Literature DB >> 9972582

A probabilistic approach for deriving acceptable human intake limits and human health risks from toxicological studies: general framework.

W Slob1, M N Pieters.   

Abstract

The use of uncertainty factors in the standard method for deriving acceptable intake or exposure limits for humans, such as the Reference Dose (RfD), may be viewed as a conservative method of taking various uncertainties into account. As an obvious alternative, the use of uncertainty distributions instead of uncertainty factors is gaining attention. This paper presents a comprehensive discussion of a general framework that quantifies both the uncertainties in the no-adverse-effect level in the animal (using a benchmark-like approach) and the uncertainties in the various extrapolation steps involved (using uncertainty distributions). This approach results in an uncertainty distribution for the no-adverse-effect level in the sensitive human subpopulation, reflecting the overall scientific uncertainty associated with that level. A lower percentile of this distribution may be regarded as an acceptable exposure limit (e.g., RfD) that takes account of the various uncertainties in a nonconservative fashion. The same methodology may also be used as a tool to derive a distribution for possible human health effects at a given exposure level. We argue that in a probabilistic approach the uncertainty in the estimated no-adverse-effect-level in the animal should be explicitly taken into account. Not only in this source of uncertainty too large to be ignored, it also has repercussions for the quantification of the other uncertainty distributions.

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Year:  1998        PMID: 9972582     DOI: 10.1023/b:rian.0000005924.18154.60

Source DB:  PubMed          Journal:  Risk Anal        ISSN: 0272-4332            Impact factor:   4.000


  16 in total

1.  Practical Risk Assessment and Management Issues Arising were we to Adopt Low-Dose Linearity for all Endpoints.

Authors:  Lorenz R Rhomberg
Journal:  Dose Response       Date:  2010-09-10       Impact factor: 2.658

2.  Human health risk assessment related to contaminated land: state of the art.

Authors:  F A Swartjes
Journal:  Environ Geochem Health       Date:  2015-03-26       Impact factor: 4.609

3.  Use of benchmark dose models in risk assessment for occupational handlers of eight pesticides used in pome fruit production.

Authors:  Jane Gurnick Pouzou; John Kissel; Michael G Yost; Richard A Fenske; Alison C Cullen
Journal:  Regul Toxicol Pharmacol       Date:  2019-10-23       Impact factor: 3.271

Review 4.  Recent Advances in Probabilistic Dose-Response Assessment to Inform Risk-Based Decision Making.

Authors:  Weihsueh A Chiu; Greg M Paoli
Journal:  Risk Anal       Date:  2020-09-23       Impact factor: 4.000

5.  A signal-to-noise crossover dose as the point of departure for health risk assessment.

Authors:  Salomon Sand; Christopher J Portier; Daniel Krewski
Journal:  Environ Health Perspect       Date:  2011-08-03       Impact factor: 9.031

6.  Balancing the risks and benefits of drinking water disinfection: disability adjusted life-years on the scale.

Authors:  A H Havelaar; A E De Hollander; P F Teunis; E G Evers; H J Van Kranen; J F Versteegh; J E Van Koten; W Slob
Journal:  Environ Health Perspect       Date:  2000-04       Impact factor: 9.031

Review 7.  Non-monotonic dose-response relationships and endocrine disruptors: a qualitative method of assessment.

Authors:  Fabien Lagarde; Claire Beausoleil; Scott M Belcher; Luc P Belzunces; Claude Emond; Michel Guerbet; Christophe Rousselle
Journal:  Environ Health       Date:  2015-02-11       Impact factor: 5.984

8.  Integrated probabilistic risk assessment for nanoparticles: the case of nanosilica in food.

Authors:  Rianne Jacobs; Hilko van der Voet; Cajo J F Ter Braak
Journal:  J Nanopart Res       Date:  2015-06-06       Impact factor: 2.253

Review 9.  Praegnatio Perturbatio-Impact of Endocrine-Disrupting Chemicals.

Authors:  Vasantha Padmanabhan; Wenhui Song; Muraly Puttabyatappa
Journal:  Endocr Rev       Date:  2021-05-25       Impact factor: 19.871

Review 10.  Dispelling urban myths about default uncertainty factors in chemical risk assessment--sufficient protection against mixture effects?

Authors:  Olwenn V Martin; Scholze Martin; Andreas Kortenkamp
Journal:  Environ Health       Date:  2013-07-01       Impact factor: 5.984

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