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Cumulative Exposures to Environmental and Socioeconomic Risk Factors in Milwaukee County, Wisconsin
  • +3
  • John K Kodros,
  • Ellison Carter,
  • Oluwatobi Oke,
  • Ander Wilson,
  • Shantanu H Jathar,
  • Sheryl Magzamen
John K Kodros
Colorado State University
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Ellison Carter
Colorado State University
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Oluwatobi Oke
Colorado State University
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Ander Wilson
Colorado State University
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Shantanu H Jathar
Colorado State University

Corresponding Author:[email protected]

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Sheryl Magzamen
Colorado State University
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Abstract

The environmental justice literature demonstrates consistently that low-income and minority communities are disproportionately exposed to environmental hazards. In this case study, we examined cumulative multipollutant, multidomain, and multimatrix environmental exposures in Milwaukee County, Wisconsin. We identified spatial hot spots in Milwaukee County both individually and through clusters across a profile of environmental pollutants that span regulatory domains and matrices of exposure, as well as socioeconomic indicators. The most sensitive cluster within the urban area was largely characterized by low socioeconomic status (SES) and an overrepresentation of the Non-Hispanic Black (NHB) population relative to the county as a whole. In this cluster, average pollutant concentrations were equivalent to the 78th percentile in county-level blood lead levels, 67th percentile in county-level NO2, 79th percentile in county-level CO, and 78th percentile in county-level air toxics while simultaneously having an average equivalent to the 62nd percentile in county-level unemployment, 70th percentile in county-level population rate lacking a high school diploma, 73rd percentile in county-level poverty rate, and 28th percentile in county-level median household income. The spatial patterns of pollutant exposure and SES indicators suggested that these disparities were not random but were instead structured by socioeconomic and racial factors. Our case study, which combines environmental pollutant exposures, sociodemographic data, and clustering analysis, provides a roadmap to identify and target overburdened communities for interventions that reduce environmental exposures and consequently improve public health.
16 Aug 2023Submitted to ESS Open Archive
21 Aug 2023Published in ESS Open Archive