Comparison of formaldehyde exposure levels in two multi-industry occupational exposure databanks using multimodel inference

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.

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.

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.

The Australian Work Exposures Study: Prevalence of Occupational Exposure to Formaldehyde

INTRODUCTION

The aims of this study were to produce a population-based estimate of the prevalence of work-related exposure to formaldehyde, to identify the main circumstances of exposure and to describe the use of workplace control measures designed to decrease those exposures.

METHODS

The analysis used data from the Australian Workplace Exposures Study, a nationwide telephone survey, which investigated the current prevalence and exposure circumstances of work-related exposure to 38 known or suspected carcinogens, including formaldehyde, among Australian workers aged 18-65 years. Using the web-based tool OccIDEAS, semi-quantitative information was collected about exposures in the current job held by the respondent. Questions were addressed primarily at tasks undertaken rather than about self-reported exposures.

RESULTS

Of the 4993 included respondents, 124 (2.5%) were identified as probably being exposed to formaldehyde in the course of their work [extrapolated to 2.6% of the Australian working population-265 000 (95% confidence interval 221 000-316 000) workers]. Most (87.1%) were male. About half worked in technical and trades occupations. In terms of industry, about half worked in the construction industry. The main circumstances of exposure were working with particle board or plywood typically through carpentry work, building maintenance, or sanding prior to painting; with the more common of other exposures circumstances being firefighters involved in fighting fires, fire overhaul, and clean-up or back-burning; and health workers using formaldehyde when sterilizing equipment or in a pathology laboratory setting. The use of control measures was inconsistent.

CONCLUSION

Workers are exposed to formaldehyde in many different occupational circumstances. Information on the exposure circumstances can be used to support decisions on appropriate priorities for intervention and control of occupational exposure to formaldehyde, and estimates of burden of cancer arising from occupational exposure to formaldehyde.

The Australian Work Exposures Study: Occupational Exposure to Lead and Lead Compounds

INTRODUCTION

The aims of this study were to produce a population-based estimate of the prevalence of work-related exposure to lead and its compounds, to identify the main circumstances of exposures, and to collect information on the use of workplace control measures designed to decrease those exposures.

METHODS

Data came from the Australian Workplace Exposures Study, a nationwide telephone survey which investigated the current prevalence and circumstances of work-related exposure to 38 known or suspected carcinogens, including lead, among Australian workers aged 18-65 years. Using the web-based tool, OccIDEAS, semi-quantitative information was collected about exposures in the current job held by the respondent. Questions were addressed primarily at tasks undertaken rather than about self-reported exposures.

RESULTS

A total of 307 (6.1%) of the 4993 included respondents were identified as probably being exposed to lead in the course of their work. Of these, almost all (96%) were male; about half worked in trades and technician-related occupations, and about half worked in the construction industry. The main tasks associated with probable exposures were, in decreasing order: soldering; sanding and burning off paint while painting old houses, ships, or bridges; plumbing work; cleaning up or sifting through the remains of a fire; radiator-repair work; machining metals or alloys containing lead; mining; welding leaded steel; and working at or using indoor firing ranges. Where information on control measures was available, inconsistent use was reported. Applied to the Australian working population, approximately 6.3% [95% confidence interval (CI) = 5.6-7.0] of all workers (i.e. 631000, 95% CI 566000-704000 workers) were estimated to have probable occupational exposure to lead.

CONCLUSIONS

Lead remains an important exposure in many different occupational circumstances in Australia and probably other developed countries. This information can be used to support decisions on priorities for intervention and control of occupational exposure to lead and estimates of burden of cancer arising from occupational exposure to lead.

Retrospective Exposure Assessment for Occupational Disease of an Individual Worker Using an Exposure Database and Trend Analysis

This article outlines a hierarchy of data required for retrospective exposure assessment for occupational disease of an individual worker. It then outlines in a step-wise manner how trend analysis using a relatively large exposure database can be used to estimate such exposure. The process of how a large database containing exposure measurements can be prepared for estimating historic occupational exposures of individual workers in relation to their illnesses is described. The asbestos subset from a large government collected air monitoring database called Medical Surveillance (MESU) was selected to illustrate the cleaning and analysis processes. After unidentifiable values were removed, the cleaned dataset was examined for possible sources of variability such as changes to sampling protocol. Limit of detection (LOD) values were substituted for all non-detectable values prior to the calculation of descriptive statistic using left censored analysis methods (i.e., maximum likelihood estimation (MLE), Kaplan Meier (KM), and simple substitution). The JoinPoint Regression Program was used to perform trend analysis and calculate an annual percentage change (APC) value for the available sampling period. An asbestos case study is presented to illustrate how the APC can then be combined with more recent job and/or process specific exposure data to estimate historic levels. The MESU asbestos dataset contained 1,610 samples from 1984-1995. An average of 17% of this data was left censored. The asbestos air sampling methods in Ontario changed around 1990. LOD values of 0.06 f/cc and 0.02 f/cc were substituted for LOD values pre- and post-1990, respectively. The annual mean fiber levels for the MLE method were an average of 44% lower than KM and substitution methods. The corresponding APC for MLE method was -6.5% and -7.7% for KM and simple substitution. The findings of this paper illustrate how the temporal trend of an exposure databases can be used to efficiently estimate historic contaminant levels in the presence of limited historical information.

Workplace measurements by the US Occupational Safety and Health Administration since 1979: descriptive analysis and potential uses for exposure assessment

BACKGROUND

Inspectors from the US Occupational Safety and Health Administration (OSHA) have been collecting industrial hygiene samples since 1972 to verify compliance with Permissible Exposure Limits. Starting in 1979, these measurements were computerized into the Integrated Management Information System (IMIS). In 2010, a dataset of over 1 million personal sample results analysed at OSHA's central laboratory in Salt Lake City [Chemical Exposure Health Data (CEHD)], only partially overlapping the IMIS database, was placed into public domain via the internet. We undertook this study to inform potential users about the relationship between this newly available OSHA data and IMIS and to offer insight about the opportunities and challenges associated with the use of OSHA measurement data for occupational exposure assessment.

METHODS

We conducted a literature review of previous uses of IMIS in occupational health research and performed a descriptive analysis of the data recently made available and compared them to the IMIS database for lead, the most frequently sampled agent.

RESULTS

The literature review yielded 29 studies reporting use of IMIS data, but none using the CEHD data. Most studies focused on a single contaminant, with silica and lead being most frequently analysed. Sixteen studies addressed potential bias in IMIS, mostly by examining the association between exposure levels and ancillary information. Although no biases of appreciable magnitude were consistently reported across studies and agents, these assessments may have been obscured by selective under-reporting of non-detectable measurements. The CEHD data comprised 1 450 836 records from 1984 to 2009, not counting analytical blanks and erroneous records. Seventy eight agents with >1000 personal samples yielded 1 037 367 records. Unlike IMIS, which contain administrative information (company size, job description), ancillary information in the CEHD data is mostly analytical. When the IMIS and CEHD measurements of lead were merged, 23 033 (39.2%) records were in common to both IMIS and CEHD datasets, 10 681 (18.2%) records were only in IMIS, and 25 012 (42.6%) records were only in the CEHD database. While IMIS-only records represent data analysed in other laboratories, CEHD-only records suggest partial reporting of sampling results by OSHA inspectors into IMIS. For lead, the percentage of non-detects in the CEHD-only data was 71% compared to 42% and 46% in the both-IMIS-CEHD and IMIS-only datasets, respectively, suggesting differential under-reporting of non-detects in IMIS.

CONCLUSIONS

IMIS and the CEHD datasets represent the biggest source of multi-industry exposure data in the USA and should be considered as a valuable source of information for occupational exposure assessment. The lack of empirical data on biases, adequate interpretation of non-detects in OSHA data, complicated by suspected differential under-reporting, remain the principal challenges to the valid estimation of average exposure conditions. We advocate additional comparisons between IMIS and CEHD data and discuss analytical strategies that may play a key role in meeting these challenges.

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

A quantitative determinants-of-exposure analysis of respirable crystalline silica (RCS) levels in the construction industry was performed using a database compiled from an extensive literature review. Statistical models were developed to predict work-shift exposure levels by trade. Monte Carlo simulation was used to recreate exposures derived from summarized measurements which were combined with single measurements for analysis. Modeling was performed using Tobit models within a multimodel inference framework, with year, sampling duration, type of environment, project purpose, project type, sampling strategy and use of exposure controls as potential predictors. 1346 RCS measurements were included in the analysis, of which 318 were non-detects and 228 were simulated from summary statistics. The model containing all the variables explained 22% of total variability. Apart from trade, sampling duration, year and strategy were the most influential predictors of RCS levels. The use of exposure controls was associated with an average decrease of 19% in exposure levels compared to none, and increased concentrations were found for industrial, demolition and renovation projects. Predicted geometric means for year 1999 were the highest for drilling rig operators (0.238 mg m(-3)) and tunnel construction workers (0.224 mg m(-3)), while the estimated exceedance fraction of the ACGIH TLV by trade ranged from 47% to 91%. The predicted geometric means in this study indicated important overexposure compared to the TLV. However, the low proportion of variability explained by the models suggests that the construction trade is only a moderate predictor of work-shift exposure levels. The impact of the different tasks performed during a work shift should also be assessed to provide better management and control of RCS exposure levels on construction sites.