IRAN OCCUPATIONAL HEALTH JOURNAL
Year:2019 | Volume:16 | Issue:1|Papers Count:8

Background and aims: ELF-EMFs (Extremely Low Frequency Magnetic Fields) are a type of non-ionizing radiation. ELF-EMFs are produced by the electromagnetic radiation of electrical equipment such as air power transmission lines or anything that electrical current passes through it. Several studies have shown that ELF fields can have direct adverse health consequences. It has been indicated that exposure to ELF-EMF could lead to genotoxic effects and DNA cancers damage, an increased risk of some cancers, depression, headaches, sleep disturbances, an increased risk of infertility and adverse pregnancy outcomes. Occupational exposure to ELF-EMF was mainly occurred in industrial processes such as welding which contains electronic elements. Welding is a common indispensable procedure in engineering works and over five million workers around the world are engaged in. Thyroid hormones have a role in fetal growth and development and regulation of the metabolism in adults and any thyroid hormone deficiency can lead to adverse mental health effects such as mood disorders like depression, drowsiness and fatigue. Work forces’ fatigue as an occupational hazard can be considered a significant problem in modern industry, since it can lead to loss in productivity, occurrence of human errors and occupational accident. The aim of this study was to assess exposure to extremely low frequency electromagnetic fields (ELF-EMFs) and its effects on secretion of thyroid hormones associated with symptoms of fatigue on electric arc welding workers. Methods: This case-control study was conducted to investigate the effects of extremely low frequency magnetic fields on level of Triiodothyronine hormone (T3), thyroxine hormone (T4) and thyroid stimulating hormone (TSH) secretion in welders (who are occupationally exposed to ELF-EMFs) and non-welders (as an unexposed group) in a mold making company. Through referring employee's medical records and consultation with occupational medicine specialist, people with known mental and physical illness were excluded from the study. Then 35 arc welders having more than one year of experience were simple randomly selected as exposed group and 35 non-welders were simple randomly selected as unexposed one. The age difference between the two groups should not be more than a year old. A signed informed consent had been obtained from all participants. Ethical approval was granted by the Research Ethics Committee of Qom University of Medical Sciences. In order to determine the level of thyroid hormones, blood samples were taken for both groups at the same time before starting working. Then, the samples were transported to the laboratory and stored at temperature less than-20º C. The enzyme-linked immunosorbent assay (ELISA) test was used to measure the level of T3 and T4 in plasma, and electrochemiluminescence immunoassay (ECLIA) method was used to measure plasma TSH. Extremely low frequency magnetic fields were measured using an electromagnetic field meter. Measurements were carried out in the area of the hand, neck, trunk and head and also at the intervals of 0. 5, 1 and 2 meters of welding equipment, according to NIOSH (National Institute of Occupational Safety and Health) guideline. Fatigue assessment was done using Samn-Perelli seven-point fatigue scale. This questionnaire is a subjective measure tool for assessing the own level of fatigue, where 1 = fully alert, wide awake and 7 = completely exhausted, unable to function effectively. This is sensitive to fatigue outside laboratory conditions and it can be easily administered in the field. Analysis was performed using SPSS v. 20 software. Analytical statistics including t-test, chi-squared test, Analysis of variance (ANOVA) were used to compare the results between the groups. Also, the Pearson correlation coefficient is used to measure the strength of a linear association between variables. Normality of the study data was tested with a 1-sample Kolmogorov-Smirnov test. The significance level was set to 0. 05. Results: Demographic analysis showed that the mean age in exposed and unexposed groups were 38 (± 6. 03) and 39 (± 6. 02) years, respectively. The mean body mass index (BMI) and duration of employment of the exposed and unexposed participants were 25. 76 (± 6. 31) and 26. 04 (± 5. 98) Kg/m2 and 13. 02 (± 5. 20) and 13. 04 (± 4. 11) years, respectively. There was no statistically significant difference between two groups in case of all studied demographic variables (p> 0. 05). The result of Kolmogorov-Smirnov (KS) test showed that all of the studied variables follow a normal distribution (p> 0. 05). The highest exposure level was found in the hand area (2683. 8 mG) and the lowest one was obtained at a distance of 2 meters from the Welding equipment (122. 2 mG). The mean exposure to ELF in exposed group, in all measurement areas, had a significant difference with the unexposed one (p<0. 0001). According to the threshold limit values (TLV) of American Conference of Governmental Industrial Hygienists (ACGIH), occupational exposure limit is between 0. 2 to 60 mT (2, 000 to 600, 000 mG) which can be changed at different frequencies. Based on the obtained results, overall exposure to extremely low frequency magnetic field is less than the recommended values by ACGIH in all participants. The mean levels of T4 and TSH were significantly lower in the exposed group than non-welders (p<0. 05). However, the mean level of T3 in the arc welders was lower than the unexposed group, but this difference was not statistically significant (p<0. 05). Thyroid hormone levels in 23 subjects (65%) of welders fell outside of the normal range at least in case of one the hormones; while thyroid hormone levels only for 15 subjects (42%) of non-welders wasn't in the normal range at least in case of one the hormones. There is no significant correlation between demographic parameters such as age, BMI, and duration of employment with the T3, T4, TSH hormones in exposed and unexposed groups (p>0. 05). The percentage of individual fatigue in welders had a significant difference with non-welders (p<0. 01). There is a weak positive relationship between ELF-MF exposure value and level of thyroid hormones (p>0. 05) and also, the score of fatigue significantly increases by reducing T3 and T4 hormones (p<0. 05). Conclusion: As a result of this study, the blood level of thyroid hormone in the exposed group was less than the unexposed one, so that the mean difference for T4 and TSH hormones were statistically significant. Moreover, the prevalence of the hormone disruption among welders was higher than the unexposed group. According our findings, the fatigue is more common in welders than non-welders. The results showed that welding can be considered one of ELF field sources. Consistent long-term exposure to ELF-EMFs from the welding process may result in abnormalities in thyroid hormones T4 and TSH, and may increase fatigue in welders. Regarding welding processes being widely used; preventive measures to ELF exposure should be adopted. Since there is no practical and cost-effective method for protection against extremely low frequency magnetic fields, it should be better to limit exposure time to these fields. In conclusion, Exposure to ELF-EMFs may disrupt the thyroid hormone secretion such as T4 and TSH levels and may increase the fatigue level. This study is only a starting point and many issues need to be addressed for drawing definite conclusions.

Background and aims: Adipose tissue is biologically superior to energy storage and an active tissue, and secretes proteins such as vaspin, called adipokine. The relationship between fatty tissue and other biological systems of the body is determined through the expression of some bioactive molecules called adipocytokines. Adipokines are involved in various metabolic processes, including appetite regulation, insulin sensitivity and insulin secretion, energy expenditure, cardiovascular function, and inflammation. Vaspin can be considered as an adipokine derived from internal adipose with insulin sensitivities. In humans, vaspin serum concentrations are associated positively with age, body mass index, and insulin sensitivity disorder. Vaspin is a serine protease inhibitor family discovered in 2005 and has a composition of 392 to 395 amino acids. This adipokine was found in the visceral fat tissue of rat, a model of obese animals with type 2 diabetes. Vaspin plays a very important role in the pathogenesis of nonalcoholic fatty liver disease. This substance not only regulates the amount of insulin sensitivity, but also acts as a mediator of inflammatory processes. It has also been reported that vaspin circulation is associated with gender, body fat percentage, glucose, insulin, and insulin resistance. It has been reported that vaspin by reacting oxygen inhibitors can inhibit the inflammatory state of smooth muscle cells. Increasing blood glucose results in oxidative stress, which in turn results in the activation of the nuclear factor and thus an increase in the level of pre-inflammatory cytokines in the bloodstream. Consumption of vaspin in obese rats with high fat diet resulted in improved glucose tolerance and insulin sensitivity and inversely altered expression of genes that are dependent on insulin resistance. Animal studies suggest that effecting vaspin on insulin sensitivity increases its effect on adipose tissue. Therefore, it is suggested that the incremental regulation of vaspin suggests a compensatory mechanism against insulin resistance. Sports activities and healthy living today are topics that we have heard or read much more in a variety of ways about their importance. In fact, most people in the world do sports and physical activity in different ways; however, with the mechanization of lifestyle communities, more people go to inertial and sedentary environments. The results of the researches confirm the theory that all people are convinced that exercise is essential for health and well-being and also regular physical activity is essential for themselves and their children. Few studies have been conducted on the effect of sports activity on vaspin and glycemic indices, which have contradictory results, some suggesting that sports activities increase, decrease or without changes in the levels of vaspin. Therefore, due to the limited and controversial studies and the importance of not engaging in sports activities, this study aimed to investigate the effect of eight weeks of aerobic training and two weeks of detraining on levels of vaspin, glucose, insulin and insulin resistance in inactive men. Methods: In this quasi-experimental and applied study, a design of two-group with pre-testpost-test with repeated measurement with control group was used. To conduct the research, 22 non-active male employees of Islamic Azad University, Fars Science and Research Branch, were selected as statistical sample. In order to conduct this research, a first announcement was made at the level of Islamic Azad University, Fars Science and Research Branch, and all volunteers were invited to participate in this study. Subsequently, during the meeting for all volunteers, the method of conducting research, potential injury and health benefits of the contribution in this study was explained. Then, 22 subjects were selected as the statistical sample among the volunteers. Among the criteria for entering this study, we can point out the lack of drug addiction, the absence of specific diseases such as high blood pressure, diabetes and cardiovascular diseases and the ability to perform exercises until the end of the study period. Further, considering that aerobic power is effective on the variables of the research, aerobic power (maximum oxygen consumption) of all subjects was first measured using Cooper field test, and the subjects regarding the aerobic power were divided into two equal groups including experimental and control groups. It is worth noting that in the present study; the statistical sample was selected based on the reported studies. Subsequently, 48 hours later, all subjects attended the laboratory at 8 AM, and from all of them received 7cc of fasting blood. The experimental group then ran a treadmill for a period of eight weeks, three sessions per week, and each session for 60 minutes with speed of 70% of the heart rate reserve on the treadmill. The control group was asked to do just their daily activities during this time. After eight weeks, blood sampling measured from experimental and control groups at 8 AM similar to the pretest at the same time. The experimental group then interrupted their trainings for two weeks. After two weeks, blood samples gathered again from both experimental and control groups. For analysis of the research findings, Kolmogorov-Smirnov, analysis of variance with repeated measures and independent sample t-tests were used (α = 0. 05). SPSS v. 20 and Excell v. 2010 software were also used. Results: The results of analysis of variance with repeated measures test showed that there were no significant difference in changes of vaspin levels in the pre-test, first post-test and second post-test between experimental and control groups (p= 0. 50); changes in fasting blood glucose levels in pretest, first post-test and second post-test between experimental and control groups (p= 0. 85); changes in insulin levels in pre-test, first post-test and second post test between experimental and control groups (p= 0. 95) and changes in insulin resistance levels in pre-test, first post-test and second post-test between experimental and control groups (p= 0. 65). Also, there were no significant difference in the changes of vaspin levels in pre-test, first post-test and second post-test in experimental (p= 0. 79) and control (P = 0. 61) groups; changes in fasting blood glucose levels in the pre-test, first post test and second post test in experimental (p= 0. 06) and control (p= 0. 23) groups; changes in insulin levels in pretest, first post test and second post test in experimental (p= 0. 55) and control (p= 0. 43) groups and changes in insulin resistance levels in pretest, first post test and second post test in experimental (p= 0. 98) and control (p= 0. 58) groups. Therefore, eight weeks of aerobic training, as well as two weeks of detraining, have no significant effect on serum levels of vaspin, glucose, insulin and insulin resistance in inactive men. Conclusion: Regarding the contradiction in the results of the reported studies, it cannot be determined with certainty that the mechanism of the effect of sports activities on vaspin, however, the exercise and weight loss in collaboration and through mechanisms that are completely separate but related, improve the cardiovascular and metabolic risk factors; So that exercise has important role due to reduced fat storage or changes in the function of adipose tissue cells as an endocrine organ which secreting adipocytokines such as interleukin-6, C-reactive protein and vaspin. Thus, if the exercise does not reduce the number of fat cells or improve the function of these cells, the ability of exercise is limited to adjusting the levels of adipokines, insulin resistance, and inflammation, or that it is not generally seen. According to the results of this study, eight weeks, three sessions per week and each session for 45 minutes running on a treadmill with intensity of 60-70% heart rate reserve had not significant effect on changes of serum levels of vaspin and glycemic indices in staff male; it concluded that eight weeks of aerobic trainings and two weeks of detraining have no significant effect on the levels of vaspin and glycemic indices in staff male.

Background: Miners are exposed to considerable airborne dusts. According to the US Department of Labor Mine Safety and Health Administration (MSHA), the rate of either mortality or morbidity of miners due to their occupations is almost six times higher than other industrial workers. Blasting, crushing, and processing of mineral ores produces particulate emissions in the diverse mining processes. Mineral dust generated by mining can cause systemic toxicity through their chemical speciation and free radical inside of the body could provoke a higher rate of hyperplasia, cancer, and cardiovascular risks. The International Agency for Research on Cancer (IARC) has not classified iron oxide compounds as a carcinogenic compound. However, an increased incidence of lung disease is associated with workers in occupations involving exposure to iron oxide dust or fumes. Generally, exposure to iron oxide particles is suspected to lead to an increased risk of lung cancer in iron ore miners, iron metal welders, iron foundry workers, and iron and steel manufacturers. The cohort epidemiological studies also support a higher risk of lung fibrosis, siderosis, and silicosis for the workers exposed to iron dust or fume. Due to the variable composition of iron ore in mines of diverse geographical locations, the contradictory and conflicting findings from epidemiological studies has been reported. Researchers have also recommended further investigation for the health effects of occupational exposure to iron ore dust in different locations. Iron oxides such as Fe2O3, FeO and Fe3O4 along with crystalline silica are the most prominent dust in iron ore mining. Despite the potential toxicity of Iron compounds, they are essential nutrients and play an important role in the metabolism of hemoglobin, mitochondrial function, enzymatic activity (especially cytochromes), and muscle metabolism, particularly myoglobin. However, an excess dose of iron compounds has been reported in iron accumulation in various organs, especially the liver (resulting in cirrhosis, liver failure, and hepatocellular carcinoma), endocrine organs (causing pituitary and gonadal failure), pancreas (causing diabetes), skin (causing pigmentation), and heart (resulting in cardiomyopathy, heart failure and arrhythmia). Most patients with severe iron overload, could develop cardiac, hepatic, conjunctivitis, choroiditis, and retinitis complications. Thus, early diagnosis and monitoring of workers are essential. Chronic inhalation of excessive concentrations of iron oxide fumes or dust may result in the development of benign pneumoconiosis, called siderosis, which could be observed in radio-graphical examination of the workers. Iron, as a transitive metal and a highly reactive oxidizing agent, can participate in the Fenton reaction, and then by producing hydroxyl radicals leads to lipid peroxidation (LPO). LPO is a chain reaction process initiated by the attack of reactive oxygen species (ROS) and reactive nitrogen species (RNS) on polyunsaturated fatty acid (PUFA) residues of phospholipids, leading to cell membrane damage and consequently to cell death. Several biomarkers of LPO have been established, such as 8-iso-prostaglandin F2α , malondialdehyde, hyroxynonenal (4-NHE), and exhaled breath ethane. Malondialdehyde is the most abundant and stable aldehydic product of LPO and due its simplicity of analysis, it is a widely used biomarker of LPO. Regarding the high prevalence of occupational diseases in iron ore mine workers, the objective of this study was to investigate the occupational exposure of mine workers to respirable dust, iron compounds and determining the correlation of their personal exposure to the biomarker of oxidative stress through the levels of serum malondialdehyde. Methods: The present study was a cross-sectional descriptive-analytic investigation. The study population was selected randomly from non-smoker healthy workers with a minimum working experience of one year. 92 workers of the concentrating and pelletizing plants and 48 office workers were recruited as the exposed and control group respectively. The sampling of respirable dust and iron oxides was performed using a plastic cyclone sampler equipped with mixed cellulose ester membrane filter connected to the SKC sampling pump according to standard methods such as NIOSH-0600, and OSHA-121 respectively. The measurement of respirable dust was conducted through gravimetric analysis, Pre and post weighing of the filter was conducted using an electronic balance (Sartorius-TE124S, precision: 10-5 gr). Analysis of iron oxides was carried out using Atomic Absorption Spectroscopy (Varian220FS). Serum malondialdehyde was measured by a spectrophotometric assay using the ZellBio GmbH kit and visible light spectrophotometer (CECIL CE2021) at a wavelength of 531. 5 nm. The correlation between either respirable dust and iron compounds with serum malondialdehyde was determined by the Spearman correlation statistical test by using SPSS software. Results: According to the results of the Mann-Whitney U test, exposure to general respirable dust, and iron oxides in the exposed and control group were (24. 8, 2. 9) and (0. 59, 0. 023) as mg/m3 respectively. The exposed workers had statistically significantly higher exposure than the control group (p<0. 001). Similarly, the Mann-Whitney test showed the serum malondialdehyde levels in the exposed group (41. 6 μ mol/L) was statistically significantly higher than their corresponding control group (22. 52 μ mol/L) (p< 0. 001). According to the Spearman correlation test, there was a statistically significant positive correlation between the parameters of exposure to respirable dust and iron compounds in the exposed group (r= 0. 835, p< 0. 001). However, the correlation between the parameters of exposure to respirable dust and serum malondialdehyde level (r= 0. 006 and p= 0. 95), or their exposure to respirable iron oxides and serum malondialdehyde level (r= 0. 022 and p= 0. 84) in the exposed group were not statistically significant. Conclusion: According to the occupational exposure limit values provided by the office of Environment and Occupation Health of the Iranian Ministry of Health and Medical Education and the American Conference of Governmental Industrial Hygienists (ACGIH) for the particles not otherwise specified (PNOS), 96. 6% of workers' exposure to respirable dust were higher than the set limit. However, due to the content of crystalline silica in the respirable dust and the probable presence of other toxic compounds such as amphibole asbestos and heavy metals such as Cd, As, Ni, Co, and Hg, the airborne general dust of Gol-e-Gohar mine may not be classified as PNOS and workers' exposure could have a more harmful consequences. In the present study, According to the occupational exposure limit values set by the office of Environment and Occupation Health of the Iranian Ministry of Health and ACGIH for the respirable iron oxide compounds, 38. 5% of workers in exposed group had higher exposure than their corresponding occupational exposure limit. In this study, the content of serum malondialdehyde of exposed workers as a nonspecific biomarker of the exposure to iron dust was statistically significantly higher than the control group. However, the correlation of workers' exposure to either respirable dust or iron compounds was not statistically significant with their serum malondialdehyde. This phenomenon could be due to the limitation of workers in exposed and control group in this study, and possibly other content of iron ore, such as crystalline silica, asbestos, and toxic metals which were quantified in this study. Miscellaneous confounding factors of oxidative stress, such as noise pollution and environmental heat stress have been reported in various studies. Although there were no significant correlation between the exposure of either respirable dust or iron oxide compounds with serum malondialdehyde, excessive workers' exposure to respirable dust and iron oxide compounds and statistically significantly higher serum malondialdehyde levels in the exposed workers compared to those in the control group, indicates the need for a more comprehensive investigation for the environmental and biological monitoring of the Gol Gohar workers. Further studies for monitoring larger exposed and control population, along with the more diverse examination of environmental dust ingredients and a more thorough biological monitoring of workers using a more specific biomarker for iron oxide compounds are recommended for the future study.

Background and aims: Lack of thermal comfort in outdoor environments can cause disorders and diseases, negative impact on productivity and performance, and even can cause death. Therefore, it is important to evaluate it. Various indices and models have been used to assess the level of comfort of humans. In most evaluations has been tried to estimate the comfort level using meteorological data such as temperature, humidity, Wind speed, solar radiation or combinations. These indices provide climate data in a way that reflects individual’ s response to climate conditions and, in a numerical classification, range from very appropriate to very inappropriate. These indices facilitate interpreting the complex effects of atmospheric elements on human comfort and allow comparison of different places from climatic comfort point of view. Today, bioclimatic studies, from human comfort point of view, are the basis of many management plans, especially health and treatment. Therefore, in this study, Becker and neurotic pressure bio climate index were used to evaluate discomfort in three different climates of Iran. Methods: In this study, thermal comfort was assessed in three different climates of Iran based on the Kö ppen climate classification including the semi-arid and cold climate (Arak), the humid subtropical climate (Sari) and the hot desert climates (Bandar Abbas) were done using of Becker and neurotic pressure bio climate index. Becker index known as Cooling Power index (CP) originated in the inclusion of only two climate parameters in the bioclimatic analysis by air temperature and wind speed. Cooling Power index has the advantage of being computed very easily; they are easily understood not only by specialists, but also by the wide public and have a good temporal applicability and availability for the studied territory. The cooling power of the environment depends on the difference between human body temperature and air temperature and also on the wind speed. The Neurotic pressure index determines the physiological pressure to provide comfort between absorption and heat release. The purpose of this index is to describe the comfort level using temperature, humidity and wind speed. This index offers separate equations for temperatures below and greater than 20° C. Meteorological data between 2014-2000 was used from the Meteorological Organization, including temperature, relative humidity and wind speed, to calculate the indices. Then the mean of the mentioned parameters was calculated daily for 15 years. Excel software and SPSS 22, were used for data analysis, descriptive statistics and linear regression were used. Results: The highest and lowest air temperature monthly mean values in Sari were recorded for August (27. 55± 0. 57° C) and January (7. 9± 0. 68° C), respectively. The highest and lowest monthly mean relative humidity values were recorded forDecember (81 ± 2. 6 %) and August (73. 7± 1. 94%), respectively. In Arak and during the surveyed years, the highest average temperature (28. 1± 0. 65) was observed in July, and the lowest average temperature (-1. 14± 1. 94) was observed in January. Also, the highest humidity rate (70. 67± 3. 87) was observed in January and the lowest humidity rate (22. 96± 1. 25) was observed in July. Also in Bandar Abbas, the highest average temperature (34. 27± 0. 26) was observed in July and the lowest average temperature (17. 44± 0. 62) was observed in January. The highest humidity (68. 39± 2. 41) was recorded in August and the lowest humidity rate (57± 4) was in December. The mean of Becker index in Arak, Sari and Bandar Abbas was respectively 15. 76± 6. 3, 13. 73± 5. 2 and 8. 93± 5. 5μ cal/cm2/s. According to the results of this index, the three climates covered cool to hot, warm and sultry. The mean of neurotic pressure index in months with temperatures below 20 ° C in Arak was 672± 148, in the city of Sari, 605. 115. 6 and in Bandar Abbas, 567. 66± 46. 76 kcal/hr/m2 and in months with a temperature above 20 ° C, respectively, was 3. 37± 2. 5. 42± 4. 9 and 11. 64± 7 kcal/hr/m2. Interpretation of this index showed that the studied areas have cold conditions (Arak) to fully uncomfortable condition (Bandar Abbas). Also, there was a high correlation between the two indexes in three different climates (R2> 0. 9). Conclusion: The results of this study showed that the comfort indices reveal the comfort and discomfort periods in three different climates of the country, and despite some differences, show relatively similar manifestations of the comfort climate of under study cities. Results have shown that the studied areas are characterized by biochemical variation from hot to very cold conditions throughout the year. Regarding the advantageous of using these indices, it should be noted that the data measured by meteorological organizations can be used to forecast and timely announcement of heat and cold stresses as well as thermal comfort in different regions. It should be noted that thermal comfort varies with respect to the race, age, type of activity, clothing, metabolism rate, accommodation, etc. Evaluating the trend of thermal comfort indices can identify high-risk areas, which in this context presence of comprehensive and innovative policy making and planning, according to the climate changes and the ability to forecast and control the risks resulting from these changes, seems necessary for community members.

Background: Road traffic accident annually lead to the death of 1. 2 million people and also the disability of some 50 million people in the world. Iran is one of the countries with the highest rates of road accidents in the world. According to the annual statistics by the Iranian Legal Medicine Organization, 15, 932 people have lost their lives in road traffic accidents in 1395 sh. According to figures in this report, over 75% of road deaths occur among men. Driving and guiding a vehicle is required to assign different levels of attention. In this regard, also can be pointed to the role of the mental workload. Mental workload known as a requirement that a duty impose on the available mental and cognitive resources of people. Mental workload is too high or too low can lead to incomplete understanding, inadequate attention and information processing to be inappropriate. A variety of factors can be effect on individuals driving performance and their mental workload such as age, gender, driving character and fatigue. According to studies, mistakes that can lead to accidents, in many cases, are the result of high mental workloads. Measurement of mental workload while driving can reflect the cognitive needs imposed on the driver. Various behavioral, selfreporting and physiological methods have been successfully used so far in order to measure the mental workload. One of the best ways to measure the mental workload is the evaluation of the individuals' reaction time. Reaction time is the time interval between the emergence of a stimulus and the individual's response. Driver’ s gender is one of the possible effective factors that can affect driving performance. This study aimed to assess the effect of gender on young drivers' mental workload and driving performances using a driving simulator. Methods: This cross-sectional study was conducted on 40 young drivers (20-29 years) including 20 women and 20 men in Tehran at 2017. The inclusion criteria for the study were aged 20 to 29 years, filling informed consent to participate in the study, sleeping enough for 8 hours at night before the test, having at least two years of driving experience, driving at least once In the week, lack of driving experience with the driving simulator, having adequate or improved vision for the eyes, or for each eye, did not use psychotropic drugs. Exclusion criteria were included the request of the participants to leave the study, having signs of discomfort caused by the simulator, expressing a physical discomfort after the start of the test for any reason. The driving simulator used in this study is a half-body Pride made by the specialists of the virtual reality group of Khajeh Nasir Tusi Industrial University. The simulator has a computer and graphics card and software tools for simulating intra-city and inter-city roads, freeways, night driving, and driving in snowy, rainy, and foggy conditions. The drivers' performances were evaluated using the PDT reaction time and vehicle lateral deviation variables under two conditions: driving with and without mental calculations. The PDT reaction time test is one of the most common and suitable methods for assessing the performance of drivers and the response time of mental workload in simulator studies. Its validity and reliability have been confirmed in various studies. The Rating Scale Mental Effort (RSME) and the Integrated Workload Scale (IWS) self-report scales were used to estimate the individuals' workload. The main scenario of the study included driving a distance of 20 km on a highway. Results: The mean lateral deviation obtained for female and male drivers was 0. 55 and 0. 51 m respectively, in the driving phase without mental calculations. Moreover in this phase the mean reaction time was 482 ms for females and 450 ms for males. In the driving phase with mental calculation, the mean lateral deviation obtained for female and male drivers was 0. 67 and 0. 62 m and mean reaction time for females and males was 606 ms and 569 ms, respectively. Based on the RSME and the IWS scales, women perceived more mental workload than men. For most variables of the study, however, the difference between male and female values was not significant based on the independent t-test (p> 0. 05). Also, performing mental calculations while driving caused a significant increase (p = 0. 05) in the values of the vehicle's lateral deviation, the drivers' reaction time, and the RSME and the IWS scales. Conclusion: Although there were no statistically significant differences in the study variables between males and females; the mean value of the lateral deviation for women was slightly higher than men, and their driving performance was slightly weaker than men. More lateral deviation of the vehicle should be considered in the process of doing mental calculation, because the high lateral deflection, especially automotive deviation to the left can be dangerous and even fatal accidents. Another important variable used in this study to evaluate the performance of drivers was reaction time. The results showed that doing mental calculations increased the imposed mental workload on drivers and decreased their performance, in other words, increased their reaction time to the visual stimulus. The other variable of this study, which is directly related to the PDT's task, is the number of non-responses to the image stimulator in the PDT's task. The important point is that the performance of female drivers was weaker as well as the reaction time in both phases without mental and mental calculus. This result may be due to the fact that women drivers tend to avoid the risk, change their traffic line counter to traffic flow and having more difficulty to parking. Women's traffic accidents are also related to cognitive errors or misconceptions judgmental about spatial perception, and women are less confident in driving. Regarding the use of self-report scales, it should also be noted that in both phases, without mental calculation and calculations, the amount of perceived mental workload by women was somewhat higher than of men based on RSME. In other words, these results confirm the results of the lateral deviation of the vehicle, reaction time and the number of non-response to the visual stimulus. Women's drivers seem to have suffered a higher mental load than male drivers. In the IWS scale, it should also be noted that its value in the female group was higher than that of men which these results also confirm the other results of this study variables. In all of these cases, the performance of the women's group was weaker and the group suffered more mental workload. Another important discussion in this study was the comparison of the performance and the level of perceived mental workload by drivers during without mental calculations and calculations. Accordingly, the difference between the values of all variables in the stages without mental calculations and calculations were significant and performing mental calculations has reduced driving performance and caused higher levels of imposed mental workload on drivers. Driving performance decreases with increasing duty levels and performing mental calculations. The other objective of this study was to study the relationship between the variables of the study. According to the findings, there was a significant correlation of over 0. 7 between lateral deviation and reaction time in both stages.

Background and aims: Performance assessment and performance indicators have a great importance in all aspects of life. These indicators can determine appropriate responses for improvement. In the past, the safety and health performance of organizations was measured using some indicators from the USA Occupational Health and Safety Administration (OSHA) such as the Rate of Recorded Injuries, the Rate of Lost Days, the Rate of Workers' Complaints, etc. Although safety and health improvements or weaknesses are cleared by the OSHA indicators, improvement procedures are a missing part. An organization is conducting safety and health measures to control health and safety risks. Safety performance indicators are divided into two main categories: the leading and the lagging indicators. The leading indicators are the organization's actions for predicting and preventing incidents and accidents before they occur, while the lagging indicators measure the organization's performance after the occurrence of the accidents to reduce its consequences. Sustainable urban development is a high-profile goal, and its realization in metropolitan areas requires the use of efficient management practices and extensive planning. The extent and complexity of urban issues and the urban ever-increasing development have made urban management a difficult task. In addition to issues such as transportation, urban planning and management is one of the important factors that has a main influence on urban constructive factors. The Integrated Health, Safety and Environment Management System (HSE-MS), by providing the appropriate structure and model, manages all these policies and plans, and, in addition to creating a specific order in the implementation of these programs, it helps to centralize costs and improve the economic status of the organization and the achievement of sustainable urban development. Measuring the performance of an organization in the HSE field is a precondition for continuous improvement. Different organizations and industries need to design performance measurement indicators to assess and monitor the performance of the HSE management system. Determining the performance assessment indicators of HSE in addition to measuring the management system performance can lead to systematic identification of improvement points and reduction of HSE related risk factors and ultimately lead to increased organizational productivity. Although there are some retrospective and prospective HSE performance assessment indicators, but these indicators are almost result-oriented and cannot measure the creation and institutionalization of processes related to the seven components of the health, safety and environmental management system. What matters here is to create an appropriate method with sufficient accuracy to determine the effectiveness of the system. This research, while introducing an innovative model for quantitative ranking of different municipal areas of metropolitans according to the HSE performance assessment using AHP technique, is to determine the key indicators of urban HSE performance assessment. Methods: This descriptive-applied study was conducted in four steps. Step 1: Selecting HSE Performance Measurement Indicators and Urban Management. In the first step, a variety of safety and health management systems (HSE-MS, OHSAS 18001, ISO 14001, etc. ), a variety of existing national and international health and safety assessment methods, guidelines, and requirements for safety and health management systems for determining the performance measurement indicators were studied. At this step, through the field visits of the different areas of the municipality and observing work processes, interviewing and organizing various meetings with HSE managers and experts, and studying documents, the HSE performance assessment indicators were categorized to three areas including process-oriented, result-oriented and urban management. Step 2: Selecting the components of the performance monitoring system: The findings suggest that the use of a systematic approach in different domains, in addition to integrating activities, has improved efficiency and effectiveness and increased operational efficiency. Accordingly, many organizations have set up various health, safety and environmental management systems as the basis of operations. The use of the main components of an integrated management system to identify weaknesses or strengths of the system is one of the effective measures of performance. At this step, after determining the assessment axes, the performance assessment components were identified for each of the performance monitoring axes. Step 3: Development of Urban HSE Performance Assessment Indicators: At this step, the indicators for assessing the performance of the urban HSE management system were determined based on the components of each of the performance monitoring axes. According to the main components, the HSE management system included 18 components such as commitment and leadership, policy, resources, etc. Also, in the urban management part 6 components including economic sustainability, social sustainability, architecture and urbanization, demographics, political, legal, and industrial were considered. Indicators related to the result performance were also developed based on the components of the HSE performance output monitoring system in the six areas including safety, health, environment, education, culture and HSE of citizenship. Step 4: Select Key Performance Indicators: To create an effective HSE-MS performance measurement method, it is necessary to reduce the number of LPIs to fewer or the most important KPIs. This means that among the existing indicators, the best and most important indicators are selected based on the considered criteria. At this step, key performance indicators were selected from all the extracted indicators based on the elements of the HSE management system using the AHP method. All indicators were compared in pairs and each of them was prioritized as a number between 1-9, 1 as the lowest priority and 9 as the most. Couple comparisons were conducted based on SMART criteria and expert’ s opinion. In this study, the paired comparison of axes and performance indicators and determining the weight vector of the indicators was performed using Expert Choice11 software. Results: In addition to examining the HSE management systems deployed in the municipalities, as well as using previous studies, the axes and indicators for assessing the performance of the urban HSE management system were determined. Of the 30 components and 155 indicators of performance assessment, 18 components and 98 indicators were related to monitoring of management system of HSE based on the seven elements and sub elements of the Health, Safety and Environment Management System (HSE-MS). Performance output and urban management axes with 40 and 17 indicators, respectively, had a smaller share of the total indicators developed. Among the process-oriented performance axes, the commitment and leadership axes (0. 198) and the HSE records of occupations (0. 016) had the highest and lowest weight, respectively. The safety components (0. 247) and training (0. 150) had the highest and lowest weight in the result-oriented performance axes respectively and economic sustainability (0. 301) and architecture and urban planning (0. 122) had the highest and lowest weight among the urban management functional axes, respectively. After weighting the indicators for measuring performance, 70 indicators that had the highest weight were selected as key performance indicators. Of the 70 indicators, 47, 16 and 7 indicators are related to the HSE process, the result and urban management, respectively. Among the functional sub-axes of the HSE process, accident management, inspection, and audit each with five key performance indicators, had the highest measurement index compared to other HSE process sub axes. In the functional axis of the HSE result, the sub-axes of ecology with 4 key performance indicators and the sub-axes of safety and health, each with 3 indicators, had the highest number of indicators. In the urban management axis, sub-axes of socio-cultural and architecture and urbanism, each with two key performance indicators, had 4 indicators of the total 70 selected key performance indicators. Conclusion: The determination of HSE performance indicators in addition to the components of the HSE management system should be performed based on the type of macro-management structure and other influential parameters of the organization. The study of the municipal management structure shows that the extracted indicators based on the components of the HSE management system alone cannot cover the urban HSE performance because of factors such as economic sustainability, socio-cultural, demographic, architectural, urban, and industrial-industrial criteria that can significantly affect the performance status of the HSE management system of a city. Therefore, it is essential to design and codify indicators and all aspects of the management system in order to achieve the most possible accuracy and reliability.

Background: Anthropometry is a branch of human science that considers the physical measurement of the human body, especially size and shape. One application of anthropometrical data in ergonomics is to design working space and the development of industrialized products. Therefore, anthropometrical study on tools, equipment and workstations, which are designed based on the physical dimensions of the workers, can increase productivity. According to statistics, 32% of workers possess awkward postures, and 15% use improper tools while working. These increases the possibility of work-related injuries, particularly musculoskeletal disorders. Therefore, most countries have made great efforts to build own anthropometrics databases for various groups of citizens. Due to the lack of comprehensive databases in Iran, often information from the Western countries, especially the United States are being used. The western nations anthropometric dimensions differ with that of the Iranian population, and western manufacturers design and develop tools and machines based on their own criteria. The mismatching of these designed tools and workstations with the dimensions of the Iranian user's body can cause complications such as fatigue or other physical damage. So, Iranian researchers have suggested that at least one comprehensive, up-to-date and general national database is needed. The results of several studies have shown a correlation between the dimensions of a body. These correlations can be used to create regression equations for estimating anthropometric dimensions. Identifying, categorizing, and determining the type of relationship between anthropometric dimensions play a significant role in treatment, fitness talent, and clothing production, etc. But, the relationship between these dimensions is affected by the environmental, economic and social factors’ change. The important affecting physical factors include age, sex, race, body structure, occupation, diet, and physical activity. Among these factors, the race has a very critical role in the variation of body size. So, the differences among diverse races are more than the variations between different nations. Ethnic diversity is a crucial factor that can affect anthropometric data and its application areas. For example, this variety in body dimensions between people with different sex and race can produce many problems in product design. Therefore, of a modern method is essential to build a comprehensive anthropometric database from different races in the country. This is to consider the dificulties of extracting appropriate information from massive data and transforming them into knowledge on one hand, and time-consuming and high expense process for collecting data on the other hand, especially in the Iranian population with many races. Data mining is a new method used to extract useful and unknown information from raw data. Classification is a data mining function that assigns items in a collection to target categories or classes. The goal of classification is to accurately predict the target class for each case in the data. Decision Tree is one of the easiest and popular classification algorithms to understand and interpret. It can be utilized for both classification and regression kind of problem. It can also remove part of the consumed time and expense of collecting anthropometric data. Therefore, this study was intended to investigate and identify the most important factors of ethnic differences in anthropometric dimensions of Iranian workers using the decision tree. Materials and Methods: The present research is a methodological study using the classification systems in the field of data mining. The sample of the study was anthropometric raw data (37 dimensions) of 3720 subjects (3, 000 men and 720 women) from six races (Fars, Turks, Kurds, Lars, Baluch, and Arabs) of Iranian workers. The decision tree (DT) method was used to identify the most important factors of racial differences in anthropometric dimensions of Iranian workers. The WEKA software (version 3. 6. 12) was used to analyze data and implement data mining algorithms. In the case of the WEKA system, the data is extracted and translated into a standard format we call ARFF, (Attribute-Relation File Format). In the current study, the preprocessing operation on raw data performed by using a classification. Data preprocessing is one of the most critical steps in a data mining process which deals with the preparation and transformation of the initial dataset. Data preprocessing methods are divided into, data cleaning, data integration, data transformation, data reduction categories. Data cleaning routines work to clean the data by filling in missing values, smoothing noisy data, identifying or removing outliers, and resolving inconsistencies. Dirty data can cause confusion for the mining procedure, thus removing these data is a more appropriate method. For data preparation, first of all, missing data values identified by using statistical methods and then to replacing the lost data, the PLS Filter and Missing Class Values algorithms were used in the WEKA software. These algorithms first classify the data and compute the average value for each class and fill the missing data of each class with the mean value of that class. Distorted data also eliminated by using the Remove Useless algorithm. Later data preparation, Principal Components Analysis (PCA), one of the most used methods, implemented. It is a statistical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables (entities each of which takes on various numerical values) into a set of values of linearly uncorrelated variables called principal components. The primary motivation behind PCA is to reduce, or summarize, a large number of variables into a smaller number of derived variables that may be readily visualized in 2-or 3-dimensional space. The new set of variables created by PCA can be used in other analyses, but most commonly as a new set of axes on which to plot your multivariate data. After data preparation, the data are standardized and then the KMO factor is calculated. The KMO factor measure of sampling adequacy and compares the observed correlations and partial correlations among the original variables. The KMO increases with an increase of the number of variables and the correlation coefficients between them but does not much depend on the sample size. Specifically, correlation matrices with KMO< 0. 5 are entirely inappropriate whereas those with KMO below 0. 6– 0. 7 must be treated with caution. Thereafter, the decision tree technique was applied. This technique is a tree-like structure that describes the set of rules that led to the decision, and the ease of interpretation is one of its most important features. This technique is used for categorization and is a graphical method for comparing alternative competition and assigning value to them by combining uncertainties, costs, and repayments by specific number values, which usually consists of several nodes called nodes Inputs and outputs are known. The rules created in the decision tree are also "if" and "then". In each node, you can also split more than two. The CHAID algorithm used to splits the target into two or more categories that are called the initial, or parent nodes. Results: For the analysis of the main factors, the 37 variables (anthropometric dimensions) converted to standard values. KMO value for the total data was 0. 947. Since the obtained KMO (0. 95) value was greater than the considered criterion (0. 7). The existence of the necessary correlation between the input variables confirms the main factors analysis. The result of the analysis indicated, of the 37 anthropometric input variables, only 21 variables had a coefficient of above 0. 7 in the seven extracted factors. The remaining 16 variables had little importance due to their high correlation with the main variables and excluded from the analysis cycle. In the decision tree, the race variable selected as the target variable or dependent variable, and its relation with 21 anthropometric variables examined. The optimal number of clusters obtained was 7 clusters. After entering and determining the type of data and dividing them into two sets: one with 70 percent of the source data, for training the model, and one with 30 percent of the source data, for testing the model. This default was chosen because a 70-30 ratio is often used in data mining. The results of the study disclosed that the distinctive factors in categorizing and creating ethnic differences among men were the Shoulder height in sitting position, the eye height in sitting position, the elbow-fingers length, bi-acromial breadth, the width of foot and length of the head, and among the women, Face Breadth, bi-acromial breadth and the length of the elbow-tip of the fingers. Conclusion: Identification of distinctive factors in the classification of racial differences is one of the main findings of the present research in various ethnic groups. According to the results of this study, these factors in Iranian women and men were different and regardless of race, the following conclusions are made; the distinguishing factors in men are related to anatomical factors (temple) and in women related to facial aesthetics (beauty). The results of this study also confirm the utility of using the decision tree method to investigate the interactions between predictor variables that can be identified the most important determinants of race by combining different nodes in the overall structure. The results from this study verified the using decision tree as an effective method of identifying important variables for classification and detection of racial differences in the anthropometric field. Furthermore, this finding could be used to designing optimal ergonomic workstations for Iranian workers with different Races, moreover to applications in the manufactures and design process, can be used in other cases such as forensic medicine for diagnosis and making orthopedic products.

Background: Undoubtedly, noise and vibration are major problems of industrial world and lot of people are very exposed to these phenomena in their workplace or residential areas. Researchers have shown that exposure to noise may increase the risks related to personal health, like nervous frailty, extreme irritability, muscle cramps, stress and anxiety, dizziness, headache and migraine, anger, loss of body balance, vomiting, pain, hypertension, high blood pressure, cardiovascular problems, deterioration of sleep quality, mental stress, etc. However, the purpose of this study was to assess and control and reduce the risks resulting from noise in the reduction unit 2 of a steel industry. Methods: This study was conducted in two steps. 1) Evaluation of noise pollution in the compressor room and its surrounding: For this purpose, total sound pressure level (SPL) and SPLpeak were measured in the places where workers worked or were traveled. The parameters were measured in the mentioned places according to a grid pattern in both the compressor turn on/off. Because the workers exposed to a noise fluctuating, in addition to SPL analysis on the octave-band frequencies to determine critical frequency when the compressor was switched on, the value of Leq was also measured. The critical frequency is very important in noise control issues. The measurements were performed by using sound level meter, model of “ B&K 2231. ” The apparatus was calibrated before and after measurements by using “ B&K 4230 calibrator. ” 2) Noise control measurements: After identifying noise leakage paths to outside of the compressor room, noise was controlled in door, wall-fans and roof window area through installing a silencer on the wall-fans and redesigning the door and the roof window using the previous step data. Results: Inside the compressor room, the total sound pressure level and the critical frequency was estimated 106. 2 dB (A) and of 250 Hz in the Lin network, respectively. The total sound pressure level in the area around the compressor and the critical frequency were also estimated 94. 3 dB (A) and 2000 Hz respectively. Moreover, the value of Leq was more than the threshold value (<85 dB) at all measured stations. In order to control the noise in the area of the fans, considering the noise assessment and the critical frequency, there was used an absorption silencer with glass wool as adsorbent material. To control noise at the door and roof window, there was designed and installed a steel door with dimensions of 3. 9 * 2. 13 meter and thickness of 1. 5 mm which was filled by a noise-adsorbent 40 mm of glass wool and attached to a metal grid. Moreover, to control noise in the roof window was applied a structure with the same specifications, but with the different dimensions (4. 2 * 4. 2 m and 7 mm mesh diameter). However, the results related to before and after implementation of the control measurements showed an acceptable attenuation in the SPL (91. 8%). The average SPL before and after implementation of the control measurements was 95 and 87. 2 dBA, respectively which this value was an acceptable level in comparison with background noise, i. e., 86. 4 dBA. On the other hand, the slight difference between the mean value of the background sound pressure level and the average of controlled sound pressure level (0. 8 dB) is due to factors such as temperature, variations in sound at different positions, generated noise sources (off or on and so no) and the movement of fluids in the pipes and so on. Conclusion: The results of the field study indicated that door, window and roof window were identified as the main paths of noise leakage to outside of the compressor room. Therefore, the implementation of the control measurements could be reduced to an acceptable level, but due to high background noise level even after the implementation of the control measurements, the noise level was lesser than the maximum permissible level (85 dB). Therefore, there were presented a few recommendations such as controlling the other sources of noise (e. g. moving fluid through pipes), utilizing the hearing protection devices and how to choose them properly to reduce background noise and the protection of workers against noise.