Journal of Occupational Medicine and Toxicology最新文献

Background: Patient handling injuries (PHIs) are among the leading causes of workplace injuries among healthcare workers. High-reliability organization (HRO) programs aim to prevent detrimental errors and improve organizational safety. This study examined the relationship between HRO implementation and direct care staffs' PHI rates.

Methods: This cross-sectional study used data from 124 Veterans Health Administration (VHA) facilities. HRO implementation was measured by program duration and HRO climate. Negative binomial regression models were used to examine the relationship between HRO implementation and PHI rates, progressively adjusting for staff-to-patient ratio, facility type, size, and complexity.

Results: A longer HRO program duration was associated with higher HRO climate (p = .01), but HRO implementation (duration and climate) was not associated with PHI rates. Higher staff-to-patient ratio was associated with lower PHI rates (p < .05). Ambulatory care service facilities had lower PHI rates than acute care facilities (β = -0.824, p = .03). The most clinically complex facilities (level 1a) had higher PHI rates than the level 3 least complex facilities (β = 0.806, p = .04).

Conclusion: While this study did not observe a significant relationship between HRO implementation and PHI rate among direct care staff, the study findings highlight the importance of adequate staffing for injury prevention and the need to consider facility type and complexity in PHI prevention efforts. Future research is needed to explore the impact of HRO on worker safety, using more sophisticated measures to assess HRO programs and climate.

Introduction: Human exposure to nanoparticles is increasing due to their widespread use in industry and consumer products. The unique physicochemical properties of these materials lead to novel toxicological effects, primarily driven by the induction of oxidative stress and inflammation, establishing nanotoxicology as a critical public health field. This scoping review synthesizes the current evidence from preclinical models to provide an overview of the mechanisms and end-organ toxicities associated with exposure to metal-containing nanoparticles.

Methods: A scoping review was conducted following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. The PubMed database was searched on August 11, 2024, using a detailed search string focused on nanoparticle inhalation, human toxicity, and metals. Inclusion criteria specified English-language articles reporting on in vivo or in vitro human tissue studies, while studies that were animal-only, reviews, or non-toxicological modeling were excluded.

Results: The initial search yielded 946 records; ultimately, 136 articles were analyzed based on the inclusion and exclusion criteria. A thematic analysis of the included studies reveals that research is heavily concentrated on the respiratory, gastrointestinal, and immune systems, with titanium dioxide and zinc oxide being the most frequently investigated nanoparticles. Across all organ systems, the principal mechanisms of toxicity were consistently identified as the generation of reactive oxygen species and the initiation of inflammatory cascades. Key organ-specific findings include disruption of the respiratory epithelial barrier, nanoparticle translocation to the cardiovascular and nervous systems, associated mitochondrial damage and protein aggregation, and dose-dependent genotoxicity, including DNA strand breaks and micronuclei formation.

Discussion: The toxicity of metal-containing nanoparticles is highly dependent on their specific physicochemical characteristics, including size, chemical composition, and agglomeration state. While in vitro models have been invaluable for elucidating these mechanistic pathways, significant limitations remain, including a lack of standardization and challenges in translating findings to clinical outcomes in humans. Future research should focus on validating advanced, reproducible models, investigating complex mixed exposures, and identifying sensitive biomarkers to better inform risk assessment and protect public health.

Clinical trial number: Not applicable.

Background: Workplace absenteeism represents a significant challenge for organizations and occupational health practitioners, with substantial implications for productivity, healthcare costs, and employee well-being. Traditional approaches to absenteeism management remain largely reactive, highlighting the need for predictive models that enable proactive interventions.

Objective: To develop and validate machine learning models for predicting workplace absenteeism patterns and identifying risk factors associated with prolonged absence in a pilot study framework, thereby demonstrating feasibility for evidence-based occupational health interventions.

Methods: This pilot study employed machine learning algorithms on a publicly available workplace absenteeism dataset from a Brazilian company (2007-2010) obtained from the UCI Machine Learning Repository. The dataset comprised 740 instances with 19 variables including demographic characteristics, clinical indicators (BMI, ICD-10 coded absence reasons), and occupational factors. Random Forest and Gradient Boosting algorithms were implemented for both classification of prolonged absences and regression of absence duration. Statistical outliers (> 30 h, 3.8% of cases) were excluded to focus on typical absence patterns.

Results: The developed models demonstrated feasibility for workplace absenteeism prediction within this pilot framework. The Random Forest classification model achieved 84% accuracy (AUC = 0.89) for distinguishing between typical and prolonged absences. For duration prediction of typical absences (≤ 30 h), the Random Forest regression model yielded R² = 0.13, RMSE = 3.93 h, and MAE = 2.37 h. Key predictors included absence reason (ICD-10 classification), body mass index, and workload metrics, with notable interactions between workload intensity and specific absence categories.

Conclusions: This pilot study demonstrates the feasibility of machine learning approaches for occupational health management by enabling identification of employees at risk for prolonged absenteeism. While showing promise for supporting personalized health interventions and resource allocation, implementation requires external validation across multiple organizations and careful consideration of ethical implications regarding employee privacy and algorithmic fairness.

Background: Zirconium (Zr) compounds have increasingly been used as alternatives to traditional toxic metals in industrial processes, yet comprehensive exposure and biomonitoring data are scarce. This study aimed to assess occupational exposure to zirconium and co-metals (cobalt, nickel, arsenic) in Taiwanese manufacturing industries through integrated environmental and biological monitoring.

Methods: A cross-sectional investigation was conducted in eight metal surface treatment plants, with biomonitoring conducted among ten exposed workers. Personal and area air sampling were analyzed for zirconium and co-metals using inductively coupled plasma-optical emission spectrometry (ICP-OES); urine and blood samples were analyzed for internal exposure biomarkers (urinary zirconium, urinary/blood cobalt, urinary nickel, blood arsenic) by inductively coupled plasma-mass spectrometry (ICP-MS). Pulmonary effects were assessed using spirometry.

Results: Airborne Zr concentrations varied substantially by process, with the highest levels observed in shelling and slurry mixing operations (up to 22.55 µg/m³). Urinary Zr was undetectable in all participants (< 0.2 µg/L), consistent with limited systemic absorption. In contrast, co-metals were consistently detected: cobalt and nickel were elevated in workers handling ceramic pigments and surface finishing tasks. Regression analyses indicated inverse associations between cobalt and hemoglobin, nickel and oxidative/inflammatory markers (8-OHdG, CRP), and positive associations between nickel and IgM, and arsenic and IgM. Spirometry indices remained within clinical reference ranges but tended to be lower among high-exposure workers.

Conclusions: This study provides the first integrated dataset of zirconium and co-metal exposure in Taiwanese industry, showing measurable airborne Zr but undetectable urinary Zr under current conditions. Co-metals (cobalt, nickel, arsenic) demonstrated significant associations with hematologic, oxidative, and immunologic markers, underscoring the complexity of mixed-metal exposures. These findings support ongoing workplace surveillance and further research on health implications of zirconium and co-metal co-exposures.

Background: Inhaled mineral fibers including asbestos are associated with lung cancer and pleural disease. In this study, we evaluated methodologies for mineral fiber isolation with subsequent physical and chemical characterization from pulmonary tissues of rats exposed to Libby amphibole asbestos 2007 (LA 2007) fibers via repeated nose-only inhalation. At the completion of the exposures, lungs were collected either as is or instilled with liquid agarose to produce a pulmonary cast. To extract fibers, lung tissue with and without pulmonary casts were further processed by either high temperature ashing or chemical digestion. The use of liquid agarose to produce pulmonary casts was discontinued after the first study assessment as no fibers were present in the pleural cavity for evaluation. Fibers isolated from the lungs were analyzed by transmission electron microscopy (TEM) coupled with selected area electron diffraction (SAED) and energy dispersive X-ray spectroscopy (EDS) for physical and chemical characterization. The bulk LA 2007 test material was also analyzed to provide comparison of fiber dimensions and chemical composition of the fibers introduced during exposure. Particular interest was focused on the comparison between high temperature ashing and chemical digestion extraction methodologies.

Results: Chemical digestion of lung tissue with and without pulmonary casts resulted in fiber dimensions and chemical profiles similar to the bulk LA 2007 test chemical and exposure atmosphere. Conversely, high temperature ashing resulted in degraded fibers with chemically altered profiles.

Conclusions: Based on the findings in this study, chemical digestion of lung tissue is the preferred preparation method for the isolation of inhaled mineral fibers for lung burden analysis.

Background: Water vapour resistance of thermal insulating protective clothing impedes sweat evaporation, the most substantial pathway of heat dissipation for working humans. Consequently, metabolic heat can increase body core temperature rapidly, which can result in life-threatening heat illnesses. The evaporative microclimate cooling method Dry Air Comfort (DAC) has been shown to be very effective for reducing the risk of heat induced illnesses. Aim of this study was to determine whether DAC can also prevent heat stress when used in intervals.

Methods: Using a balanced within-subject design twelve men in protective overalls were randomly assigned (max. 205 min, 25 °C, 50% relative humidity/RH, 0.2 m/s wind speed) to a work-rest schedule (5 × 20 min work respectively rest each; work: treadmill, 3 km/h, 5% incline; handling of loads) without cooling and with insufflating conditioned air (30 °C, < 3% RH, 600 l/min) into an air-diffusing undergarment during rest periods (interval cooling).

Results: With interval cooling, all participants tolerated the whole exposure time never exceeding a mean core temperature of 38.0 °C. In contrast, without cooling eight subjects had to terminate work because of high core temperatures (39 °C, n = 5), subjective exhaustion or reaching 90% of the maximum individual heart rate (HR; n = 3). All parameters indicated lower heat stress and distinctive heat dissipation with interval cooling: e.g., HR between both conditions differed significantly (p ≤ 0.05; p ≤ 0.01), as were the skin temperatures (p ≤ 0.001). HR decline was more pronounced during rest periods during interval cooling, indicating significant recovery: e.g., 105.1 ± 17.0 b/min vs. 149.7 ± 15.5 b/min (rest 4, 165. min vs. work 4, 145. min, n = 12). Without cooling HR showed only minor recovery: e.g., 138.4 ± 15.0 b/min vs. 158.7 ± 12.3 b/min (rest 4, 165. min vs. work 4, 145. min, n = 8) and exceeded the level of HR in rest periods of interval cooling.

Conclusions: Interval heat evaporation during rests periods with the microclimate cooling method DAC was shown to be effective in preventing body heat accumulation during alternating work-rest cycles. The method can improve occupational health and safety of men working in thermal protective clothing.

Background: Overweight and obesity have a negative impact on health and have a detrimental effect on the operational readiness of soldiers. Different prevention and intervention measures against obesity include diet, physical activity, education, coaching or medication or a combination of several aspects have been investigated. This review systematically assesses the effectiveness of lifestyle, dietary, educational, and pharmacological interventions on weight, body composition, and military readiness in active-duty personnel.

Methods: We carried out a systematic review based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. A search was conducted in various electronic databases from 2000 to July 2024. The search strategy combined three concepts: military population, outcome terms, interventions or programs. For the review, 21 articles met the inclusion criteria (total n = 1696). Where possible, the effect size (ES) was calculated.

Results: In studies that only examined exercise, minor effects were reported, e.g. a reduction in weight (-0.5 kg), Body Mass Index (BMI) (-0.3 kg/m²), waist circumference (-0.1 cm) and body fat percentage (-1.1%) without relevant statistical ES. Studies with nutritional programs reported low to moderate ES. Combined programs including dietary and exercise countermeasures showed to be more effective than programs based on diet or exercise alone. Combined programs with exercise and educational methods showed a moderate to large effect size (ES 0.6-1.3) for weight reduction. Pharmacological treatment for reducing fat intake resulted in a larger effect sizes for weight loss. The greatest efficacy (ES > 1.0) was observed for a combined intervention program consisting of lifestyle changing components based on individually tailored cognitive behavioral therapies, psychoeducation, exercise and nutritional interventions.

Conclusions: Effective countermeasure for reducing body weight found in this study were combined interventions, like education on lifestyle changes, dietary habits and promotion of physical activity in military personnel, as well as by ketogenic dietary interventions combined with physical activity and followed by pharmacological intervention approaches. Combined interventions appear promising in some studies, but future evaluations may focus on combinations of physical activity and exercise with new pharmaceutical approaches like Semaglutide or Bimagrumab medication in the long term for military personnel due to probable favorable body composition adaptations and military readiness.

Background: Night shift work disrupts circadian rhythms and has been associated with various health disorders, particularly in older adults. Biological age indicators, such as telomere length (TL) and DNA methylation (DNAm) age, offer effective tools to assess early ageing-related changes Linked to occupational exposures. This study aims to investigate the association between night shift work and biological ageing markers among workers aged over 50 years.

Methods: Participants were classified as current, former, or never night shift workers. TL was measured via quantitative PCR, and DNAm age was estimated based on methylation at five CpG sites. Age acceleration (AA) was calculated as the residual from regressing DNAm age on chronological age. Associations between shift work and ageing markers were evaluated using univariate and multivariate analyses.

Results: Out of 330 workers invited, a total of 262 (response rate 79.6%) were recruited, predominantly male (87%) with a mean age of 54.5 ± 3.1 years. Current night shift workers exhibited significantly shorter telomeres compared to non-current shift workers (adjusted β = -0.07, p = 0.03). Among former shift workers, longer cumulative exposure was associated with reduced TL (β = -0.01, p = 0.004). Additionally, TL increased and AA decreased with each year since night shift cessation (β = 0.01, p=0.001 and β = -0.08, p=0.05, respectively).

Conclusions: Prolonged night shift work is associated with telomere shortening, suggesting increased cellular ageing, partially reversible after night-shift cessation. DNAm age appears less sensitive to recent or cumulative shift work exposure.