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Development of a population attributable risk screening tool to estimate health consequences of consumer product exposure

Author

Listed:
  • Amy B. Rosenstein

    (U.S. Army Corps of Engineers North Atlantic Division)

  • Treye Thomas

    (U.S. Consumer Product Safety Commission)

  • Igor Linkov

    (U.S. Army Engineer Research and Development Center Environmental Laboratory (ERDC-EL))

  • Christopher Cummings

    (U.S. Army Engineer Research and Development Center Environmental Laboratory (ERDC-EL))

  • Kelby Kramer

    (U.S. Army Engineer Research and Development Center Environmental Laboratory (ERDC-EL))

  • Jason Deng

    (Independent Software Engineer)

  • Miriam Pollock

    (U.S. Army Engineer Research and Development Center Environmental Laboratory (ERDC-EL))

  • Jeffrey M. Keisler

    (University of Massachusetts)

Abstract

Chemical exposures from consumer products are a major concern in modern society. To address the need for accurate health risk estimation, particularly for chronic chemical hazards that may be less evident such as those contained in consumer products, this study reports on the development of the Population Attributable Risk Screening Tool (PAR Tool) Version 1.0. The PAR Tool was designed for the use of professional staff at the Consumer Product Safety Commission (CPSC), and assumes some prior knowledge of chemical risk assessment. This tool provides reasonable estimates of potential acute and chronic health impacts and mortality resulting from exposure to chemicals in consumer products. The PAR Tool provides the ability to integrate diverse data sources, including consumer product composition, user exposures, chemical toxicity data, consumer use patterns, and other pertinent factors to estimate the Population Attributable Risk associated with exposures to chemical components in consumer products. By generating PAR estimates on a chemical-by-chemical basis, the tool will assist the CPSC in assessing potential health risks and prioritizing efforts for risk reduction. Output from the tool provides an estimate of the number of specific health outcomes that may occur in the population of users of a specific consumer product. Interim steps produce exposure percentiles that are used along with dose–response data for a selected chemical and exposure pathway to calculate the proportion of the population at risk. The output is an estimated number of cases of an adverse health effect or mortality in a product user population potentially related to exposures to a single chemical in a product. These results are based primarily on user inputs, and the rationale for selection of these inputs is documented. All inputs and calculations within the PAR Tool are traceable and based on accepted practices and resources. The ongoing development of the PAR Tool aims to enhance its functionalities, incorporating features such as uncertainty analysis, increased automation, and user support. For example, future iterations may allow CPSC users to analyze multiple chemicals and health endpoints simultaneously and introduce sensitivity analysis capabilities for exposure and toxicity parameters. Ultimately, the PAR Tool represents a valuable advancement in comprehending product risks related to consumer product exposure, contributing to enhanced consumer protection and improved health outcomes.

Suggested Citation

  • Amy B. Rosenstein & Treye Thomas & Igor Linkov & Christopher Cummings & Kelby Kramer & Jason Deng & Miriam Pollock & Jeffrey M. Keisler, 2024. "Development of a population attributable risk screening tool to estimate health consequences of consumer product exposure," Environment Systems and Decisions, Springer, vol. 44(2), pages 280-292, June.
  • Handle: RePEc:spr:envsyd:v:44:y:2024:i:2:d:10.1007_s10669-024-09970-1
    DOI: 10.1007/s10669-024-09970-1
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    References listed on IDEAS

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    5. Elaine A. Cohen Hubal & David M. Reif & Rachel Slover & Ashley Mullikin & John C. Little, 2020. "Children’s Environmental Health: A Systems Approach for Anticipating Impacts from Chemicals," IJERPH, MDPI, vol. 17(22), pages 1-13, November.
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