Development of a quantitative North and Central European job exposure matrix for wood dust

Wood dust is an established carcinogen also linked to several non malignant respiratory disorders. A major limitation in research on wood dust and its health effects is the lack of (historical) quantitative estimates of occupational exposure for use in general population-based case-control or cohort studies. The present study aimed to develop a multinational quantitative Job Exposure Matrix (JEM) for wood dust exposure using exposure data from several Northern and Central European countries. For this, an occupational exposure database containing 12653 personal wood dust measurements collected between 1978 and 2007 in Denmark, Finland, France, The Netherlands, Norway, and the United Kingdom (UK) was established. Measurement data were adjusted for differences in inhalable dust sampling efficiency resulting from the use of different dust samplers and analysed using linear mixed effect regression with job codes (ISCO-88) and country treated as random effects. Fixed effects were the year of measurement, the expert assessment of exposure intensity (no, low, and high exposure) for every ISCO-88 job code from an existing wood dust JEM and sampling duration. The results of the models suggest that wood dust exposure has declined annually by approximately 8%. Substantial differences in exposure levels between countries were observed with the highest levels in the United Kingdom and the lowest in Denmark and Norway, albeit with similar job rankings across countries. The jobs with the highest predicted exposure are floor layers and tile setters, wood-products machine operators, and building construction labourers with geometric mean levels for the year 1997 between 1.7 and 1.9 mg/m3. The predicted exposure estimates by the model are compared with the results of wood dust measurement data reported in the literature. The model predicted estimates for full-shift exposures were used to develop a time-dependent quantitative JEM for exposure to wood dust that can be used to estimate exposure for participants of general population studies in Northern European countries on the health effects from occupational exposure to wood dust.

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.

Estimating Historical Exposure to Respirable Crystalline Silica in the Mining Industry in Ontario, Canada Using a Newly Developed Exposure Database

OBJECTIVES

To use the recently developed Ontario Mining Exposure Database (OMED) to describe historical silica exposure in the Ontario metal mining industry and identify predictors of historical silica exposure.

METHODS

Personal respirable crystalline silica (RCS) data for metal mines were extracted from OMED and included both individual and summary measures, where multiple exposure measurements (n > 1) were aggregated and entered as a single exposure value (n = 1). Data were stratified by sample location (underground/surface) for analysis. Monte Carlo simulation was used to simulate individual measures from the summary measures. A fixed effects multiple linear regression model was used to assess the effects of commodity (ore mined), sample year, source of exposure data, and occupational group on RCS concentration. Parameter estimates (β), standard errors, and 95% upper and lower confidence intervals were reported.

RESULTS

The OMED contained 12 995 silica measurements. After limiting to RCS measurements in metal mines, and measures with sufficient information for analysis, 2883 RCS measurements collected from 1974 to 1991 remained, including 2816 individual and 67 summary measurements. In total, 321 individual RCS measurements were simulated from the 67 summary measures. The analysis database contained 2771 (12% simulated) underground measurements and 366 surface measurements (0% simulated). In the underground group, an overall geometric mean (GM) of 0.05 [geometric standard deviation (GSD) 3.09] mg m-3 was estimated with a 6% annual decrease over time. In this group, the commodity with the highest average RCS level was zinc mines (GM = 0.07 mg m-3) and the lowest was iron mines (GM = 0.01 mg m-3). In the surface group, an overall GM of 0.05 (GSD 3.70) mg m-3 was estimated with an 8% decreased over time. In this group, the commodity with the highest average RCS level was gold mines (GM = 0.07 mg m-3) and the lowest was zinc mines (GM = 0.03 mg m-3). In both groups, company collected data had lower estimated RCS compared with regulator collected data.

CONCLUSIONS

Historical RCS levels decreased over time. Mean measurements exceeded the American Conference of Governmental Industrial Hygienists current health-based threshold limit value (0.025 mg m-3). The main predictors of exposure were commodity, source of exposure data, and sample year. However, low R2 and high GSD values suggest additional predictors of RCS exposures in Ontario's metal mines exist that were unavailable in OMED.

Descriptive analysis and comparison of two French occupational exposure databases: COLCHIC and SCOLA

BACKGROUND

Several countries have built databases of occupational hygiene measurements. In France, COLCHIC and SCOLA co-exist, started in 1987 and 2007, respectively.

METHODS

A descriptive comparison of the content of the two databases was carried out during the period 1987-2012, including variables, workplaces and agents, as well as exposure levels.

RESULTS

COLCHIC and SCOLA contain, respectively, 841,682 (670 chemicals) and 152,486 records (70). They cover similar industries and occupations, and contain the same ancillary information. Across 17 common agents with >500 samples, the ratio of the median concentration in COLCHIC to the median concentration in SCOLA was 3.45 [1.03-14.3] during 2007-2012. This pattern remained when stratified by industry, task, and occupation, but was attenuated when restricted to similar sampling duration.

CONCLUSIONS

COLCHIC and SCOLA represent a considerable source of information, but result from different purposes (prevention, regulatory). Potential differences due to strategies should evaluated when interpreting data from these databases.

A Source-based Measurement Database for Occupational Exposure Assessment of Electromagnetic Fields in the INTEROCC Study: A Literature Review Approach

INTRODUCTION

To date, occupational exposure assessment of electromagnetic fields (EMF) has relied on occupation-based measurements and exposure estimates. However, misclassification due to between-worker variability remains an unsolved challenge. A source-based approach, supported by detailed subject data on determinants of exposure, may allow for a more individualized exposure assessment. Detailed information on the use of occupational sources of exposure to EMF was collected as part of the INTERPHONE-INTEROCC study. To support a source-based exposure assessment effort within this study, this work aimed to construct a measurement database for the occupational sources of EMF exposure identified, assembling available measurements from the scientific literature.

METHODS

First, a comprehensive literature search was performed for published and unpublished documents containing exposure measurements for the EMF sources identified, a priori as well as from answers of study subjects. Then, the measurements identified were assessed for quality and relevance to the study objectives. Finally, the measurements selected and complementary information were compiled into an Occupational Exposure Measurement Database (OEMD).

RESULTS

Currently, the OEMD contains 1624 sets of measurements (>3000 entries) for 285 sources of EMF exposure, organized by frequency band (0 Hz to 300 GHz) and dosimetry type. Ninety-five documents were selected from the literature (almost 35% of them are unpublished technical reports), containing measurements which were considered informative and valid for our purpose. Measurement data and complementary information collected from these documents came from 16 different countries and cover the time period between 1974 and 2013.

CONCLUSION

We have constructed a database with measurements and complementary information for the most common sources of exposure to EMF in the workplace, based on the responses to the INTERPHONE-INTEROCC study questionnaire. This database covers the entire EMF frequency range and represents the most comprehensive resource of information on occupational EMF exposure. It is available at www.crealradiation.com/index.php/en/databases.

Exposed! Or not? The diminishing record of workplace exposure in Canada

The Canadian Workplace Exposure Database (CWED) is the first of its kind in Canada. It was originally developed in 2008 by the Canadian Carcinogen Exposure project (CAREX Canada) to assist in estimating worker exposures to carcinogens across the country.Following the CWED's establishment, all Canadian federal and provincial agencies responsible for administering occupational health and safety regulation were surveyed to obtain a clearer picture of the quantity and quality of regulatory exposure data available. This revealed troubling reductions in exposure measurement collection, retention, and centralization by these agencies in recent years.Such trends will limit access to workplace exposure measurements for federal and provincial regulatory agencies as well as health researchers. Workplace exposure databases are used around the world for a variety of important purposes, such as identifying hazardous workplaces and workers at risk, assessing temporal-spatial trends, setting priorities for prevention, and informing epidemiological research.Efforts are underway to preserve historical data and promote prospective collection, however future success of the CWED will require collaboration and long-term vision on the part of those responsible for collecting workplace exposure measurements in Canada.