Issues when modeling benzene, toluene, and xylene exposures using a literature database

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.

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.

Agreement between two methods for retrospective assessment of occupational exposure intensity to six chlorinated solvents: Data from The National Birth Defects Prevention Study

The wide variety of jobs encountered in population-based studies makes retrospective exposure assessment challenging in occupational epidemiology. In this analysis, two methods for estimating exposure intensity to chlorinated solvents are compared: rated (assigned by an expert rater) and modeled (assigned using statistical models). Estimates of rated and modeled intensities were compared for jobs held by mothers participating in the National Birth Defects Prevention Study with possible exposure to six chlorinated solvents: carbon tetrachloride, chloroform, methylene chloride, perchloroethylene, 1,1,1-trichloroethane, and trichloroethylene. For each possibly exposed job, an industrial hygienist assigned (1) an exposure intensity (rated intensity) and (2) determinants of exposure to be used in a statistical model of exposure intensity (modeled intensity). Of 12,326 reported jobs, between 31 (0.3%) and 746 (6%) jobs were rated as possibly exposed to each of the six solvents. Agreement between rated and modeled intensities was low overall (Spearman correlation coefficient range: -0.09 to 0.28; kappa range: -0.23 to 0.43). Although no air measurements were available to determine if rated or modeled estimates were more accurate, review of participants' job titles showed that modeled estimates were often unexpectedly high given the low-exposure tasks found in these jobs. Differences between the high-exposure jobs used to create the statistical models (obtained from air measurements in the published literature) and the low-exposure jobs in the actual study population is a potential explanation for the disagreement between the two methods. Investigators should be aware that statistical models estimating exposure intensity using existing data from one type of worker population might not be generalizable to all populations of workers.

Relative Contributions of Agricultural Drift, Para-Occupational, and Residential Use Exposure Pathways to House Dust Pesticide Concentrations: Meta-Regression of Published Data

BACKGROUND

Increased pesticide concentrations in house dust in agricultural areas have been attributed to several exposure pathways, including agricultural drift, para-occupational, and residential use.

OBJECTIVE

To guide future exposure assessment efforts, we quantified relative contributions of these pathways using meta-regression models of published data on dust pesticide concentrations.

METHODS

From studies in North American agricultural areas published from 1995 to 2015, we abstracted dust pesticide concentrations reported as summary statistics [e.g., geometric means (GM)]. We analyzed these data using mixed-effects meta-regression models that weighted each summary statistic by its inverse variance. Dependent variables were either the log-transformed GM (drift) or the log-transformed ratio of GMs from two groups (para-occupational, residential use).

RESULTS

For the drift pathway, predicted GMs decreased sharply and nonlinearly, with GMs 64% lower in homes 250 m versus 23 m from fields (interquartile range of published data) based on 52 statistics from seven studies. For the para-occupational pathway, GMs were 2.3 times higher [95% confidence interval (CI): 1.5, 3.3; 15 statistics, five studies] in homes of farmers who applied pesticides more recently or frequently versus less recently or frequently. For the residential use pathway, GMs were 1.3 (95% CI: 1.1, 1.4) and 1.5 (95% CI: 1.2, 1.9) times higher in treated versus untreated homes, when the probability that a pesticide was used for the pest treatment was 1-19% and ≥ 20%, respectively (88 statistics, five studies).

CONCLUSION

Our quantification of the relative contributions of pesticide exposure pathways in agricultural populations could improve exposure assessments in epidemiologic studies. The meta-regression models can be updated when additional data become available. Citation: Deziel NC, Beane Freeman LE, Graubard BI, Jones RR, Hoppin JA, Thomas K, Hines CJ, Blair A, Sandler DP, Chen H, Lubin JH, Andreotti G, Alavanja MC, Friesen MC. 2017. Relative contributions of agricultural drift, para-occupational, and residential use exposure pathways to house dust pesticide concentrations: meta-regression of published data. Environ Health Perspect 125:296-305; http://dx.doi.org/10.1289/EHP426.

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.

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.

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.

Developing estimates of frequency and intensity of exposure to three types of metalworking fluids in a population-based case-control study of bladder cancer

BACKGROUND

A systematic, transparent, and data-driven approach was developed to estimate frequency and intensity of exposure to straight, soluble, and synthetic/semi-synthetic metalworking fluids (MWFs) within a case-control study of bladder cancer in New England.

METHODS

We assessed frequency using individual-level information from job-specific questionnaires wherever possible, then derived and applied job group-level patterns to likely exposed jobs with less information. Intensity estimates were calculated using a statistical model developed from measurements and determinants extracted from the published literature.

RESULTS

For jobs with probabilities of exposure≥0.5, median frequencies were 8-10 hr/week, depending on MWF type. Median intensities for these jobs were 2.5, 2.1, and 1.0 mg/m3 for soluble, straight, and synthetic/semi-synthetic MWFs, respectively.

CONCLUSIONS

Compared to case-by-case assessment, these data-driven decision rules are transparent and reproducible and may result in less biased estimates. These rules can also aid future exposure assessments of MWFs in population-based studies.

Occupational exposure to silica in construction workers: a literature-based exposure database

We created an exposure database of respirable crystalline silica levels in the construction industry from the literature. We extracted silica and dust exposure levels in publications reporting silica exposure levels or quantitative evaluations of control effectiveness published in or after 1990. The database contains 6118 records (2858 of respirable crystalline silica) extracted from 115 sources, summarizing 11,845 measurements. Four hundred and eighty-eight records represent summarized exposure levels instead of individual values. For these records, the reported summary parameters were standardized into a geometric mean and a geometric standard deviation. Each record is associated with 80 characteristics, including information on trade, task, materials, tools, sampling strategy, analytical methods, and control measures. Although the database was constructed in French, 38 essential variables were standardized and translated into English. The data span the period 1974-2009, with 92% of the records corresponding to personal measurements. Thirteen standardized trades and 25 different standardized tasks are associated with at least five individual silica measurements. Trade-specific respirable crystalline silica geometric means vary from 0.01 (plumber) to 0.30 mg/m³ (tunnel construction skilled labor), while tasks vary from 0.01 (six categories, including sanding and electrical maintenance) to 1.59 mg/m³ (abrasive blasting). Despite limitations associated with the use of literature data, this database can be analyzed using meta-analytical and multivariate techniques and currently represents the most important source of exposure information about silica exposure in the construction industry. It is available on request to the research community.

Silica exposure during construction activities: statistical modeling of task-based measurements from the literature

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

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.

The Upper Midwest Health Study: industry and occupation of glioma cases and controls

BACKGROUND

Understanding glioma etiology requires determining which environmental factors are associated with glioma. Upper Midwest Health Study case-control participant work histories collected 1995-1998 were evaluated for occupational associations with glioma. "Exposures of interest" from our study protocol comprise our a priori hypotheses.

MATERIALS AND METHODS

Year-long or longer jobs for 1,973 participants were assigned Standard Occupational Classifications (SOC) and Standard Industrial Classifications (SIC). The analysis file includes 8,078 SIC- and SOC-coded jobs. For each individual, SAS 9.2 programs collated employment with identical SIC-SOC coding. Distributions of longest "total employment duration" (total years worked in jobs with identical industry and occupation codes, including multiple jobs, and non-consecutive jobs) were compared between cases and controls, using an industrial hygiene algorithm to group occupations.

RESULTS

Longest employment duration was calculated for 780 cases and 1,156 controls. More case than control longest total employment duration was in the "engineer, architect" occupational group [16 cases, 10 controls, odds ratio (OR) 2.50, adjusted for age group, sex, age and education, 95% confidence interval (CI) 1.12-5.60]. Employment as a food processing worker [mostly butchers and meat cutters] was of borderline significance (27 cases, 21 controls, adjusted OR: 1.78, CI: 0.99-3.18).

CONCLUSIONS

Among our exposures of interest work as engineers or as butchers and meat cutters was associated with increased glioma risk. Significant associations could be due to chance, because of multiple comparisons, but similar findings have been reported for other glioma studies. Our results suggest some possible associations but by themselves could not provide conclusive evidence.

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.

Association between maternal occupational exposure to organic solvents and congenital heart defects, National Birth Defects Prevention Study, 1997-2002

OBJECTIVE

To examine the relation between congenital heart defects (CHDs) in offspring and estimated maternal occupational exposure to chlorinated solvents, aromatic solvents and Stoddard solvent during the period from 1 month before conception through the first trimester.

METHODS

The study population included mothers of infants with simple isolated CHDs and mothers of control infants who delivered from 1997 through 2002 and participated in the National Birth Defects Prevention Study. Two methods to assess occupational solvent exposure were employed: an expert consensus-based approach and a literature-based approach. Multiple logistic regression was used to calculate adjusted ORs and 95% CIs for the association between solvent classes and CHDs.

RESULTS

2951 control mothers and 2047 CHD case mothers were included. Using the consensus-based approach, associations were observed for exposure to any solvent and any chlorinated solvent with perimembranous ventricular septal defects (OR 1.6, 95% CI 1.0 to 2.6 and OR 1.7, 95% CI 1.0 to 2.8, respectively). Using the literature-based approach, associations were observed for: any solvent exposure with aortic stenosis (OR 2.1, 95% CI 1.1 to 4.1) and Stoddard solvent exposure with d-transposition of the great arteries (OR 2.0, 95% CI 1.0 to 4.2), right ventricular outflow tract obstruction defects (OR 1.9, 95% CI 1.1 to 3.3) and pulmonary valve stenosis (OR 2.1, 95% CI 1.1 to 3.8).

CONCLUSIONS

The authors found evidence of associations between occupational exposure to solvents and several types of CHDs. These results should be interpreted in light of the potential for misclassification of exposure.

Estimation of particulate mass and manganese exposure levels among welders

BACKGROUND

Welders are frequently exposed to Manganese (Mn), which may increase the risk of neurological impairment. Historical exposure estimates for welding-exposed workers are needed for epidemiological studies evaluating the relationship between welding and neurological or other health outcomes. The objective of this study was to develop and validate a multivariate model to estimate quantitative levels of welding fume exposures based on welding particulate mass and Mn concentrations reported in the published literature.

METHODS

Articles that described welding particulate and Mn exposures during field welding activities were identified through a comprehensive literature search. Summary measures of exposure and related determinants such as year of sampling, welding process performed, type of ventilation used, degree of enclosure, base metal, and location of sampling filter were extracted from each article. The natural log of the reported arithmetic mean exposure level was used as the dependent variable in model building, while the independent variables included the exposure determinants. Cross-validation was performed to aid in model selection and to evaluate the generalizability of the models.

RESULTS

A total of 33 particulate and 27 Mn means were included in the regression analysis. The final model explained 76% of the variability in the mean exposures and included welding process and degree of enclosure as predictors. There was very little change in the explained variability and root mean squared error between the final model and its cross-validation model indicating the final model is robust given the available data.

CONCLUSIONS

This model may be improved with more detailed exposure determinants; however, the relatively large amount of variance explained by the final model along with the positive generalizability results of the cross-validation increases the confidence that the estimates derived from this model can be used for estimating welder exposures in absence of individual measurement data.

The role of exposure reconstruction in occupational human health risk assessment: current methods and a recommended framework

Exposure reconstruction for substances of interest to human health is a process that has been used, with various levels of sophistication, as far back as the 1930s. The importance of robust and high-quality exposure reconstruction has been recognized by many researchers. It has been noted that misclassification of reconstructed exposures is relatively common and can result in potentially significant effects on the conclusions of a human health risk assessment or epidemiology study. In this analysis, a review of the key exposure reconstruction approaches described in over 400 papers in the peer-reviewed literature is presented. These approaches have been critically evaluated and classified according to quantitative, semiquantitative, and qualitative approaches. Our analysis indicates that much can still be done to improve the overall quality and consistency of exposure reconstructions and that a systematic framework would help to standardize the exposure reconstruction process in the future. The seven recommended steps in the exposure reconstruction process include identifying the goals of the reconstruction, organizing and ranking the available data, identifying key data gaps, selecting the best information sources and methodology for the reconstruction, incorporating probabilistic methods into the reconstruction, conducting an uncertainty analysis, and validating the results of the reconstruction. Influential emerging techniques, such as Bayesian data analysis, are highlighted. Important issues that will likely influence the conduct of exposure reconstruction into the future include improving statistical analysis methods, addressing the issue of chemical mixtures, evaluating aggregate exposures, and ensuring transparency with respect to variability and uncertainty in the reconstruction effort.

Statistical modeling of occupational chlorinated solvent exposures for case-control studies using a literature-based database

OBJECTIVES

Occupational exposure assessment for population-based case-control studies is challenging due to the wide variety of industries and occupations encountered by study participants. We developed and evaluated statistical models to estimate the intensity of exposure to three chlorinated solvents-methylene chloride, 1,1,1-trichloroethane, and trichloroethylene-using a database of air measurement data and associated exposure determinants.

METHODS

A measurement database was developed after an extensive review of the published industrial hygiene literature. The database of nearly 3000 measurements or summary measurements included sample size, measurement characteristics (year, duration, and type), and several potential exposure determinants associated with the measurements: mechanism of release (e.g. evaporation), process condition, temperature, usage rate, type of ventilation, location, presence of a confined space, and proximity to the source. The natural log-transformed measurement levels in the exposure database were modeled as a function of the measurement characteristics and exposure determinants using maximum likelihood methods. Assuming a single lognormal distribution of the measurements, an arithmetic mean exposure intensity level was estimated for each unique combination of exposure determinants and decade.

RESULTS

The proportions of variability in the measurement data explained by the modeled measurement characteristics and exposure determinants were 36, 38, and 54% for methylene chloride, 1,1,1-trichloroethane, and trichloroethylene, respectively. Model parameter estimates for the exposure determinants were in the anticipated direction. Exposure intensity estimates were plausible and exhibited internal consistency, but the ability to evaluate validity was limited.

CONCLUSIONS

These prediction models can be used to estimate chlorinated solvent exposure intensity for jobs reported by population-based case-control study participants that have sufficiently detailed information regarding the exposure determinants.

A comprehensive review of the literature on exposure to metalworking fluids

An extensive literature review was conducted of studies with exposure measurements to metalworking fluids (MWFs). A database of 155 arithmetic means based on 9379 aerosol measurements from published studies was compiled. Weighted arithmetic means (WAMs) and their variance calculated across studies were summarized based on decade (prior to 1970s through 2000s), industry (auto, auto parts, small job shops, and others), operation (grinding and machining), and fluid type (straight, soluble, synthetic, and semisynthetic). Total mass and total extractable mass measurements that were simultaneously collected were compared. Average concentrations by size fractions and mass median aerodynamic diameters (MMADs) were also analyzed. Analysis of the WAMs indicated a reduction in exposure levels over time regardless of industry or type of operation or fluid, with mean levels prior to the 1970s of 5.4 mg/m(3), which dropped to 2.5 mg/m(3) in the 1970s, to 1.2 mg/m(3) in the 1980s, and to 0.5 mg/m(3) in the 1990s. No further reduction was seen in the 2000s. A comparison by industry, operation, and fluid type found no consistent patterns in the measurement results. The percent extractable mass in the total aerosol samples varied by fluid type, with an average 84% in straight fluids, 58% in synthetic fluids, 56% in soluble fluids, and 42% in the semisynthetic fluids. Exposure means from the thoracic fraction (0.3-0.5 mg/m(3)) were slightly less than those for total aerosol for both the 1990s and 2000s, the only decades for which thoracic data were available. Respirable means did not change from the 1980s to the 2000s (generally about 0.2-0.3 mg/m(3)). The MMADs of the MWF aerosols averaged 4-6 microm. These measurement data indicate a clear reduction of exposure levels over time. They will be used for the retrospective assessment of exposure levels to MWFs in a population-based, case-control study of bladder cancer.

Occupational exposure to diesel engine exhaust: a literature review

Diesel exhaust (DE) is classified as a probable human carcinogen. Aims were to describe the major occupational uses of diesel engines and give an overview of personal DE exposure levels and determinants of exposure as reported in the published literature. Measurements representative of personal DE exposure were abstracted from the literature for the following agents: elemental carbon (EC), particulate matter (PM), carbon monoxide (CO), nitrogen oxide (NO), and nitrogen dioxide (NO(2)). Information on determinants of exposure was abstracted. In total, 3528 EC, 4166 PM, 581 CO, 322 NO, and 1404 NO(2) measurements were abstracted. From the 10,001 measurements, 32% represented exposure from on-road vehicles and 68% from off-road vehicles (30% mining, 15% railroad, and 22% others). Highest levels were reported for enclosed underground work sites in which heavy equipment is used: mining, mine maintenance, and construction (EC: 27-658 microg/m(3)). Intermediate exposure levels were generally reported for above-ground (semi-) enclosed areas in which smaller equipment was run: mechanics in a shop, emergency workers in fire stations, distribution workers at a dock, and workers loading/unloading inside a ferry (generally: EC<50 microg/m(3)). Lowest levels were reported for enclosed areas separated from the source, such as drivers and train crew, or outside, such as surface mining, parking attendants, vehicle testers, utility service workers, surface construction and airline ground personnel (EC<25 microg/m(3)). The other agents showed a similar pattern. Determinants of exposure reported for enclosed situations were ventilation and exhaust after treatment devices. Reported DE exposure levels were highest for underground mining and construction, intermediate for working in above-ground (semi-) enclosed areas and lowest for working outside or separated from the source. The presented data can be used as a basis for assessing occupational exposure in population-based epidemiological studies and guide future exposure assessment efforts for industrial hygiene and epidemiological studies.

Determinants of exposure to metalworking fluid aerosols: a literature review and analysis of reported measurements

An extensive literature review of published metalworking fluid (MWF) aerosol measurement data was conducted to identify the major determinants that may affect exposure to aerosol fractions (total or inhalable, thoracic and respirable) and mass median diameters (MMDs). The identification of determinants was conducted through published studies and analysis of published measurement levels. For the latter, weighted arithmetic means (WAMs) by number of measurements were calculated and compared using analysis of variance and t-tests. The literature review found that the major factors affecting aerosol exposure levels were, primarily, decade, type of industry, operation and fluid and engineering control measures. Our analysis of total aerosol levels found a significant decline in measured levels from an average of 5.36 mg m(-3) prior to the 1970s and 2.52 mg m(-3) in the 1970s to 1.21 mg m(-3) in the 1980s, 0.50 mg m(-3) in the 1990s and 0.55 mg m(-3) in the 2000s. Significant declines from the 1990s to the 2000s also were found in thoracic fraction levels (0.48 versus 0.40 mg m(-3)), but not for the respirable fraction. The WAMs for the auto (1.47 mg m(-3)) and auto parts manufacturing industry (1.83 mg m(-3)) were significantly higher than that for small-job machine shops (0.68 mg m(-3)). In addition, a significant difference in the thoracic WAM was found between the automotive industry (0.46 mg m(-3)) and small-job machine shops (0.32 mg m(-3)). Operation type, in particular, grinding, was a significant factor affecting the total aerosol fraction [grinding operations (1.75 mg m(-3)) versus other machining (0.95 mg m(-3))], but the levels associated with these operations were not statistically different for either the thoracic or the respirable fractions. Across all decades, the total aerosol fraction for straight oils (1.49 mg m(-3)) was higher than for other fluid types (soluble = 1.08 mg m(-3), synthetic = 0.52 mg m(-3) and semisynthetic = 0.50 mg m(-3)). Fluid type was also found to be partly associated with differences in the respirable fraction level. We found that the total aerosols were measured by a variety of sampling media, devices and analytical methods. This diversity of approaches makes interpretation of the study results difficult. In conclusion, both the literature review and the measurement data analyzed found that decade and type of industry, operation and fluid were important determinants of total aerosol exposure. Industry type and fluid type were associated with differences in exposure to the thoracic and respirable fraction levels, respectively.