General Population Job-exposure Matrix Research Articles

Automated Coding of Job Descriptions From a General Population Study: Overview of Existing Tools, Their Application and Comparison.

Automatic job coding tools were developed to reduce the laborious task of manually assigning job codes based on free-text job descriptions in census and survey data sources, including large occupational health studies. The objective of this study is to provide a case study of comparative performance of job coding and JEM (Job-Exposure Matrix)-assigned exposures agreement using existing coding tools. We compared three automatic job coding tools [AUTONOC, CASCOT (Computer-Assisted Structured Coding Tool), and LabourR], which were selected based on availability, coding of English free-text into coding systems closely related to the 1988 version of the International Standard Classification of Occupations (ISCO-88), and capability to perform batch coding. We used manually coded job histories from the AsiaLymph case-control study that were translated into English prior to auto-coding to assess their performance. We applied two general population JEMs to assess agreement at exposure level. Percent agreement and PABAK (Prevalence-Adjusted Bias-Adjusted Kappa) were used to compare the agreement of results from manual coders and automatic coding tools. The coding per cent agreement among the three tools ranged from 17.7 to 26.0% for exact matches at the most detailed 4-digit ISCO-88 level. The agreement was better at a more general level of job coding (e.g. 43.8-58.1% in 1-digit ISCO-88), and in exposure assignments (median values of PABAK coefficient ranging 0.69-0.78 across 12 JEM-assigned exposures). Based on our testing data, CASCOT was found to outperform others in terms of better agreement in both job coding (26% 4-digit agreement) and exposure assignment (median kappa 0.61). In this study, we observed that agreement on job coding was generally low for the three tools but noted a higher degree of agreement in assigned exposures. The results indicate the need for study-specific evaluations prior to their automatic use in general population studies, as well as improvements in the evaluated automatic coding tools.

Parental occupational exposure to combustion products, metals, silica and asbestos and risk of childhood leukaemia: Findings from the Childhood Cancer and Leukaemia International Consortium (CLIC).

Parental occupational exposures around conception (father) or during pregnancy (mother) have been hypothesized as potential predisposing factors for childhood leukaemia. We investigated parental exposure to several known occupational carcinogens and childhood leukaemia risk. We conducted a pooled analysis using case-control data from four European countries (3362 childhood leukemia cases and 6268 controls). Parental occupational exposures to polycyclic aromatic hydrocarbons (PAH), diesel engine exhaust (DEE), chromium, nickel, crystalline silica, and asbestos were assessed by a general population job-exposure matrix. We estimated odd ratios (ORs) and 95% confidence intervals (CIs) using unconditional logistic regression models for all childhood leukaemia combined, by leukaemia type (ALL and AML) and by ALL subtype (B-lineage and T-lineage). We found an association between high paternal occupational exposure to crystalline silica and childhood ALL (OR 2.20, CI 1.60–3.01) with increasing trend from no exposure to high exposure (P = <0.001), and also for AML (OR 2.03, CI 1.04–3.97; P for trend = 0.008). ORs were similar for B- and T-lineage ALL. For ALL, ORs were also slightly elevated with wide confidence intervals for high paternal occupational exposure to chromium (OR 1.23, CI 0.77–1.96), and DEE (OR 1.21, CI 0.82–1.77). No associations were observed for paternal exposures to nickel, PAH and asbestos. For maternal occupational exposure we found several slightly elevated odds ratios but mostly with very wide confidence intervals due to low numbers of exposed mothers. This is a first study suggesting an association between fathers’ occupational exposure to crystalline silica and an increased risk of childhood leukaemia in their offspring. As this association was driven by certain occupations (field crop farmers and miners) where other potentially relevant exposures like pesticides and radon may also occur, more research is needed to confirm our findings of an association with crystalline silica, and if so, mechanistic studies to understand the pathways.

Occupational Exposure to Polycyclic Aromatic Hydrocarbons and Lung Cancer Risk: Results from a Pooled Analysis of Case-Control Studies (SYNERGY).

Exposure to polycyclic aromatic hydrocarbons (PAH) occurs widely in occupational settings. We investigated the association between occupational exposure to PAH and lung cancer risk and joint effects with smoking within the SYNERGY project. We pooled 14 case-control studies with information on lifetime occupational and smoking histories conducted between 1985 and 2010 in Europe and Canada. Exposure to benzo[a]pyrene (BaP) was used as a proxy of PAH and estimated from a quantitative general population job-exposure matrix. Multivariable unconditional logistic regression models, adjusted for smoking and exposure to other occupational lung carcinogens, estimated ORs, and 95% confidence intervals (CI). We included 16,901 lung cancer cases and 20,965 frequency-matched controls. Adjusted OR for PAH exposure (ever) was 1.08 (CI, 1.02-1.15) in men and 1.20 (CI, 1.04-1.38) in women. When stratified by smoking status and histologic subtype, the OR for cumulative exposure ≥0.24 BaP μg/m3-years in men was higher in never smokers overall [1.31 (CI, 0.98-1.75)], for small cell [2.53 (CI, 1.28-4.99)] and squamous cell cancers [1.33 (CI, 0.80-2.21)]. Joint effects between PAH and smoking were observed. Restricting analysis to the most recent studies showed no increased risk. Elevated lung cancer risk associated with PAH exposure was observed in both sexes, particularly for small cell and squamous cell cancers, after accounting for cigarette smoking and exposure to other occupational lung carcinogens. The lack of association between PAH and lung cancer in more recent studies merits further research under today's exposure conditions and worker protection measures.

Development of Nationwide Excess Lifetime Cancer Risk Evaluation Methods with Comprehensive Past Asbestos Exposure Reconstruction.

Although exposure to asbestos via various routes has been acknowledged, comprehensive exposure and risk assessment methods have not been developed at the national level. We conducted a study to reconstruct comprehensive past asbestos exposure estimations and to suggest a method to calculate the Excess Lifetime Cancer Risk (ELCR) of Koreans. The past occupational exposure reconstruction was conducted by rebuilding the previous general population job-exposure matrix (JEM). The para-occupational and household exposure estimation was based on the pooled analysis of data from other countries as well as Korea. The neighborhood exposure from occupational sources by distance was estimated by the exponential decay model. As a result, 141 JEM exposure groups across four periods including ~79, the 80s, 90s, 2000s with a ratio of 2.0:1.0:0.5:0.05 were reconstructed. The para-occupational and household exposures were 11% and 1% of the JEM respectively. The environmental exposure source concentration from outside occupational exposure was 2.5% of the inside concentration. The ratio of the concentration of environmental exposure source (C0) to distance d (Cd) was with a decay constant k of 6.834. The mean concentrations (f/cc) were 2.28 × 10−3 for outdoor, 4.65 × 10−5 for indoor, 1.95 × 10−2 for transportation activity, 4.44 × 10−2 for agricultural activity, and 4.68 × 10−2 for daily life activity in naturally occurring asbestos areas. Indoor and outdoor asbestos concentrations from living in a slate roof house were 1.73 × 10−6 and 2.70 × 10−8, respectively. For improved generalizability, validity, and applicability of the proposed method, further studies on each route with real assessments and experiments are required.

A Quantitative General Population Job Exposure Matrix for Occupational Noise Exposure.

Occupational noise exposure is a known risk factor for hearing loss and also adverse cardiovascular effects have been suggested. A job exposure matrix (JEM) would enable studies of noise and health on a large scale. The objective of this study was to create a quantitative JEM for occupational noise exposure assessment of the general working population. Between 2001-2003 and 2009-2010, we recruited workers from companies within the 10 industries with the highest reporting of noise-induced hearing loss according to the Danish Working Environment Authority and in addition workers of financial services and children day care to optimize the range in exposure levels. We obtained 1343 personal occupational noise dosimeter measurements among 1140 workers representing 100 different jobs according to the Danish version of the International Standard Classification of Occupations 1988 (DISCO 88). Four experts used 35 of these jobs as benchmarks and rated noise levels for the remaining 337 jobs within DISCO 88. To estimate noise levels for all 372 jobs, we included expert ratings together with sex, age, occupational class, and calendar year as fixed effects, while job and worker were included as random effects in a linear mixed regression model. The fixed effects explained 40% of the total variance: 72% of the between-jobs variance, -6% of the between-workers variance and 4% of the within-worker variance. Modelled noise levels showed a monotonic increase with increasing expert score and a 20 dB difference between the highest and lowest exposed jobs. Based on the JEM estimates, metal wheel-grinders were among the highest and finance and sales professionals among the lowest exposed. This JEM of occupational noise exposure can be used to prioritize preventive efforts of occupational noise exposure and to provide quantitative estimates of contemporary exposure levels in epidemiological studies of health effects potentially associated with noise exposure.

Musculoskeletal symptoms associated with workplace physical exposures estimated by a job exposure matrix and by self-report.

A job-exposure matrix (JEM) is an efficient method to assign physical workplace exposures based on job titles. JEMs offer the possibility of linking work exposures to outcome data from national health registers that contain job titles. The French CONSTANCES JEM was constructed from self-reported physical work exposures of asymptomatic workers participating in a large general population study. We validated this general population JEM by testing its ability to demonstrate exposure-outcome associations for musculoskeletal disorders (MSD) symptoms. The CONSTANCES JEM was evaluated by assigning exposure estimates to a validation sample of new participants in the CONSTANCES study (final n = 38 730). We used weighted Kappas to compare the level of agreement between JEM-assigned and self-reported exposures across job codes for each of the 27 physical exposure variables. We computed prevalence ratios and 95% confidence intervals using Poisson regression models adjusted for age and sex for pain at six body locations associated with work exposures estimated via individual self-report and by the JEM. Agreement between individual self-reported and JEM-assigned exposures ranged from κ = 0.16 to 0.71; generally, the level of agreement was fair to good. We observed consistent and significant associations between pain and both self-reported and JEM-assigned exposures at all body locations. The CONSTANCES JEM replicated known associations between physical risk factors and prevalent MSD symptoms. Physical exposure JEMs can reduce some types of information bias, and open new avenues of research in the prevention of MSDs and other health conditions related to workplace physical activities.

Bayesian Hierarchical Modelling of Individual Expert Assessments in the Development of a General-Population Job-Exposure Matrix

The CANJEM job-exposure matrix compiles expert evaluations of 31 673 jobs from four population-based case-control studies conducted in Montreal. For each job, experts had derived indices of intensity, frequency, and probability of exposure to 258 agents. CANJEM summarizes the exposures assigned to jobs into cells defined by occupation/industry, agent, and period. Some cells may, however, be less populated than others, resulting in uncertain estimates. We developed a modelling framework to refine the estimates of sparse cells by drawing on information available in adjacent cells. Bayesian hierarchical logistic and linear models were used to estimate the probability of exposure and the geometric mean (GM) of frequency-weighted intensity (FWI) of cells, respectively. The hierarchy followed the Canadian Classification and Dictionary of Occupations (CCDO) classification structure, allowing for exposure estimates to be provided across occupations (seven-digit code), unit groups (four-digit code), and minor groups (three-digit code). The models were applied to metallic dust, formaldehyde, wood dust, silica, and benzene, and four periods, adjusting for the study from which jobs were evaluated. The models provided estimates of probability and FWI for all cells that pulled the sparsely populated cells towards the average of the higher-level group. In comparisons stratified by cell sample size, shrinkage of the estimates towards the group mean was marked below 5 jobs/cell, moderate from 5 to 9 jobs/cell, and negligible at ≥10 jobs/cell. The modelled probability of three-digit cells were slightly smaller than their descriptive estimates. No systematic trend in between-study differences in exposure emerged. Overall, the modelling framework for FWI appears to be a suitable approach to refine CANJEM estimates. For probability, the models could be improved by methods better adapted to the large number of cells with no exposure.

Trends in working conditions and health across three cohorts of older workers in 1993, 2003 and 2013: a cross-sequential study

BackgroundOver the past decades, the number of older workers has increased tremendously. This study examines trends from 1993 to 2013 in physical, cognitive and psychological functioning among three successive cohorts of Dutch older workers. The contribution of the changes in physical and psychosocial work demands and psychosocial work resources to change in functioning is examined. Insight in health of the older working population, and in potential explanatory variables, is relevant in order to reach sustainable employability.MethodsData from three cohorts (observations in 1993, 2003 and 2013) of the Longitudinal Aging Study Amsterdam (LASA) were used. Individuals aged 55–65 with a paid job were included (N = 1307). Physical functioning was measured using the Timed Chair Stand Test, cognitive functioning by a Coding Task and psychological functioning by the positive affect scale from the CES-D. Working conditions were deduced from a general population job exposure matrix. Linear and logistic regression analyses were performed.ResultsFrom 1993 to 2013, time needed to perform the Timed Chair Stand Test increased with 1.3 s (95%CI = 0.89–1.71), to a mean of 11.5 s. Coding Task scores increased with 1.7 points (95%CI = 0.81–2.59), to a mean of 31 points. The proportion of workers with low positive affect increased non-significantly from 15 to 20% (p = 0.088). Only the improvement in cognitive functioning was associated with the change in working conditions. The observed decrease of physically demanding jobs and increase of jobs with higher psychosocial resources explained 8% of the improvement.ConclusionsChanges in working conditions may not contribute to improved physical and psychological functioning, but do contribute to improved cognitive functioning to some extent. Further adjustment of physical work demands and psychosocial work resources may help to reach sustainable employability of older workers.

Applying two general population job exposure matrices to predict incident carpal tunnel syndrome: A cross-national approach to improve estimation of workplace physical exposures.

Objectives A job exposure matrix (JEM) is a tool to estimate workers' exposure to occupational physical risk factors. We evaluated the performance of two general population JEM (CONSTANCES and O*NET) to detect known exposure-disease relationships in an American prospective cohort study. We compared exposure estimates from three data sources and explored whether combining exposures from these two JEM, or combining exposure from each JEM with individual-level measures, improved prediction of carpal tunnel syndrome (CTS). Methods Using Cox proportional hazard models, we evaluated relationships between physical work exposure and incident CTS of 2393 workers using JEM-assigned and individual-level measure exposure information. We compared exposure estimates using Spearman's rank correlation and Cohen's kappa. We compared combined exposure models to single source exposure models by using binomial logistic regression and examined differences based on model fit and performance. Results The O*NET JEM [hazard ratio (HR) range 1.3-2.01] demonstrated generally similar exposure-disease associations as individual-level measures (HR range 1.00-1.42); we found fewer associations with the CONSTANCES JEM (HR range 1.08-2.05). Comparisons between the three sources showed stronger correlations and agreement at the job versus worker level. Combined models improved goodness-of-fit and had lower Akaike information criterion (AIC) values compared to single-source models. Conclusions JEM can be applied cross nationally and there is potential to combine complementary exposure methods to improve estimation of workplace physical exposures in the prediction of CTS. More investigations are needed to explore exposure-disease associations in other samples and combinations of exposure data from different methods.

A Quantitative General Population Job Exposure Matrix for Occupational Daytime Light Exposure.

High daytime light levels may reduce the risk of affective disorders. Outdoor workers are during daytime exposed to much higher light intensities than indoor workers. A way to study daytime light exposure and disease on a large scale is by use of a general population job exposure matrix (JEM) combined with national employment and health data. The objective of this study was to develop a JEM applicable for epidemiological studies of exposure response between daytime light exposure, affective disorders, and other health effects by combining expert scores and light measurements. We measured light intensity during daytime work hours 06:00-17:59 for 1-7 days with Philips Actiwatch Spectrum® light recorders (Actiwatch) among 695 workers representing 71 different jobs. Jobs were coded into DISCO-88, the Danish version of the International Standard Classification of Occupations 1988. Daytime light measurements were collected all year round in Denmark (55-56°N). Arithmetic mean white light intensity (lux) was calculated for each hour of observation (n = 15,272), natural log-transformed, and used as the dependent variable in mixed effects linear regression models. Three experts rated probability and duration of outdoor work for all 372 jobs within DISCO-88. Their ratings were used to construct an expert score that was included together with month of the year and hour of the day as fixed effects in the model. Job, industry nested within job, and worker were included as random effects. The model estimated daytime light intensity levels specific for hour of the day and month of the year for all jobs with a DISCO-88 code in Denmark. The fixed effects explained 37% of the total variance: 83% of the between-jobs variance, 57% of the between industries nested in jobs variance, 43% of the between-workers variance, and 15% of the within-worker variance. Modeled daytime light intensity showed a monotonic increase with increasing expert score and a 30-fold ratio between the highest and lowest exposed jobs. Building construction laborers were based on the JEM estimates among the highest and medical equipment operators among the lowest exposed. This is the first quantitative JEM of daytime light exposure and will be used in epidemiological studies of affective disorders and other health effects potentially associated with light exposure.

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

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. 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. 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. 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.

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

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. 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. 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. 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.

Surgery for subacromial impingement syndrome in relation to intensities of occupational mechanical exposures across 10-year exposure time windows

ObjectivesWe aimed to identify intensities of occupational mechanical exposures (force, arm elevation and repetition) that do not entail an increased risk of surgery for subacromial impingement syndrome (SIS) even after...

Risk of Central Nervous System Tumors in Children Related to Parental Occupational Pesticide Exposures in three European Case-Control Studies.

The aim of this study was to assess the risk of childhood central nervous system (CNS) tumors associated with parental occupational pesticide exposure. We pooled three population-based case-control studies from France, Germany, and the United Kingdom. Cases were children below 15 years of age with CNS tumors; controls were matched by gender and age. A general population job-exposure matrix assessed parental occupational pesticide exposure. Logistic regressions estimated odds ratios (ORs) and 95% confidence intervals (CIs). The study included 1361 cases and 5498 controls. Prevalence of maternal occupational pesticide exposure during pregnancy was low and no association with childhood CNS tumors was detected (OR 0.76, 95% CI: 0.41 to 1.41). Around conception, OR for childhood CNS tumors associated with paternal occupational pesticide exposure was 0.71 (95% CI: 0.53 to 0.95). Our results do not suggest a role of parental occupational pesticide exposure in the etiology of childhood CNS tumors.

Developing Asbestos Job Exposure Matrix Using Occupation and Industry Specific Exposure Data (1984-2008) in Republic of Korea.

BackgroundThe goal of this study is to develop a general population job-exposure matrix (GPJEM) on asbestos to estimate occupational asbestos exposure levels in the Republic of Korea.MethodsThree Korean domestic quantitative exposure datasets collected from 1984 to 2008 were used to build the GPJEM. Exposure groups in collected data were reclassified based on the current Korean Standard Industrial Classification (9th edition) and the Korean Standard Classification of Occupations code (6th edition) that is in accordance to international standards. All of the exposure levels were expressed by weighted arithmetic mean (WAM) and minimum and maximum concentrations.ResultsBased on the established GPJEM, the 112 exposure groups could be reclassified into 86 industries and 74 occupations. In the 1980s, the highest exposure levels were estimated in “knitting and weaving machine operators” with a WAM concentration of 7.48 fibers/mL (f/mL); in the 1990s, “plastic products production machine operators” with 5.12 f/mL, and in the 2000s “detergents production machine operators” handling talc containing asbestos with 2.45 f/mL. Of the 112 exposure groups, 44 groups had higher WAM concentrations than the Korean occupational exposure limit of 0.1 f/mL.ConclusionThe newly constructed GPJEM which is generated from actual domestic quantitative exposure data could be useful in evaluating historical exposure levels to asbestos and could contribute to improved prediction of asbestos-related diseases among Koreans.

Upper arm elevation and repetitive shoulder movements: a general population job exposure matrix based on expert ratings and technical measurements

ObjectivesWe recently constructed a general population job exposure matrix (JEM), The Shoulder JEM, based on expert ratings. The overall aim of this study was to convert expert-rated job exposures for...

General population job exposure matrix applied to a pooled study of prevalent carpal tunnel syndrome.

A job exposure matrix may be useful for the study of biomechanical workplace risk factors when individual-level exposure data are unavailable. We used job title-based exposure data from a public data source to construct a job exposure matrix and test exposure-response relationships with prevalent carpal tunnel syndrome (CTS). Exposures of repetitive motion and force from the Occupational Information Network were assigned to 3,452 active workers from several industries, enrolled between 2001 and 2008 from 6 studies. Repetitive motion and force exposures were combined into high/high, high/low, and low/low exposure groupings in each of 4 multivariable logistic regression models, adjusted for personal factors. Although force measures alone were not independent predictors of CTS in these data, strong associations between combined physical exposures of force and repetition and CTS were observed in all models. Consistent with previous literature, this report shows that workers with high force/high repetition jobs had the highest prevalence of CTS (odds ratio = 2.14-2.95) followed by intermediate values (odds ratio = 1.09-2.27) in mixed exposed jobs relative to the lowest exposed workers. This study supports the use of a general population job exposure matrix to estimate workplace physical exposures in epidemiologic studies of musculoskeletal disorders when measures of individual exposures are unavailable.

Parental occupational exposure and risk of childhood central nervous system tumors: a pooled analysis of case-control studies from Germany, France, and the UK.

To assess the risk of childhood central nervous system (CNS) tumors associated with parental occupational exposure to polycyclic aromatic hydrocarbons (PAH), diesel motor exhaust (DME), asbestos, crystalline silica, and metals, which are established carcinogens in adults. We pooled data from three population-based case-control studies from Germany, France, and the UK. Cases were children aged up to 15years and diagnosed with CNS tumor, and controls were frequency-matched by age and sex. Socio-demographic data and parental occupation around conception/pregnancy and at diagnosis were collected using standardized interviews, face-to-face or by telephone. A general population job-exposure matrix was used to assign a level of exposure to each job. Logistic regression models were fitted to compute odds ratios and 95% confidence intervals. Our study included 1,361 cases of CNS tumors and 5,500 controls. Paternal exposure to PAH, asbestos, and metals around conception was associated with an increased moderate risk of CNS tumors, although statistically non-significant. The association with exposure to asbestos around conception and diagnosis was stronger when fathers were exposed to high levels. Paternal exposure to DME and silica, and maternal exposure to PAH, DME, asbestos, silica, and metals, were not associated with an increased risk of CNS tumors. Our large pooled study showed weak evidence of a modest association between paternal occupational exposure to PAH and CNS tumor risk. Our findings need further exploration in the future studies.

0382 CANJEM: a general population job exposure matrix based on past expert assessments of exposure to over 250 agents

ObjectivesTo create a general population job-exposure matrix (JEM) from a database of expert assessments performed during four community-based case-control studies of cancer (lung, breast, brain, and multisite) conducted in Montreal...

Occupational asbestos exposure and risk of oral cavity and pharyngeal cancer in the prospective Netherlands Cohort Study.

The evidence for an association between occupational asbestos exposure and pharyngeal cancer (PhC) is limited, while for oral cavity cancer (OCC) the literature is even sparser. We studied OCC and PhC risk both separately and combined (OCPC) in relation to occupational asbestos exposure, specifically addressing the influence of potential confounders, the existence of an exposure-response relation, and the presence of interaction between asbestos and smoking. Using the prospective Netherlands Cohort Study (N=58 279 men, aged 55-69 years), we estimated asbestos exposure by linkage to a general population job-exposure matrix (DOMJEM) and a Finnish job exposure matrix (FINJEM). After 17.3 years of follow-up, 58 OCC and 53 PhC cases were available for analysis. No association between asbestos and risk of OCC was observed for either JEM. Hazard ratios (HR) of PhC and OCPC increased after adjusting for confounders, particularly alcohol consumption and socioeconomic status. For PhC, a multivariable-adjusted increased HR was observed for "ever" versus "never" exposed to asbestos [HR 2.20, 95% confidence interval (95% CI) 1.08-4.49] when using FINJEM, but a trend of increased risks with higher cumulative exposure could not be demonstrated for either JEM. Results for OCPC showed patterns similar to those observed for PhC. None of the cancers showed a significant interaction between asbestos and smoking. This prospective population-based study showed no convincing evidence of an association between asbestos and risk of OCC, PhC, and OCPC as an exposure-response relation was lacking, and results were not robust against the use of different JEM. However, the potentially increased HR of PhC and OCPC observed in this and previous studies warrant further research.