HOME HELP FEEDBACK SUBSCRIPTIONS ARCHIVE SEARCH TABLE OF CONTENTS		QUICK SEARCH:   [advanced] Author: Keyword(s): Year:  Vol:  Page:

This Article Full Text (PDF) Submit a response Purchase Article View Shopping Cart Alert me when this article is cited Alert me when eLetters are posted Alert me if a correction is posted Services Related articles in AJPH Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Download to citation manager Citing Articles Citing Articles via HighWire Citing Articles via Google Scholar Google Scholar Articles by Hertz-Picciotto, I Search for Related Content PubMed PubMed Citation Articles by Hertz-Picciotto, I

Epidemiology and quantitative risk assessment: a bridge from science to policy.

I Hertz-Picciotto

Department of Epidemiology, University of North Carolina School of Public Health, Chapel Hill 27599-7400, USA.

Quantitative risk assessment provides formalized scientific input to regulatory agencies that set occupational and environmental standards for potentially toxic exposures. Current practice relies heavily on statistical extrapolation from high-dose animal studies. Human data obviate the need for interspecies extrapolation and reduce the range of high-to-low dose extrapolation. This paper proposes a framework for classifying individual epidemiologic studies as to their adequacy for use in dose-response extrapolation. The framework considers five criteria: (1) a stable positive association with an adverse health outcome; (2) high overall study quality; (3) no substantial confounding; (4) quantitative exposure assessment for individuals; (5) evidence of a dose-response relationship. With these criteria, studies can be categorized as (1) suitable to serve as a basis for extrapolation; (2) inadequate to be the basis for direct extrapolation but appropriate to use for evaluating the plausibility of animal-derived risk estimates; or (3) useful only for hazard identification, not for dose-response assessment. Methods for using studies in the first two categories are briefly described. The emphasis is not on establishing rigid rules, but rather on ensuring a consistent, reliable process that makes optimum use of available data.

Related articles in AJPH:

Epidemiologic data in risk assessment--imperfect but valuable.

R E Shore
AJPH 1995 85: 474-476. [PDF]  

Comment: integrating epidemiologic data into risk assessment.

D Wartenberg and R Simon
AJPH 1995 85: 491-493. [PDF]  

A graphical method for pooling epidemiological studies.

W R Chappell and L B Gratt
AJPH 1996 86: 748-750. [PDF]  

This article has been cited by other articles:

				G M. Swaen A framework for using epidemiological data for risk assessment Human and Experimental Toxicology, March 1, 2006; 25(3): 147 - 155. [Abstract] [PDF]

				J Mindell, E Ison, and M Joffe A glossary for health impact assessment J. Epidemiol. Community Health, September 1, 2003; 57(9): 647 - 651. [Abstract] [Full Text] [PDF]

				A M Garcia and H Checkoway A glossary for research in occupational health J. Epidemiol. Community Health, January 1, 2003; 57(1): 7 - 10. [Abstract] [Full Text] [PDF]

				M McCarthy, J P Biddulph, M Utley, J Ferguson, and S Gallivan A health impact assessment model for environmental changes attributable to development projects J. Epidemiol. Community Health, August 1, 2002; 56(8): 611 - 616. [Abstract] [Full Text] [PDF]

				K. Steenland, J. Deddens, and L. Piacitelli Risk Assessment for 2,3,7,8-Tetrachlorodibenzo-p-Dioxin (TCDD) based on an Epidemiologic Study Am. J. Epidemiol., September 1, 2001; 154(5): 451 - 458. [Abstract] [Full Text] [PDF]

				L. STAYNER, A. J. BAILER, R. SMITH, S. GILBERT, F. RICE, and E. KUEMPEL Sources of Uncertainty in Dose-Response Modeling of Epidemiological Data for Cancer Risk Assessment Ann. N.Y. Acad. Sci., January 1, 1999; 895(1): 212 - 222. [Abstract] [Full Text] [PDF]