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Associations between socio-demographic characteristics and chemical concentrations contributing to cumulative exposures in the United States

Abstract

Association rule mining (ARM) has been widely used to identify associations between various entities in many fields. Although some studies have utilized it to analyze the relationship between chemicals and human health effects, fewer have used this technique to identify and quantify associations between environmental and social stressors. Socio-demographic variables were generated based on U.S. Census tract-level income, race/ethnicity population percentage, education level, and age information from the 2010–2014, 5-Year Summary files in the American Community Survey (ACS) database, and chemical variables were generated by utilizing the 2011 National-Scale Air Toxics Assessment (NATA) census tract-level air pollutant exposure concentration data. Six mobile- and industrial-source pollutants were chosen for analysis, including acetaldehyde, benzene, cyanide, particulate matter components of diesel engine emissions (namely, diesel PM), toluene, and 1,3-butadiene. ARM was then applied to quantify and visualize the associations between the chemical and socio-demographic variables. Census tracts with a high percentage of racial/ethnic minorities and populations with low income tended to have higher estimated chemical exposure concentrations (fourth quartile), especially for diesel PM, 1,3-butadiene, and toluene. In contrast, census tracts with an average population age of 40–50 years, a low percentage of racial/ethnic minorities, and moderate-income levels were more likely to have lower estimated chemical exposure concentrations (first quartile). Unsupervised data mining methods can be used to evaluate potential associations between environmental inequalities and social disparities, while providing support in public health decision-making contexts.

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Acknowledgements

We thank Dr. Eric S. Hall and Dr. Brandall Ingle for their feedback during the EPA internal review process. This research was supported in part by an appointment to the Postdoctoral Research Program at the U.S. Environmental Protection Agency’s National Exposure Research Laboratory (Research Triangle Park, NC, USA) administered by the Oak Ridge Institute for Science and Education through an Interagency Agreement between the U.S. Department of Energy and the U.S. Environmental Protection Agency. The views expressed in this article are those of the authors and do not necessarily represent the views or policies of the U.S. Environmental Protection Agency.

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Correspondence to Hongtai Huang.

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This article has been subjected to review by the EPA and approved for publication. Although this work was performed as research for the U.S. Environmental Protection Agency, it does not necessarily represent endorsement of official Agency policies.

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Huang, H., Tornero-Velez, R. & Barzyk, T. Associations between socio-demographic characteristics and chemical concentrations contributing to cumulative exposures in the United States. J Expo Sci Environ Epidemiol 27, 544–550 (2017). https://doi.org/10.1038/jes.2017.15

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Keywords

  • Combined 53 Effects
  • Cumulative Risks
  • Environmental Justice
  • Multiple Stressors
  • Rule Mining

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