The Association between Trans, Trans-Muconic Acid as a Biomarker for Benzene Exposure and the Platelet Count.
- Author:
Young Sun MIN
1
;
Kuck Hyun WOO
;
Jin Seok KIM
;
Jay Young YOO
;
Kwan LEE
;
Hyun Sul LIM
;
Heon KIM
Author Information
1. Department of Occupational Medicine, Soonchunhyang University Kumi Hospital, Korea. wookhn@sch.ac.kr
- Publication Type:Original Article
- Keywords:
Benzene;
Muconic acid;
Platelet
- MeSH:
Benzene;
Blood Platelets;
Creatinine;
Korea;
Linear Models;
Occupations;
Odds Ratio;
Platelet Count;
Questionnaires;
Smoke;
Smoking;
Sorbic Acid
- From:Korean Journal of Occupational and Environmental Medicine
2010;22(2):95-101
- CountryRepublic of Korea
- Language:Korean
-
Abstract:
OBJECTIVE: Recent researches suggest that trans,trans-muconic acid (t,t-MA) would be an adequate metabolic biomarker for low-level benzene exposure. Few study have investigated the association between the t,t-MA and platelet count, and this is the primary aim of this study. METHODS: From May 2004 to June 2004, 326 chemical factory workers took part in a questionnaire survey and they underwent urinary t,t-MA and CBC assessment. The questionnaire covered general aspects of health and the occupational and smoking histories. Statistical analyses of outcomes were performed using SPSS 14.0 for Windows. RESULTS: The subjects' urinary t,t-MA concentration (geometric mean and geometric standard deviation) was 0.28 mg/g creatinine (2.62). No significant differences between different occupations among the chemical workers were found. The urinary t,t-MA concentrations in the smokers and non-smokers were 0.32 mg/g creatinine (2.44) and 0.25 mg/g creatinine (2.77) respectively, and the difference was statistically significant (p<0.05). There was no significant difference in the platelet count based on occupation and the smoking history. There was significant correlation between log(platelet) and log(t,t-MA)(r=-0.116 p=0.039). The regression equation log(platelet) = -0.002xAge + [-0.029xlog(t,t-MA)] + 2.436, R2=0.032, was calculated from linear regression analysis with log(platelet) as the dependent variable. Cross-tabulation between 2 subgroups that were divided by the 90-percentile level of the t,t-MA (0.819 mg/g creatinine), and 2 subgroups that were divided by the 10-percentile level of the platelet count (175,000) was conducted. Higher distribution in subgroup with platelet count below 175,000 was demonstrated in the subgroup with a urinary t,t-MA above the 90-percentile, with an odds ratio of 3.01. CONCLUSIONS: The study may be limited by not taking into account factors such as smoking quantity and sorbic acid, which may confound urinary the t,t-MA concentration as well as medication and infection that may affect the platelet count. Yet it is meaningful that the correlation between the urinary t,t-MA concentration and the platelet count was found through linear regression analysis and the chi-square test, and further, this outcome may be used as a basis for a study to establish the acceptable limit of urinary t,t-MA in Korea.
