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PLoS One. 2018 May 23;13(5):e0196720. doi: 10.1371/journal.pone.0196720. eCollection 2018.

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

Author information

1
Department of Internal Medicine, Section of General Internal Medicine, Yale School of Medicine, New Haven, Connecticut, United States of America.
2
Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati, Ohio, United States of America.
3
Division of Critical Care, Cincinnati Children's Hospital Medical Center, Cincinnati, Ohio, United States of America.
4
Department of Internal Medicine, Section of Cardiovascular Medicine, Yale School of Medicine, Center for Outcomes Research and Evaluation, New Haven, Connecticut, United States of America.
5
Tivity Health, Franklin, Tennessee, United States of America.
6
Yale University, New Haven, Connecticut, United States of America.
7
Department of Internal Medicine, Section of Cardiovascular Medicine, Yale School of Medicine; Department of Health Policy and Management, Yale School of Public Health; Center for Outcomes Research and Evaluation, Yale-New Haven Hospital, New Haven, Connecticut, United States of America.

Abstract

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.

PMID:
29791476
PMCID:
PMC5965855
DOI:
10.1371/journal.pone.0196720
[Indexed for MEDLINE]
Free PMC Article

Conflict of interest statement

The authors declare the following competing interests: partial support from the Agency for Healthcare Research and Quality (BR and ES) and the Robert Wood Johnson Foundation (BR, CR, and AA) and the Veterans Administration (BR) for the submitted work; AA was partially supported by the Yale Center for Clinical Investigation through Clinical and Translational Science Award during the study period; BR and CR are consultants for the Institute for Healthcare Improvement 100 Million Healthier Lives initiative; ER and KK are current or former employees and shareholders of the Healthways corporation (acquired by Sharecare), the company that developed the measure of well-being used in this article; ES, JH, and HK also report receiving support from the Centers for Medicare & Medicaid Services; Dr. Krumholz is a recipient of research agreements from Medtronic and Johnson & Johnson (Janssen), through Yale, to develop methods of clinical trial data sharing; is the recipient of a grant from Medtronic and the Food and Drug Administration, through Yale, to develop methods for postmarket surveillance of medical devices; works under contract with the Centers for Medicare & Medicaid Services to develop and maintain performance measures; chairs a cardiac scientific advisory board for UnitedHealth; is a participant/participant representative of the IBM Watson Health Life Sciences Board; is a member of the Advisory Board for Element Science and the Physician Advisory Board for Aetna; and is the founder of Hugo, a personal health information platform. This does not alter our adherence to PLOS ONE policies on sharing data and materials.

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