|Title:||Assessing the cancer risk associated with arsenic-contaminated seafood||Authors:||Chen B.-C.
|Keywords:||Arsenic; Cancer risk; Physiologically based pharmacokinetic model; Seafood; Urine||Issue Date:||2010||Journal Volume:||181||Journal Issue:||1-3||Start page/Pages:||161-169||Source:||Journal of Hazardous Materials||Abstract:||
Tens of millions of people worldwide ingest excessive amounts of arsenic (As) through drinking water and food. The dietary intake of seafood is the major As exposure route in humans and can cause As-related adverse health effects including cancers. The aim of this study was to quantify potential cancer risks of As exposure for children and adults through seafood consumption. By coupling the age-specific physiologically based pharmacokinetic (PBPK) model and a Weibull-based dose-response function, a more accurate estimate of urinary arsenic metabolites could be achieved to better characterize potential cancer risks. The simulation results show that the proportion of inorganic As, monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) in human urine are estimated to total 6.7, 26.9, and 66.4% for children, and 6.2, 27.4, and 66.4% for adults, respectively. The estimated median cumulative cancer incidence ratios were respectively 2.67×10-6 and 3.83×10-6 for children and adults, indicating a low cancer risk for local residents exposed to As through the consumption of seafood. However, it is necessary to incorporate other exposure routes into the model to make it more realistic. The methodology proposed here can not only be applied to calculate the concentrations of As metabolites in urine, but also to provide a direct estimation of adverse health effects caused by the calculated internal concentrations. ? 2010 Elsevier B.V.
|URI:||https://scholars.lib.ntu.edu.tw/handle/123456789/448808||ISSN:||0304-3894||DOI:||10.1016/j.jhazmat.2010.04.112||SDG/Keyword:||Adverse health effects; Cancer risk; Dietary intakes; Dimethylarsinic acids; Dose response; Drinking water; Human urine; Local residents; Monomethylarsonic acids; Physiologically based pharmacokinetic model; Physiologically based pharmacokinetic models; Seafood consumption; Simulation result; Urinary arsenic; Weibull; Arsenic; Body fluids; Health risks; Meats; Metabolism; Metabolites; Pharmacokinetics; Physiological models; Potable water; Risk perception; Weibull distribution; Chemical contamination; arsenic; cacodylic acid; methanearsonic acid; arsenic; cacodylic acid; dangerous goods; organoarsenic derivative; adult; arsenic; cancer; carboxylic acid; child health; disease incidence; dose-response relationship; food consumption; health impact; health risk; ingestion rate; metabolite; numerical model; physiological response; pollution exposure; public health; risk assessment; seafood; urine; article; cancer incidence; cancer risk; metabolite; sea food; urine level; age; chemically induced; dangerous goods; environmental exposure; food contamination; human; metabolism; Neoplasms; pharmacokinetics; risk; sea food; toxicity; urine; Age Factors; Arsenic; Arsenicals; Cacodylic Acid; Environmental Exposure; Food Contamination; Hazardous Substances; Humans; Neoplasms; Pharmacokinetics; Risk; Seafood; Age Factors; Arsenic; Arsenicals; Cacodylic Acid; Environmental Exposure; Food Contamination; Hazardous Substances; Humans; Neoplasms; Pharmacokinetics; Risk; Seafood
|Appears in Collections:||生物環境系統工程學系|
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