From Source to Dose: Modeling Human Exposure to Poly- and Perfluoroalkyl Substances

Monday, Apr 29 2019, 7:00 PM - 8:30 PM, CAPA Symposium
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Monday, Apr 29 2019 7:00 PM Monday, Apr 29 2019 8:30 PM America/New_York From Source to Dose: Modeling Human Exposure to Poly- and Perfluoroalkyl Substances OPEN TO THE PUBLIC | Xindi (Cindy) Hu, ScD is a data scientist at Mathematica Policy Research. She will be giving a talk titled From Source to Dose: Modeling Human Exposure to Poly- and Perfluoroalkyl Substances. CAPA Symposium Bennington College

OPEN TO THE PUBLIC | Poly- and Perfluoroalkyl Substances (PFASs) are a class of synthetic organic chemicals that have been in production since the 1950s. They are detectable in virtually all Americans and have been linked to a suite of adverse health outcomes including developmental, metabolic and immunotoxic effects. Elucidating the origin of contamination and the relative importance of exposure pathways is critical for designing effective public health interventions to reduce exposure and prevent adverse health outcomes. Pathways for human exposure to these compounds include marine foods, drinking water, and consumer goods. Several recent drinking water PFAS contamination has drawn nationwide attention.

In this talk, Hu will link environmental sources and human exposure to understand the role of the environment in the overall exposure and health risks related to PFASs. Using diverse data sources including the latest national-level occurrence data and samples from a large U.S.-based prospective cohort, Hu found that drinking water contamination by PFAS is prevalent and can be an important exposure pathway even for the general population living far away from the point sources. Hu's research has important implications for current risk assessment practice and drinking water health advisory levels. Hu's research shows the increasing importance of environmental sources for PFAS exposure as these compounds are being phased out in consumer products. Risk assessment needs to incorporate temporal changes, interindividual variability and source information to be effective and health protective.