Journal of Health and Safety at Work

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Introduction: In recent years, many national and international expert groups have considered specific improvements in risk assessment of chemical pollutants. This study considered to assess the risk of workers exposure to air pollutants in an automobile manufacturing in order to evaluate the health risk assessment due to the inhalation exposure.  

Material and Method: To perform this study, a cross-sectional research was done in 2016. Methods number 1501 and 7602 of the National Institute of occupational safety and Health (NIOSH) were used for sampling and analysis of compounds BTEX and silica in the air. A total of 40 samples of compound BTEX were taken and analyzed by Gas Chromatography-Flame Ionization Detector (GC-FID). A total of 6 samples of silica were collected during the campaign. Silica analyses were performed by using visible spectrophotometry. Risk ranking was calculated using the hazard and exposure rate. Finally, the relative risk of blood cancer caused by exposure to benzene was estimated.   

Result: The result demonstrated that, workers were exposed to 5 chemicals including silica, benzene, toluene, ethyl-benzene, and xylene during their work in manufactory. Among the pollutants in the breathing zone of workers, Silica and benzene were hazardous chemicals at high risk level. Following the estimation of relative risk of blood cancer caused by exposure to benzene, workers cumulative exposure to benzene was obtained to be 23.1 ppm per year and the capture relative risk was 1.1. The consequence demonstrated that, significant relationships were seen between workers exposure to benzene and both age and work experience, so that degree of exposure decreased steadily with increasing age and experience (P<0.001).

Conclusion: This research demonstrated that, benzene and silica in the automobile manufacturing were the highest risk. Also, painting hall workers, at automobile manufacturing, were directly exposed to the blood cancer risk of benzene.

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Introduction: Being aware of the explosion, fire radius, and their damages, has an important role in accident prevention methods. Therefore, the aim of this study was modeling and evaluation of the consequences of propylene oxide spill in a petrochemical company.
 

Material and Method: The QRA method including seven steps was used in this study. In the present study, in order to examine and modeling of the propagation propylene oxide, first a familiarization with the process information of the unit was done then, a risk assessment was carried out adopting HAZOP technique to identify existing hazards. Consequence analysis in a process unit includes: selecting important scenarios, characterizing scenario, modeling the consequences of scenarios, analyzing the results and determining the percentage of mortality. PHAST software version 6.51 was used for modeling of outcomes and assessment propylene leak.
 

Result: urves of the firing zones of sudden release of propylene oxide showed that the influence puts are included up to radius of 0.15 meters in the scenario of leakage 5 mm, in scenarios with leaks 25 mm to a radius of 1.1 meters and in scenarios with leakage of 100 mm to a radius of 39 meters. The maximum intensity of flash fire in the initial point Scenario 5 mm was 4.2 kW/m2, in the scenario of radiation leakage was 25 mm at the distance to 5 meters from the fire intensity up to maximum of 9 kW/m2, and also in the scenario with 100 mm flash fire radiation leak at an earlier point fire was 14 kW/m2. The maximum intensity of thermal radiation at the distance to 5 meters up to 16.5 kW/m2, and maximum distance of 80 meters around the reservoir affected. The mortality rate of flash fire has exposed employees, was 50 percent.
 

Conclusion: Many accidents caused by leakage and explosion were due to corrosion, spoil tanks and equipment, and the majority of such accidents can be prevented by technical inspections and continuous audits.

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Introduction: Workers in steel manufacturing companies are extensively exposed to the volatile organic compounds (VOCs). Considering the health effects of these compounds, the purpose of this study was to determine occupational exposure to the BTEX compounds and also evaluation of carcinogenic risk due to benzene and non- carcinogenic risk for BTEX compounds in a steel industry.

Material and Method: This cross-sectional study was conducted in the coke production unit of the steel making industry. After collecting personal samples from breathing zone of the workers and analyzing of the samples the levels of exposure to the BTEX were quantitatively determined using Gas chromatography equipped with Flame Ionization Detector (GC-FID), according to the NIOSH 1501 standard method. Then, cancer risk due to benzene and non-cancer risks from BTEX compounds were calculated using Monte-Carlo technique.

Result: The analysis of personal samples indicated that benzene concentration in energy and biochemistry and benzol refinement sections of the plant were higher than occupational exposure limits (OELs). Among the studied sections, benzol refinement as the most polluted section had the highest concentration of BTEX compounds. Non-cancer risk due to BTEX compounds in all studied sections was lower than one. Benzene cancer risk in energy and biochemistry, benzol refinement and experimental furnace sections was higher than maximum recommended value by EPA.

Conclusion: Due to the high concentration of benzene in energy and biochemistry and benzene refinement sections as well as the resultant carcinogenic risk, improvement of existing control systems and the use of modern engineering systems are necessary to control occupational exposure.

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Introduction: Examining the effect of bus drivers’ demographic characteristics as well as workplace conditions on their traffic behavior and performance is important not only for drivers’ health and safety, but also for the safety of bus passengers. The aim of this study was to investigate the relationship between demographic variables and work shift schedule on the behaviors pertaining to “hazard monitoring”, “relax driving”, “fatigue proneness”, and “thrill seeking” among intercity bus drivers.

Material and Method: In this cross-sectional study a sample of 321 bus drivers were randomly selected from Tehran intercity bus terminals. The BDRI questionnaire was used to collect data. The Pearson’s correlation coefficient and the ANOVA and Tukey’s HSD tests were used to analyze the data.

Result: In general, the findings showed that age, driving experience and rest time period positively correlate to lower fatigue, lower thrill seeking and more relaxed driving. Drivers with higher vehicle age were found to perform worse than others in hazard monitoring and to be more prone to the stress and fatigue. Also, fatigue and relaxed driving were significantly related to the marital status and cigarette usage. In addition, drivers who were college graduate or above were found to perform worse than other drivers considering all of the four factors. Furthermore, those who drive in mountainous routes were found to perform worse than other drivers in hazard monitoring and fatigue proneness.

Conclusion: Since the age and driving experience were found to influence fatigue proneness, hazard monitoring and relaxed driving, thus, setting up specific training courses for different driver age groups aiming to enhance their awareness concerning on managing these factors might help drivers improve their performance in these factors. Furthermore, regarding the effect of rest period and route type on the drivers’ fatigue and hazard monitoring ability, appropriate regulations are needed to mitigate the effect of these factors on the performance of drivers.

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Introduction: One of the harmful pollutants in the indoor environments is particulate matters. Particles smaller than 2.5 micrometer in diameter that are suspend in the industrial environments air are the most deleterious dusts which can cause lung disease and cancer. In present study PM2.5 concentration in the fast-food shops air and its cancer risk for shop workers were assessed.  
Material and Methods: In this descriptive-analytical study, all of Sari city 132 fast foods were included. Air sampling was conducted by calibrated real-time GRIMM-monitor device. Data were analyzed by using of SPSS16 and Prism6 software with T-test, Pearson correlation and descriptive statistics. Finally PM2.5 cancer risk in workers was calculated by EPA method equation.
Results: The PM2.5 concentration in shops indoor air (308.5µg/m3) significantly was higher than its concentration in outdoor air (121.98µg/m3) (p<0.05). Highest correlation was observed between indoor PM2.5 concentration with smoking (0.366) and local ventilation (-0.384) (p<0.01). The concentration PM2.5 in the indoor and the outdoor of shops was 273.55 and 86.98µg/m3 higher than acceptable level respectively. Cancer risk was 5.6 per 100 thousands and 1.97 per 10 thousands in the rest and cooking time respectively.
Conclusion: The most affective source in the elevation of PM2.5 level in shops indoor air is the cook-emitted particles. PM2.5 concentration in shops indoor and outdoor air was much higher than EPA admissible level and cancer risk for workers was unacceptable that it has required to basic solutions for air pollution control at source.

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Introduction: People’s risk perception in an emergency situation affects how they behave. During the pandemic of a disease like COVID-19, the fear of the disease and its consequences causes people to deal with anxiety. The present study was conducted with the aim of determining the relationship between the perception of the risk of COVID-19 and the experience of anxiety caused by it among workers in manufacturing industries. 
Material and Methods: The present descriptive-analytical study was conducted cross-sectionally in 2022 among 545 workers of manufacturing industries located in Tehran, Mazandaran and North-Khorasan provinces. In the study, data collection was conducted using three questionnaires: a demographic information questionnaire, the COVID-19 Disease Anxiety Scale (CDAS), and the COVID-19 Risk Perception and Psychological Predictors against COVID-19 questionnaire. Data analysis was done using descriptive (mean and standard deviation) and analytical statistics (Canonical Correlation Coefficients or CCC) in SPSS V25 software.
Results: The mean ± SD of the workers’ age was 35.98 ± 7.58 years, while the scores for risk perception and anxiety were 12.89 ± 3.31 and 4.51 ± 1.51, respectively. The Concordance Correlation Coefficient (CCC) between risk perception and anxiety caused by the COVID-19 disease in the first Canonical point was 0.734, and in the second Canonical point, it was 0.229. The corresponding p-value was found to be less than 0.01. Psychological symptoms (Canonical loading = -0.725) and physical symptoms (Canonical loading = -0.421) played a significant role in predicting the variability of the risk perception of COVID-19.
Conclusion: The perception of risk related to the COVID-19 disease resulted in a decrease in anxiety, having a more pronounced effect on psychological symptoms compared to physical symptoms. Therefore, in times of pandemic outbreaks similar to COVID-19, implementing measures that enhance workers’ awareness and understanding of the disease risks can prove effective in managing anxiety. 

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Introduction: Steel erection is known as one of the most hazardous construction activities. From an occupational health and safety perspective, this process carries high risk. Therefore, this study aims to conduct a qualitative risk analysis of steel structure assembly and model it using the Functional Resonance Analysis Method (FRAM).
Material and Methods: In this cross-sectional study, the construction site of a high-rise building steel structure was first visited to identify the main processes involved. Then, semi-structured and open-ended interviews were conducted with 33 workers partaking in this process. Data from the interviews and process identification were entered into FRAM Model Visualiser (FMV) software to investigate and model complex relationships and interactions between daily tasks.
Results: Of the 19 major system component functions identified, four functions had potential instability and defects due to complex human, organizational, and technological function interactions. By intensifying the FRAM graphic model, risks may be imposed on the system if the interactions of these four functions are neglected. These include coordination with the experienced rigger, preparation of the tower crane, attachment of parts at the installation site, and execution of the rescue rope.
Conclusion: The findings demonstrate that conducting qualitative risk assessment and modeling the steel frame construction process using FRAM allows for an in-depth understanding of nonlinear conditions and dynamics resulting from escalating technical-social interactions. This approach enables a comprehensive analysis of system safety status.