Journal of Occupational Health最新文献

Objectives: 2-Ethyl-1-hexanol (2EH) is a volatile organic compound that can cause sick building syndrome and can be released from flooring materials for more than 10 years through the hydrolysis of compounds with 2-ethylhexyl moieties. Previous studies using mice have raised concerns about tissue-damaging effects on the olfactory epithelium (OE), olfactory bulb (OB), brain, lungs, and skin. A subchronic mouse study observed degeneration of OE at concentrations as low as 20 ppm. However, the effects of long-term exposure to 2EH remain unclear. This study aimed to elucidate the histopathological effects of chronic exposure to 2EH relative to its airborne concentration.

Methods: Ten-week-old male ICR mice were exposed to 0, 0.5, 10, or 100 ppm 2EH by inhalation for 8 h/d, 5 d/wk, for 6 months. Subsequently, histopathological analysis was conducted.

Results: At 0.5 ppm, acute and chronic inflammation were observed in the OE and alveoli, with tissue repair in the OE, and thickening of the epithelium and smooth muscle in the bronchi. Metaplasia of OE in the respiratory epithelium was induced at 10 and 100 ppm. At all concentrations, the number of mature neurons in the OE and immature neurons in the OB decreased, suggesting that olfactory nerve activity was suppressed. Fibroblasts increased in the dorsal skin. Microglia in the hippocampus and amygdala increased in number.

Conclusions: Chronic inhalation exposure at as low as 0.5 ppm caused inflammation in the OE, OB, segmental bronchi, and alveoli, and affected the target area of OB neurons.

Objectives: This scoping review aims to assess the role of machine learning in workplace mental health research by systematically analyzing existing studies to understand current methodologies, applications, and trends.

Methods: We conducted a comprehensive search across multiple databases, including Ebsco, Scopus, ProQuest, Web of Science, PsycINFO, IEEE, and ACM, screening a total of 5600 abstracts. Altogether, we analyzed 92 journal articles, conference papers, and book chapters published before September 2025.

Results: Since 2020, there has been a notable increase in publications on the topic. Studies have mainly employed cross-sectional designs (73%) and workplace questionnaires (51%) targeting specific occupational groups (67%), particularly from Asia excluding China (41%). Supervised learning methods, such as Random Forest and Neural Networks, have been frequently utilized to investigate conditions like depression, burnout, and anxiety. Most studies predicting mental health at work using machine learning are currently conducted by data scientists as single-measurement studies, whereas longitudinal studies from medicine, epidemiology, social sciences, or behavioral sciences are comparatively rare. In the context of machine learning, prediction denotes the model's ability to infer outcomes based on input data. However, most publications do not systematically analyze the temporal dynamics of mental health or forecast mental health outcomes from an epidemiological perspective.

Conclusions: The application of machine learning in occupational mental health research remains in its preliminary stages, with a primary focus on methodology and computer science. The review highlights the necessity for interdisciplinary collaboration to fully leverage the potential of machine learning in advancing occupational health research.

Objectives: Firefighters face a disproportionately high risk of developing cancer due to occupational exposure to carcinogens, including combustion byproducts, diesel exhaust, and per- and polyfluoroalkyl substances (PFAS) found in firefighting foams and protective gear. This study aimed to systematically review existing literature on cancer risks among firefighters, with particular attention to exposures, prevention strategies, and decontamination practices, and to propose a novel model addressing current gaps.

Methods: A systematic review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Peer-reviewed articles, international reports, and high-quality training materials were included. A total of 37 records were included in the final review. Data were synthesized across thematic areas relevant to firefighter cancer risk.

Results: Five key themes were identified: (1) cancer incidence and mortality, (2) occupational exposure sources, (3) basic prevention practices, (4) gear hygiene, and (5) station decontamination models. The review also identified a critical gap in current decontamination protocols for volunteer firefighters in rural areas who often respond to emergencies using personal vehicles. To address this, we proposed a novel, volunteer-specific decontamination framework, the Schutte Model, developed, adapting existing best practices to minimize carcinogen transfer during gear transport.

Conclusion: This study provides both an evidence-based synthesis and a novel intervention model. Findings underscore the urgent need for inclusive, low-cost, and culturally tailored prevention strategies to reduce cancer risks among all firefighters, particularly volunteers operating in under-resourced and decentralized contexts.

Objectives: To develop and validate a predictive model for mental health-related sick leave using data from Japan's Stress Check program linked with personnel records (demographics and sick-leave history), and to evaluate its predictive performance compared with the conventional high-stress classification.

Methods: We conducted a retrospective cohort study of employees (2020-2024) in a 14-company corporate group spanning diverse occupations. A mixed-effects logistic regression model was developed using data from 2020-2023, with company and year as random intercepts. Variable robustness was confirmed through LASSO logistic regression. Model calibration and discrimination were evaluated using the Brier score and area under the curve (AUC), respectively. The model was temporally validated on 2024 data.

Results: Among 87 138 person-years in the development phase, 695 employees took mental health-related sick leave (0.8%). Seven predictors- younger age, anxiety, depression, sleep disturbance, low job control, poor job suitability, and low coworker support-were significantly associated with sick leave. The recalibrated model showed good discrimination (AUC = 0.708) and calibration (Brier score = 0.0079) in development, and higher performance in validation (AUC = 0.819; Brier score = 0.0026). The conventional high-stress classification performed poorly.

Conclusions: The proposed model demonstrated robust predictive validity and outperformed the conventional high-stress classification. By providing quantitative and continuous risk stratification within the Stress Check framework, it offers a practical approach to support risk-based prioritization and decision-making in occupational health practice.

Objective: Special health examinations in Japan lack standardized judgment guidelines, potentially leading to wide variation in outcomes. This study quantified inter-institutional differences in abnormal-finding rates for examinations targeting specified chemical substances and organic solvents, and examined whether institutional judgment criteria are associated with these rates.

Methods: We conducted a cross-sectional questionnaire survey of 115 facilities affiliated with the National Federation of Industrial Health Organizations (Zen-Eiren). Facilities reported abnormal-finding rates for fiscal years 2022-2024. Physicians' judgment criteria were assessed using case vignettes addressing the use of exposure information and biological monitoring. Associations between rates and judgment criteria were evaluated using non-parametric tests (Spearman's rank correlation; Wilcoxon rank-sum).

Results: Valid responses were obtained from 45 facilities (39.1%). Abnormal-finding rates for specified chemical substances and organic solvent examinations were strongly correlated within facilities. For organic solvent examinations, facilities that did not emphasize the exposure-finding association reported higher abnormal-finding rates than those that did. A similar, but non-significant trend was observed for specified chemical substance examinations (P = 0.066). Abnormal finding Rates tended to rise when biological monitoring alone triggered abnormalities and non-occupational factors were not excluded in both examinations.

Conclusion: Major special health examinations in Japan show substantial inter-institutional variation in abnormal-finding rates, partly explained by differences in judgment criteria-particularly the weight placed on linking clinical findings to workplace exposure. Establishing standardized national guidelines is essential to improve consistency, reliability, and system effectiveness.

Objectives: Inappropriate telework environments, including work-from-home (WFH) settings, have been linked to physical and mental health problems. However, no systematic assessment has been conducted regarding the WFH environment (WFH-E). The aim of this study was to clarify the current methods used to assess the WFH-E and its association with health- and work-related outcomes through a scoping review.

Methods: We searched PubMed, Web of Science, and Ichushi for literature published since 2010 on WFH-E assessment. Based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews guidelines, assessment methods were summarized using 18 items categorized into nine domains. Additionally, associations between the WFH-E and health- and work-related outcomes were reviewed.

Results: Of 1669 articles collected, 37 studies published from 2020 were ultimately included in this review. Thirty-four articles involved subjective assessments, and nine involved objective assessments. The most frequently assessed item was artificial lighting, followed by thermal conditions and noise. Items such as color, greenery, building materials, and odor were rarely assessed. Most studies showed significant associations between the WFH-E and health- and work-related outcomes.

Conclusions: Studies on the WFH-E increased following the coronavirus disease 2019 pandemic, showing significant associations between the WFH-E and health- and work-related outcomes. However, most assessments were subjective, with objective assessments remaining rare. Additionally, the assessment items were limited and biased, indicating that interior design elements were insufficiently assessed. Developing additional objective and comprehensive methods for assessing the WFH-E is needed.