Literature DB >> 7100851

Effects of approximation in exposure assessments on estimates of exposure- response relationships.

B G Armstrong, D Oakes.   

Abstract

Information on exposure in cohort studies of occupational groups is often very incomplete. If assessments of exposure level are attempted, they are inevitably subject to random error. Even when unbiased, such measurement error can give rise to bias in an estimate of an exposure-response relationship. Since practical techniques exist to account for this effect only in certain situations where response may be measured on a continuous scale, a technique suitable for mortality studies needs developing. In the present report a procedure is described for reducing the bias due to random error in the estimated exposure-response relationship from a cohort mortality study. This procedure is based on a mechanism for adjusting exposure assessments, taking into account the distribution of exposures, and the independently estimated distribution of measurement errors. The initial bias and its reduction through analysis is shown for some simulated data sets. The results of applying this technique to a cohort mortality study of asbestos workers are presented.

Mesh:

Substances:

Year:  1982        PMID: 7100851

Source DB:  PubMed          Journal:  Scand J Work Environ Health        ISSN: 0355-3140            Impact factor:   5.024


  4 in total

1.  Determinants of respiratory symptoms in insulation workers exposed to asbestos and synthetic mineral fibres.

Authors:  P Ernst; S Shapiro; R E Dales; M R Becklake
Journal:  Br J Ind Med       Date:  1987-02

2.  Limitations to the use of employee exposure data on air contaminants in epidemiologic studies.

Authors:  U Ulfvarson
Journal:  Int Arch Occup Environ Health       Date:  1983       Impact factor: 3.015

3.  Biomarker variance component estimation for exposure surrogate selection and toxicokinetic inference.

Authors:  Jon R Sobus; Joachim D Pleil; Michael D McClean; Robert F Herrick; Stephen M Rappaport
Journal:  Toxicol Lett       Date:  2010-09-22       Impact factor: 4.372

Review 4.  Geographic exposure modeling: a valuable extension of geographic information systems for use in environmental epidemiology.

Authors:  J Beyea
Journal:  Environ Health Perspect       Date:  1999-02       Impact factor: 9.031

  4 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.