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Per- and polyfluoroalkyl substances (PFAS) exposure from dietary and drinking water by integrating probabilistic modeling and community-based research in a vulnerable community in the Central Savannah River Area, USA

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NIAID Data Ecosystem2026-05-10 收录
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https://figshare.com/articles/dataset/Per-_and_polyfluoroalkyl_substances_PFAS_exposure_from_dietary_and_drinking_water_by_integrating_probabilistic_modeling_and_community-based_research_in_a_vulnerable_community_in_the_Central_Savannah_River_Area_USA/31974767
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This study evaluated exposure to per- and polyfluoroalkyl substances (PFAS) through routine dietary and tap water intake among residents of Downtown Augusta (GA, USA) in the Central Savannah River Area. Using community-based participatory research methods, we recruited 18 households (63 participants) and collected detailed grocery records, dietary intake data, and unfiltered residential tap water samples. Dietary PFAS exposure was modeled using national-level concentration data from the U.S. Food and Drug Administration, while drinking water samples were analyzed for targeted PFAS compounds. Monte Carlo simulations were employed to estimate individual intake rates, incorporating variability in contaminant levels, ingestion behavior, and body weight. Results showed that 33.3% of households exceeded the U.S. Environmental Protection Agency’s (EPA) Maximum Contaminant Levels for PFOA and PFOS in tap water. Simulated intake estimates indicated that 100% of participants exceeded the EPA’s draft reference dose (RfD) for PFOA, and 92.4% exceeded the RfD for PFOS. Although households provided food samples, these were not analyzed due to funding limitations. Sociodemographic analyses revealed that households with lower income and educational attainment experienced greater exposure risk. These findings highlight a disproportionate PFAS burden in underserved communities and reinforce the need for targeted mitigation strategies. The integration of environmental sampling, exposure modeling, and community engagement provides a replicable framework for identifying at-risk populations and informing equitable environmental health policies.
创建时间:
2026-04-09
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