Background: There is a recognized need to improve the application of epidemiologic data in human health risk assessment especially for understanding and characterizing risks from environmental and occupational exposures. Although there is uncertainty associated with the results of most epidemiologic studies, techniques exist to characterize uncertainty that can be applied to improve weight-of-evidence evaluations and risk characterization efforts.
Methods: This report derives from a Health and Environmental Sciences Institute (HESI) workshop held in Research Triangle Park, North Carolina, to discuss the utility of using epidemiologic data in risk assessments, including the use of advanced analytic methods to address sources of uncertainty. Epidemiologists, toxicologists, and risk assessors from academia, government, and industry convened to discuss uncertainty, exposure assessment, and application of analytic methods to address these challenges.
Synthesis: Several recommendations emerged to help improve the utility of epidemiologic data in risk assessment. For example, improved characterization of uncertainty is needed to allow risk assessors to quantitatively assess potential sources of bias. Data are needed to facilitate this quantitative analysis, and interdisciplinary approaches will help ensure that sufficient information is collected for a thorough uncertainty evaluation. Advanced analytic methods and tools such as directed acyclic graphs (DAGs) and Bayesian statistical techniques can provide important insights and support interpretation of epidemiologic data.
Conclusions: The discussions and recommendations from this workshop demonstrate that there are practical steps that the scientific community can adopt to strengthen epidemiologic data for decision making.
1The Dow Chemical Company, Midland, Michigan, USA; 2National Center for Environmental Assessment (NCEA), U.S. Environmental Protection Agency (EPA), Cincinnati, Ohio, USA; 3Health and Environmental Sciences Institute, International Life Sciences Institute (ILSI-HESI), Washington, DC, USA; 4NCEA, U.S. EPA, Washington, DC, USA; 5Department of Environmental and Occupational Health, Drexel University School of Public Health, Philadelphia, Pennsylvania, USA; 6Monsanto, St. Louis, Missouri, USA; 7Department of Environmental Health, Indiana University School of Public Health, Bloomington, Indiana, USA; 8NCEA, U.S. EPA, Research Triangle Park, North Carolina, USA; 9Bayer CropScience, Research Triangle Park, North Carolina, USA; 10School of Environmental Sciences, University of Guelph, Guelph, Ontario, Canada; 11ExxonMobil Biomedical Sciences Inc., Annandale, New Jersey, USA; 12E.I. du Pont de Nemours and Company, Newark, Delaware, USA; 13Syngenta Crop Protection LLC, Greensboro, North Carolina, USA
Recommended Citation:
Carol J. Burns,1 J. Michael Wright,2 Jennifer B. Pierson,et al. Evaluating Uncertainty to Strengthen Epidemiologic Data for Use in Human Health Risk Assessments[J]. Environmental Health Perspectives,2014-01-01,Volume 122(Issue 11):1160