کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
1150586 | 957960 | 2007 | 19 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
From sources to biomarkers: A hierarchical Bayesian approach for human exposure modeling
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
ریاضیات
ریاضیات کاربردی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
This paper investigates, from sources to biomarkers, the pathways of human exposure to arsenic. We use a multi-scale (individual level, county level) hierarchical Bayesian model (HBM) that has explicit stages for pollutant sources, global and local environmental levels, personal exposures, and biomarkers. By analyzing these stages simultaneously, we provide an analysis of exposure pathways from the sources of toxic substances in the environment to biomarker levels observed in individuals. The complexity of our approach, in terms of levels of hierarchy, variety of (misaligned) data sources, and computational requirements, illustrates what is possible using hierarchical Bayesian modeling. Our HBM draws on individual-specific measurements from the National Human Exposure Assessment Survey (NHEXAS) Phase I, supplemented by arsenic-concentration measurements in topsoil and stream sediments. We focus on arsenic and its air, soil, water, and food pathways of exposure for individuals in the US Environmental Protection Agency's Region 5 (Illinois, Indiana, Michigan, Minnesota, Ohio, and Wisconsin).
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Journal of Statistical Planning and Inference - Volume 137, Issue 11, 1 November 2007, Pages 3361-3379
Journal: Journal of Statistical Planning and Inference - Volume 137, Issue 11, 1 November 2007, Pages 3361-3379
نویسندگان
Noel Cressie, Bruce E. Buxton, Catherine A. Calder, Peter F. Craigmile, Crystal Dong, Nancy J. McMillan, Michele Morara, Thomas J. Santner, Ke Wang, Gregory Young, Jian Zhang,