Reverse dosimetry modeling of toluene exposure concentrations based on biomonitoring levels from the Canadian health measures survey
Biomonitoring might provide useful estimates of population exposure to environmental chemicals. However, data uncertainties stemming from interindividual variability are common in large population biomonitoring surveys. Physiologically based pharmacokinetic (PBPK) models might be used to account for...
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Zusammenfassung: | Biomonitoring might provide useful estimates of population exposure to environmental chemicals. However, data uncertainties stemming from interindividual variability are common in large population biomonitoring surveys. Physiologically based pharmacokinetic (PBPK) models might be used to account for age- and gender-related variability in internal dose. The objective of this study was to reconstruct air concentrations consistent with blood toluene measures reported in the third Canadian Health Measures Survey using reverse dosimetry PBPK modeling techniques. Population distributions of model’s physiological parameters were described based upon age, weight, and size for four subpopulations (12–19, 20–39, 40–59, and 60–79 years old). Monte Carlo simulations applied to PBPK modeling allowed converting the distributions of venous blood measures of toluene obtained from CHMS into related air levels. Based upon blood levels observed at the 50th, 90th and 95th percentiles, corresponding air toluene concentrations were estimated for teenagers aged 12–19 years as being, respectively, 0.009, 0.04 and 0.06 ppm. Similarly, values were computed for adults aged 20–39 years (0.007, 0.036, and 0.06 ppm), 40–59 years (0.007, 0.036 and 0.06 ppm) and 60–79 years (0.006, 0.022 and 0.04 ppm). These estimations are well below Health Canada’s maximum recommended chronic air guidelines for toluene. In conclusion, PBPK modeling and reverse dosimetry may be combined to help interpret biomonitoring data for chemical exposure in large population surveys and estimate the associated toxicological health risk. |
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DOI: | 10.6084/m9.figshare.7261424 |