID-19 infection
title_full_unstemmed A model of disparities: risk factors associated with COVID-19 infection
title_short A model of disparities: risk factors associated with COVID-19 infection
title_sort model of disparities: risk factors associated with covid-19 infection
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7387879/
https://www.ncbi.nlm.nih.gov/pubmed/32727486
http://dx.doi.org/10.1186/s12939-020-01242-z
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