A statistical assessment on the stochastic relationship between biomarker concentrations and environmental exposures

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.