Dataset Information

Identifying characteristics of high-poverty counties in the United States with high well-being: an observational cross-sectional study.

ABSTRACT: OBJECTIVE:To identify county characteristics associated with high versus low well-being among high-poverty counties. DESIGN:Observational cross-sectional study at the county level to investigate the associations of 29 county characteristics with the odds of a high-poverty county reporting population well-being in the top quintile versus the bottom quintile of well-being in the USA. County characteristics representing key determinants of health were drawn from the Robert Wood Johnson Foundation County Health Rankings and Roadmaps population health model. SETTING:Counties in the USA that are in the highest quartile of poverty rate. MAIN OUTCOME MEASURE:Gallup-Sharecare Well-being Index, a comprehensive population-level measure of physical, mental and social health. Counties were classified as having a well-being index score in the top or bottom 20% of all counties in the USA. RESULTS:Among 770 high-poverty counties, 72 were categorised as having high well-being and 311 as having low well-being. The high-well-being counties had a mean well-being score of 71.8 with a SD of 2.3, while the low-well-being counties had a mean well-being score of 60.2 with a SD of 2.8. Among the six domains of well-being, basic access, which includes access to housing and healthcare, and life evaluation, which includes life satisfaction and optimism, differed the most between high-being and low-well-being counties. Among 29 county characteristics tested, six were independently and significantly associated with high well-being (p<0.05). These were lower rates of preventable hospital stays, higher supply of primary care physicians, lower prevalence of smoking, lower physical inactivity, higher percentage of some college education and higher percentage of heavy drinkers. CONCLUSIONS:Among 770 high-poverty counties, approximately 9% outperformed expectations, reporting a collective well-being score in the top 20% of all counties in the USA. High-poverty counties reporting high well-being differed from high-poverty counties reporting low well-being in several characteristics.

SUBMITTER: Arora A

PROVIDER: S-EPMC7500307 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Identifying characteristics of high-poverty counties in the United States with high well-being: an observational cross-sectional study.

Arora Anita A Spatz Erica S ES Herrin Jeph J Riley Carley C Roy Brita B Rula Elizabeth Y EY Kell Kenneth Patton KP Krumholz Harlan M HM

BMJ open 20200917 9

<h4>Objective</h4>To identify county characteristics associated with high versus low well-being among high-poverty counties.<h4>Design</h4>Observational cross-sectional study at the county level to investigate the associations of 29 county characteristics with the odds of a high-poverty county reporting population well-being in the top quintile versus the bottom quintile of well-being in the USA. County characteristics representing key determinants of health were drawn from the Robert Wood Johns ...[more]

PMID: 32948545

Similar Datasets

Project description:ImportanceMore than half of the adult population in the United States has ever had a family member incarcerated, an experience more common among Black individuals. The impacts of family incarceration on well-being are not fully understood.ObjectiveTo assess the associations of incarceration of a family member with perceived well-being and differences in projected life expectancy.Design, setting, and participantsThis nationally representative cross-sectional study used data from the 2018 Family History of Incarceration Survey to examine how experiences of family member incarceration were associated with a holistic measure of well-being, including physical, mental, social, financial, and spiritual domains. Well-being was used to estimate change in life expectancy and was compared across varying levels of exposure to immediate and extended family member incarceration using logistic regression models to adjust for individual and household characteristics. Data were analyzed from October 2019 to April 2020.ExposuresRespondents' history of family member incarceration, including immediate and extended family members.Main outcomes and measuresThe main outcome was self-reported life-evaluation, a measure of overall well-being from the 100 Million Healthier Lives Adult Well-being Assessment. Respondents were considered thriving with a current life satisfaction score of 7 or greater and a future life optimism score of 8 or greater, each on a scale of 0 to 10. Other outcomes included physical health, mental health, social support, financial well-being, and spiritual well-being, each measured with separate scales. Additionally, life expectancy projections were estimated using population-level correlations with the Life Evaluation Index. All percentages were weighted to more closely represent the US population.ResultsOf 2815 individuals included in analysis, 1472 (51.7%) were women, 1765 (62.8%) were non-Hispanic White, and 868 (31.5%) were aged 35 to 54 years. A total of 1806 respondents (45.0%) reported having an immediate family member who was incarcerated. Compared with respondents with no family incarceration, any family member incarceration was associated with lower well-being overall (thriving: 69.5% [95% CI, 65.0%-75.0%] vs 56.9% [95% CI, 53.9%-59.9%]) and in every individual domain (eg, physical thriving: 51.1% [95% CI, 46.2-56.0] vs 35.5% [95% CI, 32.6%-38.3%]) and with a mean (SE) estimated 2.6 (0.03) years shorter life expectancy. Among those with any family incarceration, Black respondents had a mean (SE) estimated 0.46 (0.04) fewer years of life expectancy compared with White respondents.Conclusions and relevanceThese findings suggest that family member health and well-being may be an important avenue through which incarceration is associated with racial disparities in health and mortality. Decarceration efforts may improve population-level well-being and life expectancy by minimizing detrimental outcomes associated with incarceration among nonincarcerated family members.

Project description:BackgroundThe gap between the highest and lowest life expectancies for race-county combinations in the United States is over 35 y. We divided the race-county combinations of the US population into eight distinct groups, referred to as the "eight Americas," to explore the causes of the disparities that can inform specific public health intervention policies and programs.Methods and findingsThe eight Americas were defined based on race, location of the county of residence, population density, race-specific county-level per capita income, and cumulative homicide rate. Data sources for population and mortality figures were the Bureau of the Census and the National Center for Health Statistics. We estimated life expectancy, the risk of mortality from specific diseases, health insurance, and health-care utilization for the eight Americas. The life expectancy gap between the 3.4 million high-risk urban black males and the 5.6 million Asian females was 20.7 y in 2001. Within the sexes, the life expectancy gap between the best-off and the worst-off groups was 15.4 y for males (Asians versus high-risk urban blacks) and 12.8 y for females (Asians versus low-income southern rural blacks). Mortality disparities among the eight Americas were largest for young (15-44 y) and middle-aged (45-59 y) adults, especially for men. The disparities were caused primarily by a number of chronic diseases and injuries with well-established risk factors. Between 1982 and 2001, the ordering of life expectancy among the eight Americas and the absolute difference between the advantaged and disadvantaged groups remained largely unchanged. Self-reported health plan coverage was lowest for western Native Americans and low-income southern rural blacks. Crude self-reported health-care utilization, however, was slightly higher for the more disadvantaged populations.ConclusionsDisparities in mortality across the eight Americas, each consisting of millions or tens of millions of Americans, are enormous by all international standards. The observed disparities in life expectancy cannot be explained by race, income, or basic health-care access and utilization alone. Because policies aimed at reducing fundamental socioeconomic inequalities are currently practically absent in the US, health disparities will have to be at least partly addressed through public health strategies that reduce risk factors for chronic diseases and injuries.

Dataset Information

Identifying characteristics of high-poverty counties in the United States with high well-being: an observational cross-sectional study.

Publications

Identifying characteristics of high-poverty counties in the United States with high well-being: an observational cross-sectional study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets