Evaluating Uncertainty to Strengthen Epidemiologic Data for Use in Human Health Risk Assessments

被引：24

作者：

Burns, Carol J. ^{[1
]}

Wright, Michael ^{[2
]}

Pierson, Jennifer B. ^{[3
]}

Bateson, Thomas F. ^{[4
]}

Burstyn, Igor ^{[5
]}

Goldstein, Daniel A. ^{[6
]}

Klaunig, James E. ^{[7
]}

Luben, Thomas J. ^{[8
]}

Mihlan, Gary ^{[9
]}

Ritter, Leonard ^{[10
]}

Schnatter, A. Robert ^{[11
]}

Symons, J. Morel ^{[12
]}

Yi, Kun Don ^{[13
]}

机构：

[1] Dow Chem Co USA, Midland, MI 48674 USA

[2] US EPA, NCEA, Cincinnati, OH USA

[3] ILSI, HESI, Washington, DC USA

[4] US EPA, NCEA, Washington, DC 20460 USA

[5] Drexel Univ, Sch Publ Hlth, Dept Environm & Occupat Hlth, Philadelphia, PA 19104 USA

[6] Monsanto Co, St Louis, MO USA

[7] Indiana Univ, Sch Publ Hlth, Dept Environm Hlth, Bloomington, IN USA

[8] US EPA, NCEA, Res Triangle Pk, NC USA

[9] Bayer CropSci, Res Triangle Pk, NC USA

[10] Univ Guelph, Sch Environm Sci, Guelph, ON N1G 2W1, Canada

[11] ExxonMobil Biomedical Sci Inc, Annandale, NJ USA

[12] EI Pont Nemours & Co, Newark, DC USA

[13] Syngenta Crop Protect LLC, Greensboro, NC USA

来源：

ENVIRONMENTAL HEALTH PERSPECTIVES | 2014年 / 122卷 / 11期

关键词：

MEASUREMENT ERROR; SENSITIVITY-ANALYSIS; OCCUPATIONAL ASTHMA; BAYESIAN-ANALYSIS; EXPOSURE; MISCLASSIFICATION; FRAMEWORK; CONFOUNDER; VALIDATION; ADJUSTMENT;

D O I：

10.1289/ehp.1308062

中图分类号：

X [环境科学、安全科学];

学科分类号：

08 ; 0830 ;

摘要：

Background: There is a recognized ned to improve the application of epidemiologic data in human health risk assessment especially for understanding and characterizing risks from environmental and occupational exposures. Although there is uncertainty associated with the results of most epidemiologic studies, techniques exist to characterize uncertainty that can be applied to improve weight-of-evidence evaluations and risk characterization efforts. Methods: This report derives from a Health and Environmental Sciences Institute (HESI) workshop held in Research Triangle Park, North Carolina, to discuss the utility of using epidemiologic data in risk assessments, including the use of advanced analytic methods to address sources of uncertainty. Epidemiologists, toxicologists, and risk assessors from academia, government, and industry convened to discuss uncertainty, exposure assessment, and application of analytic methods to address these challenges. Synthesis: Several recommendations emerged to help improve the utility of epidemiologic data in risk assessment. For example, improved characterization of uncertainty is needed to allow risk assessors to quantitatively assess potential sources of bias. Data are needed to facilitate this quantitative analysis, and inter-disciplinary approaches will help ensure that sufficient information is collected for a thorough uncertainty evaluation. Advanced analytic methods and tools such as directed acyclic graphs (DAGs) and Bayesian statistical techniques can provide important insights and support interpretation of epidemiologic data. Conclusions: The discussions and recommendations from this workshop demonstrate that there are practical steps that the scientific community can adopt to strengthen epidemiologic data for decision making.

引用

页码：1160 / 1165

页数：6

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