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

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

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Cross-Sectional Studies
  • Environment
  • Female
  • Humans
  • Male
  • Mammography / statistics & numerical data
  • Middle Aged
  • Poverty / statistics & numerical data
  • Quality of Life
  • Residence Characteristics / statistics & numerical data*
  • Socioeconomic Factors
  • Transportation / statistics & numerical data
  • Young Adult