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Biomonitoring - An Exposure Science Tool for Exposure and Risk Assessment
Citation:
TAN, YU-MEI, C. C. DARY, D. CHANG, E. M. ULRICH, J. M. VAN EMON, J. XUE, J. D. PLEIL, J. F. KENNEKE, J. SOBUS, L. S. SHELDON, M. K. MORGAN, M. GOLDSMITH, R. TORNERO-VELEZ, R. HIGHSMITH, R. C. FORTMANN, T. W. COLLETTE, AND V. G. ZARTARIAN. Biomonitoring - An Exposure Science Tool for Exposure and Risk Assessment. U.S. Environmental Protection Agency, Washington, DC, EPA/600/R-12/039 (NTIS PB2012-112321), 2012.
Impact/Purpose:
The National Exposure Research Laboratory′s (NERL′s) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA′s mission to protect human health and the environment. HEASD′s research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA′s strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and policies for EPA.
Description:
Biomonitoring studies of environmental stressors are useful for confirming exposures, estimating dose levels, and evaluating human health risks. However, the complexities of exposure-biomarker and biomarker-response relationships have limited the use of biomarkers in exposure science studies. In this document, an updated source-to-outcome continuum is presented to better define biomarkers as tools for human health research; specific attention is given to biomarker applications in exposure research. This continuum links exposure sources and health outcomes using a compilation of measurements, mathematical models, and model estimates. A tiered approach to biomonitoring analyses is presented, based on this continuum, to categorize the uses of biomonitoring data given various research objectives, and the availability of specific measurements and models. Tools that can be used to infer critical model parameters and model estimates (when they are unavailable) are also discussed to improve biomarker utilization for exposure and risk assessments. Finally, frequently encountered complications in biomonitoring studies are discussed along with suggestions to address these challenges.