Considerations of peak exposure indices for the epidemiology of beryllium sensitization.
Virji-MA; Stefaniak-A; Park-JY; Day-G; Stanton-M; Kent-M; Kreiss-K; Schuler-C
Epidemiology 2011 Jan; 22(1)(Suppl. S):S27-S28
Background/Aims: Short-term "peak" exposures can potentially overwhelm the capacity of normal defense mechanisms and induce adverse health effects. Peak exposures may be particularly relevant to susceptible beryllium-exposed individuals as exceeding an exposure threshold may activate an immune response that leads to beryllium sensitization (BeS). Exposure indices currently used in epidemiologic studies of BeS generally do not reflect peak exposures. There is little consensus in the literature as to what constitutes a biologically-relevant peak exposure. Furthermore, real-time monitoring methods are lacking for beryllium requiring alternative methods for investigating peak exposures. Methods: A stochastic approach was used to develop measures of peak exposure using full-shift beryllium exposure data (n = 4026) collected for 269 jobs at a beryllium manufacturing facility. The geometric standard deviation (GSD) was used as an indicator of the likelihood that a specific job could experience exposure excursions. This was combined with the geometric mean (GM), an indicator of the likelihood that a job exposure will exceed a biologically-relevant threshold. The combined GM-GSD measure indicates the likelihood that workers in a job will experience peak exposures. Additional indices of peak exposure for jobs include: the 95th percentile; and the fractions of job-specific measurements that exceeded occupational exposure limits (0.2 microg/m3 or 2 microg/m3). The relationships among these indices of peak exposure were evaluated using correlation coefficients and kappa statistics. Results: The combined GM-GSD metric and the categorized 95th percentile showed poor agreement (kappa = 0.04). Pearson correlation coefficients for the 2 exceedance fractions and the 95th percentile ranged from 0.33 to 0.65. The degree of agreement among these exposure metrics suggests that each may reflect different aspects of peak exposure, and therefore could prove useful in exploring exposure-response relationships in epidemiologic studies of BeS. Conclusion: Understanding peak exposures and the relationship of such exposures to immune-mediated biological responses may permit a more effective and targeted prevention strategy.
Beryllium-compounds; Beryllium-disease; Occupational-exposure; Sensitization; Short-term-exposure; Exposure-assessment; Exposure-limits; Biological-monitoring; Immune-reaction; Threshold-limit-values; Dose-response; Epidemiology; Disease-prevention