Annals Of Work Exposures and Health最新文献

Diesel engine exhaust (DEE) is carcinogenic and potentially hazardous for those working in close proximity to diesel-powered machines. This study characterizes workplace exposure to DEE and its associated particulate matter (PM) during outdoor construction activities. We sampled at 4 construction sites in the Copenhagen metropolitan area. We used portable constant-flow pumps and quartz-fiber filters to quantify personal exposure to elemental carbon (EC), and used real-time instruments to collect activity-based information about particle number and size distribution, as well as black carbon (BC) concentration. Full-shift measurements of EC concentration ranged from < 0.3 to 6.4 µg/m3. Geometric mean (GM) EC exposure was highest for ground workers (3.4 µg/m3 EC; geometric standard deviation, GSD = 1.3), followed by drilling rig operators (2.6 µg/m3 EC; GSD = 1.4). Exposure for non-drilling-rig machine operators (1.2 µg/m3 EC; GSD = 2.9) did not differ significantly from background (0.9 µg/m3 EC; GSD = 1.7). The maximum 15-min moving average concentration of BC was 17 µg/m3, and the highest recorded peak concentration was 44 µg/m3. In numbers, the particle size distributions were dominated by ultrafine particles ascribed to DEE and occasional welding activities at the sites. The average total particle number concentrations (PNCs) measured in near-field and far-field positions across all worksites were 10,600 (GSD = 3.0) and 6,000 (GSD = 2.8)/cm3, respectively. Sites with active drilling rigs saw significantly higher average total PNCs at their near-field stations (13,600, 32,000, and 9,700/cm3; GSD = 2.4, 3.4, and 2.4) than sites without (4,700/cm3; GSD = 1.6). Overall, the DEE exposures at these outdoor construction sites were below current occupational exposure limits for EC (10 µg/m3 in Denmark; 50 µg/m3 in the European Union), but extended durations of exposure to the observed DEE levels may still be a health risk.

Construction framers who cut and install steel studs as part of their daily tasks are exposed to hazardous noise levels during their work shift in large part due to the power saws they use to cut steel studs. This investigation characterized the sound pressure levels of power saws used to cut steel studs on active construction sites. Further, the length of time it took to cut various studs on a construction site was investigated to understand worker exposure times to saw noise. In general, power saws used on the study sites to cut steel studs had a mean A-weighted equivalent continuous sound pressure level (LAeq) of 107.2 dB and a C-weighted peak sound pressure level (LCpeak) of 120.1 dB. Three of the saws-the chopsaw, the cut-off saw, and the grinder-had similar noise levels, whereas the cordless circular saw had higher noise levels. It took an average of 13.2 s to cut each stud, and workers in the study used power saws to cut steel studs for an average of 371.5 s per day. This average exposure time at the average recorded sound pressure levels (SPLs) suggests these saws can increase the risk of occupational noise-induced hearing loss, according to National Institute for Occupational Safety and Health (NIOSH) recommendations.

Workplace exposure is an important source of ill health. The use of wearable sensors and sensing technologies may help improve and maintain worker health, safety, and wellbeing. Input from workers should inform the integration of these sensors into workplaces. We developed an online survey to understand the acceptability of wearable sensor technologies for occupational health and safety (OSH) management. The survey was disseminated to members of OSH-related organizations, mainly in the United Kingdom and the Netherlands. There were 158 respondents, with over half (n = 91, 58%) reporting current use of wearable sensors, including physical hazards (n = 57, 36%), air quality (n = 53, 34%), and location tracking (n = 36, 23%), although this prevalence likely also captures traditional monitoring equipment. There were no clear distinctions in wearable sensor use between the reported demographic and occupational characteristics, with the exception that hygienists were more likely than non-hygienists (e.g. safety professionals) to use wearable sensors (66% versus 34%). Overall, there was an interest in how sensors can help OSH professionals understand patterns of exposure and improve exposure management practices. Some wariness was expressed primarily around environmental and physical constraints, the quality of the data, and privacy concerns. This survey identified a need to better identify occupational situations that would benefit from wearable sensors and to evaluate existing devices that could be used for occupational hygiene. Further, this work underscores the importance of clearly defining "sensor" according to the occupational setting and context.

Protective clothing standards, such as test methods published by ASTM International, play an integral role in ensuring the performance of personal protective equipment. The standard tests are not without limitations and are periodically reviewed and often updated. Some tests may not be reflective of in-use conditions. A new test cell was designed using sanitary fixtures to evaluate the effect of glove stretch on barrier performance using fluorescein solution as the challenge agent for enhanced visualization and fluorometer detection. Domed-shaped and flat screens were developed to permit and limit glove stretch within the test cell. The barrier performance of glove swatches was evaluated for both stretched and unstretched states. Latex, nitrile, and vinyl glove models of various thicknesses were evaluated. The tests were conducted following pressure and time parameters specified in ASTM F903, ASTM F1670, and ASTM F1671. Fluorescein solution movement, which may occur through penetration, was measured using a fluorometer. Glove stretch caused a reduction in glove thickness ranging from 16% to 40%. Overall, 21 sample failures were found (16.7%; n = 126) regardless of test condition. Nitrile gloves provided better barrier efficacy with the lowest failure rates (2.38%; 1 failure out of 42) compared to latex (19.4%; 7 failures out of 36) and vinyl gloves (27.1%; 13 failures out of 48). Differences in failure rates between stretched and unstretched gloves were insignificant; however, the latex material showed a 2.5 times increase in failures when stretched compared to unstretched. The new test apparatus was able to differentiate between the barrier performance of different glove materials. The use of a domed screen allowed the gloves to stretch, a condition that better represents the state of gloves when in use. Analysis of samples collected from the glove surface opposite to the exposure may provide a way to assess chemical permeation in addition to penetration.

A series of experiments in stationary and moving passenger rail cars were conducted to measure removal rates of particles in the size ranges of SARS-CoV-2 viral aerosols and the air changes per hour provided by existing and modified air handling systems. Such methods for exposure assessments are customarily based on mechanistic models derived from physical laws of particle movement that are deterministic and do not account for measurement errors inherent in data collection. The resulting analysis compromises on reliably learning about mechanistic factors such as ventilation rates, aerosol generation rates, and filtration efficiencies from field measurements. This manuscript develops a Bayesian state-space modeling framework that synthesizes information from the mechanistic system as well as the field data. We derive a stochastic model from finite difference approximations of differential equations explaining particle concentrations. Our inferential framework trains the mechanistic system using the field measurements from the chamber experiments and delivers reliable estimates of the underlying physical process with fully model-based uncertainty quantification. Our application falls within the realm of the Bayesian "melding" of mechanistic and statistical models and is of significant relevance to environmental hygienists and public health researchers working on assessing the performance of aerosol removal rates for rail car fleets.

In Europe, respiratory protective devices must be certified before they can be marketed. Among the parameters of interest, inward leakage (IL) characterizes the tightness between the face seal and the face, to verify that the device is well-designed. European standard EN 13274-1 (2001) and International Organization for Standardization (ISO) standard ISO 16900-1 (2019) specify that IL should be measured using sodium chloride (NaCl) aerosol or sulfur hexafluoride (SF6) gas. For reusable masks made of nonporous materials, both test agents are considered equally acceptable. However, the few studies that have compared IL values measured with various aerosols and gases have come to divergent conclusions. This work then aimed to measure IL with the test agents recommended by the standards to determine whether they are really equivalent. Since krypton (Kr) is an interesting candidate for replacing SF6 in standard tests, IL was assessed with SF6 and Kr simultaneously, and with NaCl aerosol using various calculation methods. Tests were carried out on 5 models of full-face masks donned on a headform connected to a breathing machine simulating 3 sinusoidal breathing rates of various intensities. The respirator fit on the headform was evaluated using a controlled negative pressure method to determine a manikin fit factor. Four scenarios were then tested to represent very poor, bad, good, and excellent fit. Gas concentration was measured using a mass spectrometer, and IL was calculated for SF6 and Kr. A combination of 3 devices allowed the determination of the number-based concentration of particles with diameters between 20 nm and 2 µm, and IL was calculated for each of the 33 channels, as well as using a cumulative number concentration. In addition, to comply with standards, a conversion was carried out to calculate IL using a cumulative mass concentration. The results of this work evidenced that the IL values measured with NaCl were systematically lower than those determined with gases. IL was also shown to vary with particle size, with a maximum value exceeding that calculated with cumulative concentrations (in number or mass). As part of the revision of the standards, protocols for measuring inward leakage should be redefined. On the one hand, acceptability thresholds should be re-evaluated according to the nature of the test agent (gas or aerosol), as it is clear that the 2 options do not give the same results for a given configuration. On the other hand, the aerosol leakage measurement protocol needs to be reworked to enable the measurement of a well-defined, robust, and reproducible inward leakage value.

Internationally, respirable crystalline silica (RCS) occupational exposure limits (OELs) are being reassessed and, in some jurisdictions, lowered, putting pressure on the capabilities of the analytical techniques used to achieve robust analyses and reliable detection limits. In preparation of a lower OEL, options for lowering the limit of detection (LoD) for RCS analysis have been assessed. Using a Direct-on-Filter X-Ray Diffraction (XRD) analysis under reduced scan speeds in combination with low-noise RCS sampling filters, an LoD of 0.25 µg/filter and a limit of quantification (LoQ) of 0.82 µg/filter can be achieved. Both limits would translate in an LoD of 0.24 µg/m3 and LoQ of 0.78 µg/m3 when sampling respirable dust for 8 h at 2.2 L/min, providing a technical solution to monitor exposures at the proposed OEL of 0.025 mg/m3 (25 µg /m3) and below, with general sampling conditions as typically applied in Australia. This is the first report showing that the OEL of 0.025 mg/m3 (25 µg /m3) is measurable by one of the standardized, direct-on-filter XRD methods.

The COVID-19 pandemic has disproportionately affected workers in certain industries and occupations, and the workplace can be a high-risk setting for SARS-CoV-2 transmission. In this study, we measured SARS-CoV-2 antibody prevalence and identified work-related risk factors in a population primarily working at industrial livestock operations. We used a multiplex salivary SARS-CoV-2 IgG assay to determine infection-induced antibody prevalence among 236 adult (≥18 yr) North Carolina residents between February 2021 and August 2022. We used the National Institute for Occupational Safety and Health Industry and Occupation Computerized Coding System (NIOCCS) to classify employed participants' industry. Most participants (55%, 95% confidence interval [CI] 49% to 62%) were infection-induced IgG positive, including 71% (95% CI 60% to 83%) of animal slaughtering and processing industry workers, 1.5 to 4.3 times North Carolina general population infection-induced seroprevalence estimates during overlapping time periods. Considering self-reported diagnostic test positivity and vaccination history in addition to antibodies, the proportion of participants with evidence of prior infection increased slightly to 61% (95% CI 55% to 67%), including 75% (95% CI 64% to 87%) of animal slaughtering and processing workers. Participants with more than 1000 compared to 10 or fewer coworkers at their jobsite had higher odds of prior infection (adjusted odds ratio 4.5, 95% CI 1.0 to 21.0). This study contributes evidence of the severe and disproportionate impacts of COVID-19 on animal slaughtering and processing workers and workers in large congregate settings.

Background: In studies of occupational health, longitudinal environmental exposure, and biomonitoring data are often subject to right skewing and left censoring, in which measurements fall below the limit of detection (LOD). To address right-skewed data, it is common practice to log-transform the data and model the geometric mean, assuming a log-normal distribution. However, if the transformed data do not follow a known distribution, modeling the mean of exposure may result in bias and reduce efficiency. In addition, when examining longitudinal data, it is possible that certain covariates may vary over time.

Objective: To develop predictive quantile regression models to resolve the issues of left censoring and time-dependent covariates and to quantitatively evaluate if previous and current covariates can predict current and/or future exposure levels.

Methods: To address these gaps, we suggested incorporating different substitution approaches into quantile regression and utilizing a method for selecting a working type of time dependency for covariates.

Results: In a simulation study, we demonstrated that, under different types of time-dependent covariates, the approach of multiple random value imputation outperformed the other approaches. We also applied our methods to a carbon nanotube and nanofiber exposure study. The dependent variables are the left-censored mass of elemental carbon at both the respirable and inhalable aerosol size fractions. In this study, we identified some potential time-dependent covariates with respect to worker-level determinants and job tasks.

Conclusion: Time dependency for covariates is rarely accounted for when analyzing longitudinal environmental exposure and biomonitoring data with values less than the LOD through predictive modeling. Mistreating the time-dependency as time-independency will lead to an efficiency loss of regression parameter estimation. Therefore, we addressed time-varying covariates in longitudinal exposure and biomonitoring data with left-censored measurements and illustrated an entire conditional distribution through different quantiles.