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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...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2018
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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. |
format | Online Article Text |
id | pubmed-5965855 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
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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