Literature DB >> 17238141

Evaluating measurement error in estimates of worker exposure assessed in parallel by personal and biological monitoring.

Elaine Symanski1, Nicole M H Greeson, Wenyaw Chan.   

Abstract

BACKGROUND: While studies indicate that the attenuating effects of imperfectly measured exposure can be substantial, they have not had the requisite data to compare methods of assessing exposure for the same individuals monitored over common time periods.
METHODS: We examined measurement error in multiple exposure measures collected in parallel on 32 groups of workers. Random-effects models were applied under both compound symmetric and exponential correlation structures. Estimates of the within- and between-worker variances were used to contrast the attenuation bias in an exposure-response relationship that would be expected using an individual-based exposure assessment for different exposure measures on the basis of the intra-class correlation coefficient (ICC).
RESULTS: ICC estimates ranged widely, indicative of a great deal of measurement error in some exposure measures while others contained very little. There was generally less attenuation in the biomarker data as compared to measurements obtained by personal sampling and, among biomarkers, for those with longer half-lives. The interval ICC estimates were often-times wide, suggesting a fair amount of imprecision in the point estimates. Ignoring serial correlation tended to over estimate the ICC values.
CONCLUSIONS: Although personal sampling results were typically characterized by more intra-individual variability than inter-individual variability when compared to biological measurements, both types of data provided examples of exposure measures fraught with error. Our results also indicated substantial imprecision in the estimates of exposure measurement error, suggesting that greater emphasis needs to be given to studies that collect sufficient data to better characterize the attenuating effects of an error-prone exposure measure.

Mesh:

Year:  2007        PMID: 17238141     DOI: 10.1002/ajim.20422

Source DB:  PubMed          Journal:  Am J Ind Med        ISSN: 0271-3586            Impact factor:   2.214


  5 in total

1.  Evaluation of occupational exposure: comparison of biological and environmental variabilities using physiologically based toxicokinetic modeling.

Authors:  G Truchon; R Tardif; G Charest-Tardif; A de Batz; P O Droz
Journal:  Int Arch Occup Environ Health       Date:  2012-03-13       Impact factor: 3.015

2.  Evaluating predictors of lead exposure for activities disturbing materials painted with or containing lead using historic published data from U.S. workplaces.

Authors:  Sarah J Locke; Nicole C Deziel; Dong-Hee Koh; Barry I Graubard; Mark P Purdue; Melissa C Friesen
Journal:  Am J Ind Med       Date:  2017-02       Impact factor: 2.214

3.  Estimation of Lead Exposure Intensity by Industry Using Nationwide Exposure Databases in Korea.

Authors:  Dong-Hee Koh; Ju-Hyun Park; Sang-Gil Lee; Hwan-Cheol Kim; Hyejung Jung; Inah Kim; Sangjun Choi; Donguk Park
Journal:  Saf Health Work       Date:  2021-07-17

4.  Evaluating uncertainty to strengthen epidemiologic data for use in human health risk assessments.

Authors:  Carol J Burns; J Michael Wright; Jennifer B Pierson; Thomas F Bateson; Igor Burstyn; Daniel A Goldstein; James E Klaunig; Thomas J Luben; Gary Mihlan; Leonard Ritter; A Robert Schnatter; J Morel Symons; Kun Don Yi
Journal:  Environ Health Perspect       Date:  2014-07-31       Impact factor: 9.031

5.  Comparison of personal air benzene and urine t,t-muconic acid as a benzene exposure surrogate during turnaround maintenance in petrochemical plants.

Authors:  Dong-Hee Koh; Mi-Young Lee; Eun-Kyo Chung; Jae-Kil Jang; Dong-Uk Park
Journal:  Ind Health       Date:  2018-04-12       Impact factor: 2.179

  5 in total

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