Yan Yin

Although studies have shown that work-related musculoskeletal disorders (WMSDs) are common and continue to be a major source of disability and work time loss, there are few reports about elbow WMSDs. The aim of this study was to explore the prevalence and associated factors of elbow WMSDs. The valid questionnaires of 57501 workers from 15 different industries nationwide were collected and the c² test and logistic regression analysis were applied to reveal the prevalence and risk factors of elbow WMSDs. The findings indicated that the overall prevalence of elbow WMSDs among workers was 7.3%. However, the prevalence of elbow WMSDs in toy manufacturing was 21.3%, which was significantly higher than that in other industries (P < .05). Logistic regression analysis showed that age 40 and above, married, very poor health, left-handedness, lifting weights (more than 20 kg each time), work requiring upper limb or hand force, work in an uncomfortable position, repetitive operations within 1 minute, using vibrating tools, work involving cold, cool draughts, or temperature changes, work being completed in the same workshop, work being done outdoors, frequent dealings with customers, 2 shifts, often working overtime, staff shortage, and often working for colleagues were risk factors for elbow WMSDs. A higer education level, monthly income, and enough rest time were protective factors for elbow WMSDs. Toy manufacturing is a high-risk industry for elbow WMSDs. Promotion of education about ergonomics should be strengthened, and workers’ ergonomics awareness should be improved to reduce the impact of WMSDs.

Objectives: To describe the prevalence of self-reported musculoskeletal disorders among workers in the electronics manufacturing industry and to investigate the relations between work-related musculoskeletal disorders (WMSDs) and work-related variables.Methods: An interview-based questionnaire survey was carried out in thirty electronics manufacturing factories in China in 2018. The prevalence of WMSDs was estimated using the modified Nordic Musculoskeletal Questionnaire (NMQ). A multivariate logistic regression model was applied to evaluate the effects of risk factors on WMSDs on multiple body parts.Results: The 12-month prevalence of WMSDs among participants was 40.6%, and the common body sites affected were the neck (26.8%), shoulder (22.8%), upper back (14.9%), and lower back (14.8%). The results of logistic regression showed that female adults, > 5 job tenure and work-related factors (including awkward posture, lifting or carrying weights, excessive repetition, prolonged sitting, monotonous work and working under conditions of cold or temperature variations) led to a higher risk of WMSDs on most body parts. Upper back, wrist/hand and elbow pain levels were significantly higher for workers with vibration. However, more frequently, physical exercise was a protective factor against WMSDs on most body parts except the upper back, leg and knee.Conclusions: The study indicates a high prevalence of musculoskeletal pain among the electronics manufacturing industry in China. Different personal and work factors are related to the occurrence of WMSD on different body parts. Preventive measures should be implemented based on the characteristics of WMSD in the electronic manufacturing industry. Furthermore, the training and intervention guidance of ergonomic hazards in the workplace need to be strengthened by understanding the impact of bad posture, avoiding long-term sitting posture and increasing physical activities.

Background: With the development of the electronics manufacturing industry, the demand for human resources has increased, which has also led to the frequent occurrence of multi-site work-related musculoskeletal disorders. Method: The participants (n = 7307) were recruited from 30 enterprises in China in 2018. The prevalence of musculoskeletal disorders was estimated using a modified Chinese version of the Musculoskeletal Disorders Questionnaire. The multivariate logistic regression model was applied to evaluate the effects of risk factors on multi-site musculoskeletal symptoms. Additionally, the log-binomial model was established to examine the correlation between the various sites of musculoskeletal symptoms in the body. Results: The 12-month prevalence of musculoskeletal symptoms among participants was 40.6%. The proportion of musculoskeletal symptoms involving single-site and 2/>2 body sites were 11.6% and 29.0%, respectively. The results of logistic regression showed that female adults who smoked, had >5-year job tenure, and always stood or sat for long period at work had a higher risk in 2/>2 body sites of musculoskeletal symptoms (p < 0.05). However, physical exercise during leisure time and “Squatting or kneeling for long period at work” were more frequently protective factors. Furthermore, the log-binomial model indicated that the neck and shoulder were significantly related to each other (Prevalence Ratio, PR: 5.511 and 7.017). Conclusions: Several demographic characteristics and work-related factors were associated with multi-site musculoskeletal symptoms in the electronics manufacturing industry in China. Improving the levels of physical exercise and reducing posture problems and force loads may help to promote the health of workers.