U.S. Environmental Protection Agency, Office of Research and Development, National Exposure Research Laboratory, Research Triangle Park, North Carolina, USA.
Environ Health Perspect. 2010 Mar;118(3):345-50. doi: 10.1289/ehp.0901205.
Dietary exposure from food to toxic inorganic arsenic (iAs) in the general U.S. population has not been well studied.
The goal of this research was to quantify dietary As exposure and analyze the major contributors to total As (tAs) and iAs. Another objective was to compare model predictions with observed data.
Probabilistic exposure modeling for dietary As was conducted with the Stochastic Human Exposure and Dose Simulation Dietary (SHEDS-Dietary) model, based on data from the National Health and Nutrition Examination Survey. The dose modeling was conducted by combining the SHEDS-Dietary model with the MENTOR-3P (Modeling ENvironment for TOtal Risk with Physiologically Based Pharmacokinetic Modeling for Populations) system. Model evaluation was conducted via comparing exposure and dose-modeling predictions against duplicate diet data and biomarker measurements, respectively, for the same individuals.
The mean modeled tAs exposure from food is 0.38 microg/kg/day, which is approximately 14 times higher than the mean As exposures from the drinking water. The mean iAs exposure from food is 0.05 microg/kg/day (1.96 microg/day), which is approximately two times higher than the mean iAs exposures from the drinking water. The modeled exposure and dose estimates matched well with the duplicate diet data and measured As biomarkers. The major food contributors to iAs exposure were the following: vegetables (24%); fruit juices and fruits (18%); rice (17%); beer and wine (12%); and flour, corn, and wheat (11%). Approximately 10% of tAs exposure from foods is the toxic iAs form.
The general U.S. population may be exposed to tAs and iAs more from eating some foods than from drinking water. In addition, this model evaluation effort provides more confidence in the exposure assessment tools used.
美国普通人群从食物中摄入的有毒无机砷（iAs）的情况尚未得到充分研究。
本研究旨在量化饮食砷暴露量，并分析总砷（tAs）和 iAs 的主要来源。另一个目的是将模型预测与观察数据进行比较。
基于国家健康和营养调查的数据，使用 Stochastic Human Exposure and Dose Simulation Dietary（SHEDS-Dietary）模型对饮食砷暴露进行概率性暴露建模。通过将 SHEDS-Dietary 模型与 MENTOR-3P（Population 基于生理的基于药代动力学模型的环境总风险建模）系统相结合，进行剂量建模。通过将暴露和剂量建模预测与同一人群的重复饮食数据和生物标志物测量值进行比较，对模型进行评估。
从食物中摄入的平均模型化 tAs 暴露量为 0.38 微克/千克/天，约为饮用水中砷暴露量的 14 倍。从食物中摄入的平均 iAs 暴露量为 0.05 微克/千克/天（1.96 微克/天），约为饮用水中 iAs 暴露量的两倍。模型化的暴露和剂量估计与重复饮食数据和测量的砷生物标志物吻合良好。iAs 暴露的主要食物来源如下：蔬菜（24%）；果汁和水果（18%）；大米（17%）；啤酒和葡萄酒（12%）；以及面粉、玉米和小麦（11%）。约 10%的食物来源的 tAs 暴露是有毒的 iAs 形式。
美国普通人群可能通过食用某些食物而摄入的 tAs 和 iAs 比通过饮用水摄入的更多。此外，这项模型评估工作为使用的暴露评估工具提供了更多的信心。
