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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/41464

    Title: A statistical assessment on the stochastic relationship between biomarker concentrations and environmental exposures
    Authors: 陳主智;Chen, Chu-chih;Wu, Kuen-yuh;Chang, Ming J. W.
    Contributors: 淡江大學數學學系
    Keywords: Biological exposure indices;Inter-individual difference;Random-effects model;Physiologically-based pharmacokinetic model;Sampling design Threshold limit value
    Date: 2004-12-01
    Issue Date: 2010-01-28 07:37:56 (UTC+8)
    Publisher: Springer
    Abstract: Biological monitoring has gradually developed into a powerful tool in the identification and quantification of exposures to occupational and/or environmental hazards in environmental and occupational health studies. Aggregate individual exposure to pollutants and evidence for exploring dose-response relationship in the human bodies can be assessed through biomarker measurements. The existence of inter-individual differences among a study population, however, often hampers the relationship assessment between exposure and the biomarker. In this paper, a statistical random effects model identified from a simplified one-compartment pharmacokinetic model is applied to establish the dynamic relationship between a biomarker and its corresponding external exposure. This model avoids the complex parameter estimation problem encountered using a physiologically based pharmacokinetic (PBPK) model, and incorporates inter-individual variations often ignored in the usual regression approach. In addition, the relevant parameters for the generic kinetic process can be estimated directly. As a guideline for preliminary sampling strategy, tables of required sample sizes and the number of repeated measurements to achieve the desired statistical power and test efficiency are given. The currently established biological exposure indices (BEIs) for benzene and methyl chloroform are employed to illustrate the impact of inter- individual variations on the percentages of protection for workers exposed to the threshold limit value (TLV) of the corresponding chemical.
    Relation: Stochastic Environmental Research and Risk Assessment 18(6), pp.377-385
    DOI: 10.1007/s00477-004-0208-2
    Appears in Collections:[Graduate Institute & Department of Mathematics] Journal Article

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