Jean-François Sauvé

Creatinine and Specific Gravity Normalization in Biological Monitoring of Occupational Exposures

Reference values for the biological monitoring of occupational exposures are generally normalized on the basis of creatinine (CR) concentration or specific gravity (SG) to account for fluctuations in urine dilution. For instance, the American Conference of Governmental Industrial Hygienists (ACGIH®) uses a reference value of 1g/L for CR. The comparison of urinary concentrations of biomarkers between studies requires the adjustment of results based on a reference CR and/or SG value, although studies have suggested that age, sex, muscle mass, and time of the day can exert non-negligible influences on CR excretion, while SG appears to be less affected. The objective of this study was to propose reference values for urinary CR and SG based on the results of samples sent for analysis by occupational health practitioners to the laboratory of the Occupational Health and Safety Research Institute of Québec (IRSST). We analyzed a database containing 20,395 urinary sample results collected between 1985 and 2010. Linear mixed-effects models with worker as a random effect were used to estimate the influence of sex and collection period on urinary CR and SG. Median CR concentrations were 25–30% higher in men (1.6 g/L or 14.4 mmol/L) than in women (1.2 g/L or 10.2 mmol/L). Four percent of the samples for men and 12% for women were below the acceptable threshold for CR (4.4 mmol/L). For SG, 5% of samples for men and 12% for women were below the threshold of 1.010. The difference in SG levels between sexes was lower than for CR, with a median of 1.024 for men compared to 1.020 for women. Our results suggest that the normalization of reference values based on a standard CR value of 1 g/L as proposed by the ACGIH is a conservative approach. According to the literature, CR excretion is more influenced by physiological parameters than SG. We therefore suggest that correction based on SG should be favored in future studies involving the proposal of reference values for the biological monitoring of occupational exposures.

Silica Exposure During Construction Activities: Statistical Modeling of Task-Based Measurements from the Literature

Many construction activities can put workers at risk of breathing silica containing dusts, and there is an important body of literature documenting exposure levels using a task-based strategy. In this study, statistical modeling was used to analyze a data set containing 1466 task-based, personal respirable crystalline silica (RCS) measurements gathered from 46 sources to estimate exposure levels during construction tasks and the effects of determinants of exposure. Monte-Carlo simulation was used to recreate individual exposures from summary parameters, and the statistical modeling involved multimodel inference with Tobit models containing combinations of the following exposure variables: sampling year, sampling duration, construction sector, project type, workspace, ventilation, and controls. Exposure levels by task were predicted based on the median reported duration by activity, the year 1998, absence of source control methods, and an equal distribution of the other determinants of exposure. The model containing all the variables explained 60% of the variability and was identified as the best approximating model. Of the 27 tasks contained in the data set, abrasive blasting, masonry chipping, scabbling concrete, tuck pointing, and tunnel boring had estimated geometric means above 0.1mg m(-3) based on the exposure scenario developed. Water-fed tools and local exhaust ventilation were associated with a reduction of 71 and 69% in exposure levels compared with no controls, respectively. The predictive model developed can be used to estimate RCS concentrations for many construction activities in a wide range of circumstances.

Occupational exposure to benzene, toluene, xylene and styrene and risk of prostate cancer in a population-based study

Objectives While several monocyclic aromatic hydrocarbons are classified as definite or possible carcinogens to humans, little data exist on their role in prostate cancer (PCa). We examined occupational exposure to benzene, toluene, xylene (BTX) and styrene and PCa risk in a population-based case–control study in Montreal, Canada. Methods Cases aged ≤75 years diagnosed with PCa in 2005–2009 (n=1920) and population controls frequency-matched on age (n=1989) provided detailed work histories. Experts evaluated the certainty, frequency and concentration of exposure to monocyclic aromatic hydrocarbons in each job lasting ≥2 years. Logistic regression estimated OR and 95% CIs for PCa risk, adjusting for potential confounders. Results Exposures to BTX were highly intercorrelated, except for durations of exposure at substantial levels. Ever exposure to any BTX was associated with overall PCa (OR 1.27, 95% CI 1.05 to 1.53), while the OR for styrene was 1.19. However, increases in risk were largely confined to low-grade tumours, with ORs of 1.33 (95%CI 1.08 to 1.64) and 1.41 (95% CI 0.85 to 2.31) for ever exposure to any BTX and styrene, respectively, and a duration response pattern for any BTX. Risks for low-grade tumours were elevated among men exposed ≥25 years at substantial levels of benzene (OR 2.32) and styrene (OR 2.44). Some cumulative exposure categories showed increased risks but without clear trends. Conclusion Exposure to any BTX was associated with higher risks of overall PCa. Prolonged exposures at the substantial level to benzene and styrene increased risks of low-grade tumours. These novel findings were independent from PCa screening.

Diesel engine exhaust exposure in underground mines: Comparison between different surrogates of particulate exposure

ABSTRACT Exposure to diesel particulate matter (DPM) is frequently assessed by measuring indicators of carbon speciation, but these measurements may be affected by organic carbon (OC) interference. Furthermore, there are still questions regarding the reliability of direct-reading instruments (DRI) for measuring DPM, since these instruments are not specific and may be interfered by other aerosol sources. This study aimed to assess DPM exposure in 2 underground mines by filter-based methods and DRI and to assess the relationship between the measures of elemental carbon (EC) and the DRI to verify the association of these instruments to DPM. Filter-based methods of respirable combustible dust (RCD), EC, and total carbon (TC) were used to measure levels of personal and ambient DPM. For ambient measurements, DRI were used to monitor particle number concentration (PNC; PTrak), particle mass concentration (DustTrak DRX and DustTrak 8520), and the submicron fraction of EC (EC1;Airtec). The association between ambient EC and the DRI was assessed by Spearman correlation. Geometric mean concentrations of RCD, respirable TC (TCR) and respirable elemental EC (ECR) were 170 µg/m3, 148 µg/m3, and 83 µg/m3 for personal samples, and 197 µg/m3, 151 µg/m3, and 100 µg/m3 for ambient samples. Personal measurements had higher TCR:ECR ratios compared to ambient samples (1.8 vs. 1.50) and weaker association between ECR and TCR. Among the DRI, the measures of EC1 by the Airtec (ρ = 0.86; P < 0.001) and the respirable particles by the DustTrak 8520 (ρ = 0.74; P < 0.001) showed the strongest association with EC, while PNC showed a weak and non-significant association with EC. In conclusion, this study provided important information about the concentrations of DPM in underground mines by measuring several indicators using filter-based methods and DRI. Among the DRI, the Airtec proved to be a good tool for estimating EC concentrations and, although the DustTrak showed good association with EC, interferences from other aerosol sources should be considered when using this instrument to assess DPM.

Development of and Selected Performance Characteristics of CANJEM, a General Population Job-Exposure Matrix Based on Past Expert Assessments of Exposure

Objectives We developed a job-exposure matrix called CANJEM using data generated in population-based case-control studies of cancer. This article describes some of the decisions in developing CANJEM, and some of its performance characteristics. Methods CANJEM is built from exposure information from 31673 jobs held by study subjects included in our past case-control studies. For each job, experts had evaluated the intensity, frequency, and likelihood of exposure to a predefined list of agents based on jobs histories and descriptions of tasks and workplaces. The creation of CANJEM involved a host of decisions regarding the structure of CANJEM, and operational decisions regarding which parameters to present. The goal was to produce an instrument that would provide great flexibility to the user. In addition to describing these decisions, we conducted analyses to assess how well CANJEM covered the range of occupations found in Canada. Results Even at quite a high level of resolution of the occupation classifications and time periods, over 90% of the recent Canadian working population would be covered by CANJEM. Prevalence of exposure of specific agents in specific occupations ranges from 0% to nearly 100%, thereby providing the user with basic information to discriminate exposed from unexposed workers. Furthermore, among exposed workers there is information that can be used to discriminate those with high exposure from those with low exposure. Conclusions CANJEM provides good coverage of the Canadian working population and possibly that of several other countries. Available in several occupation classification systems and including 258 agents, CANJEM can be used to support exposure assessment efforts in epidemiology and prevention of occupational diseases.

Development of Quantitative Estimates of Wood Dust Exposure in a Canadian General Population Job-Exposure Matrix Based on Past Expert Assessments

Objectives The CANJEM general population job-exposure matrix summarizes expert evaluations of 31 673 jobs from four population-based case-control studies of cancer conducted in Montreal, Canada. Intensity in each CANJEM cell is represented as relative distributions of the ordinal (low, medium, high) ratings of jobs assigned by the experts. We aimed to apply quantitative concentrations to CANJEM cells using Canadian historical measurements from the Canadian Workplace Exposure Database (CWED), taking exposure to wood dust as an example. Methods We selected 5170 personal and area wood dust measurements from 31 occupations (2011 Canadian National Occupational Classification) with a non-zero exposure probability in CANJEM between 1930 and 2005. The measurements were taken between 1981 and 2003 (median 1989). A Bayesian hierarchical model was applied to the wood dust concentrations with occupations as random effects, and sampling duration, year, sample type (area or personal), province, and the relative proportion of jobs exposed at medium and high intensity in CANJEM cells as fixed effects. Results The estimated geometric mean (GM) concentrations for a CANJEM cell with all jobs exposed at medium or high intensity were respectively 1.3 and 2.4 times higher relative to a cell with all jobs at low intensity. An overall trend of -3%/year in exposure was observed. Applying the model estimates to all 198 cells in CANJEM with some exposure assigned by the experts, the predicted 8-hour, personal wood dust GM concentrations by occupation for 1989 ranged from 0.48 to 1.96 mg m-3. Conclusions The model provided estimates of wood dust concentrations for any CANJEM cell with exposure, applicable for quantitative risk assessment at the population level. This framework can be implemented for other agents represented in both CANJEM and CWED.

0288 Development of quantitative estimates of wood dust exposure in a canadian general population job-exposure matrix based on past expert assessments

Objectives The CANJEM general population job-exposure matrix summarises expert evaluations of 31 673 jobs from four population-based case-control studies of cancer conducted in Montreal, Canada. Intensity in each CANJEM cell is represented as relative distributions of the ordinal (low, medium, high) ratings of jobs assigned by the experts. We aimed to estimate quantitative concentrations for CANJEM cells using Canadian historical measurements, taking exposure to wood dust as an example. Methods Wood dust measurements came from the Canadian Workplace Exposure Database (CWED). We selected personal and area samples in occupations (2011 Canadian National Occupational Classification) with a non-zero exposure probability in CANJEM in period 1930–2005 (minimum 10 samples/occupation in CWED). Concentrations were modelled with sampling duration, year and type, source database and proportion of jobs at medium and high intensity in cells (fixed effects), and occupations (random effects). Results 5170 samples from 31 occupations spanning 1981–2003 were retained. Estimated geometric mean (GM) concentrations for a cell with all jobs at medium or high intensity were respectively 1.3 and 2.3 times higher than a cell with all jobs at low intensity. An overall trend of −5%/year in exposure was observed. Predicted GMs for 8 hours, breathing zone and year 1989 for CANJEM cells associated with exposure ranged 0.49–1.67 mg/m3. Conclusions The model provided estimates of wood dust concentrations for any CANJEM cell with exposure, even for those without measurements by using the calibrated intensity ratings. This framework could be implemented for other agents represented in both CANJEM and CWED.

O43-4 Evaluation of a hybrid expert approach for retrospective assessment of occupational exposures in a population-based study of prostate cancer in montreal, canada

Objective To evaluate the performance of a hybrid expert approach for retrospective occupational exposure assessment. Methods PROtEuS is a population-based case-control study of prostate cancer in Montreal, Canada, comprising approximately 4000 subjects. Semi-structured interviews and questionnaires were used to collect lifetime occupational histories. Experts evaluated exposure to 345 agents, assigning semi-quantitative levels (3 categories) by certainty, intensity and frequency of exposure. Towards this, they used job-exposure profiles (JEPs) developed using traditional expert ratings from a case-control study of lung cancer conducted in Montreal in the 1990s. JEPs present summaries of ratings across agents by job title, as well as guidelines helping experts adjust their ratings based on specific exposure circumstances. We compared expert ratings with JEP distributions to evaluate how experts modulated their assessments beyond those proposed by the JEPs while taking into account the information provided by study subjects. We restricted comparisons to blue collar occupations, and to agents and 7-digit 1971 Canadian Classification and Dictionary of Occupation codes common between the two sets. Results A total of 279 agents and 667 blue collar occupations were retained for analysis. Experts rated exposures with higher certainty (OR 1.18, 95% CI: 1.16–1.21) and intensity (OR 1.07, 95% CI: 1.04–1.10) relative to JEPs, while the opposite trend was found for frequency (OR 0.75, 95% CI: 0.73–0.76). Weighted Kappa values for the agreement between the ratings assigned by experts with those with the highest proportion of jobs in JEPs was highest for frequency (0.70) and intensity (0.66) compared to certainty (0.44). Conclusions PROtEuS experts provided with JEPs rated exposures with higher certainty and intensity, and with lower frequency, compared to the ratings from the JEPs themselves. This suggests that experts can use subjects’ job descriptions to modulate the ratings proposed by JEPs towards an overall greater confidence in their occupational exposure assignments.

0381 Adjustment for multiple comparisons in a job and industry-title analysis of a case-control study of prostate cancer

Objectives To evaluate the impacts of empirical Bayes (EB) and semi-Bayes (SB) adjustment to account for multiple testing in a hypothesis-generating study of prostate cancer (PCa) risk by occupation and industry. Method The study population comprises 1937 PCa cases and 1995 population controls aged 40–75 years, all residing in Montreal. Odds ratios (OR) and 95% confidence intervals (CI) of PCa risk for ever employment in an occupation and industry were estimated using unconditional logistic regression models adjusted for age, ancestry, and family history of PCa. EB and SB adjustment was applied to the estimates, with prior variances of 0.15, 0.25 and 0.35 selected for SB. Occupation and industry effects were considered mutually exchangeable, with the risk estimates shrunk towards their respective global mean. Results 5 of the 89 occupations and 3 of the 63 industries had a significantly elevated PCa risk prior to EB/SB adjustment, compared to an expected 2 and 1.5 categories due to random chance. The only positive association remaining significant following EB was for subjects ever employed in government (OR=1.4, 95% CI 1.1–1.5). The remaining elevated PCa risks with SB were found for employment in social science occupations (OR=1.5, 95% CI 1.1–2.0) and for forestry workers (OR=1.7, 95% CI 1.1–2.6), in addition to government (OR=1.4, 95% CI 1.1–1.7). The choice of prior variance had a negligible impact on the estimates. Conclusions The use of EB and SB reduced the number of positive associations compared to the unadjusted estimates. The elevated PCa risk observed for employment in government remained consistent across the adjustment approaches.

Correction: Statistical modeling of crystalline silica exposure by trade in the construction industry using a database compiled from the literature

Correction for ‘Statistical modeling of crystalline silica exposure by trade in the construction industry using a database compiled from the literature’ by Jean-Francois Sauve et al., J. Environ. Monit., 2012, 14, 2512–2520.