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Sponsoring Section/Society: Risk

Session Slot: 10:30-12:20 Wednesday

Estimated Audience Size: 40-60

AudioVisual Request: slide projector, overhead

Session Title: Environmental Risk Assessment

Theme Session: Yes/No

Applied Session: Yes/No

Session Organizer: Rockette, Howard E. University of Pittsburgh

Address: Department of Biostatistics 318C Parran Hall Pittsburgh, PA 15261

Phone: 412-624-3022

Fax: 412-624-2183


Session Timing: 110 minutes total (Sorry about format):

Opening Remarks by Chair - 0 minutes First Speaker - 30 minutes Second Speaker - 30 minutes Third Speaker - 30 minutes Discussant - 15 minutes Floor Discussion - 5 minutes

Session Chair: Rockette, Howard E. University of Pittsburgh

Address: Department of Biostatistics 318C Parran Hall Pittsburgh, PA 15261

Phone: 412-624-3022

Fax: 412-624-2183


1. Spatial Modeling of Environmental Exposure to Pesticides

Calvin, James,   Texas A&M University

Address: Statistics Department College Station, Texas 77843

Phone: 409-845-3141

Fax: 409-845-3144


Abstract: The South Texas Pregnancy Study is a multi-year case-control study of the relationship between pesticides and neural tube defects (NTDs), which are one of the most common forms of birth defects. As part of this study, samples of water, soil and sediment were taken at varying times and at a variety of locations throughout a three county region. Chemical analysis of these samples yields interesting levels of quantities that may be by-products of pesticide use (e.g., atrazine). This talk will discuss the difficulty in modeling these spatially and temporally linked measurements, as well as, techniques for relating the exposure model to NTDs.

2. Modeling Reproductive Risks from Environmental Agents

Mazumdar, Sati,   University of Pittsburgh

Address: 306 Parran Hall Department of Biostatistics Pittsburgh, PA 15261

Phone: 412-624-3023

Fax: 412-624-2183


Mattison, Donald R., University of Pittsburgh

Sussman, Nancy B., University of Pittsburgh

Abstract: Successful reproduction requires complex processes that occur in the male, the female, and the couple. The adverse effects of toxic exposure on these processes can have such impacts on reproductive health as, alternations in sexual behavior, reduced fertility, or adverse pregnancy outcome. Various biomarkers and endpoints can be used to characterize the impact of reproductive toxicity on a population. In this discussion, we present an overview of the statistical methods for the characterization of reproductive toxicity with emphasis on the quantitative estimation of human reproductive risk. We discuss issues related to the temporal effects that may reveal possible recovery of the affected biomarkers, the necessity of utilizing several biomarkers characterizing the same hazard, and the uncertainty in the estimation of the reproductive risk. We describe the usefulness of multivariate mixed-effects models in this endeavor as a useful analytical tool. The need for more andrologic research to gather appropriate data for successful quantitative risk estimation is discussed. Finally, methods and the issues are illustrated by modeling the reproductive risks from 1,2,-dibromo-3, chloropopane and ethylene dibromide to a human population.

3. Increasing Use of Probabilistic Techniques in Human Health Risk Assessments

Sielken, R.L.,   Sielken, Inc.

Address: 3833 Texas Avenue Suite 230 Bryan, Texas 77802

Phone: 409-846-5175

Fax: 409-846-2671


Abstract: Increasing regulatory demands and new legislation such as the Food Quality Protection Act (FQPA) requiring aggregate exposure assessments combining multiple exposure pathways (e.g., drinking water, multiple foods, and residential) and cumulative risk assessments combining multiple chemicals with a common mechanism of toxicity have stimulated the development and implementation of new probabilistic techniques facilitating higher-tier assessments of exposure incorporating more of the available data than current default initial screening assessments. These new probabilistic techniques are introduced and illustrated in terms of recent submissions of EPA related to pesticides. Real numerical examples illustrate how probabilistic techniques (including Monte Carlo and other distributional analyses) enable the relative likelihood or frequency information in data distributions (e.g., consumption and concentration distributions for drinking water; consumption, application rate, and residue concentration distributions for food sources; joint distributions of several pesticide residues in the same food source; and distributions of residential duration and pesticide application rates for residential exposures) to be used instead of worst case characterizations. Examples include acute, short-term, intermediate-term, and chronic exposures as well as the incorporation of age-dependence and subpopulation differences. Probabilistic techniques make it possible to more realistically combine exposures from multiple time periods, multiple subpopulations, multiple exposure pathways, and multiple chemicals without having to assume to assume the worst case for each component. New probabilistic techniques can help provide greater risk management flexibility and avoid the pitfalls of compounding multiple conservatisms and exaggerating the magnitude of exposure in human health risk assessments.

Discussant: Wong, Otto   Applied Health Sciences, Inc.; Department of Biostatistics and Epidemiology, Tulane University

Address: 181 Second Avenue Suite 628 Post Office Box 2078 San Mateo, CA 94401

Phone: 650-347-7898

Fax: 650-344-6887


List of speakers who are nonmembers: None

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Next: ASA Social Statistics (3) Up: ASA Risk Analysis (1) Previous: ASA Risk Analysis (1)
David Scott