Institute for Work and Health, Lausanne University, Lausanne, Switzerland.
J Occup Environ Hyg. 2010 Mar;7(3):177-84. doi: 10.1080/15459620903530052.
Biological monitoring of occupational exposure is characterized by important variability, due both to variability in the environment and to biological differences between workers. A quantitative description and understanding of this variability is important for a dependable application of biological monitoring. This work describes this variability, using a toxicokinetic model, for a large range of chemicals for which reference biological reference values exist. A toxicokinetic compartmental model describing both the parent compound and its metabolites was used. For each chemical, compartments were given physiological meaning. Models were elaborated based on physiological, physicochemical, and biochemical data when available, and on half-lives and central compartment concentrations when not available. Fourteen chemicals were studied (arsenic, cadmium, carbon monoxide, chromium, cobalt, ethylbenzene, ethyleneglycol monomethylether, fluorides, lead, mercury, methyl isobutyl ketone, penthachlorophenol, phenol, and toluene), representing 20 biological indicators. Occupational exposures were simulated using Monte Carlo techniques with realistic distributions of both individual physiological parameters and exposure conditions. Resulting biological indicator levels were then analyzed to identify the contribution of environmental and biological variability to total variability. Comparison of predicted biological indicator levels with biological exposure limits showed a high correlation with the model for 19 out of 20 indicators. Variability associated with changes in exposure levels (GSD of 1.5 and 2.0) is shown to be mainly influenced by the kinetics of the biological indicator. Thus, with regard to variability, we can conclude that, for the 14 chemicals modeled, biological monitoring would be preferable to air monitoring. For short half-lives (less than 7 hr), this is very similar to the environmental variability. However, for longer half-lives, estimated variability decreased.
职业暴露的生物监测具有重要的变异性，这既是由于环境的变化，也是由于工人之间的生物学差异。对这种变异性进行定量描述和理解，对于生物监测的可靠应用非常重要。本工作使用毒代动力学模型，对大量存在参考生物参考值的化学物质的这种变异性进行了描述。使用了一个描述母体化合物及其代谢物的毒代动力学室模型。对于每种化学物质，都赋予了腔室生理学意义。当有生理、物理化学和生化数据时，根据这些数据来详细说明模型；当没有这些数据时，则根据半衰期和中央腔室浓度来详细说明模型。研究了 14 种化学物质（砷、镉、一氧化碳、铬、钴、乙苯、乙二醇单甲醚、氟化物、铅、汞、甲基异丁基酮、五氯苯酚、苯酚和甲苯），代表 20 种生物标志物。使用蒙特卡罗技术模拟职业暴露，对个体生理参数和暴露条件的分布进行了现实模拟。然后分析由此产生的生物标志物水平，以确定环境和生物学变异性对总变异性的贡献。将预测的生物标志物水平与生物暴露限值进行比较的结果表明，该模型与 20 个生物标志物中的 19 个有高度相关性。与暴露水平变化相关的变异性（GSD 为 1.5 和 2.0）主要受生物标志物动力学的影响。因此，就变异性而言，我们可以得出结论，对于所建模的 14 种化学物质，生物监测将优于空气监测。对于半衰期较短（小于 7 小时）的化学物质，这与环境变异性非常相似。然而，对于半衰期较长的化学物质，估计的变异性会降低。
