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Heat-Related Illness Is Associated with Lack of Air Conditioning and Pre-Existing Health Problems in Detroit, Michigan, USA: A Community-Based Participatory Co-Analysis of Survey Data

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  • Jacqueline E. Cardoza

    (School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA)

  • Carina J. Gronlund

    (Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104, USA)

  • Justin Schott

    (EcoWorks, Detroit, MI 48219, USA)

  • Todd Ziegler

    (Environmental Health Sciences, University of Michigan School of Public Health, Ann Arbor, MI 48109, USA)

  • Brian Stone

    (Georgia Institute of Technology School of City and Regional Planning, Atlanta, GA 30332, USA)

  • Marie S. O’Neill

    (School of Public Health, University of Michigan, Ann Arbor, MI 48109, USA)

Abstract

The objective of the study was to investigate, using academic-community epidemiologic co-analysis, the odds of reported heat-related illness for people with (1) central air conditioning (AC) or window unit AC versus no AC, and (2) fair/poor vs. good/excellent reported health. From 2016 to 2017, 101 Detroit residents were surveyed once regarding extreme heat, housing and neighborhood features, and heat-related illness in the prior 5 years. Academic partners selected initial confounders and, after instruction on directed acyclic graphs, community partners proposed alternate directed acyclic graphs with additional confounders. Heat-related illness was regressed on AC type or health and co-selected confounders. The study found that heat-related illness was associated with no-AC ( n = 96, odds ratio (OR) = 4.66, 95% confidence interval (CI) = 1.22, 17.72); living ≤5 years in present home ( n = 57, OR = 10.39, 95% CI = 1.13, 95.88); and fair/poor vs. good/excellent health ( n = 97, OR = 3.15, 95% CI = 1.33, 7.48). Co-analysis suggested multiple built-environment confounders. We conclude that Detroit residents with poorer health and no AC are at greater risk during extreme heat. Academic-community co-analysis using directed acyclic graphs enhances research on community-specific social and health vulnerabilities by identifying key confounders and future research directions for rigorous and impactful research.

Suggested Citation

  • Jacqueline E. Cardoza & Carina J. Gronlund & Justin Schott & Todd Ziegler & Brian Stone & Marie S. O’Neill, 2020. "Heat-Related Illness Is Associated with Lack of Air Conditioning and Pre-Existing Health Problems in Detroit, Michigan, USA: A Community-Based Participatory Co-Analysis of Survey Data," IJERPH, MDPI, vol. 17(16), pages 1-11, August.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:16:p:5704-:d:395791
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    References listed on IDEAS

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    1. Jaime Madrigano & Kathryn Lane & Nada Petrovic & Munerah Ahmed & Micheline Blum & Thomas Matte, 2018. "Awareness, Risk Perception, and Protective Behaviors for Extreme Heat and Climate Change in New York City," IJERPH, MDPI, vol. 15(7), pages 1-11, July.
    2. Cashman, S.B. & Adeky, S. & Allen III, A.J. & Corburn, J. & Israel, B.A. & Montaño, J. & Rafelito, A. & Rhodes, S.D. & Swanston, S. & Wallerstein, N. & Eng, E., 2008. "The power and the promise: Working with communities to analyze data, interpret findings, and get to outcomes," American Journal of Public Health, American Public Health Association, vol. 98(8), pages 1407-1417.
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    4. Jalonne L. White-Newsome & Sabrina McCormick & Natalie Sampson & Miatta A. Buxton & Marie S. O'Neill & Carina J. Gronlund & Linda Catalano & Kathryn C. Conlon & Edith A. Parker, 2014. "Strategies to Reduce the Harmful Effects of Extreme Heat Events: A Four-City Study," IJERPH, MDPI, vol. 11(2), pages 1-29, February.
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