Journal of Health and Safety at Work

An Evolutionary Rule Based Framework for Real-Time Risk Governance of Noise and Fumigant Hazards in Marine-Manufacturing Systems

Mohammad Ali Afsharkazemi

Introduction: Fumigant gases in maritime and container chains, along with occupational noise in marine and manufacturing industries, are among the most significant chronic risk factors. They are usually assessed separately, despite their simultaneous impact on workers’ health. The importance of this study lies in presenting an integrated approach for real-time monitoring of combined risk and aligning it with occupational exposure limits (OELs). The aim is to develop and validate an interpretable, regulation-oriented framework for predicting combined risk.
Material and Methods: This research integrated and normalized data from the Global Burden of Disease (GBD) 2021 study including age-standardized disability rates (ASDR) and average annual percentage change (AAPC) for 204 countries with occupational exposure limit tables for fumigants. A Sugeno-type fuzzy inference system with three inputs and four rules was designed. Weights and membership function boundaries were optimized using the Prairie Dog Optimization algorithm, and a threshold-based scenario generation module was applied to produce high-risk synthetic data. Model performance was evaluated through an OEL compliance test.
Results: Findings revealed that the proposed optimization reduced the loss function by 42% compared to random search. The mean absolute error (0.028 ± 0.006) and root mean square error (0.041) were obtained. Threshold-based scenario generation improved data coverage in high-risk regions from 0.62 to 0.90 and increased the accuracy of critical condition detection from 0.71 to 0.89. The OEL compliance index reached 0.93, confirming input weighting as the most influential factor.
Conclusion: The proposed framework simultaneously ensures numerical accuracy, interpretability, and regulatory compliance with occupational exposure limits. It can be deployed within real-time monitoring dashboards for ports and factories. Future research should integrate IoT sensors and multi-objective optimization to enable dynamic updates in response to evolving regulations and operational conditions.

Evaluating the Effectiveness of Pressure Sensors in Mitigating the Risk of Ammonia Cargo Release in Transit: A QRA-Based Case Study in a Petrochemical Transport Company

Ali Karimi

Introduction: Transporting hazardous materials is inherently associated with multiple risks that can threaten human health, the environment, property and infrastructure. The deployment and operation of ammonia tanks in various industrial projects and organizations with diverse objectives present serious safety, health and environmental challenges. Therefore, conducting risk assessment in the chemical sector is essential. This study aimed to evaluate the effectiveness of a pressure sensor in reducing the risk of ammonia cargo release during road transportation, based on Quantitative Risk Assessment (QRA) in a petrochemical transport company.
Material and Methods: This study assessed the risk of ammonia release from a pressurized tanker and investigated the risk-reducing effects of employing a pressure sensor for leak prediction. Consequence modeling and QRA were conducted using SAFETI version 9.
Results: The results showed that the installation of a pressure sensor on the ammonia tanker reduced the gas release duration from 40 to 25 minutes, which consequently decreased the volume of the leaked gas and ultimately reduced the overall risk level of accidents. This risk reduction varied between 55% and 99% under different atmospheric conditions. By decreasing the release time from 40 to 25 minutes, the lethal radius of ammonia was consistently reduced in all weather conditions. The analysis of individual risk contours in the sudden rupture scenario revealed that atmospheric conditions, particularly during winter nights, had the greatest impact on the expansion of lethal zones.
Conclusion: The use of pressure sensors and alert systems can effectively reduce individual risk level. Continuous monitoring of tank conditions and prompt alerts in the event of leaks or pressure drops enable faster response and help prevent escalation of accident consequences.

Developing an Integrated Framework to Reduce Uncertainty in Process Risk Assessment Based on Dempster-Shafer Evidence Theory and Bayesian Network: A Case Study in Oil Reservoirs Using Multiple Sources of Evidence

Mostafa Pouyakian

Introduction: Fire risk assessment in oil storage tanks faces challenges due to incomplete, conflicting, and uncertain data, particularly when empirical evidence is limited. Traditional point-based likelihood estimates often fail to capture expert doubt and epistemic uncertainty. This study aims to develop and evaluate a novel hybrid framework combining Dempster-Shafer Theory (DST) and Bayesian Networks (BN) to improve the trustworthiness of fire risk prediction in such industrial settings.
Material and Methods: The proposed approach integrates DST to model expert uncertainty through interval probabilities (Bel–Pl) and BN to dynamically update causal relationships as new information appears. The study implements computational coding to enable DST calculations for five expert opinions across 243 scenarios, overcoming prior limitations in multi-expert modeling due to computational complexity.
Results: The hybrid DST-BN framework demonstrated superior ability to incorporate incomplete and conflicting expert data, reducing overconfidence linked to point estimates. Interval probabilities offered more trustworthy representations of epistemic uncertainty, while BN integration allowed traceable and adaptable causal modeling. The computational solution facilitated practical application of DST with multiple experts, enhancing the strength of the risk assessment.
Conclusion: This research provides an effective DST-BN hybrid methodology for assessing fire risk in fixed-roof oil tanks, improving accuracy and trustworthiness in complex industrial environments. By addressing the shortcomings of point-based methods and enabling multi-expert participation, the framework supports clearer and more defensible probabilistic inferences. Future work may focus on integrating real-time sensor data and AI-based decision systems to further strengthen dynamic risk assessment capabilities.

Studying the Effect of Noise Annoyance on the Anxiety of Workers in a Corrugated Packaging Manufacturing Company: A Case Study

Hamideh Bidel

Introduction: Workplace noise is one of the main sources of health problems. Noise can have many direct and indirect effects that threaten human health in various ways. The aim of this study was to investigate the effect of noise annoyance on anxiety among workers.
Material and Methods: This study included 60 workers from a carton manufacturing company, who were divided into two groups based on noise exposure: exposure (noise level more than 85 dB) and control (noise level less than 85 dB). Noise exposure of the individuals at the workplace was measured in accordance with ISO 9612:2009 standard and using a TES-1354 dosimeter. Anxiety levels were assessed using the Spielberger Anxiety Inventory (STAI), and noise annoyance was measured using a 100-point visual analog scale. Statistical analysis was performed using STATA statistical software.
Results: The mean age and work experience of the study subjects were 35.78 and 10.78 years, respectively. The results indicated a statistically significant difference (P-value < 0.05) in the mean noise annoyance scores between the groups. The mean noise annoyance score in the exposed group was significantly higher (88.03) than in the non-exposed group (47.6). The average anxiety scores in the exposure and control groups were 106.81 and 101.6, respectively. In addition, regression analysis showed that each unit increase in noise annoyance level resulted in a 1.08-fold increase in anxiety in the exposed group.
Conclusion: Noise annoyance is often the most common psychological response to noise exposure and can be a predictor of many mental disorders or illnesses, including anxiety. Therefore, it is important to implement control measures to reduce noise exposure in the workplace.

The Relationship Between Physical Activity and Commercial Truck Driver Performance: The Mediating Role of Occupational Fatigue

Mohammadreza Shahabi Kaseb

Introduction: Commercial trucking is one of the most challenging occupations, with long work hours, short rest periods, and substantial psychological pressures that contribute to fatigue and deterioration at work. Since regular physical activity is one of the pillars of healthy life and can improve physical and mental functioning, the present study investigated the relationship between physical activity and driver performance with occupational fatigue as a possible mediator.
Material and Methods: The study population was intercity commercial truck drivers in several cities of Razavi Khorasan Province. Using Green’s formula, we calculated a sample size of 140 participants. Data were collected with the Swedish Occupational Fatigue Inventory, the Sharkey Physical Activity Questionnaire, and the Driver Performance Questionnaire (unsafe behaviors). Statistical analyses included Pearson correlation coefficients and multiple regression analyses.
Results: Our results showed a significant positive correlation between occupational fatigue and driver performance problems (P=0.001). Both the correlation between physical activity and work fatigue, and the correlation between physical activity and driver performance were significant negative correlations (P=0.001). In addition, the indirect link between physical activity and driver performance via occupational fatigue was also significantly negative (P=0.001).
Conclusion: Based on our research results, enhanced physical activity contributes to enhanced driver performance (decreased unsafe behaviors) of commercial truck operators, directly and indirectly through decreased occupational fatigue. This study provides scientific evidence for the development of safety policy in the transportation industry of Iran.

Comparative Quantitative and Semi-Quantitative Occupational Risk Assessment of BTEX Compounds and Heavy Metals in a Power Equipment Manufacturing Industry

Saba Kalantary

Introduction: Occupational exposure to volatile organic compounds (BTEX) and heavy metals in industrial settings poses significant health concerns. These substances may lead to toxic, carcinogenic, and hematobiochemical effects. This study aimed to assess the health risks associated with exposure to these pollutants in a power equipment manufacturing industry over a 10-year period and to compare the accuracy of quantitative (USEPA) and semi-quantitative (Singapore) risk assessment methods.
Material and Methods: This cross-sectional study was conducted across six occupational groups. Personal air sampling of BTEX and heavy metals was performed according to NIOSH protocols. Carcinogenic and non-carcinogenic risks were estimated using the USEPA method and the Singapore semi-quantitative approach. Additionally, hematological and biochemical indicators of exposed workers were analyzed.
Results: Nickel had the highest cancer risk, and the highest hazard quotient (HQ) values were related to xylene, benzene, and nickel. While the semi-quantitative method classified most risks as negligible to low, the USEPA method identified several cases with definite health risks. Significant effects were observed on SGOT, SGPT, fasting blood sugar, creatinine, and blood pressure among exposed groups.
Conclusion: The USEPA method demonstrated higher sensitivity and reliability in identifying occupational chemical hazards and should be prioritized in future assessments. Furthermore, the findings underscore the importance of preventive measures to reduce chronic exposure to BTEX and heavy metals in similar industrial settings.

The Mediating Role of Work Engagement in the Relationship Between Job Security, Work-Family Conflict, and Emotional Burnout Among Office Workers

Seyed Abolfazl Zakerian

Introduction: Job factors play a critical role in shaping employee health and mitigating burnout. Work-family conflict leads to outcomes such as burnout, emotional exhaustion, and decreased performance. Similarly, employees’ perception of job insecurity can negatively affect their burnout, work attitudes, well-being, commitment, and interpersonal relationships. This study investigates the interplay between job security, work-family conflict, and burnout, with a focus on the mediating role of work engagement among office workers.
Material and Methods: This cross-sectional study was conducted in 2024, collecting data from 119 employees in administrative units at a medical university in Iran. Structural equation modeling was employed for data analysis. The measurement tools included standardized questionnaires for work engagement, work-family conflict, job security, and job burnout. The questionnaires were utilized based on a Likert scale, with confirmed validity and reliability.
Results: The findings from the correlation analysis indicated that job security had a significant positive relationship with work engagement. In contrast, burnout showed a negative correlation with job security and work engagement, while it had a positive correlation with work-family conflict. Results from the structural equation modeling revealed that work-family conflict had a direct relationship with burnout but did not significantly affect work engagement. Work engagement acted as a protective factor in reducing burnout and served as a mediator between job security and burnout; however, its mediating role between work-family conflict and burnout was not confirmed.
Conclusion: Numerous factors impact the psychological health of administrative employees. Organizations should tailor their interventions based on these factors and their interrelations. Overall, employee empowerment programs aimed at increasing work engagement and reducing work-family conflict can enhance the quality of working life and decrease burnout within organizations.

Investigation of Human Factors Contributing to Accidents and Unsafe Acts of Employees and Their Prioritization Using HFACS, DEMATEL, and ANP Methods: A Case Study in the Rebar Production Unit of a Steel Manufacturing Company

Abolfazl Ghahramani

Introduction: Unsafe acts are one of the main causes of workplace accidents. Given the critical role of the steel industry in our country, and the limited research on human factors, and the importance of identifying the contributors to accidents, this study was conducted with the aim of identifying human factors influencing accidents and unsafe behaviors using the Human Factors Analysis and Classification System (HFACS). The identified factors were then prioritized using the Decision-Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP) methods. Based on the results, appropriate recommendations were proposed for the prevention of accidents and the reduction of unsafe acts.
Material and Methods: This descriptive-analytical study was carried out in the rebar production unit of a steel manufacturing plant. Among 35 recorded accidents over the past two years, 28 were related to the rebar production unit. Data were collected through review of accident reports, seven on-site observations during high-risk shifts, and interviews with employees. After analyzing the occupational accidents, the rebar production process in the rolling unit was identified as a high-risk area. The HFACS checklist was used to assess this process and classify the human factors contributing to accidents. Subsequently, DEMATEL and ANP methods were applied to determine causal relationships and prioritize the factors.
Results: The HFACS analysis identified 236 human factors, among which the preconditions for unsafe acts and organizational factors had the highest frequency (24.57% each), while external factors had the lowest (8.47%). According to DEMATEL results, organizational influences exerted the greatest impact on other levels, whereas external factors had the least effect. In terms of being influenced by other levels, unsafe acts showed the highest level of susceptibility, whereas unsafe supervision had the lowest levels. Based on ANP findings, the preconditions for unsafe acts had the highest importance, while unsafe supervision had the lowest in contributing to unsafe acts.
Conclusion: The findings of this study suggest that improving safety culture, improving organizational regulations, implementing targeted training programs, and updating equipment can play a significant role in reducing accidents caused by unsafe acts. The results provide practical insights for managers and policymakers and can serve as a useful tool for decision-making in occupational health and safety within the steel industry.

The Relationship Between Work-Family Conflict Components and Psychological Distress in Female Nurses of Bushehr Province: A Path Analysis Study

Introduction: Work-family conflict can lead to negative outcomes such as psychological distress in all employees, especially female nurses, as they face unique occupational challenges. However, the specific aspect of work-family conflict that contributes most significantly to psychological distress, as well as the underlying mechanisms involved, has not been thoroughly examined. The present study aimed to investigate the relationship between work-family conflict dimensions and psychological distress.
Material and Methods: This descriptive-analytical study was conducted in 2022 on 277 female nurses employed at public hospitals in Bushehr Province. The data collection tool consisted of work–family conflict and psychological distress questionnaires. The data were analyzed using SPSS v. 19 and PLS Graph v. 3, with path analysis.
Results: The direct effects of two dimensions of work-family conflict, namely “the interference of work with personal and family life” and “the interference of family life with work,” on psychological distress were found to be statistically significant (p < 0.05). In addition, the mediating effect of the “work interference with personal and family life” on the relationship between “insufficient facilities and support” and psychological distress was statistically significant (p < 0.05). Meanwhile, the mediating effect of the “family dissatisfaction” in the relationship between “the interference of work with personal and family life” and psychological distress was not statistically significant (p > 0.05).
Conclusion: The interference of work with personal and family life, and the interference of family life with work, were identified as significant factors that directly affect psychological distress. In addition, “insufficient support and facilities” can increase “the interference of work with personal and family life”, thereby leading to greater psychological distress among female nurses. Planning to enhance support measures in both the workplace and personal life can help reduce the negative consequences of work-family conflict, such as psychological distress in female nurses.

Comparison of the Effects and Practice Retention of Core, Operational, and Skill-Based Stability Exercises on Firefighters’ Balance With and Without Firefighting, Rescue, and Hazmat Protective Clothing

Mohammad Mahmoudi

Introduction: Relief work is inherently associated with various stress-inducing factors due to the nature of the profession. Among relief-related professions, firefighters, due to the responsibilities related to firefighting and safety services, are exposed to various physical and chemical hazards. Therefore, the primary aim of this research was to compare the effect and practice retention, central and operational and skill-based stability over the balance of the firefighters with and without firefighting and rescue clothing and Hazardous Materials.
Material and Methods: The statistical population consisted of 5500 firefighters from the city of Tehran. As for the intervention, in the first group, central stability exercises, and in the second group, operational and skill-based exercises were performed by the firefighters during their shift days for a period of 6 weeks. The balance of the firefighters in both groups was measured at three stages: at the beginning of the intervention, immediately after the 6-week training period, and one month after the end of the training. The “Y Balance” board was used to assess the firefighters’ balance. Data analysis was performed using repeated measures analysis of variance and the Bonferroni post hoc test at a 5% significance level, using version 26 of the SPSS software.
Results: According to the results of this study, the balance of firefighters in both the right and left legs was significantly greater in the operational and skill-based training group compared to the central stability training group, both immediately after training and one month later (p < 0.05). With performing operational and skill-based training, right leg balance in the rescue suit was significantly higher than in the fire protection and hazmat suits (p < 0.05), while there was no significant difference between the fire protection and hazmat suits (p > 0.05). Left leg balance in the rescue suit was significantly higher than in both the fire protection and hazmat suits, and balance in the fire protection suit was significantly higher than in the hazmat suit (p < 0.05). Additionally, firefighters’ balance significantly improved after balance training (p < 0.05), and there was no significant difference between the balance measured one month after training and immediately after training (p > 0.05).
Conclusion: In addition to the fact that core stability exercises particularly task specific functional training are effective in improving balance and preventing injuries, the retention of these effects over time should be taken into account.

Investigating Thermal Comfort and Ventilation in Schools: A Systematic Review

Somayeh Farhang Dehghan

Introduction: Students play a key role in shaping the future of any society and spend a significant amount of time in educational environments. Creating an optimal learning environment requires close attention to factors affecting student well-being, particularly thermal comfort and indoor air quality. This study aims to systematically review the existing literature on thermal comfort and ventilation systems in schools.
Material and Methods: This systematic review was conducted based on the Cochrane methodology, involving a comprehensive search of three major databases — Scopus, Web of Science, and PubMed — for articles published between 2020 and 2024. The inclusion criteria encompassed peer-reviewed, conference, and review articles published in English that included the keywords “thermal comfort,” “ventilation,” and “school” in their title, abstract, or keywords. Studies focusing on preschools, universities, or other non-primary/secondary educational settings, as well as those conducted during the COVID-19 pandemic, were excluded.
Results: A total of 42 articles were selected after a rigorous screening process. The highest number of publications was reported in 2023. Key findings included: Most studies focused on elementary and secondary schools. The majority of research was conducted during the summer season, which may limit generalizability across seasons. There was considerable variation in CO₂ levels, with some exceeding recommended standards. In simulation studies, DesignBuilder and EnergyPlus were the most frequently used software tools. Additionally, results showed that: Indoor air quality and thermal comfort are significantly influenced by the type of ventilation system. Schools using natural ventilation often experienced higher CO₂ concentrations and lower thermal comfort than recommended. Implementation of Demand-Controlled Ventilation (DCV) has shown promise in improving indoor air quality and reducing pollutant levels.
Conclusion: This paper can contribute to the improvement of educational space design, enhancement of student learning, and promotion of indoor environmental health. It also provides insights into the latest methods for measuring and simulating thermal comfort and indoor air quality. For more practical outcomes, long-term studies with larger sample sizes across different seasons and times of day are needed. Combining computer simulations with real-world measurements can support cost-effective and optimized design of educational spaces. Future research should focus on standardizing temperature, humidity, CO₂ levels, and selecting the most appropriate ventilation strategies for classrooms.

An Overview of the Applications and Conditions for Using Artificial Intelligence and Digitalization in Occupational Health and Safety in the Workplace

Ali Askari

Introduction: Artificial Intelligence (AI) and digitalization are pivotal in enhancing Occupational Health and Safety (OHS), reducing workplace accidents, improving conditions, and boosting organizational productivity. This study examines the impacts, challenges, and opportunities of these technologies in workplace safety.
Material and Methods: A narrative review was conducted via databases (Google Scholar, PubMed, IEEE Xplore, ScienceDirect) using keywords like “AI in occupational safety” (2013–January 2025). After screening 125 articles, 71 met the inclusion criteria (Persian or English publications). Qualitative content analysis identified key challenges and opportunities.
Results: Artificial intelligence has been used in predicting incidents, monitoring, process optimization, and analyzing OHS challenges. By analyzing historical data and hazard patterns, AI enables proactive risk mitigation. Continuous learning in AI models enhances predictive accuracy and environmental adaptability. However, data quality issues persist; techniques such as transfer learning offer potential solutions. AI-driven automation reduces human error, yet challenges include ethical concerns and infrastructure gaps.
Conclusion: AI and digital technologies are transforming OHS through predictive analytics and real-time surveillance. To fully leverage these benefits, future efforts must focus on addressing data quality issues, establishing robust ethical frameworks, and developing advanced infrastructure. Further research is essential for the practical implementation of AI in a variety of work environments.