Risk Analysis

What to Do at Low Doses: A Bounding Approach for Economic Analysis

Journal Article

  • Author(s): Charles W. Griffiths, Chris Dockins, Nicole Owens, Nathalie B. Simon, Daniel A. Axelrad
  • Article first published online: 03 Oct 2002
  • DOI: 10.1111/0272-4332.00060
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To quantify the health benefits of environmental policies, economists generally require estimates of the reduced probability of illness or death. For policies that reduce exposure to carcinogenic substances, these estimates traditionally have been obtained through the linear extrapolation of experimental dose‐response data to low‐exposure scenarios as described in the U.S. Environmental Protection Agency's Guidelines for Carcinogen Risk Assessment (1986). In response to evolving scientific knowledge, EPA proposed revisions to the guidelines in 1996. Under the proposed revisions, dose‐response relationships would not be estimated for carcinogens thought to exhibit nonlinear modes of action. Such a change in cancer‐risk assessment methods and outputs will likely have serious consequences for how benefit‐cost analyses of policies aimed at reducing cancer risks are conducted. Any tendency for reduced quantification of effects in environmental risk assessments, such as those contemplated in the revisions to EPA's cancer‐risk assessment guidelines, impedes the ability of economic analysts to respond to increasing calls for benefit‐cost analysis. This article examines the implications for benefit‐cost analysis of carcinogenic exposures of the proposed changes to the 1986 Guidelines and proposes an approach for bounding dose‐response relationships when no biologically based models are available. In spite of the more limited quantitative information provided in a carcinogen risk assessment under the proposed revisions to the guidelines, we argue that reasonable bounds on dose‐response relationships can be estimated for low‐level exposures to nonlinear carcinogens. This approach yields estimates of reduced illness for use in a benefit‐cost analysis while incorporating evidence of nonlinearities in the dose‐response relationship. As an illustration, the bounding approach is applied to the case of chloroform exposure.

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