Characterizing Risk for Cumulative Risk Assessments: Characterizing Risk for Cumulative Risk Assessments
Abstract
In assessing environmental health risks, the risk characterization step synthesizes information gathered in evaluating exposures to stressors together with dose-response relationships, characteristics of the exposed population, and external environmental conditions. This article summarizes key steps of a cumulative risk assessment (CRA) followed by a discussion of considerations for characterizing cumulative risks. Cumulative risk characterizations differ considerably from single chemical- or single source-based risk characterization. CRAs typically focus on a specific population instead of a pollutant or pollutant source and should include an evaluation of all relevant sources contributing to the exposures in the population and other factors that influence dose-response relationships. Second, CRAs may include influential environmental and population-specific conditions, involving multiple chemical and nonchemical stressors. Third, a CRA could examine multiple health effects, reflecting joint toxicity and the potential for toxicological interactions. Fourth, the complexities often necessitate simplifying methods, including judgment-based and semi-quantitative indices that collapse disparate data into numerical scores. Fifth, because of the higher dimensionality and potentially large number of interactions, information needed to quantify risk is typically incomplete, necessitating an uncertainty analysis. Three approaches that could be used for characterizing risks in a CRA are presented: the multiroute hazard index, stressor grouping by exposure and toxicity,more »
- Authors:
-
- Argonne National Lab. (ANL), Argonne, IL (United States). Environmental Science Division
- Emory Univ., Atlanta, GA (United States). Biomathematics Consulting and Dept. of Environmental Health
- US Environmental Protection Agency (EPA), Cincinnati, OH (United States). National Center for Environmental Assessment, Office of Research and Development
- Linda Teuschler and Associates, St. Petersburg FL (United States)
- Publication Date:
- Research Org.:
- Argonne National Lab. (ANL), Argonne, IL (United States)
- Sponsoring Org.:
- USEPA; USDOE; U.S. Environmental Protection Agency (EPA) - Office of Research and Development - National Center for Environmental Assessment
- OSTI Identifier:
- 1459874
- Alternate Identifier(s):
- OSTI ID: 1493876
- Grant/Contract Number:
- AC02-06CH11357
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Risk Analysis
- Additional Journal Information:
- Journal Volume: 38; Journal Issue: 6; Journal ID: ISSN 0272-4332
- Publisher:
- Wiley
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 60 APPLIED LIFE SCIENCES; cumulative risk assessment; multiple stressors; risk characterization
Citation Formats
MacDonell, Margaret M., Hertzberg, Richard C., Rice, Glenn E., Wright, J. Michael, and Teuschler, Linda K. Characterizing Risk for Cumulative Risk Assessments: Characterizing Risk for Cumulative Risk Assessments. United States: N. p., 2017.
Web. doi:10.1111/risa.12933.
MacDonell, Margaret M., Hertzberg, Richard C., Rice, Glenn E., Wright, J. Michael, & Teuschler, Linda K. Characterizing Risk for Cumulative Risk Assessments: Characterizing Risk for Cumulative Risk Assessments. United States. https://doi.org/10.1111/risa.12933
MacDonell, Margaret M., Hertzberg, Richard C., Rice, Glenn E., Wright, J. Michael, and Teuschler, Linda K. Thu .
"Characterizing Risk for Cumulative Risk Assessments: Characterizing Risk for Cumulative Risk Assessments". United States. https://doi.org/10.1111/risa.12933. https://www.osti.gov/servlets/purl/1459874.
@article{osti_1459874,
title = {Characterizing Risk for Cumulative Risk Assessments: Characterizing Risk for Cumulative Risk Assessments},
author = {MacDonell, Margaret M. and Hertzberg, Richard C. and Rice, Glenn E. and Wright, J. Michael and Teuschler, Linda K.},
abstractNote = {In assessing environmental health risks, the risk characterization step synthesizes information gathered in evaluating exposures to stressors together with dose-response relationships, characteristics of the exposed population, and external environmental conditions. This article summarizes key steps of a cumulative risk assessment (CRA) followed by a discussion of considerations for characterizing cumulative risks. Cumulative risk characterizations differ considerably from single chemical- or single source-based risk characterization. CRAs typically focus on a specific population instead of a pollutant or pollutant source and should include an evaluation of all relevant sources contributing to the exposures in the population and other factors that influence dose-response relationships. Second, CRAs may include influential environmental and population-specific conditions, involving multiple chemical and nonchemical stressors. Third, a CRA could examine multiple health effects, reflecting joint toxicity and the potential for toxicological interactions. Fourth, the complexities often necessitate simplifying methods, including judgment-based and semi-quantitative indices that collapse disparate data into numerical scores. Fifth, because of the higher dimensionality and potentially large number of interactions, information needed to quantify risk is typically incomplete, necessitating an uncertainty analysis. Three approaches that could be used for characterizing risks in a CRA are presented: the multiroute hazard index, stressor grouping by exposure and toxicity, and indices for screening multiple factors and conditions. Other key roles of the risk characterization in CRAs are also described, mainly the translational aspect of including a characterization summary for lay readers (in addition to the technical analysis), and placing the results in the context of the likely risk-based decisions.},
doi = {10.1111/risa.12933},
journal = {Risk Analysis},
number = 6,
volume = 38,
place = {United States},
year = {Thu Nov 23 00:00:00 EST 2017},
month = {Thu Nov 23 00:00:00 EST 2017}
}
Web of Science
Figures / Tables:
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