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The Town-Level Prevalence of Chronic Lung Conditions and Death From COVID-19 Among Older Adults in Connecticut and Rhode Island

INTRODUCTION: As of November 2021, older adults (aged ≥65 y) accounted for 81% of all deaths from COVID-19 in the US. Chronic lung diseases increase the risk for severe COVID-19 illness and death. The aim of this research was to examine the association between town-level rates of asthma and chronic...

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Autores principales: Jansen, Taylor, Man Lee, Chae, Xu, Shu, Silverstein, Nina M., Dugan, Elizabeth
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Centers for Disease Control and Prevention 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9258446/
https://www.ncbi.nlm.nih.gov/pubmed/35772039
http://dx.doi.org/10.5888/pcd19.210421
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author Jansen, Taylor
Man Lee, Chae
Xu, Shu
Silverstein, Nina M.
Dugan, Elizabeth
author_facet Jansen, Taylor
Man Lee, Chae
Xu, Shu
Silverstein, Nina M.
Dugan, Elizabeth
author_sort Jansen, Taylor
collection PubMed
description INTRODUCTION: As of November 2021, older adults (aged ≥65 y) accounted for 81% of all deaths from COVID-19 in the US. Chronic lung diseases increase the risk for severe COVID-19 illness and death. The aim of this research was to examine the association between town-level rates of asthma and chronic obstructive pulmonary disease (COPD) and deaths from COVID-19 in 208 towns in Connecticut and Rhode Island. METHODS: We conducted a multistep analysis to examine the association between town-level chronic lung conditions and death from COVID-19. Pairwise correlations were estimated and bivariate maps were created to assess the relationship between COVID-19 deaths per 100,000 people and 1) asthma prevalence and 2) COPD prevalence among adults aged 65 years or older. We used multiple linear regression models to examine whether chronic lung conditions and other town-level factors were associated with COVID-19 death rates in Connecticut and Rhode Island. RESULTS: Initial bivariate correlation and mapping analyses suggested positive correlations between asthma and COPD prevalence and COVID-19 death rates. However, after controlling for town-level factors associated with chronic lung conditions and COVID-19 death rates, multiple linear regression models did not support an association, but town-level factors (African American race and Hispanic ethnicity, age ≥65 y, and low educational attainment) were significant predictors of COVID-19 death rates. CONCLUSION: We found significant associations between town-level factors and COVID-19, adding to the current understanding of the impact of social determinants of health on outcomes.
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spelling pubmed-92584462022-07-18 The Town-Level Prevalence of Chronic Lung Conditions and Death From COVID-19 Among Older Adults in Connecticut and Rhode Island Jansen, Taylor Man Lee, Chae Xu, Shu Silverstein, Nina M. Dugan, Elizabeth Prev Chronic Dis Original Research INTRODUCTION: As of November 2021, older adults (aged ≥65 y) accounted for 81% of all deaths from COVID-19 in the US. Chronic lung diseases increase the risk for severe COVID-19 illness and death. The aim of this research was to examine the association between town-level rates of asthma and chronic obstructive pulmonary disease (COPD) and deaths from COVID-19 in 208 towns in Connecticut and Rhode Island. METHODS: We conducted a multistep analysis to examine the association between town-level chronic lung conditions and death from COVID-19. Pairwise correlations were estimated and bivariate maps were created to assess the relationship between COVID-19 deaths per 100,000 people and 1) asthma prevalence and 2) COPD prevalence among adults aged 65 years or older. We used multiple linear regression models to examine whether chronic lung conditions and other town-level factors were associated with COVID-19 death rates in Connecticut and Rhode Island. RESULTS: Initial bivariate correlation and mapping analyses suggested positive correlations between asthma and COPD prevalence and COVID-19 death rates. However, after controlling for town-level factors associated with chronic lung conditions and COVID-19 death rates, multiple linear regression models did not support an association, but town-level factors (African American race and Hispanic ethnicity, age ≥65 y, and low educational attainment) were significant predictors of COVID-19 death rates. CONCLUSION: We found significant associations between town-level factors and COVID-19, adding to the current understanding of the impact of social determinants of health on outcomes. Centers for Disease Control and Prevention 2022-06-30 /pmc/articles/PMC9258446/ /pubmed/35772039 http://dx.doi.org/10.5888/pcd19.210421 Text en https://creativecommons.org/licenses/by/4.0/Preventing Chronic Disease is a publication of the U.S. Government. This publication is in the public domain and is therefore without copyright. All text from this work may be reprinted freely. Use of these materials should be properly cited.
spellingShingle Original Research
Jansen, Taylor
Man Lee, Chae
Xu, Shu
Silverstein, Nina M.
Dugan, Elizabeth
The Town-Level Prevalence of Chronic Lung Conditions and Death From COVID-19 Among Older Adults in Connecticut and Rhode Island
title The Town-Level Prevalence of Chronic Lung Conditions and Death From COVID-19 Among Older Adults in Connecticut and Rhode Island
title_full The Town-Level Prevalence of Chronic Lung Conditions and Death From COVID-19 Among Older Adults in Connecticut and Rhode Island
title_fullStr The Town-Level Prevalence of Chronic Lung Conditions and Death From COVID-19 Among Older Adults in Connecticut and Rhode Island
title_full_unstemmed The Town-Level Prevalence of Chronic Lung Conditions and Death From COVID-19 Among Older Adults in Connecticut and Rhode Island
title_short The Town-Level Prevalence of Chronic Lung Conditions and Death From COVID-19 Among Older Adults in Connecticut and Rhode Island
title_sort town-level prevalence of chronic lung conditions and death from covid-19 among older adults in connecticut and rhode island
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9258446/
https://www.ncbi.nlm.nih.gov/pubmed/35772039
http://dx.doi.org/10.5888/pcd19.210421
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