Suppr超能文献

国家人类暴露评估调查(NHEXAS):美国环境保护局第5区域铅、砷和挥发性有机化合物的分布及关联

National Human Exposure Assessment Survey (NHEXAS): distributions and associations of lead, arsenic and volatile organic compounds in EPA region 5.

作者信息

Clayton C A, Pellizzari E D, Whitmore R W, Perritt R L, Quackenboss J J

机构信息

Research Triangle Institute, Research Triangle Park, North Carolina 27709, USA.

出版信息

J Expo Anal Environ Epidemiol. 1999 Sep-Oct;9(5):381-92. doi: 10.1038/sj.jea.7500055.

Abstract

The National Human Exposure Assessment Survey (NHEXAS) Phase I field study conducted in EPA Region 5 provides extensive exposure data on approximately 250 study participants selected via probability sampling. Associated environmental media and biomarker (blood, urine) concentration data were also obtained to aid in the understanding of relationships of the exposures to both contaminant sources and doses. Distributional parameters for arsenic (As), lead (Pb), and four volatile organic compounds (VOCs)--benzene, chloroform, tetrachloroethylene, and trichloroethylene--were estimated for each of the relevant media using weighted data analysis techniques. Inter-media associations were investigated through correlation analysis, and longitudinal correlations and models were used to investigate longitudinal patterns. Solid food appeared to be a major contributor to urine As levels, while Pb levels in household (HH) dust, personal air, and beverages all were significantly associated with blood Pb levels. Relatively high (>0.50) longitudinal correlations were observed for tap water Pb and As, as compared to only moderate longitudinal correlations for the personal air VOCs.

摘要

在环境保护局第5区域开展的全国人类暴露评估调查(NHEXAS)第一阶段实地研究,提供了通过概率抽样选取的约250名研究参与者的大量暴露数据。还获取了相关环境介质和生物标志物(血液、尿液)浓度数据,以帮助理解暴露与污染物来源和剂量之间的关系。使用加权数据分析技术,针对每种相关介质估算了砷(As)、铅(Pb)以及四种挥发性有机化合物(VOCs)——苯、氯仿、四氯乙烯和三氯乙烯的分布参数。通过相关分析研究介质间的关联,并使用纵向相关性和模型来研究纵向模式。固体食物似乎是尿砷水平的主要贡献源,而家庭(HH)灰尘、个人空气和饮料中的铅水平均与血铅水平显著相关。与个人空气中挥发性有机化合物的纵向相关性仅为中等相比,自来水铅和砷的纵向相关性相对较高(>0.50)。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验