| Autor: |
Amzal, Billy1 Billy.AMZAL@efsa.europa.eu, Julin, Bettina2, Vahter, Marie3, Wolk, Alicja2, Johanson, Gunnar4, Åkesson, Agneta2,3 |
| Předmět: |
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| Zdroj: |
Environmental Health Perspectives. Aug2009, Vol. 117 Issue 8, p1293-1301. 9p. 3 Charts, 8 Graphs. |
| Abstrakt: |
Background: Cadmium is a widespread environmental pollutant that has been shown to exert toxic effects on kidney and bones in humans after long-term exposure. Urinary cadmium concentration is considered a good biomarker of accumulated cadmium in kidney, and diet is the main source of cadmium among nonsmokers. Objective: Modeling the link between urinary cadmium and dietary cadmium intake is a key step in the risk assessment of long-term cadmium exposure. There is, however, little knowledge on how this link may vary, especially for susceptible population strata. Methods: We used a large population-based study (the Swedish Mammography Cohort), with repeated dietary intake data covering a period of 20 years, to compare estimated dietary cadmium intake with urinary cadmium concentrations on an individual basis. A modified version of the Nordberg-Kjellström model and a one-compartment model were evaluated in terms of their predictions of urinary cadmium. We integrated the models and quantified the between-person variability of cadmium half-life in the population. Finally, sensitivity analyses and Monte Carlo simulations were performed to illustrate how the latter model could serve as a robust tool supporting the risk assessment of cadmium in humans. Results: The one-compartment population model appeared to be an adequate modeling option to link cadmium intake to urinary cadmium and to describe the population variability. We estimated the cadmium half-life to be about 11.6 years, with about 25% population variability. Conclusions: Population toxicokinetic models can be robust and useful tools for risk assessment of chemicals, because they allow quantification and integration of population variability in toxicokinetics. [ABSTRACT FROM AUTHOR] |
| Databáze: |
GreenFILE |
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