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Journal of Toxicology
Volume 2012, Article ID 404329, 14 pages
Research Article

Modeling the Human Kinetic Adjustment Factor for Inhaled Volatile Organic Chemicals: Whole Population Approach versus Distinct Subpopulation Approach

1Département de Santé Environnementale et de Santé au Travail, Université de Montréal, Montreal, QC, Canada H3T 1A8
2Institut National de Santé Publique du Québec, Montréal, QC, Canada H2P 1E2

Received 21 September 2011; Accepted 21 October 2011

Academic Editor: Marina V. Evans

Copyright © 2012 M. Valcke et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


The objective of this study was to evaluate the impact of whole- and sub-population-related variabilities on the determination of the human kinetic adjustment factor (HKAF) used in risk assessment of inhaled volatile organic chemicals (VOCs). Monte Carlo simulations were applied to a steady-state algorithm to generate population distributions for blood concentrations (CAss) and rates of metabolism (RAMs) for inhalation exposures to benzene (BZ) and 1,4-dioxane (1,4-D). The simulated population consisted of various proportions of adults, elderly, children, neonates and pregnant women as per the Canadian demography. Subgroup-specific input parameters were obtained from the literature and P3M software. Under the “whole population” approach, the HKAF was computed as the ratio of the entire population’s upper percentile value (99th, 95th) of dose metrics to the median value in either the entire population or the adult population. Under the “distinct subpopulation” approach, the upper percentile values in each subpopulation were considered, and the greatest resulting HKAF was retained. CAss-based HKAFs that considered the Canadian demography varied between 1.2 (BZ) and 2.8 (1,4-D). The “distinct subpopulation” CAss-based HKAF varied between 1.6 (BZ) and 8.5 (1,4-D). RAM-based HKAFs always remained below 1.6. Overall, this study evaluated for the first time the impact of underlying assumptions with respect to the interindividual variability considered (whole population or each subpopulation taken separately) when determining the HKAF.