Health risk assessment of perfluorooctane sulfonate and perfluorooctanoic acid exposure in China based on epidemiological data

Health risk assessment based on epidemiological data for perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) are evidenced. Whereas information about health-based guidance values (HBGVs) and health risk for Chinese population related to PFOS and PFOA is scarce. To provide candidate HBGVs for PFOS and PFOA based on Chinese epidemiological data and assess the health risk related to excessive exposure. We reviewed scientific literature and collected available original data from epidemiological studies conducted in China. Critical endpoints and data were selected and used in benchmark dose (BMD) analysis to obtain lower confidence limits of BMD (BMDLs) of PFOS and PFOA. Physiologically based pharmacokinetic (PBPK) models were applied to calculate the point of departure (PODs) for PFOS and PFOA, which led to the determination of the HBGVs for the said chemicals. Margin of exposure (MOE) method was used to evaluate the health risk of population based on exposure data among Chinese and HBGVs. Alanine aminotransferase (ALT), total cholesterol (TC) and birth weight (BW) were selected as critical endpoints. Epidemiological data from 4,224 adults, 2,153 paired mother-newborn, 2,518 newborns, 439 pregnant women and 733 children in China were included in this study. BMDLs and PODs for PFOS are varied while BMDLs for PFOA were similar. PODs for PFOS (1.56 ng/kg/day) and PFOA (1.52 ng/kg/day) based on BW using National Birth Cohort Study were selected as HBGVs. Most MOEs for PFOS and PFOA among Chinese population were larger than 1 and smaller than 100, indicating moderate concern. Around 16% MOEs for PFOS were smaller than 1, implying high concern. The HBGVs for PFOS and PFOA were 1.56 ng/kg/day and 1.52 ng/kg/day, respectively. Health risk of Chinese population related to PFOS and PFOA exposure should be concerned and more studies should be conducted to evaluate the risk of the chemicals.