Combined Before-and-After Workplace Intervention to Promote Healthy Lifestyles in Healthcare Workers (STI-VI Study): Short-Term Assessment.

Health care workers (HCWs) are prone to a heavy psycho-physical workload. Health promotion programs can help prevent the onset of chronic and work-related diseases. The aim of the STI-VI 'before-and-after' study, with assessments scheduled at 6 and 12 months, was to improve the lifestyle of HCWs with at least one cardiovascular risk factor. A tailored motivational counseling intervention, focusing on dietary habits and physical activity (PA) was administered to 167 HCWs (53 males; 114 females). BMI, waist circumference, blood pressure, and cholesterol, triglyceride, and blood glucose levels were measured before and after the intervention. The 6-month results (total sample and by gender) showed a marked effect on lifestyle: PA improved (+121.2 MET, p = 0.01), and diets became more similar to the Mediterranean model (+0.8, p < 0.001). BMI dropped (-0.2, p < 0.03), and waist circumference improved even more (-2.5 cm; p < 0.001). Other variables improved significantly: total and LDL cholesterol (-12.8 and -9.4 mg/dL, p < 0.001); systolic and diastolic blood pressure (-4.4 and -2.5 mmHg, p < 0.001); blood glucose (-1.5 mg/dL, p = 0.05); and triglycerides (significant only in women), (-8.7 mg/dL, p = 0.008); but HDL cholesterol levels dropped too. If consolidated at 12 months, these results indicate that our intervention can help HCWs maintain a healthy lifestyle and work ability.

High-frequency hearing thresholds: effects of age, occupational ultrasound and noise exposure.

PURPOSE: It has been suggested that high-frequency audiometry (HFA) could represent a useful preventive measure in exposed workers. The aim was to investigate the effects of age, ultrasound and noise on high-frequency hearing thresholds. METHODS: We tested 24 industrial ultrasound-exposed subjects, 113 industrial noise-exposed subjects and 148 non-exposed subjects. Each subject was tested with both conventional-frequency (0.125-8 kHz) and high-frequency (9-18 kHz) audiometry. RESULTS: The hearing threshold at high frequency deteriorated as a function of age, especially in subjects more than 30 years old. The ultrasound-exposed subjects had significantly higher hearing thresholds than the non-exposed ones at the high frequencies, being greatest from 10 to 14 kHz. This hearing loss was already significantly evident in subjects with exposure <5 years and increased with years of exposure and advancing age. The noise exposure group had significantly higher hearing thresholds than the non-exposed group at the conventional frequencies 4 and 6 kHz and at the high frequency of 14 kHz. After stratification for age, there was a significant difference between the two groups at 9-10 and 14-15 kHz only for those under 30 years of age. CONCLUSION: Multivariate analysis indicated that age was the primary predictor, and noise and ultrasound exposure the secondary predictors of hearing thresholds in the high-frequency range. The results suggest that HFA could be useful in the early diagnosis of noise-induced hearing loss in younger groups of workers (under 30 years of age).

Biomonitoring occupational sevoflurane exposure at low levels by urinary sevoflurane and hexafluoroisopropanol.

This study aimed to correlate environmental sevoflurane levels with urinary concentrations of sevoflurane (Sev-U) or its metabolite hexafluoroisopropanol (HFIP) in order to assess and discuss the main issues relating to which biomarker of sevoflurane exposure is best, and possibly suggest the corresponding biological equivalent exposure limit values. Individual sevoflurane exposure was measured in 100 healthcare operators at five hospitals in north-east Italy using the passive air sampling device Radiello(®), and assaying Sev-U and HFIP concentrations in their urine collected at the end of the operating room session. All analyses were performed by gas chromatography-mass spectrometry. Environmental sevoflurane levels in the operating rooms were also monitored continuously using an infrared photoacoustic analyzer. Our results showed very low individual sevoflurane exposure levels, generally below 0.5 ppm (mean 0.116 ppm; range 0.007-0.940 ppm). Sev-U and HFIP concentrations were in the range of 0.1-17.28 µg/L and 5-550 µg/L, respectively. Both biomarkers showed a statistically significant correlation with the environmental exposure levels (Sev-U, r=0.49; HFIP, r=0.52), albeit showing fairly scattered values. Sev-U values seem to be influenced by peaks of exposure, especially at the end of the operating-room session, whereas HFIP levels by exposure on the previous day, the data being consistent with the biomarkers' very different half-lives (2.8 and 19 h, respectively). According to our results, both Sev-U and HFIP are appropriate biomarkers for assessing sevoflurane exposure at low levels, although with some differences in times/patterns of exposure. More work is needed to identify the best biomarker of sevoflurane exposure and the corresponding biological equivalent exposure limit values.

Biological monitoring of exposure to perchloroethylene in dry cleaning workers.

BACKGROUND: Perchloroethylene (PCE) is the most widely used solvent in dry cleaning. OBJECTIVES: The aim was to evaluate PCE pollution and to identify the most reliable biological indicators for the assessment of workers' exposure. METHODS: The study was performed in 40 dry cleaning shops covering a total of 71 subjects. Environmental monitoring was carried out with personal diffusive samplers (Radiello) for the entire work shift; biological monitoring was performed by measuring PCE in urine and blood and trichloroacetic acid (TCA) in urine on Thursday evening at end-of shift and on Friday morning pre-shift. RESULTS: The mean concentration of PCE in air was 52.32 mg/m3, about 30% of the TLV-TWA and the mean value of the PCE inpre-shift blood samples was 0.304 mg/l, slightly more than 50% of the BEI. In dry cleaning shops employing less than 3 persons PCE in air exceeded the TLV-TWA in 7.8% of cases; the size of the shops was inversely related to pollution. Statistically significant correlations were found between PCE exposure and PCE in blood end-of-shift (r = 0.67) and pre-shift (r = 0.70), and PCE in urine end-of-shift (r = 0.68); no correlation was found between exposure and PCE in urine pre-shift and urinary TCA. CONCLUSIONS: Dry cleaning shops still register conditions of exposure and pollution by PCE, although to a lesser extent than in the past. The most reliable indicators for biological monitoring are CE in end-of-shift urine and PCE in blood both at end-of-shift and pre-shift at the end of the workweek.

A longitudinal study for investigating the exposure level of anesthetics that impairs neurobehavioral performance.

There is conflicting evidence on the level of anesthetics that impairs neurobehavioral performance, leading to differences in exposure standards (25 or 50 ppm for N(2)O). Thirty-eight operating room nurses and 23 unexposed nurses were asked to provide information on confounding variables: age, gender, years of schooling, alcohol and coffee consumption, smoking, length of work, symptoms (Euroquest) and results of Block Design test. Afterward, all workers were repeatedly examined (on Monday and Friday of a working week, before and after workshift) for stress and arousal (Mood Scale) and complex reaction times (Color Word Vigilance, CWV), the latter being the outcome. Individual exposure was assessed through urinary end-shift concentrations of nitrous oxide (N(2)O) and isoflurane. According to the highest value of urinary excretion of N(2)O in the week, exposed workers were subdivided in three groups (<13; > or =13 and <27; and > or = 27 microg/l). The values of 13 and 27 microg/l correspond to environmental concentrations of 25 and 50 ppm, respectively. In order to take into account the pre-existing abilities of exposed and reference workers, and investigate the neurobehavioral changes over time, longitudinal data were analyzed by a two-stage regression model and analysis of variance for repeated measures (MANOVA). The former method, controlling for confounding factors and Monday morning CWV (which conveyed the pre-existing ability of the subjects), showed that, with respect to unexposed nurses, reaction times were significantly (p<0.020) higher only in workers with urinary N(2)O> or = 27 microg/l. Therefore, at MANOVA, all subjects were categorized in two classes (N(2)O urinary concentrations or = 27 microg/l), and CWV results were adjusted for the confounding variables and effects of stress and arousal, taken concurrently with CWV. CWV significantly (p<0.039) decreased over a working week (indicating a learning effect) in workers with urinary N(2)O<27 microg/l, while remained steady (indicating impairment of neurobehavioral performance) in those with urinary N(2)O> 27 microg/l.

Comparison of exposure assessment methods in occupational exposure to benzene in gasoline filling-station attendants.

The aim of this study was to assess gasoline filling-station attendants' exposure to benzene and to determine which biological exposure index (BEI), trans,trans-muconic acid (t,t-MA) or S-phenylmercapturic acid (S-PMA), shows better correlation with environmental exposure. Exposure to benzene was measured using passive samplers (Radiello) attached to the collar of the overalls of subjects (n=33) just before the work-shift (approximately 8h); analysis was performed by GC-FID. S-PMA and t,t-MA were determined, respectively, by an immunochemiluminescent assay based on specific monoclonal antibodies and by HPLC-UV at 264 nm. Both methods of biological monitoring were performed on beginning and end-shift urine samples, and expected t,t-MA and S-PMA values were calculated. Smoking habits and life-style were ascertained by means of a questionnaire. Both environmental and biological monitoring data showed that benzene exposure for gasoline filling-station attendants was low when compared with the respective ACGIH limit values (means-benzene: 0.044 mg/m(3); t,t-MA: 171 microg/g creatinine; S-PMA: 2.7 microg/g creatinine). No significant correlation was found between exposure to benzene and t,t-MA or S-PMA excretion data. The use of expected values was also experimented for S-PMA and t,t-MA. This consists of calculating, on the basis of the known half-life of the benzene metabolite, the concentration of that metabolite that a worker should present at the end of the work-shift, the difference between this value and the value actually found is a measure of benzene exposure during work. The use of expected values in biological monitoring did not improve correlations. At these low benzene levels, environmental monitoring seems to be the best method of evaluating individual exposure. However, biological monitoring remains useful, as a mean of assessing group exposure.

Biological indices of kidney involvement in personnel exposed to sevoflurane in surgical areas.

BACKGROUND: Fluoride, a main metabolite, and one degradation product of sevoflurane (SEV), called Compound A, are known to cause kidney effects in experimental animals. Other than in volunteers and patients, no research is available on exposed workers. The possible effects on the kidney in workers exposed in surgical areas were studied. METHODS: Subjects exposed to SEV and nitrous oxide (N(2)O) in surgical areas (N = 61) using open (N = 25) or semi-closed (N = 36) circuits were submitted to biological monitoring. The same biological indices were determined in 43 controls also. Sevoflurane (SEVU), nitrous oxide (N(2)OU), total urinary proteins (TUP), N-acetyl-beta-D-glucosaminidase (NAGU), and glutamine synthetase (GSU) were measured in urine. RESULTS: The mean values of environmental exposure were 31.3 ppm (range 0.9-111.6 ppm) for N(2)O and 0.28 ppm (range 0-1.88 ppm) for SEV. Exposed subjects had significantly higher excretion of TUP; a higher, not significant, excretion of GSU was also observed in subjects using open circuits. A significant correlation was found in all exposed subjects between NAGU and SEVU (r = 0.303, P < 0.05), GSU and N(2)OU (r = 0.382, P < 0.01) and, especially, GSU and SEVU (r = 0.650, P < 0.001). These correlations appeared to be influenced by the use of open circuits; infact, NAGU was well correlated to N(2)OU (r = 0.770, P < 0.001) and SEVU (r = 0.863, P < 0.001); GSU to N(2)OU (r = 0.468, P < 0.05) and SEVU (r = 0.735, P < 0.001). CONCLUSIONS: Results show that no relevant effect on the kidney is present for the levels of exposure studied. Nevertheless, correlation between dose and response urinary indices supports that SEV, other than N(2)O, may influence kidney function, especially when open circuits are used.