Concerns about health problems due to the increasing use of mobile phones are growing. Excessive use of mobile phones can affect the quality of sleep as one of the important issues in the health literature and general health of people. Therefore, this study investigated the relationship between the excessive use of mobile phones and general health and quality of sleep on 450 Occupational Health and Safety (OH&S) students in five universities of medical sciences in the North East of Iran in 2014. To achieve this objective, special questionnaires that included Cell Phone Overuse Scale, Pittsburgh's Sleep Quality Index (PSQI) and General Health Questionnaire (GHQ) were used, respectively. In addition to descriptive statistical methods, independent t-test, Pearson correlation, analysis of variance (ANOVA) and multiple regression tests were performed. The results revealed that half of the students had a poor level of sleep quality and most of them were considered unhealthy. The Pearson correlation co-efficient indicated a significant association between the excessive use of mobile phones and the total score of general health and the quality of sleep. In addition, the results of the multiple regression showed that the excessive use of mobile phones has a significant relationship between each of the four subscales of general health and the quality of sleep. Furthermore, the results of the multivariate regression indicated that the quality of sleep has a simultaneous effect on each of the four scales of the general health. Overall, a simultaneous study of the effects of the mobile phones on the quality of sleep and the general health could be considered as a trigger to employ some intervention programs to improve their general health status, quality of sleep and consequently educational performance.

Objectives: The study objective was to assess hydration status by measuring USG among construction workers in Iran. Materials and Methods:The study design was comparative and experimental. Sixty participants were randomly selected from the construction workers from a construction campus with a similar type of work, climate and diet and formed 2 groups (individuals exposed to the sun and non-exposed individuals). TWL and USG were measured in both groups on 2 consequent days, at the beginning, mid and end of the work shift. Results: USG test showed that mean USG was 1.0213±0.0054 in the control group and in the exposed group, where it was significantly higher, it amounted to 1.026±0.005. In the exposed group, 38% of workers had a USG level between 1.026-1.030, representing a higher risk of heat illness and impaired performance and 12.72% had a USG level above 1.030 representing a clinically dehydrated status, while this proportion in the control group was 15.2% and 0.58%, respectively. The mean TWL index measure was 215.8±5.2 W/m 2 for the control group and 144±9.8 W/m 2 for the exposed group, where, again, it was significantly higher. The Pearson correlation measure showed a significant correlation between USG and TWL. Conclusions: Strong correlation between TWL, as an indicator of thermal stress and USG shows that USG can be considered as a predictor of thermal stress. The difference between USG among the exposed and non-exposed workers and the increase in USG during midday work show the sensitivity of this measure in different thermal and climatic conditions, whereas, the high level of dehydration among workers despite acceptable TWL level, shows that heat stress management without considering the real hydration status of workers, is insufficient.

Background Metabolic syndrome (MetS) is a major public health concern due to its high prevalence and association with heart disease and diabetes. Artificial neural networks (ANN) are emerging as a reliable means of modelling relationships towards understanding complex illness situations such as MetS. Using ANN, this research sought to clarify predictors of metabolic syndrome (MetS) in a working age population. Methods Four hundred sixty-eight employees of an oil refinery in Iran consented to providing anthropometric and biochemical measurements, and survey data pertaining to lifestyle, work-related stressors and sleep variables. National Cholesterol Education Programme Adult Treatment Panel ІІI criteria was used for determining MetS status. The Management Standards Indicator Tool and STOP-BANG questionnaire were used to measure work-related stress and obstructive sleep apnoea respectively. With 17 input variables, multilayer perceptron was used to develop ANNs in 16 rounds of learning. ANNs were compared to logistic regression models using the mean squared error criterion for validation. Results Sex, age, exercise habit, smoking, high risk of obstructive sleep apnoea, and work-related stressors, particularly Role, all significantly affected the odds of MetS, but shiftworking did not. Prediction accuracy for an ANN using two hidden layers and all available input variables was 89%, compared to 72% for the logistic regression model. Sensitivity was 82.5% for ANN compared to 67.5% for the logistic regression, while specificities were 92.2 and 74% respectively. Conclusions Our analyses indicate that ANN models which include psychosocial stressors and sleep variables as well as biomedical and clinical variables perform well in predicting MetS. The findings can be helpful in designing preventative strategies to reduce the cost of healthcare associated with MetS in the workplace.

BACKGROUND: Work-related Musculoskeletal Disorders (WMSDs) are major challenges in the occupational health services industry. Dental practitioners are regularly subjected to ergonomic risks, which can cause Musculoskeletal Disorders (MSDs) in various body regions. OBJECTIVE: This comparative cross-sectional study aimed to investigate MSDs and select a proper ergonomic risk assessment method in dental practice. METHODS: This study was conducted on 70 dentists and 70 administrative staff of dental offices (comparison group) from Shahroud, Iran. The Cornell Musculoskeletal Discomfort Questionnaire (CMDQ) and two observational ergonomic risk assessment methods, including Quick Exposure Check (QEC) and Rapid Entire Body Assessment (REBA), were utilized. RESULTS: The results suggested that the mean score of musculoskeletal discomforts was significantly higher in dentists than in the administrative personnel. Additionally, the results of multiple regression analysis technique inferred that job tenure, working hours, and age had a significant impact on total MSDs. Regular exercise was found to significantly reduce neck discomfort complaints. It was also found that QEC was more effective in predicting musculoskeletal discomforts compared to REBA. CONCLUSION: Considering the high incidence of WMSDs in dentists, various interventional measures revolving around ergonomically redesigned workstations, enhanced physical working conditions, and ergonomic training courses are suggested.

Background: It is generally accepted that laboratory staff are often exposed to chemical risks in various ways. Objectives: The aim of this study is to evaluate the occupational exposure risk assessment from chemical substances utilized in the laboratories of health centers at Shahroud University of Medical Sciences in 2016-2017. Methods: The method used in this study was based on the methodology presented by the Department of Occupational Safety and Health-Ministry of Human Resources (DOSH). Also, descriptive statistics, as well as the chi-square statistical tests were used to examine the relationship between occupational incidents and independent variables. Results: Approximately 19.81% of the studied laboratories had a significant exposure risk such that 6.6% of laboratories had a very high-risk level and 13.21% had a high-risk level. The most dangerous substance was Formalin 10% solution (Formaldehyde solution). The lowest risks were accredited to the endocrinology and serology laboratory. Conclusions: It is recommended that hazardous chemicals (risk rating = 4 or 5) specifications be determined on a specific form. This form can include the chemical name, the chemical composition, the name of the test, which may use the specified chemical substance, the TLV values, and instructions for using the chemicals and the places where the chemicals are stored and maintained. Finally, the necessary training is provided on employee risk management. Also, it is recommended to work under ventilation hood and use of appropriate PPE.