Combining a job-exposure matrix with exposure measurements to assess occupational exposure to benzene in a population cohort in shanghai, china

Respirable crystalline silica and lung cancer in community-based studies: impact of job-exposure matrix specifications on exposure-response relationships

OBJECTIVES

The quantitative job-exposure matrix SYN-JEM consists of various dimensions: job-specific estimates, region-specific estimates, and prior expert ratings of jobs by the semi-quantitative DOM-JEM. We analyzed the effect of different JEM dimensions on the exposure-response relationships between occupational silica exposure and lung cancer risk to investigate how these variations influence estimates of exposure by a quantitative JEM and associated health endpoints.

METHODS

Using SYN-JEM, and alternative SYN-JEM specifications with varying dimensions included, cumulative silica exposure estimates were assigned to 16 901 lung cancer cases and 20 965 controls pooled from 14 international community-based case-control studies. Exposure-response relationships based on SYN-JEM and alternative SYN-JEM specifications were analyzed using regression analyses (by quartiles and log-transformed continuous silica exposure) and generalized additive models (GAM), adjusted for age, sex, study, cigarette pack-years, time since quitting smoking, and ever employment in occupations with established lung cancer risk.

RESULTS

SYN-JEM and alternative specifications generated overall elevated and similar lung cancer odds ratios ranging from 1.13 (1st quartile) to 1.50 (4th quartile). In the categorical and log-linear analyses SYN-JEM with all dimensions included yielded the best model fit, and exclusion of job-specific estimates from SYN-JEM yielded the poorest model fit. Additionally, GAM showed the poorest model fit when excluding job-specific estimates.

CONCLUSION

The established exposure-response relationship between occupational silica exposure and lung cancer was marginally influenced by varying the dimensions of SYN-JEM. Optimized modelling of exposure-response relationships will be obtained when incorporating all relevant dimensions, namely prior rating, job, time, and region. Quantitative job-specific estimates appeared to be the most prominent dimension for this general population JEM.

Prerequisite for Imputing Non-detects among Airborne Samples in OSHA's IMIS Databank: Prediction of Sample's Volume

INTRODUCTION

The US Integrated Management Information System (IMIS) contains workplace measurements collected by Occupational Safety and Health Administration (OSHA) inspectors. Its use for research is limited by the lack of record of a value for the limit of detection (LOD) associated with non-detected measurements, which should be used to set censoring point in statistical analysis. We aimed to remedy this by developing a predictive model of the volume of air sampled (V) for the non-detected results of airborne measurements, to then estimate the LOD using the instrument detection limit (IDL), as IDL/V.

METHODS

We obtained the Chemical Exposure Health Data from OSHA's central laboratory in Salt Lake City that partially overlaps IMIS and contains information on V. We used classification and regression trees (CART) to develop a predictive model of V for all measurements where the two datasets overlapped. The analysis was restricted to 69 chemical agents with at least 100 non-detected measurements, and calculated sampling air flow rates consistent with workplace measurement practices; undefined types of inspections were excluded, leaving 412,201/413,515 records. CART models were fitted on randomly selected 70% of the data using 10-fold cross-validation and validated on the remaining data. A separate CART model was fitted to styrene data.

RESULTS

Sampled air volume had a right-skewed distribution with a mean of 357 l, a median (M) of 318, and ranged from 0.040 to 1868 l. There were 173,131 measurements described as non-detects (42% of the data). For the non-detects, the V tended to be greater (M = 378 l) than measurements characterized as either 'short-term' (M = 218 l) or 'long-term' (M = 297 l). The CART models were complex and not easy to interpret, but substance, industry, and year were among the top three most important classifiers. They predicted V well overall (Pearson correlation (r) = 0.73, P < 0.0001; Lin's concordance correlation (rc) = 0.69) and among records captured as non-detects in IMIS (r = 0.66, P < 0.0001l; rc = 0.60). For styrene, CART built on measurements for all agents predicted V among 569 non-detects poorly (r = 0.15; rc = 0.04), but styrene-specific CART predicted it well (r = 0.87, P < 0.0001; rc = 0.86).

DISCUSSION

Among the limitations of our work is the fact that samples may have been collected on different workers and processes within each inspection, each with its own V. Furthermore, we lack measurement-level predictors because classifiers were captured at the inspection level. We did not study all substances that may be of interest and did not use the information that substances measured on the same sampling media should have the same V. We must note that CART models tend to over-fit data and their predictions depend on the selected data, as illustrated by contrasting predictions created using all data vs. limited to styrene.

CONCLUSIONS

We developed predictive models of sampled air volume that should enable the calculation of LOD for non-detects in IMIS. Our predictions may guide future work on handling non-detects in IMIS, although it is advisable to develop separate predictive models for each substance, industry, and year of interest, while also considering other factors, such as whether the measurement evaluated long-term or short-term exposure.

Developing a company-specific job exposure matrix for the Asbest Chrysotile Cohort Study

OBJECTIVES

Exposure assessment for retrospective industrial cohorts are often hampered by limited availability of historical measurements. This study describes the development of company-specific job-exposure matrices (JEMs) based on measurements collected over five decades for a cohort study of 35 837 workers (Asbest Chrysotile Cohort Study) in the Russian Federation to estimate their cumulative exposure to chrysotile containing dust and fibres.

METHODS

Almost 100 000 recorded stationary dust measurements were available from 1951-2001 (factories) and 1964-2001 (mine). Linear mixed models were used to extrapolate for years where measurements were not available or missing. Fibre concentrations were estimated using conversion factors based on side-by-side comparisons. Dust and fibre JEMs were developed and exposures were allocated by linking them to individual workers' detailed occupational histories.

RESULTS

The cohort covered a total of 515 355 employment-years from 1930 to 2010. Of these individuals, 15% worked in jobs not considered professionally exposed to chrysotile. The median cumulative dust exposure was 26 mg/m3 years for the entire cohort and 37.2 mg/m3 years for those professionally exposed. Median cumulative fibre exposure was 16.4 fibre/cm3 years for the entire cohort and 23.4 fibre/cm3 years for those professionally exposed. Cumulative exposure was highly dependent on birth cohort and gender. Of those professionally exposed, women had higher cumulative exposures than men as they were more often employed in factories with higher exposure concentrations rather than in the mine.

CONCLUSIONS

Unique company-specific JEMs were derived using a rich measurement database that overlapped with most employment-years of cohort members and will enable estimation of quantitative exposure-response.

Simultaneous modeling of detection rate and exposure concentration using semi-continuous models to identify exposure determinants when left-censored data may be a true zero

BACKGROUND

Most methods for treating left-censored data assume the analyte is present but not quantified. Biased estimates may result if the analyte is absent such that the unobserved data represents a mixed exposure distribution with an unknown proportion clustered at zero.

OBJECTIVE

We used semi-continuous models to identify time and industry trends in 52,457 OSHA inspection lead sample results.

METHOD

The first component of the semi-continuous model predicted the probability of detecting concentrations ≥ 0.007 mg/m³ (highest estimated detection limit, 62% of measurements). The second component predicted the median concentration of measurements ≥ 0.007 mg/m³. Both components included a random-effect for industry and fixed-effects for year, industry group, analytical method, and other variables. We used the two components together to predict median industry- and time-specific lead concentrations.

RESULTS

The probabilities of detectable concentrations and the median detected concentrations decreased with year; both were also lower for measurements analyzed for multiple (vs. one) metals and for those analyzed by inductively-coupled plasma (vs. atomic absorption spectroscopy). The covariance was 0.30 (standard error = 0.06), confirming the two components were correlated.

SIGNIFICANCE

We identified determinants of exposure in data with over 60% left-censored, while accounting for correlated relationships and without assuming a distribution for the censored data.

Trends in Exposure to Diesel Particulate Matter and Prevalence of Respiratory Symptoms in Western Australian Miners

Diesel-powered equipment is used frequently in the mining industry. They are energetically more efficient and emit lower quantities of carbon monoxide and carbon dioxide than the gasoline equipment. However, diesel engines release more diesel particulate matter (DPM) during the combustion process which has been linked to harmful health effects. This study assessed the trends in DPM exposure and the prevalence of respiratory symptoms among Western Australian miners, using the available secondary data collected from 2006 to 2012. The data consisted of elemental carbon (EC) concentrations and information on miner's respiratory symptoms. The measured EC concentrations from n = 2598 miners ranged between 0.01 mg/m3 and 1.00 mg/m3 and tended to significantly decrease over the study period (p < 0.001). Underground mine workers were exposed to significantly higher (p < 0.01) median EC concentrations of 0.069 mg/m3 (IQR 0.076) when compared to surface workers' 0.038 mg/m3 (IQR 0.04). Overall, 29% of the miners reported at least one respiratory symptom, with the highest frequency recorded for cough (16%). Although the exposure levels of DPM in the mining industry of Western Australia have declined over the study period, they are still high and adhering to stringent occupational standard for DPM is recommended.

Retrospective Exposure Assessment Methods Used in Occupational Human Health Risk Assessment: A Systematic Review

As part of the assessment and management of chemical risk and occupational hygiene, retrospective exposure assessment (REA) to chemical agents can be defined as the estimate of exposure associated with a person's work history. The fundamental problem underlying the reconstruction of the exposure is that of transforming this type of information in quantitative terms to obtain an accurate estimate. REA can follow various approaches, some of which are technically complicated and both time and resource consuming. The aim of this systematic review is to present the techniques mainly used for occupational REA. In order to carry out this evaluation, a systematic review of the scientific literature was conducted. Forty-four studies were identified (published from 2010 to date) and analyzed. In exposure reconstruction studies, quantitative approaches should be preferable, especially when estimates will be used in the context of health impact assessment or epidemiology, although it is important to stress how, ideally, the experimental data available for the considered scenario should be used whenever possible as the main starting information base for further processing. To date, there is no single approach capable of providing an accurate estimate of exposure for each reasonably foreseeable condition and situation and the best approach generally depends on the level of information available for the specific case. The use of a combination of different reconstruction techniques can, therefore, represent a powerful tool for weighting and integrating data obtained through qualitative and quantitative approaches, in order to obtain the best possible estimate.

Peaks, Means, and Determinants of Real-Time TVOC Exposures Associated with Cleaning and Disinfecting Tasks in Healthcare Settings

Cleaning and disinfecting tasks and product use are associated with elevated prevalence of asthma and respiratory symptoms among healthcare workers; however, the levels of exposure that pose a health risk remain unclear. The objective of this study was to estimate the peak, average, and determinants of real-time total volatile organic compound (TVOC) exposure associated with cleaning tasks and product-use. TVOC exposures were measured using monitors equipped with a photoionization detector (PID). A simple correction factor was applied to the real-time measurements, calculated as a ratio of the full-shift average TVOC concentrations from a time-integrated canister and the PID sample, for each sample pair. During sampling, auxiliary information, e.g. tasks, products used, engineering controls, was recorded on standardized data collection forms at 5-min intervals. Five-minute averaged air measurements (n = 10 276) from 129 time-series comprising 92 workers and four hospitals were used to model the determinants of exposures. The statistical model simultaneously accounted for censored data and non-stationary autocorrelation and was fit using Markov-Chain Monte Carlo within a Bayesian context. Log-transformed corrected concentrations (cTVOC) were modeled, with the fixed-effects of tasks and covariates, that were systematically gathered during sampling, and random effect of person-day. The model-predicted geometric mean (GM) cTVOC concentrations ranged from 387 parts per billion (ppb) for the task of using a product containing formaldehyde in laboratories to 2091 ppb for the task of using skin wipes containing quaternary ammonium compounds, with a GM of 925 ppb when no products were used. Peak exposures quantified as the 95th percentile of 15-min averages for these tasks ranged from 3172 to 17 360 ppb. Peak and GM task exposures varied by occupation and hospital unit. In the multiple regression model, use of sprays was associated with increasing exposures, while presence of local exhaust ventilation, large room volume, and automatic sterilizer use were associated with decreasing exposures. A detailed understanding of factors affecting TVOC exposure can inform targeted interventions to reduce exposures and can be used in epidemiologic studies as metrics of short-duration peak exposures.

Benzene Exposure Response and Risk of Myeloid Neoplasms in Chinese Workers: A Multicenter Case-Cohort Study

BACKGROUND

There is international consensus that benzene exposure is causally related to acute myeloid leukemia (AML), and more recent evidence of association with myelodysplastic syndromes (MDS). However, there are uncertainties about the exposure response, particularly risks by time since exposure and age at exposure.

METHODS

In a case-cohort study in 110 631 Chinese workers followed up during 1972-1999 we evaluated combined MDS/AML (n = 44) and chronic myeloid leukemia (n = 18). We estimated benzene exposures using hierarchical modeling of occupational factors calibrated with historical routine measurements, and evaluated exposure response for cumulative exposure and average intensity using Cox regression; P values were two-sided.

RESULTS

Increased MDS/AML risk with increasing cumulative exposure in our a priori defined time window (2 to <10 years) before the time at risk was suggested (Ptrend = 08). For first exposure (within the 2 to <10-year window) before age 30 years, the exposure response was stronger (P = .004) with rate ratios of 1.12 (95% confidence interval [CI] = 0.27 to 4.29), 5.58 (95% CI = 1.65 to 19.68), and 4.50 (95% CI = 1.22 to 16.68) for cumulative exposures of more than 0 to less than 40, 40 to less than 100, and at least 100 ppm-years, respectively, compared with no exposure. There was little evidence of exposure response after at least 10 years (Ptrend = .94), regardless of age at first exposure. Average intensity results were generally similar. The risk for chronic myeloid leukemia was increased in exposed vs unexposed workers, but appeared to increase and then decrease with increasing exposure.

CONCLUSION

For myeloid neoplasms, the strongest effects were apparent for MDS/AML arising within 10 years of benzene exposure and for first exposure in the 2 to less than 10-year window before age 30 years.

Estimation of Source-Specific Occupational Benzene Exposure in a Population-Based Case-Control Study of Non-Hodgkin Lymphoma

OBJECTIVES

Occupational exposures in population-based case-control studies are increasingly being assessed using decision rules that link participants' responses to occupational questionnaires to exposure estimates. We used a hierarchical process that incorporated decision rules and job-by-job expert review to assign occupational benzene exposure estimates in a US population-based case-control study of non-Hodgkin lymphoma.

METHODS

We conducted a literature review to identify scenarios in which occupational benzene exposure has occurred, which we grouped into 12 categories of benzene exposure sources. For each source category, we then developed decision rules for assessing probability (ordinal scale based on the likelihood of exposure > 0.02 ppm), frequency (proportion of work time exposed), and intensity of exposure (in ppm). The rules used the participants' occupational history responses and, for a subset of jobs, responses to job- and industry-specific modules. For probability and frequency, we used a hierarchical assignment procedure that prioritized subject-specific module information when available. Next, we derived job-group medians from the module responses to assign estimates to jobs with only occupational history responses. Last, we used job-by-job expert review to assign estimates when job-group medians were not available or when the decision rules identified possible heterogeneous or rare exposure scenarios. For intensity, we developed separate estimates for each benzene source category that were based on published measurement data whenever possible. Frequency and intensity annual source-specific estimates were assigned only for those jobs assigned ≥75% probability of exposure. Annual source-specific concentrations (intensity × frequency) were summed to obtain a total annual benzene concentration for each job.

RESULTS

Of the 8827 jobs reported by participants, 8% required expert review for one or more source categories. Overall, 287 (3.3%) jobs were assigned ≥75% probability of exposure from any benzene source category. The source categories most commonly assigned ≥75% probability of exposure were gasoline and degreasing. The median total annual benzene concentration among jobs assigned ≥75% probability was 0.11 ppm (interquartile range: 0.06-0.55). The highest source-specific median annual concentrations were observed for ink and printing (2.3 and 1.2 ppm, respectively).

CONCLUSIONS

The applied framework captures some subject-specific variability in work tasks, provides transparency to the exposure decision process, and facilitates future sensitivity analyses. The developed decision rules can be used as a starting point by other researchers to assess occupational benzene exposure in future population-based studies.

Use and Reliability of Exposure Assessment Methods in Occupational Case-Control Studies in the General Population: Past, Present, and Future

Introduction

Retrospective occupational exposure assessment has been challenging in case-control studies in the general population. We aimed to review (i) trends of different assessment methods used in the last 40 years and (ii) evidence of reliability for various assessment methods.

Methods

Two separate literature reviews were conducted. We first reviewed all general population cancer case-control studies published from 1975 to 2016 to summarize the exposure assessment approach used. For the second review, we systematically reviewed evidence of reliability for all methods observed in the first review.

Results

Among the 299 studies included in the first review, the most frequently used assessment methods were self-report/assessment (n = 143 studies), case-by-case expert assessment (n = 139), and job-exposure matrices (JEMs; n = 82). Usage trends for these methods remained relatively stable throughout the last four decades. Other approaches, such as the application of algorithms linking questionnaire responses to expert-assigned exposure estimates and modelling of exposure with historical measurement data, appeared in 21 studies that were published after 2000. The second review retrieved 34 comparison studies examining methodological reliability. Overall, we observed slightly higher median kappa agreement between exposure estimates from different expert assessors (~0.6) than between expert estimates and exposure estimates from self-reports (~0.5) or JEMs (~0.4). However, reported reliability measures were highly variable for different methods and agents. Limited evidence also indicates newer methods, such as assessment using algorithms and measurement-calibrated quantitative JEMs, may be as reliable as traditional methods.

Conclusion

The majority of current research assesses exposures in the population with similar methods as studies did decades ago. Though there is evidence for the development of newer approaches, more concerted effort is needed to better adopt exposure assessment methods with more transparency, reliability, and efficiency.

Characterization of the Selective Recording of Workplace Exposure Measurements into OSHA's IMIS Databank

Objectives

The Integrated Management Information System (IMIS) is the largest multi-industry source of exposure results available in North America. In 2010, the Occupational Safety and Health Administration (OSHA) released the Chemical Exposure Health Data (CEHD) that contains analytical results of samples collected by OSHA inspectors. However, the two databanks only partially overlap, raising suspicion of bias in IMIS data. We investigated the factors associated with selective recording of CEHD results into the IMIS databank.

Methods

This analysis was based on personal exposure measurements of 24 agents from 1984 to 2009. The association between nine variables (level of exposure coded as detected versus non-detected (ND), whether a sampling result was part of a panel of chemicals, duration of sampling, issuance of a citation, presence of other detected levels during the same inspection, year, OSHA region, amount of penalty, and establishment size) and a CEHD sampling result being reported in IMIS was analyzed using modified Poisson regression.

Results

A total of 461900 CEHD sampling results were examined. The proportion of CEHD sampling results recorded into IMIS was 38% (51% for detected and 28% for ND measurements). In the models, the detected sampling results were associated with a higher probability of recording into IMIS than ND sampling results, and this difference was similar for panel versus non-panel samples. Probability of recording remained constant from 1984 to 2009 for sampling results measured on panels but increased for sampling results of single determinations of an agent. Some OSHA regions had probability of recording two times higher than others. No other variables that we examined were associated with a CEHD sampling result being reported in IMIS.

Conclusions

Our results indicate that the under-reporting of sampling results in IMIS is differential: ND results (especially those determined from the panels) seem less likely to be recorded in IMIS than other results. It is important to consider both IMIS and CEHD data in order to reduce bias in evaluation of exposures in workplaces inspected by OSHA.

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.

New Opportunities in Exposure Assessment of Occupational Epidemiology: Use of Measurements to Aid Exposure Reconstruction in Population-Based Studies

PURPOSE OF REVIEW

Exposure assessment efforts in population-based studies are increasingly incorporating measurements. The published literature was reviewed to identify the measurement sources and the approaches used to incorporate measurements into these efforts.

RECENT FINDINGS

The variety of occupations and industries in these studies made collecting participant-specific measurements impractical. Thus, the starting point was often the compilation of large databases of measurements from inspections, published literature, and other exposure surveys. These measurements usually represented multiple occupations, industries, and worksites, and spanned multiple decades. Measurements were used both qualitatively and quantitatively, dependent on the coverage and quality of the data. Increasingly, statistical models were used to derive job-, industry-, time period-, and other determinant-specific exposure concentrations. Quantitative measurement-based approaches are increasingly replacing expert judgment, which facilitates the development of quantitative exposure-response associations. Evaluations of potential biases in these measurement sources, and their representativeness of typical exposure situations, warrant additional examination.

Development of a source-exposure matrix for occupational exposure assessment of electromagnetic fields in the INTEROCC study

To estimate occupational exposures to electromagnetic fields (EMF) for the INTEROCC study, a database of source-based measurements extracted from published and unpublished literature resources had been previously constructed. The aim of the current work was to summarize these measurements into a source-exposure matrix (SEM), accounting for their quality and relevance. A novel methodology for combining available measurements was developed, based on order statistics and log-normal distribution characteristics. Arithmetic and geometric means, and estimates of variability and maximum exposure were calculated by EMF source, frequency band and dosimetry type. The mean estimates were weighted by our confidence in the pooled measurements. The SEM contains confidence-weighted mean and maximum estimates for 312 EMF exposure sources (from 0 Hz to 300 GHz). Operator position geometric mean electric field levels for radiofrequency (RF) sources ranged between 0.8 V/m (plasma etcher) and 320 V/m (RF sealer), while magnetic fields ranged from 0.02 A/m (speed radar) to 0.6 A/m (microwave heating). For extremely low frequency sources, electric fields ranged between 0.2 V/m (electric forklift) and 11,700 V/m (high-voltage transmission line-hotsticks), whereas magnetic fields ranged between 0.14 μT (visual display terminals) and 17 μT (tungsten inert gas welding). The methodology developed allowed the construction of the first EMF-SEM and may be used to summarize similar exposure data for other physical or chemical agents.

Contribution of job-exposure matrices for exposure assessment in occupational safety and health monitoring systems: application from the French national occupational disease surveillance and prevention network

OBJECTIVES

To detect new hazards ("signals"), occupational health monitoring systems mostly rest on the description of exposures in the jobs held and on reports by medical doctors; these are subject to declarative bias. Our study aims to assess whether job-exposure matrices (JEMs) could be useful tools for signal detection by improving exposure reporting.

METHODS

Using the French national occupational disease surveillance and prevention network (RNV3P) data from 2001 to 2011, we explored the associations between disease and exposure prevalence for 3 well-known pathology/exposure couples and for one debatable couple. We compared the associations measured when using physicians' reports or applying the JEMs, respectively, for these selected diseases and across non-selected RNV3P population or for cases with musculoskeletal disorders, used as two reference groups; the ratio of exposure prevalences according to the two sources of information were computed for each disease category.

RESULTS

Our population contained 58,188 subjects referred with pathologies related to work. Mean age at diagnosis was 45.8 years (95% CI 45.7; 45.9), and 57.2% were men. For experts, exposure ratios increase with knowledge on exposure causality. As expected, JEMs retrieved more exposed cases than experts (exposure ratios between 12 and 194), except for the couple silica/silicosis, but not for the MSD control group (ratio between 0.2 and 0.8).

CONCLUSIONS

JEMs enhanced the number of exposures possibly linked with some conditions, compared to experts' assessment, relative to the whole database or to a reference group; they are less likely to suffer from declarative bias than reports by occupational health professionals.

Evaluating predictors of lead exposure for activities disturbing materials painted with or containing lead using historic published data from U.S. workplaces

OBJECTIVES

We evaluated predictors of differences in published occupational lead concentrations for activities disturbing material painted with or containing lead in U.S. workplaces to aid historical exposure reconstruction.

METHODS

For the aforementioned tasks, 221 air and 113 blood lead summary results (1960-2010) were extracted from a previously developed database. Differences in the natural log-transformed geometric mean (GM) for year, industry, job, and other ancillary variables were evaluated in meta-regression models that weighted each summary result by its inverse variance and sample size.

RESULTS

Air and blood lead GMs declined 5%/year and 6%/year, respectively, in most industries. Exposure contrast in the GMs across the nine jobs and five industries was higher based on air versus blood concentrations. For welding activities, blood lead GMs were 1.7 times higher in worst-case versus non-worst case scenarios.

CONCLUSIONS

Job, industry, and time-specific exposure differences were identified; other determinants were too sparse or collinear to characterize. Am. J. Ind. Med. 60:189-197, 2017. © 2017 Wiley Periodicals, Inc.

Evaluating Exposure-Response Associations for Non-Hodgkin Lymphoma with Varying Methods of Assigning Cumulative Benzene Exposure in the Shanghai Women's Health Study

Objectives

To provide insight into the contributions of exposure measurements to job exposure matrices (JEMs), we examined the robustness of an association between occupational benzene exposure and non-Hodgkin lymphoma (NHL) to varying exposure assessment methods.

Methods

NHL risk was examined in a prospective population-based cohort of 73087 women in Shanghai. A mixed-effects model that combined a benzene JEM with >60000 short-term, area benzene inspection measurements was used to derive two sets of measurement-based benzene estimates: 'job/industry-specific' estimates (our presumed best approach) were derived from the model's fixed effects (year, JEM intensity rating) and random effects (occupation, industry); 'calibrated JEM' estimates were derived using only the fixed effects. 'Uncalibrated JEM' (using the ordinal JEM ratings) and exposure duration estimates were also calculated. Cumulative exposure for each subject was calculated for each approach based on varying exposure definitions defined using the JEM's probability ratings. We examined the agreement between the cumulative metrics and evaluated changes in the benzene-NHL associations.

Results

For our primary exposure definition, the job/industry-specific estimates were moderately to highly correlated with all other approaches (Pearson correlation 0.61-0.89; Spearman correlation > 0.99). All these metrics resulted in statistically significant exposure-response associations for NHL, with negligible gain in model fit from using measurement-based estimates. Using more sensitive or specific exposure definitions resulted in elevated but non-significant associations.

Conclusions

The robust associations observed here with varying benzene assessment methods provide support for a benzene-NHL association. While incorporating exposure measurements did not improve model fit, the measurements allowed us to derive quantitative exposure-response curves.

Developing a job-exposure matrix with exposure uncertainty from expert elicitation and data modeling

Job exposure matrices (JEMs) are tools used to classify exposures for job titles based on general job tasks in the absence of individual level data. However, exposure uncertainty due to variations in worker practices, job conditions, and the quality of data has never been quantified systematically in a JEM. We describe a methodology for creating a JEM which defines occupational exposures on a continuous scale and utilizes elicitation methods to quantify exposure uncertainty by assigning exposures probability distributions with parameters determined through expert involvement. Experts use their knowledge to develop mathematical models using related exposure surrogate data in the absence of available occupational level data and to adjust model output against other similar occupations. Formal expert elicitation methods provided a consistent, efficient process to incorporate expert judgment into a large, consensus-based JEM. A population-based electric shock JEM was created using these methods, allowing for transparent estimates of exposure.

SYN-JEM: A Quantitative Job-Exposure Matrix for Five Lung Carcinogens

OBJECTIVE

The use of measurement data in occupational exposure assessment allows more quantitative analyses of possible exposure-response relations. We describe a quantitative exposure assessment approach for five lung carcinogens (i.e. asbestos, chromium-VI, nickel, polycyclic aromatic hydrocarbons (by its proxy benzo(a)pyrene (BaP)) and respirable crystalline silica). A quantitative job-exposure matrix (JEM) was developed based on statistical modeling of large quantities of personal measurements.

METHODS

Empirical linear models were developed using personal occupational exposure measurements (n = 102306) from Europe and Canada, as well as auxiliary information like job (industry), year of sampling, region, an a priori exposure rating of each job (none, low, and high exposed), sampling and analytical methods, and sampling duration. The model outcomes were used to create a JEM with a quantitative estimate of the level of exposure by job, year, and region.

RESULTS

Decreasing time trends were observed for all agents between the 1970s and 2009, ranging from -1.2% per year for personal BaP and nickel exposures to -10.7% for asbestos (in the time period before an asbestos ban was implemented). Regional differences in exposure concentrations (adjusted for measured jobs, years of measurement, and sampling method and duration) varied by agent, ranging from a factor 3.3 for chromium-VI up to a factor 10.5 for asbestos.

CONCLUSION

We estimated time-, job-, and region-specific exposure levels for four (asbestos, chromium-VI, nickel, and RCS) out of five considered lung carcinogens. Through statistical modeling of large amounts of personal occupational exposure measurement data we were able to derive a quantitative JEM to be used in community-based studies.

Retrospective benzene exposure assessment for a multi-center case-cohort study of benzene-exposed workers in China

Quality of exposure assessment has been shown to be related to the ability to detect risk of lymphohematopoietic disorders in epidemiological investigations of benzene, especially at low levels of exposure. We set out to build a statistical model for reconstructing exposure levels for 2898 subjects from 501 factories that were part of a nested case-cohort study within the NCI-CAPM cohort of more than 110,000 workers. We used a hierarchical model to allow for clustering of measurements by factory, workshop, job, and date. To calibrate the model we used historical routine monitoring data. Measurements below the limit of detection were accommodated by constructing a censored data likelihood. Potential non-linear and industry-specific time-trends and predictor effects were incorporated using regression splines and random effects. A partial validation of predicted exposures in 2004/2005 was performed through comparison with full-shift measurements from an exposure survey in facilities that were still open. Median cumulative exposure to benzene at age 50 for subjects that ever held an exposed job (n=1175) was 509 mg/m(3) years. Direct comparison of model estimates with measured full-shift personal exposure in the 2004/2005 survey showed moderate correlation and a potential downward bias at low (<1 mg/m(3)) exposure estimates. The modeling framework enabled us to deal with the data complexities generally found in studies using historical exposure data in a comprehensive way and we therefore expect to be able to investigate effects at relatively low exposure levels.

Occupational Exposure to Benzene and Non-Hodgkin Lymphoma in a Population-Based Cohort: The Shanghai Women's Health Study

BACKGROUND

The association between benzene exposure and non-Hodgkin lymphoma (NHL) has been the subject of debate as a result of inconsistent epidemiologic evidence. An International Agency for Research on Cancer (IARC) working group evaluated benzene in 2009 and noted evidence for a positive association between benzene exposure and NHL risk.

OBJECTIVE

We evaluated the association between occupational benzene exposure and NHL among 73,087 women enrolled in the prospective population-based Shanghai Women's Health Study.

METHODS

Benzene exposure estimates were derived using a previously developed exposure assessment framework that combined ordinal job-exposure matrix intensity ratings with quantitative benzene exposure measurements from an inspection database of Shanghai factories collected between 1954 and 2000. Associations between benzene exposure metrics and NHL (n = 102 cases) were assessed using Cox proportional hazard models, with study follow-up occurring from December 1996 through December 2009.

RESULTS

Women ever exposed to benzene had a significantly higher risk of NHL [hazard ratio (HR) = 1.87, 95% CI: 1.19, 2.96]. Compared with unexposed women, significant trends in NHL risk were observed for increasing years of benzene exposure (p(trend) = 0.006) and increasing cumulative exposure levels (p(trend) = 0.005), with the highest duration and cumulative exposure tertiles having a significantly higher association with NHL (HR = 2.07, 95% CI: 1.07, 4.01 and HR = 2.16, 95% CI: 1.17, 3.98, respectively).

CONCLUSIONS

Our findings, using a population-based prospective cohort of women with diverse occupational histories, provide additional evidence that occupational exposure to benzene is associated with NHL risk.

A retrospective cohort study of cause-specific mortality and incidence of hematopoietic malignancies in Chinese benzene-exposed workers

Benzene exposure has been causally linked with acute myeloid leukemia (AML), but inconsistently associated with other hematopoietic, lymphoproliferative and related disorders (HLD) or solid tumors in humans. Many neoplasms have been described in experimental animals exposed to benzene. We used Poisson regression to estimate adjusted relative risks (RR) and the likelihood ratio statistic to derive confidence intervals for cause-specific mortality and HLD incidence in 73,789 benzene-exposed compared with 34,504 unexposed workers in a retrospective cohort study in 12 cities in China. Follow-up and outcome assessment was based on factory, medical and other records. Benzene-exposed workers experienced increased risks for all-cause mortality (RR = 1.1, 95% CI = 1.1, 1.2) due to excesses of all neoplasms (RR = 1.3, 95% CI = 1.2, 1.4), respiratory diseases (RR = 1.7, 95% CI = 1.2, 2.3) and diseases of blood forming organs (RR = ∞, 95% CI = 3.4, ∞). Lung cancer mortality was significantly elevated (RR = 1.5, 95% CI = 1.2, 1.9) with similar RRs for males and females, based on three-fold more cases than in our previous follow-up. Significantly elevated incidence of all myeloid disorders reflected excesses of myelodysplastic syndrome/acute myeloid leukemia (RR = 2.7, 95% CI = 1.2, 6.6) and chronic myeloid leukemia (RR = 2.5, 95% CI = 0.8, 11), and increases of all lymphoid disorders included excesses of non-Hodgkin lymphoma (RR = 3.9, 95%CI = 1.5, 13) and all lymphoid leukemia (RR = 5.4, 95%CI = 1.0, 99). The 28-year follow-up of Chinese benzene-exposed workers demonstrated increased risks of a broad range of myeloid and lymphoid neoplasms, lung cancer, and respiratory diseases and suggested possible associations with other malignant and non-malignant disorders.

Working environment and myeloproliferative neoplasm: A population-based case-control study following a cluster investigation

BACKGROUND

Occupational exposures, including those to polycyclic aromatic hydrocarbons (PAH), are suspected risk factors for myeloproliferative neoplasms (MPN).

METHODS

We investigated occupational exposures and MPN risk (54 cases and 472 controls) in a population-based case-control study in three rural Pennsylvania counties. Occupational histories, coded to SIC/SOC 1980, were linked to a previously created PAH job-exposure matrix. Odds ratios for industry (17 categories), occupation (26 categories), and PAH exposure were adjusted using logistic regression.

RESULTS

No industries or occupations were strongly or consistently associated with increased MPN risk. Analysis of employment duration found that being employed for 5 or more years in transportation, communications, and other public utilities was associated with MPN risk. There was no indication of an association with cumulative PAH exposure.

CONCLUSIONS

These few associations did not appear to have a common exposure. This exploratory study does not support the hypothesis that occupational exposure, including PAH, are strong risk factors for MPNs.

Lead exposure in US worksites: A literature review and development of an occupational lead exposure database from the published literature

BACKGROUND

Retrospective exposure assessment of occupational lead exposure in population-based studies requires historical exposure information from many occupations and industries.

METHODS

We reviewed published US exposure monitoring studies to identify lead measurement data. We developed an occupational lead exposure database from the 175 identified papers containing 1,111 sets of lead concentration summary statistics (21% area air, 47% personal air, 32% blood). We also extracted ancillary exposure-related information, including job, industry, task/location, year collected, sampling strategy, control measures in place, and sampling and analytical methods.

RESULTS

The measurements were published between 1940 and 2010 and represented 27 2-digit standardized industry classification codes. The majority of the measurements were related to lead-based paint work, joining or cutting metal using heat, primary and secondary metal manufacturing, and lead acid battery manufacturing.

CONCLUSIONS

This database can be used in future statistical analyses to characterize differences in lead exposure across time, jobs, and industries.

Occupational exposure to extremely low-frequency magnetic fields and electrical shocks and acute myeloid leukemia in four Nordic countries

OBJECTIVE

We studied the association between occupational exposure to extremely low-frequency magnetic fields (ELF-MF) and electrical shocks and acute myeloid leukemia (AML) in the Nordic Occupational Cancer cohort (NOCCA).

METHODS

We included 5,409 adult AML cases diagnosed between 1961 and 2005 in Finland, Iceland, Norway, and Sweden and 27,045 controls matched by age, sex, and country. Lifetime occupational ELF-MF exposure and risk of electrical shocks were assigned to jobs reported in the censuses using job-exposure matrices. We estimated hazard ratios (HRs) and 95 % confidence intervals (95 % CIs) using conditional logistic regression adjusted for concurrent occupational exposures relevant for AML risk (e.g., benzene, ionizing radiation). We conducted sensitivity analyses with different assumptions to assess the robustness of our results.

RESULTS

Approximately 40 % of the subjects were ever occupationally exposed to low levels and 7 % to high levels of ELF-MF, whereas 18 % were ever at low risk and 15 % at high risk of electrical shocks. We did not observe an association between occupational exposure to neither ELF-MF nor electrical shocks and AML. The HR was 0.88 (95 % CI 0.77-1.01) for subjects with high levels of ELF-MF exposure and 0.94 (95 % CI 0.85-1.05) for subjects with high risk of electrical shocks as compared to those with background-level exposure. Results remained materially unchanged in sensitivity analyses with different assumptions.

CONCLUSION

Our results do not support an association between occupational ELF-MF or electric shock exposure and AML.

Reliability and validity of expert assessment based on airborne and urinary measures of nickel and chromium exposure in the electroplating industry

The reliability and validity of six experts' exposure ratings were evaluated for 64 nickel-exposed and 72 chromium-exposed workers from six Shanghai electroplating plants based on airborne and urinary nickel and chromium measurements. Three industrial hygienists and three occupational physicians independently ranked the exposure intensity of each metal on an ordinal scale (1-4) for each worker's job in two rounds: the first round was based on responses to an occupational history questionnaire and the second round also included responses to an electroplating industry-specific questionnaire. The Spearman correlation (r(s)) was used to compare each rating's validity to its corresponding subject-specific arithmetic mean of four airborne or four urinary measurements. Reliability was moderately high (weighted kappa range=0.60-0.64). Validity was poor to moderate (r(s)=-0.37-0.46) for both airborne and urinary concentrations of both metals. For airborne nickel concentrations, validity differed by plant. For dichotomized metrics, sensitivity and specificity were higher based on urinary measurements (47-78%) than airborne measurements (16-50%). Few patterns were observed by metal, assessment round, or expert type. These results suggest that, for electroplating exposures, experts can achieve moderately high agreement and (reasonably) distinguish between low and high exposures when reviewing responses to in-depth questionnaires used in population-based case-control studies.

Evaluating temporal trends from occupational lead exposure data reported in the published literature using meta-regression

OBJECTIVES

The published literature provides useful exposure measurements that can aid retrospective exposure assessment efforts, but the analysis of this data is challenging as it is usually reported as means, ranges, and measures of variability. We used mixed-effects meta-analysis regression models, which are commonly used to summarize health risks from multiple studies, to predict temporal trends of blood and air lead concentrations in multiple US industries from the published data while accounting for within- and between-study variability in exposure.

METHODS

We extracted the geometric mean (GM), geometric standard deviation (GSD), and number of measurements from journal articles reporting blood and personal air measurements from US worksites. When not reported, we derived the GM and GSD from other summary measures. Only industries with measurements in ≥2 time points and spanning ≥10 years were included in our analyses. Meta-regression models were developed separately for each industry and sample type. Each model used the log-transformed GM as the dependent variable and calendar year as the independent variable. It also incorporated a random intercept that weighted each study by a combination of the between- and within-study variances. The within-study variances were calculated as the squared log-transformed GSD divided by the number of measurements. Maximum likelihood estimation was used to obtain the regression parameters and between-study variances.

RESULTS

The blood measurement models predicted statistically significant declining trends of 2-11% per year in 8 of the 13 industries. The air measurement models predicted a statistically significant declining trend (3% per year) in only one of the seven industries; an increasing trend (7% per year) was also observed for one industry. Of the five industries that met our inclusion criteria for both air and blood, the exposure declines per year tended to be slightly greater based on blood measurements than on air measurements.

CONCLUSIONS

Meta-analysis provides a useful tool for synthesizing occupational exposure data to examine exposure trends that can aid future retrospective exposure assessment. Data remained too sparse to account for other exposure predictors, such as job category or sampling strategy, but this limitation may be overcome by using additional data sources.

Historical occupational trichloroethylene air concentrations based on inspection measurements from Shanghai, China

PURPOSE

Trichloroethylene (TCE) is a carcinogen that has been linked to kidney cancer and possibly other cancer sites including non-Hodgkin lymphoma. Its use in China has increased since the early 1990s with China's growing metal, electronic, and telecommunications industries. We examined historical occupational TCE air concentration patterns in a database of TCE inspection measurements collected in Shanghai, China to identify temporal trends and broad contrasts among occupations and industries.

METHODS

Using a database of 932 short-term, area TCE air inspection measurements collected in Shanghai worksites from 1968 through 2000 (median year 1986), we developed mixed-effects models to evaluate job-, industry-, and time-specific TCE air concentrations.

RESULTS

Models of TCE air concentrations from Shanghai work sites predicted that exposures decreased 5-10% per year between 1968 and 2000. Measurements collected near launderers and dry cleaners had the highest predicted geometric means (GM for 1986 = 150-190 mg m(-3)). The majority (53%) of the measurements were collected in metal treatment jobs. In a model restricted to measurements in metal treatment jobs, predicted GMs for 1986 varied 35-fold across industries, from 11 mg m(-3) in 'other metal products/repair' industries to 390 mg m(-3) in 'ships/aircrafts' industries.

CONCLUSIONS

TCE workplace air concentrations appeared to have dropped over time in Shanghai, China between 1968 and 2000. Understanding differences in TCE concentrations across time, occupations, and industries may assist future epidemiologic studies in China.

An expert-based job exposure matrix for large scale epidemiologic studies of primary hip and knee osteoarthritis: the Lower Body JEM

BACKGROUND

When conducting large scale epidemiologic studies, it is a challenge to obtain quantitative exposure estimates, which do not rely on self-report where estimates may be influenced by symptoms and knowledge of disease status. In this study we developed a job exposure matrix (JEM) for use in population studies of the work-relatedness of hip and knee osteoarthritis.

METHODS

Based on all 2227 occupational titles in the Danish version of the International Standard Classification of Occupations (D-ISCO 88), we constructed 121 job groups comprising occupational titles with expected homogeneous exposure patterns in addition to a minimally exposed job group, which was not included in the JEM. The job groups were allocated the mean value of five experts' ratings of daily duration (hours/day) of standing/walking, kneeling/squatting, and whole-body vibration as well as total load lifted (kg/day), and frequency of lifting loads weighing ≥20 kg (times/day). Weighted kappa statistics were used to evaluate inter-rater agreement on rankings of the job groups for four of these exposures (whole-body vibration could not be evaluated due to few exposed job groups). Two external experts checked the face validity of the rankings of the mean values.

RESULTS

A JEM was constructed and English ISCO codes were provided where possible. The experts' ratings showed fair to moderate agreement with respect to rankings of the job groups (mean weighted kappa values between 0.36 and 0.49). The external experts agreed on 586 of the 605 rankings.

CONCLUSION

The Lower Body JEM based on experts' ratings was established. Experts agreed on rankings of the job groups, and rankings based on mean values were in accordance with the opinion of external experts.

Occupational determinants of cumulative lead exposure: analysis of bone lead among men in the VA normative aging study

OBJECTIVES

To examine the relation between occupation and cumulative lead exposure-assessed by measuring bone lead-in a community-dwelling population.

METHOD

We measured bone lead concentration with K-shell X-Ray Fluorescence in 1320 men in the Normative Aging Study. We categorized job titles into 14 broad US Census Bureau categories. We used ordinary least squares regression to estimate bone lead by job categories adjusted for other predictors.

RESULTS

Service workers, construction, and extractive craft workers and installation, maintenance, and repair craft workers had the highest bone lead concentrations. Including occupations significantly improved the overall model (P < 0.001) and reduced by 15% to 81% the association between bone lead and education categories.

CONCLUSION

Occupation significantly predicts cumulative lead exposure in a community-dwelling population and accounts for a large proportion of the association between education and bone lead.

Calibrating a population-based job-exposure matrix using inspection measurements to estimate historical occupational exposure to lead for a population-based cohort in Shanghai, China

The epidemiologic evidence for the carcinogenicity of lead is inconsistent and requires improved exposure assessment to estimate risk. We evaluated historical occupational lead exposure for a population-based cohort of women (n=74,942) by calibrating a job-exposure matrix (JEM) with lead fume (n=20,084) and lead dust (n=5383) measurements collected over four decades in Shanghai, China. Using mixed-effect models, we calibrated intensity JEM ratings to the measurements using fixed-effects terms for year and JEM rating. We developed job/industry-specific estimates from the random-effects terms for job and industry. The model estimates were applied to subjects' jobs when the JEM probability rating was high for either job or industry; remaining jobs were considered unexposed. The models predicted that exposure increased monotonically with JEM intensity rating and decreased 20-50-fold over time. The cumulative calibrated JEM estimates and job/industry-specific estimates were highly correlated (Pearson correlation=0.79-0.84). Overall, 5% of the person-years and 8% of the women were exposed to lead fume; 2% of the person-years and 4% of the women were exposed to lead dust. The most common lead-exposed jobs were manufacturing electronic equipment. These historical lead estimates should enhance our ability to detect associations between lead exposure and cancer risk in the future epidemiologic analyses.

Occupational exposure to trichloroethylene and perchloroethylene and the risk of lymphoma, liver, and kidney cancer in four Nordic countries

OBJECTIVES

Trichloroethylene (TCE) and Perchloroethylene (PER) are two chlorinated solvents that are applied widely as degreasers of metal parts, and in dry cleaning and other applications. In 2012, the International Agency for Research on Cancer classified TCE as carcinogenic to humans and PER as probably carcinogenic to humans. We explored exposure-response relations for TCE and PER and non-Hodgkin's lymphoma (NHL), multiple myeloma (MM), and cancers of the kidney and liver in the Nordic Occupational Cancer cohort.

METHODS

The cohort was set up by linking occupational information from censuses to national cancer registry data using personal identity codes in use in all Nordic countries. Country, time period, and job-specific exposure estimates were generated for TCE, PER and potentially confounding occupational exposures with a job-exposure matrix. A conditional logistic regression was conducted for exposure groups as well as for continuous cumulative exposure.

RESULTS

HRs for liver cancer, NHL and MM but not kidney cancer were slightly elevated in groups with high exposure to PER (compared to occupationally unexposed subjects). HRs for liver cancer and NHL also increased with increasing continuous exposure to PER. We did not observe evidence for an association between exposure to TCE and NHL, MM or liver and kidney cancer.

CONCLUSIONS

Although this study was subject to limitations related to the low prevalence of exposure to PER and TCE in the Nordic population and a limited exposure assessment strategy, we observed some evidence indicative of an excess risk of cancer of the liver and NHL in subjects exposed to PER.

Occupational benzene exposure and the risk of chronic myeloid leukemia: a meta-analysis of cohort studies incorporating study quality dimensions

OBJECTIVE

We documented previously that if study quality is accounted for, evidence from occupational cohort studies on benzene supports a possible association with some lymphoma subtypes, in particular multiple myeloma, and acute and chronic lymphocytic leukemia. Here, we extend these analyses to chronic myeloid leukemia (CML).

METHODS

Three strategies to assess study quality (stratification by the year-of-start of follow-up, stratification by the strength of the reported acute myeloid leukemia (AML) association, and stratification by the quality of benzene exposure assessment) were employed in a meta-analysis of occupational benzene exposure and CML. We hypothesized that stratification by these study quality dimensions would identify a subgroup of occupational cohort studies that is most informative for the evaluation of the possible association between benzene and CML.

RESULTS

The overall meta-relative risk (mRR) was non-significantly elevated (1.23; 95% confidence interval (CI): 0.93-1.63). The mRRs increased with increasing study quality for all dimensions with a significant elevation for studies with start of follow-up after 1970 (1.67; 95% CI: 1.02-2.74). The highest study quality stratum for AML significance and exposure quality showed an elevated but non-significant increased mRR (1.40; 95% CI: 0.86-2.27, and 1.68; 95% CI: 0.74-3.84, respectively).

CONCLUSIONS

Although limited by low statistical power, the current meta-analysis provides support for a possible association of occupational exposure to benzene and the risk of CML.

Sensitivity analyses of exposure estimates from a quantitative job-exposure matrix (SYN-JEM) for use in community-based studies

OBJECTIVES

We describe the elaboration and sensitivity analyses of a quantitative job-exposure matrix (SYN-JEM) for respirable crystalline silica (RCS). The aim was to gain insight into the robustness of the SYN-JEM RCS estimates based on critical decisions taken in the elaboration process.

METHODS

SYN-JEM for RCS exposure consists of three axes (job, region, and year) based on estimates derived from a previously developed statistical model. To elaborate SYN-JEM, several decisions were taken: i.e. the application of (i) a single time trend; (ii) region-specific adjustments in RCS exposure; and (iii) a prior job-specific exposure level (by the semi-quantitative DOM-JEM), with an override of 0 mg/m(3) for jobs a priori defined as non-exposed. Furthermore, we assumed that exposure levels reached a ceiling in 1960 and remained constant prior to this date. We applied SYN-JEM to the occupational histories of subjects from a large international pooled community-based case-control study. Cumulative exposure levels derived with SYN-JEM were compared with those from alternative models, described by Pearson correlation ((Rp)) and differences in unit of exposure (mg/m(3)-year). Alternative models concerned changes in application of job- and region-specific estimates and exposure ceiling, and omitting the a priori exposure ranking.

RESULTS

Cumulative exposure levels for the study subjects ranged from 0.01 to 60 mg/m(3)-years, with a median of 1.76 mg/m(3)-years. Exposure levels derived from SYN-JEM and alternative models were overall highly correlated (R(p) > 0.90), although somewhat lower when omitting the region estimate ((Rp) = 0.80) or not taking into account the assigned semi-quantitative exposure level (R(p) = 0.65). Modification of the time trend (i.e. exposure ceiling at 1950 or 1970, or assuming a decline before 1960) caused the largest changes in absolute exposure levels (26-33% difference), but without changing the relative ranking ((Rp) = 0.99).

CONCLUSIONS

Exposure estimates derived from SYN-JEM appeared to be plausible compared with (historical) levels described in the literature. Decisions taken in the development of SYN-JEM did not critically change the cumulative exposure levels. The influence of region-specific estimates needs to be explored in future risk analyses.