A case study of benzene urinary biomarkers quantification: the comparison between pre- and post-shift samples improves the interpretation of individual biological monitoring data. Caso studio di quantificazione dei biomarcatori urinari del benzene: il confronto di campioni di inizio e fine turno lavorativo migliora l'interpretazione dei dati individuali di monitoraggio biologico

Background: Benzene is a common industrial chemical and a component of tobacco smoke and of gasoline. It is widely used as chemical intermediate and is a constituent of crude oil and fuels with a large distribution in the environment owing to vehicles engine emissions. Besides, smoking tobacco is regarded as another major source of environmental benzene exposure. As a consequence, benzene is an ubiquitous pollutant of the outdoor and indoor human environment, and the occupational/environmental exposure concerns a large population. Data from epidemiological studies evidence benzene toxicity to humans. In fact, it is classified as a carcinogen (group A1) by the American Conference of Governmental Industrial Hygienists (ACGIH), suggesting a threshold limit value-time weighted average (TLV-TWA) of 0.5ppm. Hence health risks prevention strategies allowing to discriminate between occupational and non-occupational exposure are essential. Objective: Evaluation of occupational exposure to benzene by comparison between urinary biomarkers levels in preand post-shift samples in biological monitoring (BM) investigations. Methods: The biological monitoring of 14 (smoker and non-smoker) workers of a refueling station was performed. Urinary benzene (UB) and trans,trans-muconic acid (t,t-MA) were used as biological markers. The determinations of UB and t,t-MA were performed by head space-solid phase microextraction followed by gas chromatography/mass spectrometry operating in Selected Ion Monitoring mode and High Performance Liquid Chromatography/UltraViolet detection, respectively. Urinary creatinine levels were also determined. Urine collection was initially performed after work-shift (first BM campaign) as suggested by ACGIH. Given difficulties in interpreting data without statistical basis, the urine collection was repeated before and after the work-shift (second BM campaign). Results and Discussion: During the first BM campaign, contrasting results were found. Some workers showed low UB concentrations with respect to t,t-MA ones and vice versa, and although most investigated subjects presented UB and t,t-MA levels below Biological Equivalents (BEs) values and ACGIH’s BEI, various exceptions were found, either with exceeding UB or with exceeding t,t-MA levels. According to the ACGIH, the high biomarkers levels found in post-shift urine would have suggested an occupational exposure to benzene. Nevertheless, ACGIH’s BEI are defined on statistical basis and should not be used when individual data are interpreted, in fact results obtained by monitoring post-shift urine only without knowing individual background levels did not facilitate the interpretation of data. As a consequence, the biological monitoring investigation was repeated by collecting urine samples before and after work-shift, and a biomarkers concentration decrement was observed, allowing the discrimination between occupational and non-occupational exposure. Conclusions: The obtained findings suggest that biological monitoring strategies aimed to evaluate the exposure of individuals (single workers) to ubiquitous hazardous chemicals, need the measurement of biomarkers concentration both before and after each potential exposure cause, so that confounding factors could be taken into account during data interpretation.