IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v27y2007i2p351-371.html
   My bibliography  Save this article

Integration of Probabilistic Exposure Assessment and Probabilistic Hazard Characterization

Author

Listed:
  • Hilko Van Der Voet
  • Wout Slob

Abstract

A method is proposed for integrated probabilistic risk assessment where exposure assessment and hazard characterization are both included in a probabilistic way. The aim is to specify the probability that a random individual from a defined (sub)population will have an exposure high enough to cause a particular health effect of a predefined magnitude, the critical effect size (CES). The exposure level that results in exactly that CES in a particular person is that person's individual critical effect dose (ICED). Individuals in a population typically show variation, both in their individual exposure (IEXP) and in their ICED. Both the variation in IEXP and the variation in ICED are quantified in the form of probability distributions. Assuming independence between both distributions, they are combined (by Monte Carlo) into a distribution of the individual margin of exposure (IMoE). The proportion of the IMoE distribution below unity is the probability of critical exposure (PoCE) in the particular (sub)population. Uncertainties involved in the overall risk assessment (i.e., both regarding exposure and effect assessment) are quantified using Monte Carlo and bootstrap methods. This results in an uncertainty distribution for any statistic of interest, such as the probability of critical exposure (PoCE). The method is illustrated based on data for the case of dietary exposure to the organophosphate acephate. We present plots that concisely summarize the probabilistic results, retaining the distinction between variability and uncertainty. We show how the relative contributions from the various sources of uncertainty involved may be quantified.

Suggested Citation

  • 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.
  • Handle: RePEc:wly:riskan:v:27:y:2007:i:2:p:351-371
    DOI: 10.1111/j.1539-6924.2007.00887.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1539-6924.2007.00887.x
    Download Restriction: no

    File URL: https://libkey.io/10.1111/j.1539-6924.2007.00887.x?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Dale Hattis & J Prerna Banati & Rob Goble & David E. Burmaster, 1999. "Human Interindividual Variability in Parameters Related to Health Risks," Risk Analysis, John Wiley & Sons, vol. 19(4), pages 711-726, August.
    2. Mirjam Moerbeek & Aldert H. Piersma & Wout Slob, 2004. "A Comparison of Three Methods for Calculating Confidence Intervals for the Benchmark Dose," Risk Analysis, John Wiley & Sons, vol. 24(1), pages 31-40, February.
    3. 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.
    4. Carriquiry, Alicia L. & Fuller, Wayne A., 1996. "A Semiparametric Approach to Estimating Usual Intake Distributions," Staff General Research Papers Archive 1036, Iowa State University, Department of Economics.
    5. J. S. Evans & L. R. Rhomberg & P. L. Williams & A. M. Wilson & S. J. S. Baird, 2001. "Reproductive and Developmental Risks from Ethylene Oxide: A Probabilistic Characterization of Possible Regulatory Thresholds," Risk Analysis, John Wiley & Sons, vol. 21(4), pages 697-718, August.
    6. W. Slob & M. N. Pieters, 1998. "A Probabilistic Approach for Deriving Acceptable Human Intake Limits and Human Health Risks from Toxicological Studies: General Framework," Risk Analysis, John Wiley & Sons, vol. 18(6), pages 787-798, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Wout Slob & Martine I. Bakker & Jan Dirk te Biesebeek & Bas G. H. Bokkers, 2014. "Exploring the Uncertainties in Cancer Risk Assessment Using the Integrated Probabilistic Risk Assessment (IPRA) Approach," Risk Analysis, John Wiley & Sons, vol. 34(8), pages 1401-1422, August.
    2. Jin‐Feng Wang & Lian‐Fa Li, 2008. "Improving Tsunami Warning Systems with Remote Sensing and Geographical Information System Input," Risk Analysis, John Wiley & Sons, vol. 28(6), pages 1653-1668, December.
    3. Daniel J. Rozell & Sheldon J. Reaven, 2012. "Water Pollution Risk Associated with Natural Gas Extraction from the Marcellus Shale," Risk Analysis, John Wiley & Sons, vol. 32(8), pages 1382-1393, August.
    4. Wouter Fransman & Harrie Buist & Eelco Kuijpers & Tobias Walser & David Meyer & Esther Zondervan‐van den Beuken & Joost Westerhout & Rinke H. Klein Entink & Derk H. Brouwer, 2017. "Comparative Human Health Impact Assessment of Engineered Nanomaterials in the Framework of Life Cycle Assessment," Risk Analysis, John Wiley & Sons, vol. 37(7), pages 1358-1374, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Signe M. Jensen & Felix M. Kluxen & Christian Ritz, 2019. "A Review of Recent Advances in Benchmark Dose Methodology," Risk Analysis, John Wiley & Sons, vol. 39(10), pages 2295-2315, October.
    2. Dette, Holger & Pepelyshev, Andrey & Shpilev, Piter & Wong, Weng Kee, 2009. "Optimal designs for estimating critical effective dose under model uncertainty in a dose response study," Technical Reports 2009,07, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    3. Kan Shao & Jeffrey S. Gift, 2014. "Model Uncertainty and Bayesian Model Averaged Benchmark Dose Estimation for Continuous Data," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 101-120, January.
    4. Dette, Holger & Pepelyshev, Andrey & Shpilev, Piter & Wong, Weng Kee, 2009. "Optimal designs for estimating critical effective dose under model uncertainty in a dose response study," Technical Reports 2009,09, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    5. Esben Budtz‐Jørgensen & David Bellinger & Bruce Lanphear & Philippe Grandjean & on behalf of the International Pooled Lead Study Investigators, 2013. "An International Pooled Analysis for Obtaining a Benchmark Dose for Environmental Lead Exposure in Children," Risk Analysis, John Wiley & Sons, vol. 33(3), pages 450-461, March.
    6. Nicholas Beyler & Susanne James-Burdumy & Martha Bleeker & Jane Fortson & Max Benjamin, "undated". "Measurement Error Properties in an Accelerometer Sample of U.S. Elementary School Children," Mathematica Policy Research Reports 6c99580fa94443459f3cbd005, Mathematica Policy Research.
    7. Anne Gordon & Mary Kay Fox & Melissa Clark & Renée Nogales & Elizabeth Condon & Philip Gleason & Ankur Sarin, 2007. "School Nutrition Dietary Assessment Study III, Volume II: Student Participation and Dietary Intakes," Mathematica Policy Research Reports 5184c5f5137c460992242c5f7, Mathematica Policy Research.
    8. Walter W. Piegorsch, 2010. "Translational benchmark risk analysis," Journal of Risk Research, Taylor & Francis Journals, vol. 13(5), pages 653-667, July.
    9. Roger Cooke, 2010. "Conundrums with Uncertainty Factors," Risk Analysis, John Wiley & Sons, vol. 30(3), pages 330-339, March.
    10. Woodcock, Simon D. & Benedetto, Gary, 2009. "Distribution-preserving statistical disclosure limitation," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4228-4242, October.
    11. Jane G. Pouzou & Alison C. Cullen & Michael G. Yost & John C. Kissel & Richard A. Fenske, 2018. "Comparative Probabilistic Assessment of Occupational Pesticide Exposures Based on Regulatory Assessments," Risk Analysis, John Wiley & Sons, vol. 38(6), pages 1223-1238, June.
    12. Walter W. Piegorsch & Hui Xiong & Rabi N. Bhattacharya & Lizhen Lin, 2014. "Benchmark Dose Analysis via Nonparametric Regression Modeling," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 135-151, January.
    13. Ramya Chari & Thomas A. Burke & Ronald H. White & Mary A. Fox, 2012. "Integrating Susceptibility into Environmental Policy: An Analysis of the National Ambient Air Quality Standard for Lead," IJERPH, MDPI, vol. 9(4), pages 1-20, March.
    14. Susan Dekkers & Jan Telman & Monique A. J. Rennen & Marco J. Appel & Cees De Heer, 2006. "Within‐Animal Variation as an Indication of the Minimal Magnitude of the Critical Effect Size for Continuous Toxicological Parameters Applicable in the Benchmark Dose Approach," Risk Analysis, John Wiley & Sons, vol. 26(4), pages 867-880, August.
    15. Kristi Kuljus & Dietrich Von Rosen & Salomon Sand & Katarina Victorin, 2006. "Comparing Experimental Designs for Benchmark Dose Calculations for Continuous Endpoints," Risk Analysis, John Wiley & Sons, vol. 26(4), pages 1031-1043, August.
    16. Staudenmayer, John & Ruppert, David & Buonaccorsi, John P., 2008. "Density Estimation in the Presence of Heteroscedastic Measurement Error," Journal of the American Statistical Association, American Statistical Association, vol. 103, pages 726-736, June.
    17. Barbara L. Devaney & Elizabeth A. Stuart, 1998. "Eating Breakfast: Effects of the School Breakfast Program," Mathematica Policy Research Reports d6ccf0f21e6b4d8a8e9cfa650, Mathematica Policy Research.
    18. Elizabeth Condon & Susan Drilea & Carolyn Lichtenstein & James Mabli & Emily Madden & Katherine Niland, "undated". "Diet Quality of American School Children by National School Lunch Program Participation Status: Data from the National Health and Nutrition Examination Survey, 2005-2010," Mathematica Policy Research Reports 36c1ee6e851445d5957fb99ac, Mathematica Policy Research.
    19. Richard R. Lester & Laura C. Green & Igor Linkov, 2007. "Site‐Specific Applications of Probabilistic Health Risk Assessment: Review of the Literature Since 2000," Risk Analysis, John Wiley & Sons, vol. 27(3), pages 635-658, June.
    20. repec:mpr:mprres:5595 is not listed on IDEAS
    21. Helen L. Jacobs & Henry D. Kahn & Kathleen A. Stralka & Dung B. Phan, 1998. "Estimates of per Capita Fish Consumption in the U.S. Based on the Continuing Survey of Food Intake by Individuals (CSFII)," Risk Analysis, John Wiley & Sons, vol. 18(3), pages 283-291, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:wly:riskan:v:27:y:2007:i:2:p:351-371. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.