The results of this study provided more information about correlated factors of grip and pinch strengths. The regression equations developed in this research are applicable to clinical treatment and ergonomics programs.

In Iran, furniture is mainly manufactured in small workshops, where most activities are performed manually. This study was conducted among workers of furniture workshops to determine prevalence of musculoskeletal symptoms and to assess ergonomic working conditions to identify major risk factors associated with musculoskeletal symptoms. In this study, 410 randomly selected furniture workers participated. The Nordic questionnaire and an ergonomics checklist consisting of 6 sections were used as data collection tools. An index was calculated for each section of the checklist. Action categories indicating the priority of corrective measures were also defined. The highest prevalence of symptoms was reported in the knees (39%), lower back (35.6%) and wrists/hands (29.5%). It was found that manual material handling, poor workstation design and awkward working postures were associated with the reported symptoms in these regions (OR 1.77-4.52). Poor general working conditions and work organization showed association as well. Any interventional measures should focus on these areas.

Background: Vibration as one of the harmful physical factors is relatively present in a wide range of jobs. Musculoskeletal disorders (MSDs) are among the most prevailing complaints of workers encountering occupational factors for example vibration. Therefore, this study was conducted to investigate vibration and its association with the MSDs in upper limbs of heavy mine vehicles drivers. Materials and Methods: This cross-sectional study was conducted, on heavy mine vehicles of Gol-Gohar Sirjan Centre, Sirjan, Iran. In general, 288 drivers with 92 vehicles were working at the mine site. SVAN958 vibration meters and the Nordic Musculoskeletal Questionnaire were used to measure whole body vibration and upper limb MSDs, respectively. Finally, the data were analysed using SPSS. Results: The highest average equilibrated acceleration was in graders (2.179 m/s 2) and drills had the lowest average acceleration (0.479 m/s 2). Prevalence of MSDs within past 12 months showed a significant difference in the neck (P = 0.044) and elbow (P = 0.023) between case and control group. The whole body vibration variable was associated with MSDs in the neck (P = 0.020) and wrist/hands (P = 0.030), and with increase in vibration the MSDs showed a 59% increase in neck and 72% in wrist/hands. In multivariate analysis, the whole body vibration variable had a significant relation with MSDs in wrist/hand (P = 0.027) and caused an 83% increase in the risk of MSDs per each unit in wrist/hand. Conclusions: The prevalence of disorders in studies with short duration is probably not quite visible; however, by increasing the working experience with these vehicles which have higher vibration than standard rates, the chance of developing MSDs increases.

Background: Human error is the most important cause of occupational and non-occupational accidents. Because, it seems necessary to identify, predict and analyze human errors, and also offer appropriate control strategies to reduce errors which cause adverse consequences, the present study was carried out with the aim of identifying human errors while operating meat grinder and offer suggestions in order to reduce human errors in this human-machine system. Materials and Methods: This is a descriptive study. In this ergonomic study the "Task Analysis for Error Identification (TAFEI)" technique was used in order to identify human errors while operating a meat grinder machine. According to this technique, firstly, tasks of human side of the interaction were described by Hierarchical Task Analysis (HTA) and then the State-Space Diagrams (SSDs) were drawn. Finally, after forming the TAFEI diagrams, the transition matrix table was prepared in order to identify human errors. Results: After completing all the steps of TAFEI technique, the transition matrix table was formed. Results showed 49 illegal transition states; therefore, 49 human errors were identified and described while operating the meat grinder machine. Conclusion: The results of this study showed how and under which conditions may meat grinder users do error in the human-machine interaction. In this regard, possible human errors resulting from non-ergonomic design of Iranian meat grinder machine were identified.

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