Model estimates of arsenic exposure and dose and evaluation with 2003 NHANES data
Jianping Xue1, Valerie Zartarian1, Sheng-Wei Wang2, and Panos G. Georgopoulos2
1USEPA National Exposure Research Laboratory, RTP, NC
2Environmental & Occupational Health Sciences Institute, Piscataway, NJ
Many studies have revealed that chronic arsenic (As) exposure may be linked to various cancers, cardiovascular disease, diabetes, peripheral artery diseases, and other diseases. Modeling human exposure from dietary and drinking water ingestion of As and evaluating model predictions using real-world urine biomarker data is important for conducting source-to-effects analyses. We applied EPA/ORD’s SHEDS dietary module to estimate As exposure from dietary and drinking water using the following data: (a) direct and indirect drinking water (16934 person-days) and 30 day fish consumption recall data (2106 person) from the 2003 NHANES, (b) As food residue data from FDA , and (c) As concentrations in drinking water of 25 states reported from the Natural Resources Defense Council (Feb. 2000). The exposure distributions were then used as inputs for the calculation of target tissue doses employing the Physiologically Based Pharmacokinetic (PBPK) module of MENTOR (Modeling ENvironment for TOtal Risk studies). This offers the advantage of allowing estimation of biologically relevant doses as well as model evaluation against biomarker measurements (i.e. urinary total and speciated As concentrations from 2003 NHANES). Analyses show: 1) the average, 95th and 99th percentiles of exposure are 0.37, 1.39 and 4.63 ug/kg/day respectively, which are very comparable with As intakes from the NHEXAS duplicate food study (0.185, 0.612 ug/kg/day for mean and 95th); 2) the main contribution to the exposures are fish, shellfish, rice, and beer; 3) shellfish and seafood consumptions are statistically correlated with urine biomarker, arsenobetaine data from 2003 NHANES and rice with total As, Dimethylarsonic (DMA) and Monomethylacrsonic (MMA); and 4) estimated speciated As from the linked exposure and dose model are closely correlated with urinary biomarker data for Total As, DMA and MMA (R2, slope and intercept).