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DOI10.1016/j.yrtph.2014.05.008
A new method for generating distributions of biomonitoring equivalents to support exposure assessment and prioritization
Phillips, Martin B.1; Sobus, Jon R.1; George, Barbara J.2; Isaacs, Kristin1; Conolly, Rory2; Tan, Yu-Mei1
发表日期2014-08-01
ISSN0273-2300
卷号69期号:3页码:434-442
英文摘要

Biomonitoring data are now available for hundreds of chemicals through state and national health surveys. Exposure guidance values also exist for many of these chemicals. Several methods are frequently used to evaluate biomarker data with respect to a guidance value. The "biomonitoring equivalent" (BE) approach estimates a single biomarker concentration (called the BE) that corresponds to a guidance value (e.g., Maximum Contaminant Level, Reference Dose, etc.), which can then be compared with measured biomarker data. The resulting "hazard quotient" estimates (HQ = biomarker concentration/BE) can then be used to prioritize chemicals for follow-up examinations. This approach is used exclusively for population-level assessments, and works best when the central tendency of measurement data is considered. Complementary approaches are therefore needed for assessing individual biomarker levels, particularly those that fall within the upper percentiles of measurement distributions. In this case study, probabilistic models were first used to generate distributions of BEs for perchlorate based on the point-of-departure (POD) of 7 mu g/kg/day. These distributions reflect possible biomarker concentrations in a hypothetical population where all individuals are exposed at the POD. A statistical analysis was then performed to evaluate urinary perchlorate measurements from adults in the 2001 to 2002 National Health and Nutrition Examination Survey (NHANES). Each NHANES adult was assumed to have experienced repeated exposure at the POD, and their biomarker concentration was interpreted probabilistically with respect to a BE distribution. The HQ based on the geometric mean (GM) urinary perchlorate concentration was estimated to be much lower than unity (HQ approximate to 0.07). This result suggests that the average NHANES adult was exposed to perchlorate at a level well below the POD. Regarding individuals, at least a 99.8% probability was calculated for all but two NHANES adults that a higher biomarker concentration would have been observed compared to what was actually measured if the daily dietary exposure had been at the POD. This is strong evidence that individual perchlorate exposures in the 2001-2002 NHANES adult population were likely well below the POD. This case study demonstrates that the "stochastic BE approach" provides useful quantitative metrics, in addition to HQ estimates, for comparison across chemicals. This methodology should be considered when evaluating biomarker measurements against exposure guidance values, and when examining chemicals that have been identified as needing follow-up investigation based on existing HQ estimates. Published by Elsevier Inc.


英文关键词Biomarker;Biomonitoring;Biomonitoring equivalent;Prioritization;NHANES;PBPK;Perchlorate;Urine
语种英语
WOS记录号WOS:000339126400018
来源期刊REGULATORY TOXICOLOGY AND PHARMACOLOGY
来源机构美国环保署
文献类型期刊论文
条目标识符http://gcip.llas.ac.cn/handle/2XKMVOVA/62619
作者单位1.US EPA, Natl Exposure Res Lab, Res Triangle Pk, NC 27709 USA;
2.US EPA, Natl Hlth & Environm Effects Res Lab, Res Triangle Pk, NC 27709 USA
推荐引用方式
GB/T 7714
Phillips, Martin B.,Sobus, Jon R.,George, Barbara J.,et al. A new method for generating distributions of biomonitoring equivalents to support exposure assessment and prioritization[J]. 美国环保署,2014,69(3):434-442.
APA Phillips, Martin B.,Sobus, Jon R.,George, Barbara J.,Isaacs, Kristin,Conolly, Rory,&Tan, Yu-Mei.(2014).A new method for generating distributions of biomonitoring equivalents to support exposure assessment and prioritization.REGULATORY TOXICOLOGY AND PHARMACOLOGY,69(3),434-442.
MLA Phillips, Martin B.,et al."A new method for generating distributions of biomonitoring equivalents to support exposure assessment and prioritization".REGULATORY TOXICOLOGY AND PHARMACOLOGY 69.3(2014):434-442.
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