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Identifying county characteristics associated with resident well-being: A population based study

BACKGROUND: Well-being is a positively-framed, holistic assessment of health and quality of life that is associated with longevity and better health outcomes. We aimed to identify county attributes that are independently associated with a comprehensive, multi-dimensional assessment of individual wel...

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Autores principales: Roy, Brita, Riley, Carley, Herrin, Jeph, Spatz, Erica S., Arora, Anita, Kell, Kenneth P., Welsh, John, Rula, Elizabeth Y., Krumholz, Harlan M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5965855/
https://www.ncbi.nlm.nih.gov/pubmed/29791476
http://dx.doi.org/10.1371/journal.pone.0196720
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author Roy, Brita
Riley, Carley
Herrin, Jeph
Spatz, Erica S.
Arora, Anita
Kell, Kenneth P.
Welsh, John
Rula, Elizabeth Y.
Krumholz, Harlan M.
author_facet Roy, Brita
Riley, Carley
Herrin, Jeph
Spatz, Erica S.
Arora, Anita
Kell, Kenneth P.
Welsh, John
Rula, Elizabeth Y.
Krumholz, Harlan M.
author_sort Roy, Brita
collection PubMed
description BACKGROUND: Well-being is a positively-framed, holistic assessment of health and quality of life that is associated with longevity and better health outcomes. We aimed to identify county attributes that are independently associated with a comprehensive, multi-dimensional assessment of individual well-being. METHODS: We performed a cross-sectional study examining associations between 77 pre-specified county attributes and a multi-dimensional assessment of individual US residents’ well-being, captured by the Gallup-Sharecare Well-Being Index. Our cohort included 338,846 survey participants, randomly sampled from 3,118 US counties or county equivalents. FINDINGS: We identified twelve county-level factors that were independently associated with individual well-being scores. Together, these twelve factors explained 91% of the variance in individual well-being scores, and they represent four conceptually distinct categories: demographic (% black); social and economic (child poverty, education level [<high school, high school diploma/equivalent, college degree], household income, % divorced); clinical care (% eligible women obtaining mammography, preventable hospital stays per 100,000, number of federally qualified health centers); and physical environment (% commuting by bicycle and by public transit). CONCLUSIONS: Twelve factors across social and economic, clinical care, and physical environmental county-level factors explained the majority of variation in resident well-being.
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spelling pubmed-59658552018-06-02 Identifying county characteristics associated with resident well-being: A population based study Roy, Brita Riley, Carley Herrin, Jeph Spatz, Erica S. Arora, Anita Kell, Kenneth P. Welsh, John Rula, Elizabeth Y. Krumholz, Harlan M. PLoS One Research Article BACKGROUND: Well-being is a positively-framed, holistic assessment of health and quality of life that is associated with longevity and better health outcomes. We aimed to identify county attributes that are independently associated with a comprehensive, multi-dimensional assessment of individual well-being. METHODS: We performed a cross-sectional study examining associations between 77 pre-specified county attributes and a multi-dimensional assessment of individual US residents’ well-being, captured by the Gallup-Sharecare Well-Being Index. Our cohort included 338,846 survey participants, randomly sampled from 3,118 US counties or county equivalents. FINDINGS: We identified twelve county-level factors that were independently associated with individual well-being scores. Together, these twelve factors explained 91% of the variance in individual well-being scores, and they represent four conceptually distinct categories: demographic (% black); social and economic (child poverty, education level [<high school, high school diploma/equivalent, college degree], household income, % divorced); clinical care (% eligible women obtaining mammography, preventable hospital stays per 100,000, number of federally qualified health centers); and physical environment (% commuting by bicycle and by public transit). CONCLUSIONS: Twelve factors across social and economic, clinical care, and physical environmental county-level factors explained the majority of variation in resident well-being. Public Library of Science 2018-05-23 /pmc/articles/PMC5965855/ /pubmed/29791476 http://dx.doi.org/10.1371/journal.pone.0196720 Text en © 2018 Roy et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Roy, Brita
Riley, Carley
Herrin, Jeph
Spatz, Erica S.
Arora, Anita
Kell, Kenneth P.
Welsh, John
Rula, Elizabeth Y.
Krumholz, Harlan M.
Identifying county characteristics associated with resident well-being: A population based study
title Identifying county characteristics associated with resident well-being: A population based study
title_full Identifying county characteristics associated with resident well-being: A population based study
title_fullStr Identifying county characteristics associated with resident well-being: A population based study
title_full_unstemmed Identifying county characteristics associated with resident well-being: A population based study
title_short Identifying county characteristics associated with resident well-being: A population based study
title_sort identifying county characteristics associated with resident well-being: a population based study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5965855/
https://www.ncbi.nlm.nih.gov/pubmed/29791476
http://dx.doi.org/10.1371/journal.pone.0196720
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