[Study on risk prediction model of neck work-related musculoskeletal disorders among automobile manufacturing enterprise workers].

To explore the risk factors of neck work-related musculoskeletal disorders (WMSDs) among automobile manufacturing enterprise workers, and construct the risk prediction model. In May 2022, a cluster convenience sampling method was used to selet all front-line workers from an automobile manufacturing factory in Xiangyang City as the research objects. And a questionnaire survey was conducted using the modified Musculoskeletal Disorders Questionnaire to analyze the occurrence and exposure to risk factors of neck WMSDs. Logistic regression was used to analyze the influencing factors of workers' neck WMSDs symptoms, and Nomogram column charts was used to construct the risk prediction model. The accuracy of the model was evaluated by the receiver operating characteristic (ROC) curve, the Bootstrap resampling method was used to verify the model, Hosmer-Lemeshow goodness of fit test was used to evaluate the model, and the Calibration curve was drawn. A total of 1783 workers were surveyed, and the incidence of neck WMSDs symptoms was 24.8% (442/1783). Univariate logistic regression showed that age, female, smoking, working in uncomfortable postures, repetitive head movement, feeling constantly stressed at work, and completing conflicting tasks in work could increase the risk of neck WMSDs symptoms in automobile manufacturing enterprise workers (=1.37, 95%: 1.16-1.62; =2.85, 95%: 1.56-5.20; =1.50, 95%: 1.18-1.91; =1.18, 95%: 1.02-1.37; =1.34, 95%: 1.04-1.72; =1.62, 95%: 1.21-2.17; =1.48, 95%: 1.13-1.92; <0.05). While adequate rest time could reduce the risk of neck WMSDs symptoms (=0.56, 95%: 0.52-0.86, <0.05). The risk prediction model of neck WMSDs of workers in automobile manutacturing factory had good prediction efficiency, and the area under the ROC curve was 0.72 (95%: 0.70-0.75, <0.001) . The occurrence of neck WMSDs symptoms of workers in automobile manufacturing factory is relatively high. The risk prediction model constructed in this study can play a certain auxiliary role in predicting neck WMSDs symptoms of workers in automobile manufacturing enterprise workers.