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Modeling Long‐Term Exposure of the Whole Population to Chemicals in Food

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  • Wout Slob

Abstract

This paper discusses a statistical exposure model (STEM) that can be used to estimate the percentage of the population exceeding ingestion intake criteria (e.g., ADI or TDI). In addition, STEM may be linked to toxicokinetic models to evaluate the interindividual variability in internal doses that results from variability in consumption habits. The assumptions of STEM are investigated by analyzing dioxin and cadmium intake data for the Dutch population.

Suggested Citation

  • Wout Slob, 1993. "Modeling Long‐Term Exposure of the Whole Population to Chemicals in Food," Risk Analysis, John Wiley & Sons, vol. 13(5), pages 525-530, October.
    • Handle: RePEc:wly:riskan:v:13:y:1993:i:5:p:525-530
    DOI: 10.1111/j.1539-6924.1993.tb00011.x
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    File URL: https://doi.org/10.1111/j.1539-6924.1993.tb00011.x
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    References listed on IDEAS

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    1. Hulshof, Karin F. A. M. & Van Staveren, Wija A., 1991. "The Dutch National Food Consumption Survey: design, methods and first results," Food Policy, Elsevier, vol. 16(3), pages 257-260, June.
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    Cited by:

    1. Hilko Van Der Voet & Wout Slob, 2007. "Integration of Probabilistic Exposure Assessment and Probabilistic Hazard Characterization," Risk Analysis, John Wiley & Sons, vol. 27(2), pages 351-371, April.
    2. Wout Slob, 1994. "Uncertainty Analysis in Multiplicative Models," Risk Analysis, John Wiley & Sons, vol. 14(4), pages 571-576, August.
    3. Wout Slob, 1996. "A Comparison of Two Statistical Approaches to Estimate Long‐Term Exposure Distributions from Short‐Term Measurements," Risk Analysis, John Wiley & Sons, vol. 16(2), pages 195-200, April.

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