{L-End}Objective To investigate the influencing factors of work-related musculoskeletal disorders (WMSDs) that affect neck-shoulder-back among manufacturing workers. {L-End}Methods A total of 8 250 front-line workers from 27 manufacturing enterprises in Henan Province and Hubei Province were selected as the research subjects using cluster sampling method. The Musculoskeletal Disorders Questionnaire was used to investigate the prevalence of neck-shoulder-back (include neck, shoulder, upper back, and lower back) WMSDs in the past year. The log-binomial model, principal component analysis (PCA) and multivariate logistic regression analysis were used to analyze the influencing factors of WMSDs in the neck-shoulder-back. {L-End}Results The prevalence of WMSDs was 77.2%. The prevalence of neck-shoulder-back WMSDs was 50.9%. The prevalence ratios of WMSDs were relatively higher among the neck, shoulder, and upper back (all P<0.05). The results of PCA improved logistic regression analysis showed that the influencing factors of neck-shoulder-back WMSDs were individual factors, biomechanical factors, psychosocial factors and environmental factors. In terms of individual factors, the risk of neck-shoulder-back WMSDs was higher in females than in males (P<0.05). With the increase of age, length of service, and education level, the risk of neck-shoulder-back WMSDs increased among manufacturing workers (all P<0.05). The risk of neck-shoulder-back WMSDs of workers in textile, clothing, shoes and hats manufacturing industry was relatively lower than that in the other nine industries (all P<0.05). In terms of the biomechanical factors, spending a lot of effort to operate tools/machines, sitting for a long time at work,bending greatly bending and turning at the same time, neck leaning forward or maintaining this posture for a long time, neck twisting or maintaining this posture for a long time and uncomfortable position resulting in difficulty exerting exertion were all risk factors of neck-shoulder-back WMSDs among manufacturing workers (all P<0.05) Bending slightly for a long time was a protective factor for neck-shoulder-back WMSDs among manufacturing workers (P<0.05). In terms of the psychosocial factors, doing the same work every day, self-determination in resting time between works staff shortage, and frequent overtime work were risk factors for neck-shoulder-back WMSDs among manufacturing workers (all P<0.05). Adequate resting time was a protective factor for neck-shoulder-back WMSDs among manufacturing workers (P<0.01). In terms of environmental factors, working under cold or fluctuating temperature, having nothings to lean on, and soles slipping or falling at work were all risk factors for neck-shoulder-back WMSDs among manufacturing workers (all P<0.05). {L-End}Conclusion Manufacturing workers are prone to suffer from neck-shoulder-back WMSDs. The influencing factors include individual factors, biomechanical factors (force load and static load), psychosocial factors and environmental factors.

Ergonomic exposure is one of the important causes of work-related musculoskeletal disorders (WMSDs). Accurate measurement and evaluation of ergonomic exposure level and implementation of ergonomic intervention are of great significance to the prevention and control of WMSDs. Ergonomic exposure can be divided into external exposure and internal exposure, and its evaluation methods include subjective judgment method, systematic observation method, and direct measurement method. This paper summarized the internal exposure assessment methods based on musculoskeletal dynamics and biomarkers, introduced the overall design concept of ergonomic exposure assessment system, used the Ergonomic Assessment Worksheet (EAWS) as an example, and discussed the development trend of automation, intelligence, and compounding of ergonomic exposure assessment methods and the factors considered in the selection of ergonomic exposure assessment methods.

Background China's manufacturing industry is still labor-intensive, and assembly employees in manufacturing industry are facing a great risk of work-related musculoskeletal disorders (WMSDs). Objective To investigate and analyze the prevalence and distribution of WMSDs among assembly workers in manufacturing enterprises and explore the relationship between WMSDs and ergonomic exposure factors such as posture load and mental load. Methods From July to September 2017, by convenient sampling, a cross-sectional survey was conducted to select 670 workers engaged in electronic accessories assembly and railway vehicle manufacturing in three manufacturing enterprises in two cities in northern China as the research participants. The posture load assessment was based on the Chinese Musculoskeletal Questionnaire independently developed by our research group. The mental load assessment was based on a revised Chinese version of the Subjective Workload Assessment Technique. An unconditional logistic regression model was used to explore the relationship between ergonomic exposure and WMSDs. Results The overall prevalence rate of WMSDs was 39.6% (265/670) with 43.8% in males and 25.2% in females; the highest prevalence rate was 47.7% in the group aged 40 years and over. The prevalence rate of WMSDs in the electronic accessories assembly workers was 16.9%, that in the railway vehicle manufacturing workers was 57.3%, and the difference was statistically significant (\begin{document}$ {\chi ^2} $\end{document}=112.63, P<0.001). The mental load score [median (first quartile, third quartile)] was 55.6 (51.9, 83.3) points, and the posture load score was 27.1 (16.0, 41.5) points. The results of unconditional logistic regression model showed that women (OR=3.152, 95%CI: 1.458-6.813), drinkers (OR=1.934, 95%CI: 1.124-3.326), and railway vehicle manufacturing worker (OR=3.416, 95%CI: 1.756-6.644) had a higher risk of reporting WMSDs; The higher the mental load (OR=1.019, 95%CI: 1.007-1.031) and posture load (OR=1.034, 95%CI: 1.019-1.050), the higher the risk of reporting WMSDs. The hierarchical analysis results showed that the risk of reporting WMSDs was higher among the electronic accessories assembly workers who were older (compared with those aged <30 years, OR_30-39=2.526 and OR_≥40=12.263, respectively) and with higher posture load (OR=1.025, 95%CI: 1.002-1.049), as well as among the railway vehicle manufacturing workers who were drinking (OR=2.035, 95%CI: 1.155-3.583), obese (OR=3.094, 95%CI: 1.185-8.078), with higher mental load (OR=1.013, 95%CI: 1.001-1.025) and posture load (OR=1.033, 95%CI: 1.018-1.049). Conclusion There is a significant correlation between reporting WMSDs and ergonomic exposures such as posture load and mental load, and drinking is also a risk factor of WMSDs. The risk of reporting WMSDs in female workers in assembly manufacturing industry is higher than that in male workers. The overall prevalence rate of WMSDs in railway vehicle manufacturing workers is higher than that in electronic accessories assembly workers.

Background The prevalence rate of work-related musculoskeletal disorders (WMSDs) among manufacturing workers is relatively high and has been widely concerned. However, research on the prevalence and risk factors of multi-site WMSDs is still insufficient. Objective To explore the prevalence and risk factors of multi-site WMSDs of assembly workers in four manufacturing enterprises. Methods The "Chinese Musculoskeletal Questionnaire" was used to conduct a cross-sectional survey among 1401 assembly workers selected by convenient sampling in four manufacturing enterprises, and their demographic characteristics, the prevalence of WMSDs in various body parts, and the information about biomechanical factors, work organizations, work environment, and psychosocial factor exposure were collected. The prevalence of WMSDs and multi-site WMSDs were estimated, Pearson χ² test was used for univariate analysis of multi-site WMSDs risk factors, and logistic regression was used for multi-factor analysis. Results The total prevalence rate of WMSDs was 54.9% (769/1 401). The top three affected sites were neck (41.4%), shoulders (30.7%), and wrist/hand (25.1%). The prevalence rate of multi-site WMSDs was 41.9% (587/1 401). The prevalence rates of multi-site WMSDs in railway vehicle assembly and riveting workers were higher than those in electronic parts processing and glass manufacturing workers (P<0.001). The results of logistic regression analysis showed that individual factors such as female (OR=2.09, 95%CI: 1.48−2.97) and drinking (OR=1.52, 95%CI: 1.05−2.18), biomechanics factors such as keeping head down for a long time (OR=1.37, 95%CI: 1.22–1.53), keeping bending frequently (OR=1.18, 95%CI: 1.03–1.34), and keeping arms up for a long time (OR=1.25, 95%CI: 1.10–1.41), work organizational factors such as electronic parts processing, railway vehicle assembly, and riveting (OR values were 3.23, 5.70, and 13.83, respectively), environmental factors such as temperature a little cold (OR=4.84, 95%CI: 1.90–12.37), noise seriously affecting work (OR=2.25, 95%CI: 1.23–4.11), and psychosocial factors such as high job demands (OR=1.47, 95%CI: 1.04–2.08), fatigue after work (OR=1.92−2.61) were risk factors of multi-site WMSDs. Conclusion The prevalence rate of multi-site WMSDs in assembly workers is high, and the main influencing factors include individual factors, awkward work postures, environmental factors, and psychosocial factors.