Literature DB >> 16513810

A meta-analytic approach for characterizing the within-worker and between-worker sources of variation in occupational exposure.

Elaine Symanski1, Silvia Maberti, Wenyaw Chan.   

Abstract

While many studies have quantified the sources of variation in exposure to workplace contaminants for individual groups of workers, patterns of exposure variability have not been investigated since a comprehensive evaluation was carried out over 10 years ago. Therefore, a systematic review of the literature was conducted to identify studies that applied the one-way random-effects model to describe exposure profiles of groups of workers classified on the basis of the kind of work performed and where it was performed. Quantitative estimates of the sources of variation in exposure along with information related to the workplace, contaminant and sampling strategy were compiled. For subsets of the data, based upon the classification scheme used to group workers, weighted empirical cumulative distribution functions were constructed and compared using the non-parametric Kolomogorov-Smirnov two-sample test. Further stratifications evaluated differences by industry, agent and characteristics of the sampling strategy. The review identified nearly 60 studies that examined the within-worker and between-worker sources of variation in exposure to workplace contaminants. In pooling results across studies, the between-worker variability increased as workers were aggregated across jobs and locations. The within-worker variability for an occupational group of workers was generally larger than the between-worker variability, although the differences in the variation in exposures across work shifts relative to the variation among workers' mean exposure levels diminished as groups were combined across jobs and locations. On average, gaseous exposures were more homogeneous than exposures to aerosols or dermal agents as were exposures in the chemical industry compared with the non-chemical industry. The design of sampling strategies also plays an important role with greater variability among groups of workers who were sampled randomly rather than systematically; in addition, differences were detected on the basis of the study period and sample size. In evaluating key features of the design and methods of the studies identified in the review, several methodological issues emerged given the heterogeneity in terms of how censored data were handled, which estimation method was applied and whether underlying assumptions of the models were met. Notwithstanding the utility of quantifying sources of variation in exposure, several challenges lie ahead with regard to ensuring quality in the collection, analysis and reporting of exposure monitoring data that would enhance efforts to accurately assess exposure.

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Year:  2006        PMID: 16513810     DOI: 10.1093/annhyg/mel006

Source DB:  PubMed          Journal:  Ann Occup Hyg        ISSN: 0003-4878


  11 in total

1.  Evaluation and comparison of three exposure assessment techniques.

Authors:  R L Neitzel; W E Daniell; L Sheppard; H W Davies; N S Seixas
Journal:  J Occup Environ Hyg       Date:  2011-05       Impact factor: 2.155

2.  Evaluation of Exposure Assessment Tools under REACH: Part II-Higher Tier Tools.

Authors:  Eun Gyung Lee; Judith Lamb; Nenad Savic; Ioannis Basinas; Bojan Gasic; Christian Jung; Michael L Kashon; Jongwoon Kim; Martin Tischer; Martie van Tongeren; David Vernez; Martin Harper
Journal:  Ann Work Expo Health       Date:  2019-02-16       Impact factor: 2.179

3.  Can we explain the exposure variability found in hand-arm vibrations when using angle grinders? A round robin laboratory study.

Authors:  I Liljelind; J Wahlström; L Nilsson; M Persson; T Nilsson
Journal:  Int Arch Occup Environ Health       Date:  2009-12-05       Impact factor: 3.015

4.  Review of PCBs in US schools: a brief history, an estimate of the number of impacted schools, and an approach for evaluating indoor air samples.

Authors:  Robert F Herrick; James H Stewart; Joseph G Allen
Journal:  Environ Sci Pollut Res Int       Date:  2015-05-05       Impact factor: 4.223

5.  Estimates of Occupational Inhalation Exposures to Six Oil-Related Compounds on the Four Rig Vessels Responding to the Deepwater Horizon Oil Spill.

Authors:  Tran B Huynh; Caroline P Groth; Gurumurthy Ramachandran; Sudipto Banerjee; Mark Stenzel; Harrison Quick; Aaron Blair; Lawrence S Engel; Richard K Kwok; Dale P Sandler; Patricia A Stewart
Journal:  Ann Work Expo Health       Date:  2022-04-07       Impact factor: 2.179

6.  Reliability of job-title based physical work exposures for the upper extremity: comparison to self-reported and observed exposure estimates.

Authors:  Bethany T Gardner; David A Lombardi; Ann Marie Dale; Alfred Franzblau; Bradley A Evanoff
Journal:  Occup Environ Med       Date:  2010-04-21       Impact factor: 4.402

7.  Optimizing cost-efficiency in mean exposure assessment--cost functions reconsidered.

Authors:  Svend Erik Mathiassen; Kristian Bolin
Journal:  BMC Med Res Methodol       Date:  2011-05-21       Impact factor: 4.615

8.  Bayesian Hierarchical Modelling of Historical Data of the South African Coal Mining Industry for Compliance Testing.

Authors:  Felix Made; Ngianga-Bakwin Kandala; Derk Brouwer
Journal:  Int J Environ Res Public Health       Date:  2022-04-07       Impact factor: 3.390

9.  Finding toxicological information: An approach for occupational health professionals.

Authors:  Irja Laamanen; Jos Verbeek; Giuliano Franco; Marika Lehtola; Marita Luotamo
Journal:  J Occup Med Toxicol       Date:  2008-08-13       Impact factor: 2.646

10.  Advanced REACH Tool: a Bayesian model for occupational exposure assessment.

Authors:  Kevin McNally; Nicholas Warren; Wouter Fransman; Rinke Klein Entink; Jody Schinkel; Martie van Tongeren; John W Cherrie; Hans Kromhout; Thomas Schneider; Erik Tielemans
Journal:  Ann Occup Hyg       Date:  2014-03-24
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