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Weighing Down America: 2020 Update A Community Approach against Obesity

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Listed:
  • Lopez, Claude
  • Bendix, Joseph

Abstract

Obesity impacts segments of the US population differently based on their behavioral and socioeconomic profiles. The Milken Institute COVID-19 Community Explorer sorts US counties around eight profiles of communities that share common patterns across behavioral, economic, and social factors. This report uses these communities and identifies which of the 26 factors considered are systemically correlated with high obesity rates for each community. This report identifies three groups of factors that matter for a large part of the US population: • Social and behavioral factors, such as unemployment, excessive drinking, smoking, post-secondary education, and single-parent households, have the strongest association with obesity prevalence across all eight communities' profiles. • Urban-rural factors, including rurality, housing concerns, population density, metropolitan area, violent crime rate, and the number of fast-food establishments per 100,000 people, have the second strongest association with obesity prevalence across four communities, representing 78 percent of the US population. • The Black population factor has the third strongest association with obesity prevalence across four communities. These communities represent 61 percent of the US population. The analysis combines health, behavioral, economic, and social data sets and suggests that some aspects of the obesity epidemic would be better addressed at the local level, while others would benefit from a federal initiative. It also identifies factors for each community to consider when coordinating national and local authorities and other partners such as health-care professionals, business and community leaders, school, and child care. Finally, our analysis shows that the data sets collected need to be properly combined, processed, and analyzed to inform policy in a meaningful and actionable manner.

Suggested Citation

  • Lopez, Claude & Bendix, Joseph, 2020. "Weighing Down America: 2020 Update A Community Approach against Obesity," MPRA Paper 104562, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:104562
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    File URL: https://mpra.ub.uni-muenchen.de/104562/1/MPRA_paper_104562.pdf
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    References listed on IDEAS

    as
    1. Northridge, M.E., 1995. "Public health methods--attributable risk as a link between causality and public health action," American Journal of Public Health, American Public Health Association, vol. 85(9), pages 1202-1204.
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    More about this item

    Keywords

    obesity; community; counties; cluster; machine learning;
    All these keywords.

    JEL classification:

    • C8 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs
    • I12 - Health, Education, and Welfare - - Health - - - Health Behavior
    • I14 - Health, Education, and Welfare - - Health - - - Health and Inequality
    • I18 - Health, Education, and Welfare - - Health - - - Government Policy; Regulation; Public Health

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