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.
Keywords: Bayesian inference; alternative model development; cadmium toxicokinetics; population variability; risk assessment; toxicokinetic models; urinary cadmium.