OBJECTIVE: To investigate the correlation of mental workload and prevalence of work-related musculoskeletal disorders musculoskeletal disorders( WMSDs) in railway vehicle manufacturing workers.METHODS: A total of 362 male workers in assembling and welding workshop from a railway vehicle manufacturing enterprise were selected as study subjects by cluster sampling method.The level of mental workload and prevalence of WMSDs were investigated using a revised Subjective Workload Assessment Technique and China Musculoskeletal Questionnaire.RESULTS: The median score of mental workload was 67 and the prevalence rate of WMSDs was 56.9%.The multivariate logistic regression analysis results indicated that the higher the mental workload of railway vehicle manufacturers,the higher their risk for WMSDs after excluding the influence of confounding factors( P < 0.05).Workers in welding work showed a higher risk than those in assembling work( P < 0.01).Workers with fast work rhythm showed higher risk of WMSDs than those with regular working rhythm( P < 0.01).Workers with comfortable working environment and temperature showed lower risk of WMSDs than those with uncomfortable working environment and temperature( P < 0.01).CONCLUSION: The mental workload can increase the risk of WMSDs,with a dose-effect relationship in railway vehicle manufacturing workers.The type of work,work frequency and the temperature in working environment are also influencing factors of WMSDs.

OBJECTIVE: To analyze the prevalence and influencing factors of multisite work-related musculoskeletal disorders(WMSDs) of workers in a railway vehicle manufacturing enterprise. METHODS: A total of 366 male workers in the assembly and riveting workshop of a railway vehicle manufacturing enterprise were selected as the research subjects using the cluster sampling method. The Chinese Musculoskeletal Questionnaire was used to investigate the prevalence of multiple sites of WMSDs. Multiple logistic regression analysis was used to analyze the influencing factors. RESULTS: The total prevalence of WMSDs was 56.3%(206/366). The prevalence of WMSDs in all parts from high to low was as follows: lower back(35.5%), hand and wrist(27.6%), neck(23.2%), shoulder(21.0%), knee(19.9%), upper back(18.6%), hip and leg(18.0%), ankle/foot(15.8%) and elbow(12.3%)(P<0.01). The total prevalence of multisite WMSDs was 38.0%(139/366). The prevalence of WMSDs in different numbers of parts from high to low was as follows: 6 or more parts(12.0%), 2 parts(10.7%), 3 parts(6.6%), 5 parts(5.5%) and 4 parts(3.3%)(P<0.01). Multiple logistic regression analysis results showed that the overweight and obese workers had higher risk of multi site WMSDs than those with normal body mass index(P<0.05).Those with long-term low heads, frequent bending, long bending of the elbows, and higher frequency of work requirements, and less frequently communicated with the leader had higher risk of multi site WMSDs(P<0.05). CONCLUSION: The prevalence of multisite WMSDs in railway vehicle manufacturing enterprise is relatively high. The influencing factors include individual factors, adverse ergonomic factors and psychosocial factors.

OBJECTIVE: To form a new assessment method to evaluate postural workload comprehensively analyzing the dynamic and static postural workload for workers during their work process to analyze the reliability and validity, and to study the relation between workers' postural workload and work-related musculoskeletal disorders (WMSDs). METHODS: In the study, 844 workers from electronic and railway vehicle manufacturing factories were selected as subjects investigated by using the China Musculoskeletal Questionnaire (CMQ) to form the postural workload comprehensive assessment method. The Cronbach's α, cluster analysis and factor analysis were used to assess the reliability and validity of the new assessment method. Non-conditional Logistic regression was used to analyze the relation between workers' postural workload and WMSDs. RESULTS: Reliability of the assessment method for postural workload: internal consistency analysis results showed that Cronbach's α was 0.934 and the results of split-half reliability indicated that Spearman-Brown coefficient was 0.881 and the correlation coefficient between the first part and the second was 0.787. Validity of the assessment method for postural workload: the results of cluster analysis indicated that square Euclidean distance between dynamic and static postural workload assessment in the same part or work posture was the shortest. The results of factor analysis showed that 2 components were extracted and the cumulative percentage of variance achieved 65.604%. The postural workload score of the different occupational workers showed significant difference (P<0.05) by covariance analysis. The results of nonconditional Logistic regression indicated that alcohol intake (OR=2.141, 95%CI 1.337-3.428) and obesity (OR=3.408, 95%CI 1.629-7.130) were risk factors for WMSDs. The risk for WMSDs would rise as workers' postural workload rose (OR=1.035, 95%CI 1.022-1.048). There was significant different risk for WMSDs in the different groups of workers distinguished by work type, gender and age. Female workers exhibited a higher prevalence for WMSDs (OR=2.626, 95%CI 1.414-4.879) and workers between 30-40 years of age (OR=1.909, 95%CI 1.237-2.946) as compared with those under 30. CONCLUSION This method for comprehensively assessing postural workload is reliable and effective when used in assembling workers, and there is certain relation between the postural workload and WMSDs.
China ; Factor Analysis, Statistical ; Female ; Humans ; Logistic Models ; Male ; Musculoskeletal Diseases ; Posture ; Prevalence ; Reproducibility of Results ; Risk Factors ; Surveys and Questionnaires ; Workload