title: Variation of exposure between workers in homogeneous exposure groups.
abstract: It is generally assumed that workers employed in the same job at a given location are uniformly exposed, i.e., that they have the same long-term mean exposure. This assumption has led to observational schemes for classifying workers into homogeneous exposure groups (HEGs), based on job title, location, and other identifiable features of the work environment. This paper presents results from analysis of 183 HEGs (comprised of 15,495 personal measurements) in which it was possible to determine the between-worker component of variance in exposure. The results indicate that, contrary to popular belief, only about one fifth of the HEGs were uniformly exposed (less than a two-fold difference among 95% of individual mean exposures) while an equal number showed a high degree of variation between workers (more than 15-fold differences among 95% of individuals). Further analyses indicate that the identifiable features of the work environment, which are typically used to establish HEGs, are only marginally related to the between-person variation (accounting for only 13% of this variance component). It is concluded that industrial hygienists should not rely on observational schemes to guarantee that groups of workers are uniformly exposed. Rather, they should adopt methods of statistical sampling and analysis that allow the variance components to be estimated so that decisions regarding the evaluation of hazard and selection of controls will be appropriate.
authors.affiliation: School of Public Health, University of North Carolina, Chapel Hill 27599-7400.
authors.forename: S M
authors.initials: SM
authors.lastname: Rappaport
authors.forename: H
authors.initials: H
authors.lastname: Kromhout
authors.forename: E
authors.initials: E
authors.lastname: Symanski
mesh_terms: D000704:Analysis of Variance; D004784:Environmental Monitoring; D006801:Humans; D008962:Models, Theoretical; D016273:Occupational Exposure / Q000706:statistics & numerical data