Showing 8 results for Soltanzadeh
R. Golmohammadi , H. Ebrahimi, M. Fallahi, A. Soltanzadeh, S. S. Mousavi,
Volume 4, Issue 1 (5-2014)
Abstract
Introduction: Electromagnetic field emitted by laptops are known as extremely low frequency (ELF) Waves. The aim of this study was to investigate the intensity of electric and magnetic field with extremely low frequency emitted by common laptops.
.
Material and Method: Intensity of electric and magnetic field were measured on four sides of 40 common by used laptop at the distance of 30, 60 and 90 cm. Measurements ere done according to standard in four functional model including: non-performing turned on, sleep mode, performing office program and performing audio visual files.
.
Result: Magnetic field values for all laptops were almost constant and about 28-32 mA/m. The results of measurements related to the electric field showed different values at distances of 30, 60 and 90 cm around the laptops on four sides. Moreover, mean electric field on the keyboard at the four operating modes were statistically different for DELL and hp laptops (P< 0/05).
.
Conclusion: The results of this study showed that laptops produce extremely low frequency (ELF) electric and magnetic fields which their intensity depends on laptop type, laptop operation mode and the location of the measurement.
Ahmad Soltanzadeh, Hamidreza Heidari, Heidar Mohammad, Abolfazl Mohammadbeigi, Vali Sarsangi, Milad Darakhshan Jazari,
Volume 9, Issue 4 (12-2019)
Abstract
Introduction: The causal analysis of occupational accidents’ severity in the chemical industries may improve safety design programs in these industries. This comprehensive study was implemented to analyze the factors affecting occupational accidents’ severity in the chemical industries.
Methods and Materials: An analytical study was conducted in 22 chemical industries during 2016-2017. The study data included 41 independent factors and 872 accidents in a ten-year period (2006-2015) as a dependent variable. Feature selection algorithm and multiplied linear regression techniques were used to analyze this study.
Results: Accident severity rate mean was calculated 214.63 ± 145.12. The results of feature selection showed that 30 factors had high impacts on the severity of accidents. In addition, based on regression analysis, the severity of accidents in the chemical industries was affected by 22 individuals, organizational, HSE training, risk management, unsafe conditions and unsafe acts, as well as accident types (p<0.05).
Conclusion: The findings of this study confirmed that accidents’ severity in the chemical industry followed the multi-factorial theory. In addition, the main finding of this study indicated that the combination of features selection algorithm and multiple linear regression methods can be useful and applicable for comprehensive analysis of accidents and other HSE data.
Fatemeh Zameni, Parvin Nasiri, Mohsen Mahdinia, Ahmad Soltanzadeh,
Volume 11, Issue 1 (3-2021)
Abstract
Introduction: Damage to occupational health is one of the major challenges in the industry. Various studies have shown that productivity in industries has a significant relationship with occupational health. In addition, employee’s health in the workplace can be affected by a variety of variables i.e., job stress, job satisfaction, and work in unconventional shifts. Therefore, the purpose of this study was to evaluate the causal relationships of shift work, job stress, job satisfaction with the occupational health level in a petrochemical industry.
Material and Methods: This cross-sectional study was implemented in 2017. The study sample consisted of 20 HSE experts selected using purposeful judgment sampling. A 4×4 matrix questionnaire consisting of four main parameters i.e., shift work, job stress and job satisfaction with occupational health level, was used for data acquisition. Data analysis was done using MATLAB software and Fuzzy DEMATEL method. Also, for each variable, two key values of D+R and D-R were calculated. These values show the degree of interaction and the type of interaction of the variable with other variables, respectively.
Results: Sixty percent of the experts participating in this study were male and 40.0% were female. Only 10.0% of the participants had a PhD degree. In addition, the mean age and the mean work experience of the subjects were 39.64±9.34 and 10.22±7.10 years, respectively. The parameters of shift work and job satisfaction were identified as an effective factor due to the positive values of D-R while occupational health variable with negative value of D-R, was considered as an affected factor. In addition, these results showed that the effect of these parameters on health is different with both direct and indirect mechanisms.
Conclusion: Using the Fuzzy DEMATEL method, our findings indicated that occupational health in the large industries can be influenced by different parameters with different sizes. Considering the interactions among these parameters in health analysis and the affecting factors, therefore, is very important. So, the health level in challenging industrial environment such as petrochemical industries can be affected by shift work as a root cause. This root cause, along with job satisfaction, has a significant effect on increasing stress levels and reducing health levels. Accordingly, any action to increase the health level should focus on improving shift patterns and increasing the level of job satisfaction of employees as a pivotal root and affecting causes on health level.
Mohsen Mahdinia, Mostafa Mirzaei Aliabadi, Ahmad Soltanzadeh, Ali Reza Soltanian, Iraj Mohammadfam,
Volume 11, Issue 2 (6-2021)
Abstract
Introduction: Safety situation awareness is an important element affecting operator's reliability and safety performance, which is influenced by various variables. Identification of these variables and their relationship will play a major role in optimizing control measures. The present study was conducted for this purpose.
Material and Methods: This study was based on the situation awareness, expert’s opinions and use of a Fuzzy multi-criteria decision-making method. Triangular fuzzy numbers was used to quantify the experts' judgments and to reduce the errors that result from theirs’ subjective evaluation on the relationships between the variables.
Results: The results showed that the studied organizational variables together with "safety/g knowledge" and "experience in job/specific task” are the most important predictive variables of situation awareness. Among the organizational variables, "Organizational Safety Attitudes", "Safe System Design" and "Education" are the most important determinants of safety situation awareness.
Conclusion: Fuzzy logic was used to aggregate expert opinions to determine the most important variables affecting situation awareness and their cause-effect relationships. Organizational variables are the main determinants of situation awareness. To improve situation awareness, the best results are obtained by modifying effective root variables, i.e., organizational variables and some individual variables.
Davood Panahi, Mohsen Sadeghi-Yarandi, Noradin Gharari, Zahra Aghajani Aliabadi, Ahmad Soltanzadeh,
Volume 11, Issue 2 (6-2021)
Abstract
Introduction: Considering the importance of implementing occupational safety and health management systems for the prevention of various diseases in the workplace, as well as determining the notability and role of induction and implementation of occupational health management systems in controlling and reducing COVID-19 outbreak in work environments, as one of the most sensitive and important of society sectors, this study aimed to compare the prevalence of Covid-19 disease in two groups of industries with and without occupational health management systems and related management risk factors in several industries, in Iran.
Material and Methods: This cross-sectional study was performed in May 2020 during the outbreak of coronavirus in some industries under Shahid Beheshti University of Medical Sciences’ supervision. During the present study, 70 industries included 24 industries active in chemical products, 6 industries of automotive parts manufacturing, 14 industries of home appliance manufacturing, 16 industries of health and cosmetics products, 4 industries of metal products, and six service companies were studied. The studied population included two industries with an occupational health management system (33 industries) and industries without an occupational health management system (37 industries). In this study, a checklist was designed to collect study data based on the requirements and parameters of occupational health management systems, as well as information related to infectious diseases such as COVID-19, which included information on COVID-19 disease in two groups of studied industry, occupational medicine, biological hazards risk management, occupational health information management system, training, and employee participation, as well as the management parameters of COVID-19 outbreak. Statistical analysis of the study data was performed using the Chi-square test and Fisher’s exact test by SPSS. 23 software.
Results: The number of workers working in the two groups of industries with and without occupational health management systems was 673 and 708, respectively. Among 33 industries with occupational health management systems, 12.1% industries had health, safety, and environment management system (HSE-MS), 66.7% industries had OHSAS 18001:2007 standard, and 21.2% industries also had ISO 45001:2018 certification. It was found that the prevalence of Covid-19 disease in those industries without occupational health management systems was significantly higher (p <0.05). It has been found that Covid-19 outbreak in industries without occupational health management systems was significantly higher (p<0.05). The findings also showed that there was a significant difference between the parameters of occupational medicine, risk management of biological hazards, occupational health information management system, training and employee participation, as well as the management parameters of COVID-19 disease in the two groups of studied industries (p<0.05).
Conclusion: The findings of the present study indicated that there was a significant relationship between the scores of occupational medicine parameters and occupational health information management system, risk management of biological hazards, training and employee participation, management of COVID-19 and finally the prevalence of the disease among industries with or without occupational health management system. So, implementation and establishment of occupational health management systems can be an effective step in reducing the prevalence of viral and infectious diseases such as COVID-19.
Ali Fardi, Mohammad Karkhaneh, Hamidreza Heidari, Abolfazl Mohammadbeigi, Ahmad Soltanzadeh,
Volume 12, Issue 2 (6-2022)
Abstract
Introduction: Methane is one of the most widely used gases in industries with a high flammability potential. This study aimed to evaluate the efficiency of ventilation systems installed on methane valve pits based on hazardous areas classification.
Material and Methods: This study was implemented in a steel industry in Qom Province in 2019. The tools used in this study were a DELTA OHM pitot tube (DO-2003) to measure wind speed, EPA Protocol for equipment leak emission estimates (U.S. Environmental Protection Agency) and IEC-60079-10 for evaluating the safety of ventilation of methane valve pits.
Results: The methane LELm was about 0.0334 kg/m3, and the volume of the release area was approximately VZ = 0.053 m3. The expected leak emissions were within the Vz < 0.1 m3 range. The ventilation system embedded on methane distribution pipelines was not effective for openings with diameters of more than 0.3 mm and the volume of gas inside the valve pits would quickly exceed high ventilation border which might lead to a dangerous accumulation of gas in the valve pits.
Conclusion: Given that a very small opening or leak in gas transmission valves may lead to the formation of an explosive atmosphere, it is essential to monitor methane before entering the valve pit area and performing any operations on valve pits.
Ahmad Soltanzadeh, Iraj Mohammadfam,
Volume 12, Issue 3 (9-2022)
Abstract
Introduction: Nearly half of occupational accidents in Iran occur in construction sites. Therefore, modeling of occupational accidents in these sites is one of the solutions to design safety strategies to reduce occupational accidents in the field of construction. This study was designed and conducted with the aim of modeling the cause-consequence of accidents in construction sites.
Material and Methods: This study was conducted based on a retrospective analysis of 10-year accident data (2010-2019) in Iranian construction sites in 2020. The main variable included the types of occupational accidents in construction sites. The study tool included accidents checklist as well as a detailed report of the studiedaccidents. The required data were collected based on a conceptual model designed to model the cause-consequence of accidents in the construction sites. Cause-consequence modeling of the studied accidents has been done based on the structural equation modeling and using IBM SPSS AMOS v. 22.0.
Results: The frequency of the studied accidents was 3854 accidents. The annual averages of AFR and ASR indices were 17.27 ± 8.54 and 322.42 ± 44.23 days, respectively. The results of cause-consequence modeling of these construction accidents showed that individual and occupational, safety training and risk assessment factors as well as variables related to these factors have a negative and significant relationship with the indicators of the construction accidents, and the factors of environmental conditions and unsafe acts and variables belonged to these factors have a positive and significant relationship with these indicators (p < 0.05).
Conclusion: The findings of the study revealed that the highest impact factors on accident indicators were related to safety training, risk assessment and unsafe acts and their variables. Therefore, the results of this modeling can help to design safety strategies in construction sites.
Narges Kaydani, Mohsen Sadeghi-Yarandi, Kourosh Zare, Mojdeh Bonyadi, Ahmad Soltanzadeh,
Volume 14, Issue 3 (10-2024)
Abstract
Introduction: Shift work combined with the nature of duty in occupations such as nursing can lead to the spread of psychological consequences and disorders in nurses. The aim of this study was investigating the cognitive and psycho-social consequences associated with shift work in nurses.
Material and Methods: This study was performed in 7 hospitals in 2023. The study population was 636 nurses. Data collection tool in this study was part of a comprehensive questionnaire that translated and modified by Choobineh et al. The data were analyzed using IBM SPSS software v. 22.0, and significance level in this study was considered 0.05.
Results: Out of 636 studied nurses, 474 were shift workers and 162 were day workers. The means of age and work experience of the study population were 37.26±5.25 years and 11.60±4.78 years, respectively. The results showed that the prevalence of psychological consequences in the shift workers group was significantly more than day work nurses (p<0.05). The highest prevalence of cognitive and psycho-social consequences in shift work nurses were related to fatigue (39.66%), insomnia (36.08) and decreased sleep quality (35.44%), respectively.
Conclusion: The findings of this study indicated that the parameters of the shift work system, working hours per week, education and hospital ward are the most important factors affecting the prevalence of cognitive and psycho-social consequences and sleep disorders in the nurses. Therefore, it is suggested that a separate program should be designed and implemented for each hospital ward to control and manage the psychological consequences associated with shift work in nurses.
