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

Abstract

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.

Figure 1

Distributions of individual values obtained for CAss (a) and RAM (b) in each subpopulation within the whole Canadian population for constant inhalation exposure to benzene. From top to bottom, the distributions are shown for the entire Canadian population (thick —), adults (—), children and adolescents (— –), elderly (–·–·–), toddlers (– – -), pregnant women (-------), infants (-·-·-·-), and neonates (indistinguishable).

Figure 2

Distributions of individual values obtained for CAss (a) and RAM (b) in each subpopulation within the whole Canadian population for constant inhalation exposure to 1,4-dioxane. From top to bottom, the distributions are shown for the entire Canadian population (thick —), adults (—), children and adolescents (— –), elderly (–·–·–), toddlers (– – -), pregnant women (-------), infants (-·-·-·-), and neonates (indistinguishable).

Figure 3

Distribution of individual values obtained for CAss for constant inhalation exposure to benzene (a) and 1,4-dioxane (b) in the entire Canadian (CP, thick —) and “younger” (YP, – –) populations of 100,000 people, in 100,000 adults (—) and in 100,000 of the most susceptible neonates (neo,…). Median and 99th percentile values only (for clarity reasons) are indicated.

Figure 4

Distribution of individual values obtained for RAM for constant inhalation exposure to benzene (a) and 1,4-dioxane (b) in the entire Canadian (CP, thick —), and “younger” (YP, – –) populations of 100,000 people, in 100,000 adults (—) and in 100,000 of the most susceptible pregnant women (PW, grey —).

Figure 5

Distributions of individual values obtained for several physiological parameters in each subpopulation within the whole virtual Canadian population. From top to bottom, distributions for body weight-adjusted alveolar ventilation rate (a), body weight-adjusted liver blood flow (b) and maximal rate of metabolism of benzene (c) and 1,4-dioxane (d) are shown for the entire Canadian population ( thick —), adults (—), children and adolescents (— –), elderly (–·–·–), toddlers (– – -), pregnant women (-------), infants (-·-·-·-), and neonates (indistinguishable).