We describe an outbreak of sudden health problems in workers at a Danish grass seed plant after exposure to a particularly dusty lot of grass seeds. The seeds are called problematic seeds. The association between development of organic dust toxic syndrome (ODTS) and the handling of grass seeds causing exposure was assessed in a four-step model: (i) identification of exposure source, (ii) characterization of the emission of bioaerosols from the problematic and reference seeds, (iii) personal and stationary exposure measurement at the plant and (iv) repeated health examinations. The grass seeds were identified as the exposure source; the emissions of some bioaerosol components were up to 107 times higher from the problematic seeds than from reference seeds. Cleaning of the seeds was not enough to sufficiently reduce the high emission from the problematic seeds. Emission in terms of dust was 3.4 times as high from the problematic cleaned seeds as from cleaned reference seeds. The personal exposure reached 3 × 105 endotoxin units m−3, 1 × 106 colony-forming units (cfu) of thermophilic actinomycetes m−3, 8 × 105 cfu of Aspergillus fumigatus m−3 and 9 × 106 hyphal fragments m−3. Several workers working with the problematic seeds had symptoms consistent with ODTS. The most severe symptoms were found for the workers performing the tasks causing highest exposure. Respiratory airway protection proved efficient to avoid development of ODTS. Work with reference seeds did not cause workers to develop ODTS. Exposure was during work with the problematic seeds higher than suggested occupational exposure limits but lower than in studies where researchers for some minutes have repeated a single task expected to cause ODTS. In this study, many different bioaerosol components were measured during a whole working day. We cannot know, whether it is the combination of different bioaerosol components or a single component which is responsible for the development of ODTS. In conclusion, workers developed specific health symptoms due to the high bioaerosol exposure and were diagnosed with ODTS. Exposure to high concentrations of endotoxin, actinomycetes, fungi, hyphal fragments, β-glucan, and A. fumigatus occurred when working with a dusty lot of grass seed. Suspicion should be elicited by seeds stored without being properly dried and by seeds producing more dust than usually.

Objectives

The association between workplace bullying and psychotropic drug use is not well established. This study was aimed at exploring the association between workplace bullying, and its characteristics, and psychotropic drug use, and studying the mediating role of physical and mental health.

Methods

The study population consisted of a random sample of 3132 men and 4562 women of the working population in the South-East of France. Workplace bullying, evaluated using the validated instrument elaborated by Leymann, and psychotropic drug use, as well as covariates, were measured using a self-administered questionnaire. Covariates included age, marital status, presence of children, education, occupation, working hours, night work, physico-chemical exposures at work, self-reported health, and depressive symptoms. Statistical analysis was performed using logistic regression analysis, and was carried out separately for men and women.

Results

Workplace bullying was strongly associated with psychotropic drug use. Past exposure to bullying increased the risk for this use. The more frequent and the longer the exposure to bullying, the stronger the association with psychotropic drug use. Observing bullying on someone else at the workplace was associated with psychotropic drug use. Adjustment for covariates did not modify the results. Additional adjustment for self-reported health and depressive symptoms reduced the magnitude of the associations, especially for men.

Conclusion

The association between bullying and psychotropic drug use was found to be significant and strong, and was partially mediated by physical and mental health.

Exposure to respirable elemental carbon (REC), a component of diesel exhaust (DE), was assessed for an epidemiologic study investigating the association between DE and mortality, particularly from lung cancer, among miners at eight mining facilities from the date of dieselization (1947–1967) through 1997. To provide insight into the quality of the estimates for use in the epidemiologic analyses, several approaches were taken to evaluate the exposure assessment process and the quality of the estimates. An analysis of variance was conducted to evaluate the variability of 1998–2001 REC measurements within and between exposure groups of underground jobs. Estimates for the surface exposure groups were evaluated to determine if the arithmetic means (AMs) of the REC measurements increased with increased proximity to, or use of, diesel-powered equipment, which was the basis on which the surface groups were formed. Estimates of carbon monoxide (CO) (another component of DE) air concentrations in 1976–1977, derived from models developed to predict estimated historical exposures, were compared to 1976–1977 CO measurement data that had not been used in the model development. Alternative sets of estimates were developed to investigate the robustness of various model assumptions. These estimates were based on prediction models using: (i) REC medians rather AMs, (ii) a different CO:REC proportionality than a 1:1 relation, and (iii) 5-year averages of historical CO measurements rather than modeled historical CO measurements and DE-related determinants. The analysis of variance found that in three of the facilities, most of the between-group variability in the underground measurements was explained by the use of job titles. There was relatively little between-group variability in the other facilities. The estimated REC AMs for the surface exposure groups rose overall from 1 to 5 μg m−3 as proximity to, and use of, diesel equipment increased. The alternative estimates overall were highly correlated (∼0.9) with the primary set of estimates. The median of the relative differences between the 1976–1977 CO measurement means and the 1976–1977 estimates for six facilities was 29%. Comparison of estimated CO air concentrations from the facility-specific prediction models with historical CO measurement data found an overall agreement similar to that observed in other epidemiologic studies. Other evaluations of components of the exposure assessment process found moderate to excellent agreement. Thus, the overall evidence suggests that the estimates were likely accurate representations of historical personal exposure levels to DE and are useful for epidemiologic analyses.

Background:

Generic job-exposure matrices (JEMs) are often used in population-based epidemiologic studies to assess occupational risk factors when only the job and industry information of each subject is available. JEM ratings are often based on professional judgment, are usually ordinal or semi-quantitative, and often do not account for changes in exposure over time. We present an empirical Bayesian framework that combines ordinal subjective JEM ratings with benzene measurements. Our aim was to better discriminate between job, industry, and time differences in exposure levels compared to using a JEM alone.

Methods:

We combined 63 221 short-term area air measurements of benzene exposure (1954–2000) collected during routine health and safety inspections in Shanghai, China, with independently developed JEM intensity ratings for each job and industry using a mixed-effects model. The fixed-effects terms included the JEM intensity ratings for job and industry (both ordinal, 0–3) and a time trend that we incorporated as a b-spline. The random-effects terms included job (n = 33) and industry nested within job (n = 399). We predicted the benzene concentration in two ways: (i) a calibrated JEM estimate was calculated using the fixed-effects model parameters for calendar year and JEM intensity ratings; (ii) a job-/industry-specific estimate was calculated using the fixed-effects model parameters and the best linear unbiased predictors from the random effects for job and industry using an empirical Bayes estimation procedure. Finally, we applied the predicted benzene exposures to a prospective population-based cohort of women in Shanghai, China (n = 74 942).

Results:

Exposure levels were 13 times higher in 1965 than in 2000 and declined at a rate that varied from 4 to 15% per year from 1965 to 1985, followed by a small peak in the mid-1990s. The job-/industry-specific estimates had greater differences between exposure levels than the calibrated JEM estimates (97.5th percentile/2.5th percentile exposure level, BGR95B: 20.4 versus 3.0, respectively). The calibrated JEM and job-/industry-specific estimates were moderately correlated in any given year (Pearson correlation, rp = 0.58). We classified only those jobs and industries with a job or industry JEM exposure probability rating of 3 (>50% of workers exposed) as exposed. As a result, 14.8% of the subjects and 8.7% of the employed person-years in the study population were classified as benzene exposed. The cumulative exposure metrics based on the calibrated JEM and job-/industry-specific estimates were highly correlated (rp = 0.88).

Conclusions:

We provide a useful framework for combining quantitative exposure data with expert-based exposure ratings in population-based studies that maximized the information from both sources. Our framework calibrated the ratings to a concentration scale between ratings and across time and provided a mechanism to estimate exposure when a job/industry group reported by a subject was not represented in the exposure database. It also allowed the job/industry groups’ exposure levels to deviate from the pooled average for their respective JEM intensity ratings.

Objectives: To address questions surrounding noise-induced hearing loss (NIHL) from variable noise, we have been evaluating noise exposures and changes in hearing in a prospective cohort of construction workers (representing eight trades) and controls. In this paper, we develop and explore several long-term exposure estimates for cohort members.

Methods: We followed cohort members between 1999 and 2009 and interviewed them approximately annually to obtain a detailed work history for the previous subject-interval while also collecting tests of hearing sensitivity. Over the same period, we also collected a sample of full-shift average noise measurements and activity information. We used data from these two sources to develop various exposure estimates for each subject for specific subject intervals and for the duration of the study. These estimates included work duration, trade-mean (TM)-equivalent continuous exposure level (LEQ), task-based (TB) LEQ, a hybrid LEQ combining TB and subjective information, and an estimate of noise exposure ‘peakiness’.

Results: Of the 456 subjects enrolled in the study, 333 had at least 2 interviews and met several inclusion criteria related to hearing sensitivity. Depending on the metric used, between one-third and three-quarters of 1310 measured full-shift noise exposures exceeded permissible and recommended exposure limits. Hybrid and TB exposure estimates demonstrated much greater variability than TM estimates. Work duration and estimates of exposure peakiness showed poor agreement with average exposures, suggesting that these metrics evaluate different aspects of exposure and may have different predictive value for estimating NIHL.

Conclusions: Construction workers in the cohort had subject-interval and study-average exposures which present a substantial potential risk of NIHL. In a subsequent paper, we will use these estimates to evaluate the exposure–response relationship between noise and NIHL.

Objectives: To identify and quantify determinants of captan exposure among 74 private orchard pesticide applicators in the Agricultural Health Study (AHS). To adjust an algorithm used for estimating pesticide exposure intensity in the AHS based on these determinants and to compare the correlation of the adjusted and unadjusted algorithms with urinary captan metabolite levels.

Methods: External exposure metrics included personal air, hand rinse, and dermal patch samples collected from each applicator on 2 days in 2002–2003. A 24-h urine sample was also collected. Exposure determinants were identified for each external metric using multiple linear regression models via the NLMIXED procedure in SAS. The AHS algorithm was adjusted, consistent with the identified determinants. Mixed-effect models were used to evaluate the correlation between the adjusted and unadjusted algorithm and urinary captan metabolite levels.

Results: Consistent determinants of captan exposure were a measure of application size (kilogram of captan sprayed or application method), wearing chemical-resistant (CR) gloves and/or a coverall/suit, repairing spray equipment, and product formulation. Application by airblast was associated with a 4- to 5-fold increase in exposure as compared to hand spray. Exposure reduction to the hands, right thigh, and left forearm from wearing CR gloves averaged ∼80%, to the right and left thighs and right forearm from wearing a coverall/suit by ∼70%. Applicators using wettable powder formulations had significantly higher air, thigh, and forearm exposures than those using liquid formulations. Application method weights in the AHS algorithm were adjusted to nine for airblast and two for hand spray; protective equipment reduction factors were adjusted to 0.2 (CR gloves), 0.3 (coverall/suit), and 0.1 (both).

Conclusions: Adjustment of application method, CR glove, and coverall weights in the AHS algorithm based on our exposure determinant findings substantially improved the correlation between the AHS algorithm and urinary metabolite levels.

Background: In epidemiologic studies that rely on professional judgment to assess occupational exposures, the raters’ accurate assessment is vital to detect associations. We examined the influence of the type of questionnaire, type of industry, and type of rater on the raters’ ability to reliably and validly assess within-industry differences in exposure. Our aim was to identify areas where improvements in exposure assessment may be possible.

Methods: Subjects from three foundries (n = 72) and three textile plants (n = 74) in Shanghai, China, completed an occupational history (OH) and an industry-specific questionnaire (IQ). Six total dust measurements were collected per subject and were used to calculate a subject-specific measurement mean, which was used as the gold standard. Six raters independently ranked the intensity of each subject’s current job on an ordinal scale (1–4) based on the OH alone and on the OH and IQ together. Aggregate ratings were calculated for the group, for industrial hygienists, and for occupational physicians. We calculated intra-class correlation coefficients (ICCs) to evaluate the reliability of the raters. We calculated the correlation between the subject-specific measurement means and the ratings to evaluate the raters’ validity. Analyses were stratified by industry, type of questionnaire, and type of rater. We also examined the agreement between the ratings by exposure category, where the subject-specific measurement means were categorized into two and four categories.

Results: The reliability and validity measures were higher for the aggregate ratings than for the ratings from the individual raters. The group’s performance was maximized with three raters. Both the reliability and validity measures were higher for the foundry industry than for the textile industry. The ICCs were consistently lower in the OH/IQ round than in the OH round in both industries. In contrast, the correlations with the measurement means were higher in the OH/IQ round than in the OH round for the foundry industry (group rating, OH/IQ: Spearman rho = 0.77; OH: rho = 0.64). No pattern by questionnaire type was observed for the textile industry (group rating, Spearman rho = 0.50, both assessment rounds). For both industries, the agreement by exposure category was higher when the task was reduced to discriminating between two versus four exposure categories.

Conclusions: Assessments based on professional judgment may reduce misclassification by using two or three raters, by using questionnaires that systematically collect task information, and by defining intensity categories that are distinguishable by the raters. However, few studies have the resources to use multiple raters and these additional efforts may not be adequate for obtaining valid subjective ratings. Thus, improving exposure assessment approaches for studies that rely on professional judgment remain an important research need.

Objectives: US commercial airline pilots, like all flight crew, are at increased risk for specific cancers, but the relation of these outcomes to specific air cabin exposures is unclear. Flight time or block (airborne plus taxi) time often substitutes for assessment of exposure to cosmic radiation. Our objectives were to develop methods to estimate exposures to cosmic radiation and circadian disruption for a study of chromosome aberrations in pilots and to describe workplace exposures for these pilots.

Methods: Exposures were estimated for cosmic ionizing radiation and circadian disruption between August 1963 and March 2003 for 83 male pilots from a major US airline. Estimates were based on 523 387 individual flight segments in company records and pilot logbooks as well as summary records of hours flown from other sources. Exposure was estimated by calculation or imputation for all but 0.02% of the individual flight segments’ block time. Exposures were estimated from questionnaire data for a comparison group of 51 male university faculty.

Results: Pilots flew a median of 7126 flight segments and 14 959 block hours for 27.8 years. In the final study year, a hypothetical pilot incurred an estimated median effective dose of 1.92 mSv (absorbed dose, 0.85 mGy) from cosmic radiation and crossed 362 time zones. This study pilot was possibly exposed to a moderate or large solar particle event a median of 6 times or once every 3.7 years of work. Work at the study airline and military flying were the two highest sources of pilot exposure for all metrics. An index of work during the standard sleep interval (SSI travel) also suggested potential chronic sleep disturbance in some pilots. For study airline flights, median segment radiation doses, time zones crossed, and SSI travel increased markedly from the 1990s to 2003 (Ptrend < 0.0001). Dose metrics were moderately correlated with records-based duration metrics (Spearman’s r = 0.61–0.69).

Conclusions: The methods developed provided an exposure profile of this group of US airline pilots, many of whom have been exposed to increasing cosmic radiation and circadian disruption from the 1990s through 2003. This assessment is likely to decrease exposure misclassification in health studies.

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.

We have quantified vegetable growers’ exposure to fungal bioaerosol components including (1→3)-β-d-glucan (β-glucan), total fungal spores, and culturable fungal units. Furthermore, we have evaluated factors that might affect vegetable growers’ exposure to fungal bioaerosols and airborne dust. Investigated environments included greenhouses producing cucumbers and tomatoes, open fields producing cabbage, broccoli, and celery, and packing facilities. Measurements were performed at different times during the growth season and during execution of different work tasks. Bioaerosols were collected with personal and stationary filter samplers. Selected fungal species (Beauveria spp., Trichoderma spp., Penicillium olsonii, and Penicillium brevicompactum) were identified using different polymerase chain reaction-based methods and sequencing. We found that the factors (i) work task, (ii) crop, including growth stage of handled plant material, and (iii) open field versus greenhouse significantly affected the workers’ exposure to bioaerosols. Packing of vegetables and working in open fields caused significantly lower exposure to bioaerosols, e.g. mesophilic fungi and dust, than harvesting in greenhouses and clearing of senescent greenhouse plants. Also removing strings in cucumber greenhouses caused a lower exposure to bioaerosols than harvest of cucumbers while removal of old plants caused the highest exposure. In general, the exposure was higher in greenhouses than in open fields. The exposures to β-glucan during harvest and clearing of senescent greenhouse plants were very high (median values ranging between 50 and 1500 ng m−3) compared to exposures reported from other occupational environments. In conclusion, vegetable growers’ exposure to bioaerosols was related to the environment, in which they worked, the investigated work tasks, and the vegetable crop.

This report provides an overview of the exposure assessment process for an epidemiologic study that investigated mortality, with a special focus on lung cancer, associated with diesel exhaust (DE) exposure among miners. Details of several components are provided in four other reports. A major challenge for this study was the development of quantitative estimates of historical exposures to DE. There is no single standard method for assessing the totality of DE, so respirable elemental carbon (REC), a component of DE, was selected as the primary surrogate in this study. Air monitoring surveys at seven of the eight study mining facilities were conducted between 1998 and 2001 and provided reference personal REC exposure levels and measurements for other agents and DE components in the mining environment. (The eighth facility had closed permanently prior to the surveys.) Exposure estimates were developed for mining facility/department/job/year combinations. A hierarchical grouping strategy was developed for assigning exposure levels to underground jobs [based on job titles, on the amount of time spent in various areas of the underground mine, and on similar carbon monoxide (CO, another DE component) concentrations] and to surface jobs (based on the use of, or proximity to, diesel-powered equipment). Time trends in air concentrations for underground jobs were estimated from mining facility-specific prediction models using diesel equipment horsepower, total air flow rates exhausted from the underground mines, and, because there were no historical REC measurements, historical measurements of CO. Exposures to potentially confounding agents, i.e. respirable dust, silica, radon, asbestos, and non-diesel sources of polycyclic aromatic hydrocarbons, also were assessed. Accuracy and reliability of the estimated REC exposures levels were evaluated by comparison with several smaller datasets and by development of alternative time trend models. During 1998–2001, the average measured REC exposure level by facility ranged from 40 to 384 μg m−3 for the underground workers and from 2 to 6 μg m−3 for the surface workers. For one prevalent underground job, ‘miner operator’, the maximum annual REC exposure estimate by facility ranged up to 685% greater than the corresponding 1998–2001 value. A comparison of the historical CO estimates from the time trend models with 1976–1977 CO measurements not used in the modeling found an overall median relative difference of 29%. Other comparisons showed similar levels of agreement. The assessment process indicated large differences in REC exposure levels over time and across the underground operations. Method evaluations indicated that the final estimates were consistent with those from alternative time trend models and demonstrated moderate to high agreement with external data.

Diesel exhaust (DE) has been implicated as a potential lung carcinogen. However, the exact components of DE that might be involved have not been clearly identified. In the past, nitrogen oxides (NOx) and carbon oxides (COx) were measured most frequently to estimate DE, but since the 1990s, the most commonly accepted surrogate for DE has been elemental carbon (EC). We developed quantitative estimates of historical exposure levels of respirable elemental carbon (REC) for an epidemiologic study of mortality, particularly lung cancer, among diesel-exposed miners by back-extrapolating 1998–2001 REC exposure levels using historical measurements of carbon monoxide (CO). The choice of CO was based on the availability of historical measurement data. Here, we evaluated the relationship of REC with CO and other current and historical components of DE from side-by-side area measurements taken in underground operations of seven non-metal mining facilities. The Pearson correlation coefficient of the natural log-transformed (Ln)REC measurements with the Ln(CO) measurements was 0.4. The correlation of REC with the other gaseous, organic carbon (OC), and particulate measurements ranged from 0.3 to 0.8. Factor analyses indicated that the gaseous components, including CO, together with REC, loaded most strongly on a presumed ‘Diesel exhaust’ factor, while the OC and particulate agents loaded predominantly on other factors. In addition, the relationship between Ln(REC) and Ln(CO) was approximately linear over a wide range of REC concentrations. The fact that CO correlated with REC, loaded on the same factor, and increased linearly in log–log space supported the use of CO in estimating historical exposure levels to DE.

Background: Assessment of occupational pesticide exposures based on self-reported information can be challenging, particularly with immigrant farm worker populations for whom specialized methods are needed to address language and cultural barriers and account for limited literacy. An audio computer-assisted self-interview (A-CASI) survey instrument was developed to collect information about organophosphate (OP) and N-methyl-carbamate (CB) exposures and other personal characteristics among male agricultural pesticide handlers for an ongoing cholinesterase biomonitoring study in Washington State.

Objectives: To assess the feasibility of collecting data using the A-CASI instrument and evaluate reliability for a subset of survey items.

Methods: The survey consisted of 64 items administered in Spanish or English on a touch-screen tablet computer. Participants listened to digitally recorded questions on headphones and selected responses on the screen, most of which were displayed as images or icons to facilitate participation of low literacy respondents. From 2006–2008, a total of 195 participants completed the survey during the OP/CB application seasons on at least one occasion. Percent agreement and kappa coefficients were calculated to evaluate test–retest reliability for selected characteristics among 45 participants who completed the survey on two separate occasions within the same year.

Results: Almost all participants self-identified as Hispanic or Latino (98%), and 97% completed the survey in Spanish. Most participants completed the survey in a half-hour or less, with minimal assistance from on-site research staff. Analyses of test–retest reliability showed substantial agreement for most demographic, work history, and health characteristics and at least moderate agreement for most variables related to personal protective equipment use during pesticide applications.

Conclusions: This A-CASI survey instrument is a novel method that has been used successfully to collect information about OP/CB exposures and other personal characteristics among Spanish-speaking agricultural pesticide handlers.

Urinary 1,6-hexamethylene diamine (HDA) may serve as a biomarker for systemic exposure to 1,6-hexamethylene diisocyanate (HDI) in occupationally exposed populations. However, the quantitative relationships between dermal and inhalation exposure to HDI and urine HDA levels have not been established. We measured acid-hydrolyzed urine HDA levels along with dermal and breathing-zone levels of HDI in 48 automotive spray painters. These measurements were conducted over the course of an entire workday for up to three separate workdays that were spaced approximately 1 month apart. One urine sample was collected before the start of work with HDI-containing paints and subsequent samples were collected during the workday. HDA levels varied throughout the day and ranged from nondetectable to 65.9 μg l−1 with a geometric mean and geometric standard deviation of 0.10 μg l−1 ± 6.68. Dermal exposure and inhalation exposure levels, adjusted for the type of respirator worn, were both significant predictors of urine HDA levels in the linear mixed models. Creatinine was a significant covariate when used as an independent variable along with dermal and respirator-adjusted inhalation exposure. Consequently, exposure assessment models must account for the water content of a urine sample. These findings indicate that HDA exhibits a biphasic elimination pattern, with a half-life of 2.9 h for the fast elimination phase. Our results also indicate that urine HDA level is significantly associated with systemic HDI exposure through both the skin and the lungs. We conclude that urinary HDA may be used as a biomarker of exposure to HDI, but biological monitoring should be tailored to reliably capture the intermittent exposure pattern typical in this industry.

A low cost, battery-operated, portable, real-time aerosol analyzer is not available for monitoring diesel particulate matter (DPM) concentrations in underground mines. This study summarizes a field evaluation conducted at an underground limestone mine to evaluate the potential of the TSI AM 510 portable photometer (equipped with a Dorr-Oliver cyclone and 1.0-μm impactor) to qualitatively track time-weighted average mass and elemental, organic, and total carbon (TC) measurements associated with diesel emissions. The calibration factor corrected correlation coefficient (R2) between the underground TC and photometer measurements was 0.93. The main issues holding back the use of a photometer for real-time estimation of DPM in an underground mine are the removal of non-DPM-associated particulate matter from the aerosol stream using devices, such as a cyclone and/or impactor and calibration of the photometer to mine-specific aerosol.

Friction stir welding (FSW) is considered one of the most significant developments in joining technology over the last half century. Its industrial applications are growing steadily and so are the number of workers using this technology. To date, there are no reports on airborne exposures during FSW. The objective of this study was to investigate possible emissions of nanoscale (<100 nm) and fine (<1 μm) aerosols during FSW of two aluminum alloys in a laboratory setting and characterize their physicochemical composition. Several instruments measured size distributions (5 nm to 20 μm) with 1-s resolution, lung deposited surface areas, and PM2.5 concentrations at the source and at the breathing zone (BZ). A wide range aerosol sampling system positioned at the BZ collected integrated samples in 12 stages (2 nm to 20 μm) that were analyzed for several metals using inductively coupled plasma mass spectrometry. Airborne aerosol was directly collected onto several transmission electron microscope grids and the morphology and chemical composition of collected particles were characterized extensively. FSW generates high concentrations of ultrafine and submicrometer particles. The size distribution was bimodal, with maxima at ∼30 and ∼550 nm. The mean total particle number concentration at the 30 nm peak was relatively stable at ∼4.0 × 105 particles cm−3, whereas the arithmetic mean counts at the 550 nm peak varied between 1500 and 7200 particles cm−3, depending on the test conditions. The BZ concentrations were lower than the source concentrations by 10–100 times at their respective peak maxima and showed higher variability. The daylong average metal-specific concentrations were 2.0 (Zn), 1.4 (Al), and 0.24 (Fe) μg m−3; the estimated average peak concentrations were an order of magnitude higher. Potential for significant exposures to fine and ultrafine aerosols, particularly of Al, Fe, and Zn, during FSW may exist, especially in larger scale industrial operations.

Exposure to volatile organic compounds (VOCs) from bridge painting was measured in New York City and New Jersey during the summer and fall seasons from 2005 to 2007. The effect of painting activities (paint coating layer, confinement setup, and application method) and meteorological conditions (temperature, humidity, and wind speed) on solvent exposure to aromatic, ketone, ester, and alkane compounds were individually evaluated. Mixed-effect models were used to examine the combination effects of these factors on the air concentration of total VOCs as the individual compound groups were not present in all samples. Air concentration associated with spraying was not affected by meteorological conditions since spraying was done in a confined space, thus reducing their impact on solvent air concentration. The mixed models for brushing and rolling samples included two fixed factors, i.e. application method and temperature, and one random factor, i.e. sampling day. An independent dataset (daily air samples) was used to validate the mixed model constructed for brushing and rolling samples. The regression line of the predicted values and actual measurements had a slope of 1.32 ± 0.15 for daily brushing and rolling samples, with almost all points being within the 95% confidence bands. The constructed model provides practical approaches for estimating the solvent exposure from brushing and rolling activities among construction painters. An adjusted mean air concentration derived from the activity-specific spray samples was the best estimate for that painting application.

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.

Objectives: Aerosols generated during dental procedures have been reported to contain endotoxin as a result of bacterial contamination of dental unit water lines. This study investigated the determinants of airborne endotoxin exposure in dental healthcare settings.

Methods: The study population included dental personnel (n = 454) from five academic dental institutions in South Africa. Personal air samples (n = 413) in various dental jobs and water samples (n = 403) from dental handpieces and basin taps were collected. The chromogenic-1000 limulus amebocyte lysate assay was used to determine endotoxin levels. Exposure metrics were developed on the basis of individually measured exposures and average levels within each job category. Analysis of variance and multivariate linear regression models were constructed to ascertain the determinants of exposure in the dental group.

Results: There was a 2-fold variation in personal airborne endotoxin from the least exposed (administration) to the most exposed (laboratory) jobs (geometric mean levels: 2.38 versus 5.63 EU m−3). Three percent of personal samples were above DECOS recommended exposure limit (50 EU m−3). In the univariate linear models, the age of the dental units explained the most variability observed in the personal air samples (R2 = 0.20, P < 0.001), followed by the season of the year (R2 = 0.11, P < 0.001). Other variables such as institution and total number of dental units per institution also explained a modest degree of variability. A multivariate model explaining the greatest variability (adjusted R2 = 0.40, P < 0.001) included: the age of institution buildings, total number of dental units per institution, ambient temperature, ambient air velocity, endotoxin levels in water, job category (staff versus students), dental unit model type and age of dental unit.

Conclusions: Apart from job type, dental unit characteristics are important predictors of airborne endotoxin levels in this setting.

Quantification of amines in biological samples is important for evaluating occupational exposure to diisocyanates. In this study, we describe the quantification of 1,6-hexamethylene diamine (HDA) levels in hydrolyzed plasma of 46 spray painters applying 1,6-hexamethylene diisocyanate (HDI)-containing paint in vehicle repair shops collected during repeated visits to their workplace and their relationship with dermal and inhalation exposure to HDI monomer. HDA was detected in 76% of plasma samples, as heptafluorobutyryl derivatives, and the range of HDA concentrations was ≤0.02–0.92 μg l−1. After log-transformation of the data, the correlation between plasma HDA levels and HDI inhalation exposure measured on the same workday was low (N = 108, r = 0.22, P = 0.026) compared with the correlation between plasma HDA levels and inhalation exposure occurring ∼20 to 60 days before blood collection (N = 29, r = 0.57, P = 0.0014). The correlation between plasma HDA levels and HDI dermal exposure measured on the same workday, although statistically significant, was low (N = 108, r = 0.22, P = 0.040) while the correlation between HDA and dermal exposure occurring ∼20 to 60 days before blood collection was slightly improved (N = 29, r = 0.36, P = 0.053). We evaluated various workplace factors and controls (i.e. location, personal protective equipment use and paint booth type) as modifiers of plasma HDA levels. Workers using a downdraft-ventilated booth had significantly lower plasma HDA levels relative to semi-downdraft and crossdraft booth types (P = 0.0108); this trend was comparable to HDI inhalation and dermal exposure levels stratified by booth type. These findings indicate that HDA concentration in hydrolyzed plasma may be used as a biomarker of cumulative inhalation and dermal exposure to HDI and for investigating the effectiveness of exposure controls in the workplace.