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The utility of biomarkers as exposure and dose measures.
NIOSH 2001 Dec; :1-18
This study examined variation in the levels of biological measures of exposure to workplace contaminants. Although intra- and inter-individual differences have been characterized for a large number of airborne exposures across occupational groups, similar variation had not been investigated extensively for biological measures. A primary objective of this study was to compile a database of repeated biological measures so that the within- and between-worker sources of variability could be partitioned for as wide a range of biomarkers as possible. Following a review of the world's published literature, biological monitoring data were abstracted from 52 studies that examined workers' exposures to metals, solvents, polycyclic aromatic hydrocarbons, and pesticides. Forty-four percent of the studies also reported personal sampling results, which were compiled as well. Over 4,000 measurements collected on 577 workers in 55 workplaces are contained in the biological database, which represents a wide range of biomarkers collected in blood, urine, and exhaled air. In addition, two relatively large databases of monitoring data collected on workers at a Swedish chloralkali plant from 1988-1997 and at eight reinforced plastics plants in the Emilia-Romagna region of Italy during 1985-1999 were compiled. At the chloralkali plant, 325 air mercury measurements, 847 blood mercury measurements, and 1,165 urinary mercury measurements had been collected and included in the database. For the styrene database, a total of 1,714 measurements of mandelic acid and phenylglyoxalic acid were abstracted from laboratory reports and compiled. Occupational groups of workers were classified on the basis of a common work environment (i.e., on the basis of plant or facility). When sufficient data were available, workers were further classified by job title or primary work tasks performed. To evaluate sources of variation in the biological monitoring data, random- and mixed effects models were applied. Based on our assessment, there was generally more variation among workers employed at the same plant than across shifts. Owing to the effects of intra-individual variation, we confirmed that estimating workers' exposures from relatively few measurements could attenuate measures of effect should the monitoring data be used in an epidemiologic study to evaluate workers' exposures. Given the physiological and kinetic parameters that influence body burdens of contaminants, statistical methods that incorporate the serial dependence among measures were applied, where possible. Notwithstanding the advantages that biomarkers offer in assessing exposure, the use of biological indices of exposure places an additional burden on an exposure assessment strategy since data may be serially correlated (as evidenced in our study), which could result in biased estimates of the variance components if autocorrelation is undetected or ignored in the statistical analyses. In the application of random- and mixed-effects models, which provide invaluable information that can be used in the control of hazards in the workplace and in the design of studies to evaluate health effects associated with occupational exposures, it is advantageous to pool information across different groups of workers. Yet, the underlying assumption that the degree of variation over time and among workers is the same for all groups has yet to be fully investigated. In our study of four groups of workers exposed to inorganic mercury at a chloralkali plant, there was no evidence of significant heterogeneity in the levels of variation over time or between workers for air mercury levels. For the biological monitoring data, however, our findings indicate that groups did not share common levels of variability and that it was not appropriate to pool the data and obtain single estimates of the within- and between-worker variance components. Our results suggest that additional studies are warranted to evaluate whether it is reasonable to assume that the degree to which exposures vary over time and among workers is the same across occupational groups who share common work environments.
Information-retrieval-systems; Biological-monitoring; Chemical-indicators; Occupational-exposure; Epidemiology; Exposure-methods; Mercury-compounds; Styrenes; Dose-response; Air-contamination
University of Texas School of Public Health, 1200 Herman Pressler Drive, Houston, TX 77225
Final Grant Report
NTIS Accession No.
Research Tools and Approaches: Exposure Assessment Methods
National Institute for Occupational Safety and Health
University of Texas School of Public Health, Houston, Texas
Page last reviewed: April 12, 2019
Content source: National Institute for Occupational Safety and Health Education and Information Division