Further examination of log Pow-based procedures to estimate biological occupational exposure limits

Literature Review: Biological Monitoring of Occupational Tetrachloroethylene Exposure in Workers

Introduction: One of the most common chlorinated solvents in the world is tetrachloroethylene (TCE) because it is widely used in various industries. Exposure to tetrachloroethylene can cause health problems so biological monitoring is necessary to do. The aim of this research is to assess which one is more feasible to use among the various types of biological monitoring for tetrachloroethylene exposure, based on the evidence-based literature. Methods: The literature searching was performed via electronic databases from PubMed, Scopus, and Proquest. The keywords used were “biological monitoring”, “biomonitoring”, “tetrachloroethylene”, “perchloroethylene”, “work” and “occupation”. The articles were chosen based on the given inclusion and exclusion criteria. Selected articles were then critically appraised. Results: Initially 29 papers were collected, but only6 cross-sectional articles were selected after the screening process and manual searching. Based on the selected evidence-based literatures, statistically meaningful associations were found between tetrachloroethylene exposure and tetrachloroethylene in blood in pre- and end-of-shift, in urine at end of shift, and in exhaled air at end-of-shift. Moreover, micronucleus frequency and DNA damages between dry cleaning workers and the controls differed significantly. Conclusion: The level of tetrachloroethylene in blood, urine, and exhaled air becomes an appropriate biological exposure index for assessing tetrachloroethylene exposure in dry-cleaning workers. In Indonesia, biomonitoring that is more feasible to be implemented is micronucleus frequency evaluation from buccal mucosal epithelial smears since it is a simpler, faster, and less expensive procedure.Keywords: biological monitoring, biomonitoring, occupational exposure, tetrachloroethylene

Biological monitoring of occupational ethylbenzene exposure by means of urinalysis for un-metabolized ethylbenzene

This study aimed to examine quantitative relation between ethylbenzene (EB) in air (EB-A) and un-metabolized EB in urine (EB-U) for biological monitoring of occupational EB exposure by urinalysis for EB. In total, 49 men in furniture production factories participated in the study. Time-weighted average EB-A was monitored by diffusive sampling. Urinalysis for EB was conducted by head-space gas-chromatography with end-of-shift samples. Data were subjected to regression analysis for statistical evaluation. A geometric mean (GM) and the maximum (Max) EB-A levels were 2.1 and 45.5 ppm, respectively. A GM and the Max for EB-U (observed values) were 4.6 and 38.7 µg/l. A significant linear correlation was observed. The regression equation was Y=3.1+0.73X where X is EB-A (ppm) and Y is EB-U (μg/l) (r=0.91, p<0.01). The significant correlation between EB-A and EB-U coupled with a small intercept suggests that biological monitoring of occupational EB exposure is possible by analysis for un-metabolized EB in end-of-shift urine samples. Further validation studies (including those on applicability to women) are envisaged. The feasibility should be examined for biological monitoring and the applicability of the equation among the workers exposed to EB at low levels.

Simplified procedures for estimation of biological occupational exposure limits

OBJECTIVES

To simplify the procedures to estimate biological occupational exposure limits (BOELs) by use of the ratio of geometric mean (GM) concentration of un-metabolized organic solvent in urine (U-GM) over GM organic solvent concentration in air (A-GM) (the [U-GM/A-GM] ratio).

METHODS

Occupational Exposure Limits (OELs) and BOELs were cited from publications from the Japan Society of Occupational Health (JSOH) and the American Conference of Governmental Industrial Hygienists (ACGIH). Data on [U-GM/A-GM] and the SLOPE of exposure-excretion regression line were collected from published articles (men and women were treated separately). Correlation analysis and paired t test were employed as the method to examine statistical significances.

RESULTS

Significant linear correlation was established between the SLOPE and the [U-GM/A-GM]. Thus, it was considered to be possible to calculate the SLOPE value from the [U-GM/A-GM]. Previously established equation of BOEL = SLOPE × OEL allowed to estimate BOEL values in 22 cases of data sets. The comparison of the estimated BOELs with the existing BOELs (JSOH's BOELs and ACGIH's BEIs) in terms of the ratio of [(estimated BOEL)/(existing BOEL)] showed that the ratios for the 22 cases probably distributed log-normally with a GM of 0.85, and the maximum was 5. Therefore, the estimated BOEL may be generally applicable in occupational health when BOEL remains yet to be established. In the worst case, the estimated BOEL may be five times greater than it should be. The recommended procedures for application of estimated BOEL values were described.

CONCLUSION

Simplified procedures for estimation of BOEL values are proposed.