Falahati Mohsen, Dehghani Fatemeh, Malakoutikhah Mahdi, Karimi Ali, Zare Asma, Yazdani Rad Saeed
Social Determinants of Health Research Center, Saveh University of Medical Sciences, Saveh, Iran.
Research Center for Health Sciences, Institute of Health, Department of Occupational Health Engineering, School of Health, Shiraz University of Medical Sciences, Shiraz, Iran.
Med J Islam Repub Iran. 2019 Dec 16;33:136. doi: 10.34171/mjiri.33.136. eCollection 2019.
Musculoskeletal disorders (MSDs) are considered an important health concern, particularly in automotive assembly industries. Evaluation of the effects of all MSDs risk factors is difficult due to its multifactorial nature. In addition, the risk factors cannot be detected accurately when they are only based on individual opinions. Thus, in this study, fuzzy logic tool was used to evaluate the combined effects of all risk factors on MSDs. This cross sectional study was conducted on 100 male workers in an automotive industry. Job satisfaction, job stress, job fatigue, and body posture were evaluated by a self-reported questionnaire. Body posture was evaluated using Rapid Entire Body Assessment (REBA). Primary data analysis on extracting the input variables of MATLAB was performed by SPSS 22, with a significant level of 0.05. T test, one-way Anova, and Pearson correlation analysis were used to extract the input variables for the fuzzy logic model. The results obtained from the Nordic questionnaire was selected as the output of the fuzzy model. Fuzzy logic assessment was performed using MATLAB software version 7.0. There were significant differences between WMSDs factors, including job fatigue, strain, working posture, and the REBA final score, and pain in all limbs of the body (p<0.05). A significant difference was also found between working posture with wrist score (p<0.05). The findings on defuzzification showed a strong correlation between real and modelling results. The results showed that many factors such as posture, fatigue, and strain affect MSDs. Based on the obtained results, all categories of risk factors, including personal, psychosocial, and occupational, should be considered to predict MSDs, which can be achieved by a modeling approach.
肌肉骨骼疾病（MSDs）被视为一个重要的健康问题，尤其是在汽车装配行业。由于其多因素性质，评估所有MSDs风险因素的影响很困难。此外，当仅基于个人观点时，风险因素无法被准确检测。因此，在本研究中，使用模糊逻辑工具来评估所有风险因素对MSDs的综合影响。这项横断面研究是针对一家汽车行业的100名男性工人进行的。通过自我报告问卷评估工作满意度、工作压力、工作疲劳和身体姿势。使用快速全身评估（REBA）来评估身体姿势。通过SPSS 22对提取MATLAB输入变量进行初步数据分析，显著性水平为0.05。使用T检验、单因素方差分析和Pearson相关分析来提取模糊逻辑模型的输入变量。从北欧问卷获得的结果被选为模糊模型的输出。使用MATLAB软件版本7.0进行模糊逻辑评估。WMSDs因素之间存在显著差异，包括工作疲劳、应变、工作姿势和REBA最终得分，以及身体所有肢体的疼痛（p<0.05）。工作姿势与手腕得分之间也存在显著差异（p<0.05）。去模糊化的结果表明实际结果与建模结果之间有很强的相关性。结果表明，姿势、疲劳和应变等许多因素会影响MSDs。基于获得的结果，应考虑所有类别的风险因素，包括个人、心理社会和职业因素，以预测MSDs，这可以通过建模方法实现。
