Promising biological monitoring for occupational 1,2-Dichloropropane exposure by urinalysis for unmetabolized solvent

Validation of urinary 1,2-dichloropropane concentration as a biological exposure index for workers exposed to 1,2-dichloropropane

Background

The International Agency for Research on Cancer classified 1,2-dichloropropane (1,2-DCP) as a human carcinogen in 2016. It is necessary to establish a health monitoring system for workers exposed to 1,2-DCP. We investigated the correlation between 1,2-DCP concentration in air and urine to determine whether it is appropriate to measure 1,2-DCP in urine as a biological exposure index (BEI).

Methods

Twenty-seven workers from 3 manufacturing industries handling 1,2-DCP participated in this study. Airborne 1,2-DCP was collected by personal air. Urine samples were collected at the end of work and analyzed using gas chromatography-mass spectrometry. Correlation analysis and simple regression analysis were performed to investigate the relationship between 1,2-DCP concentration in urine and air.

Results

Pearson correlation coefficients between total 1,2-DCP in air and urine (uncorrected, creatinine-corrected) were 0.720 and 0.819, respectively. For urine samples analyzed within 2 weeks, the Spearman's rho of 1,2-DCP concentration in urine (uncorrected and creatinine-corrected) was 0.906 and 0.836, respectively. Simple regression analysis of 1,2-DCP in air and urinary 1,2-DCP concentrations within 2 weeks, which showed the highest correlation, revealed that the coefficient of determination of 1,2-DCP concentration in urine (uncorrected and creatinine-corrected) was 0.801 and 0.784, respectively.

Conclusions

As a BEI for workers exposed to 1,2-DCP, urinary 1,2-DCP without creatinine correction better reflects the exposure levels of 1,2-DCP in air.

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

The objective of the study is to establish exposure-excretion relationship between dichlorometane (DCM) in air (DCM-A) and in urine (DCM-U) in workplace to confirm a previous report. Male workers in a screen-printing plant participated in the study. Time-weighted average DCM-A was measured by diffusive sampling followed by gas-chromatography (GC), and DCM in end-of-shift urine samples was by head-space GC. The data were subjected to regression and other statistical analyses. In practice, 30 sets of DCM-A and DCM-U values were available. The geometric mean DCM-A was 8.4 ppm and that of DCM-U (as observed) was 41.1 µg/l. The correlation coefficients (0.70-0.85) were statistically significant across the correction for urine density. Thus, the analysis for un-metabolized DCM in end-of-shift urine samples is applicable for biological monitoring of occupational exposure to DCM, in support of and in agreement with the previous report. In conclusion, biological monitoring of occupational DCM exposure is possible by use of analysis for un-metabolized DCM in end-of-shift urine.

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.

Estimation of biological occupational exposure limit values for selected organic solvents from logartihm of octarol water partition coefficient

OBJECTIVES

For several organic solvents (solvents in short), biological occupational exposure limits (BOELs) have been established for un-metabolized solvents in urine, based on the solvent exposure-urinary excretion relationship. This study was initiated to investigate the possibiliy of estimating a BOEL from the Pow (the partition coefficient between n-octyl alcohol and water), a physico-chemical parameter.

METHODS

Data were available in the literatures for exposure-excretion relationship with regard to 10 solvents for men and 7 solvents for women.

RESULTS

Statistical analysis revealed that the slopes (after correction for molecular weights and logarithmic conversion) of the exposure-excretion regression lines linearly correlated (p<0.01) with the log Pow values the respective solvents. No significant difference (p>0.05) was observed between men and women, and it was acceptable to combine the data for the two sexes. Thus the log Pow-log slope relation was represented by a single equation for both sexes. Based on the observations, procedures were established to estimate BOEL values from Pow. Successful estimations of BOELs for styrene, tetrahydrofuran and m-xylene (a representative of xylene isomers) were calculated as examples.

CONCLUSIONS

The present study proposed promising procedures for estimation of a BOEL from the Pow.