Tibbi-i-kar

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Abstract Background: Now musculoskeletal disorders are common among occupational disorders and these are one reason for absence of the work that lead to reduction of performance. According the report of Social Security organization in 1990-1993, musculoskeletal disorders had led to 14.4% impairments in Iran. By these statistics, the aim of this study is the assessment of musculoskeletal disorders associated with welding by OWAS posture assessment method. Methods: First we Nordic questions are to determine whether this job requires ergonomic assessment and then posture were photographed during 40 minutes for 30 seconds. Intervals At the last, the associated pictures to any posture were evaluated with OWAS method. Results: The most necessary corrective for lumbar and arms is in level 2, whereas these for legs and complex postures are in level 1. Conclusion: Most musculoskeletal complains are in lumbar (52%), knee (48%) and back (38%). Therefore, OWAS can be suitable method for assessment of postures in this job.

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Introduction: Musculoskeletal disorders are one of the main problems of industries and administrative jobs, which are caused by various factors. The study aimed to determine the role of each individual, physical, psychosocial, and environmental factors in causing musculoskeletal disorders; Identifying and controlling risk factors, is an important step in reducing and preventing these disorders.
Materials and methods: The present study is a cross-sectional study of 342 employees working in different government offices in Saveh city in 2021. In this study, the Nordic summary questionnaire and ROSA checklist were used to investigate the prevalence of musculoskeletal disorders. Also, to investigate individual and psychosocial factors of the work environment, a personal information questionnaire and a general Nordic questionnaire were used. In addition, the evaluation of conditions of work environment was done by Hagner model E1 lux meter devices, TIS10 model thermal stress measuring device, and TES1358 sound meter. Finally, all the resulting data were entered into SPSS software and tested after coding.
Results: The results showed that body mass index and gender have a significant effect on suffering from musculoskeletal disorders (p-value<0.05). The results of the Pearson correlation test indicated that there is a significant relationship between the report of pain or discomfort in the neck area with the screen-phone risk score, wrist/hand with the keyboard-mouse risk score, as well as shoulder, upper back, elbow and lower back with the chair risk score. p-value <0.05). In addition, there is a significant relationship between the report of pain or discomfort in the neck, shoulder, and wrist/hand areas with the overall ROSA score. Also, there is a significant difference between the prevalence of musculoskeletal disorders and levels of job demands, levels of job control, levels of social interactions, levels of leadership, levels of the organizational atmosphere, levels of job satisfaction, and levels of stress (p-value<0.05).
Conclusion: The results of this study showed that several factors play a role in musculoskeletal disorders, such as job requirements, social interactions, and stress in the group of psychosocial factors that had considerable importance in causing musculoskeletal disorders. Among the individual factors, gender and body mass index (BMI) is important, and among the workstation factors, the chair has played a significant role in causing musculoskeletal disorders.

 

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Introduction: Each year, numerous workers worldwide lose their lives due to workplace accidents, leading not only to significant economic consequences for countries but also to social effects on the families involved.  Consequently, identifying the influencing factors and predicting their occurrence of accidents can significantly reduce their frequency. This study aimed to provide a predictive model for workplace accidents.
Materials and Methods: This research gathered data on workplace accidents from industries that agreed to participate over the last three years. Among the recorded incidents, the research team concentrated on those classified as reportable events under OSHA guidelines. Accordingly, 1,734 accidents met the conditions for analysis. After further examination, several incidents were excluded from the study due to insufficient information and lack of appropriate analysis, leading to a final total of 1011 accidents included in the study. Structural Equation Modeling (SEM) was employed to predict and determine the impact of each variable influencing  accident occurrences. .
Results: The result from the first hypothesis test (individual and demographic variables affect the types of accidents that occur) showed a significant negative impact of individual and demographic characteristics on the type of accidents, with a path coefficient of -0.720 and a t-value of -7.27. In testing the second hypothesis (demographic factors influence occupational factors), a path coefficient of 0.812 and a t-value of 35.37 indicated a strong and significant effect of demographic factors on occupational factors.
Conclusion: The findings of this research indicate that path analysis utilizing the SEM approach is effective for analyzing the severity of injuries resulting from workplace accidents. The results from SEM clearly show that demographic indicators, organizational factors, timing, and causes leading to accidents are indirectly related to the severity of occupational injuries, whereas the type of accidents has a direct correlation with occupational injury severity in various industries.