Compliance versus risk in assessing occupational exposures.
Assessments of occupational exposures to chemicals are generally based upon the practice of compliance testing in which the probability of compliance is related to the exceedance [gamma, the likelihood that any measurement would exceed an occupational exposure limit (OEL)] and the number of measurements obtained. On the other hand, workers' chronic health risks generally depend upon cumulative lifetime exposures which are not directly related to the probability of compliance. In this paper we define the probability of "overexposure" (theta) as the likelihood that individual risk (a function of cumulative exposure) exceeds the risk inherent in the OEL (a function of the OEL and duration of exposure). We regard theta as a relevant measure of individual risk for chemicals, such as carcinogens, which produce chronic effects after long-term exposures but not necessarily for acutely-toxic substances which can produce effects relatively quickly. We apply a random-effects model to data from 179 groups of workers, exposed to a variety of chemical agents, and obtain parameter estimates for the group mean exposure and the within- and between-worker components of variance. These estimates are then combined with OELs to generate estimates of gamma and theta. We show that compliance testing can significantly underestimate the health risk when sample sizes are small. That is, there can be large probabilities of compliance with typical sample sizes, despite the fact that large proportions of the working population have individual risks greater than the risk inherent in the OEL. We demonstrate further that, because the relationship between theta and gamma depends upon the within- and between-worker components of variance, it cannot be assumed a priori that exceedance is a conservative surrogate for overexposure. Thus, we conclude that assessment practices which focus upon either compliance or exceedance are problematic and recommend that employers evaluate exposures relative to the probabilities of overexposure.
Tornero-Velez
R
R
School of Public Health, University of North Carolina, Chapel Hill 27599-7400, USA.
Symanski
E
E
Kromhout
H
H
Yu
R C
RC
Rappaport
S M
SM
D000395:Air Pollutants, Occupational / Q000009:adverse effects; D006801:Humans; D007221:Industry; D015233:Models, Statistical; D016273:Occupational Exposure / Q000009:adverse effects* / Q000592:standards / Q000706:statistics & numerical data; D016272:Occupational Health; D012306:Risk; D014481:United States; D014489:United States Occupational Safety and Health Administration
D000395:Air Pollutants, Occupational