Work-related musculoskeletal disorders (WMSDs) refer to injuries to local muscles, tendons, bones, cartilage, ligaments, nerves, and other parts of the body caused or aggravated by occupational activities, resulting in varying degrees of damage. Approximately 1.71 billion people have musculoskeletal conditions worldwide (1). WMSDs are the leading contributor to disability worldwide, with low back WMSDs being the single leading cause of disability in 160 countries (2, 3). WMSDs significantly limit mobility and dexterity, leading to early retirement from work, lower levels of well-being and reduced ability to participate in society. Because of population growth and ageing, the number of people living with WMSDs and associated functional limitations, is rapidly increasing which has become a major occupational-related disease affecting the health of the working population. Many countries, including the United States, the United Kingdom, Germany, and Japan, had included WMSDs in their list of legally recognized occupational diseases or compensable diseases (4, 5). Therefore, it is necessary to conduct research on the prevalence and risk factors of WMSDs, which is of great significance for the prevention and treatment of WMSDs and the health protection of the working population.

Beijing, as the capital of China, is undergoing a major restructuring of its industrial structure. Currently, there are large number of workers worked in emerging industries, such as electronics, pharmaceutical, and motor manufacturing industries (6). Risk factors such as forced postures, unreasonable work systems, repetitive tasks, and long working hours were common in these industries (7, 8), which were widely presented and can easily result to local muscle fatigue and increase the risk of WMSDs (9, 10), which was significant different to the traditional risk factors, such as carry heavy objects. Electronics, pharmaceutical, and motor manufacturing industries were typical emerging manufacturing industries. The main characteristics of those enterprises were the high degree of automation and light manual labor, which was the future development direction of most enterprises. The characteristics and prevalence of WMSDs probably be different from traditional manufacturing workers, such as building industry, iron and steel industry. Therefore, it is necessary to evaluate the prevalence of WMSDs in these types of enterprises to light the other developing countries in the future. However, there are no reports on the prevalence and risk factors of WMSDs among emerging manufacturing workers in China. The objective of this study was to evaluate the prevalence of WMSDs among emerging manufacturing workers in Beijing, China. Therefore, a cross-sectional survey included 3,359 workers to determine the prevalence of WMSDs and risk factors was conducted in Beijing, which can be benefit to improve the prevention measures and occupational health status of workers, reduce the incidence of WMSDs, and alleviate the social burden.

This study aimed to investigate the prevalence and risk factors of WMSDs among emerging manufacturing workers in Beijing, China. The results showed that the prevalence of WMSDs was high among the workers, with the neck, lower back, shoulders, and upper back being the most commonly affected body parts. Female workers, older workers, workers with higher education levels, and those who never exercised were more likely to suffer from WMSDs. In addition, sitting for long periods, working in uncomfortable positions, and performing repetitive operations were identified as risk factors for WMSDs.

The prevalence of WMSDs in this study was 28.6%, which was lower than that among 7,908 manufacturing workers in Henan and Hubei Provinces, China (10), consistent with that among workers in manufacturing factories in Guangdong Province, China (15). The WMSDs prevalence of the neck, low back, shoulders, and upper back was the highest among all the body parts, which was consistent with other studies (16, 17). The work of manufacturing often involved risk factors of repetitive tasks, prolonged sitting or standing, and awkward postures, which could lead to local muscle fatigue and increase the risk of WMSDs (5). Female workers were found to be more likely to suffer from WMSDs than male workers, which is consistent with previous studies (5, 18). Women generally have smaller muscle mass and lower strength than men, which may make them more vulnerable to WMSDs (5). In addition, women were more likely to work in jobs that require repetitive tasks and prolonged standing or sitting, which are risk factors for WMSDs (19, 20). The older workers were also found to be more susceptible to WMSDs than young workers, which was consistent with previous studies (21). This may be due to age-related changes in the musculoskeletal system, such as decreased muscle strength and flexibility, soft tissue rheumatism, osteoarthritis, inflammatory arthritis, large joint prostheses, and age-related co-morbidities, which can increase the risk of WMSDs (21, 22). In addition, older workers may have accumulated more work-related physical stress over time, which can also increase the risk of WMSDs (18, 23). Furthermore, workers with higher education levels were found to be more likely to suffer from WMSDs (24), which probably be resulted to the fact that workers with higher education levels were more likely to work in jobs that require prolonged sitting, breaks less, which were risk factors for WMSDs (17). In addition, high workloads probably be another reason to increase the risk of WMSDs (25). Sitting for long periods, working in uncomfortable positions, and performing repetitive operations were identified as risk factors for WMSDs, which was consistent with previous studies (5, 8). These factors can lead to local muscle fatigue and increase the risk of WMSDs (5). Therefore, it is important to implement ergonomic interventions, such as adjusting workstations, providing rest breaks, and rotating tasks, to reduce the risk of WMSDs (8). As for the factors of work posture load, sitting for long periods, working in uncomfortable posture, and performing repetitive operations were identified as risk factors for WMSDs, factors of which could lead to local muscle fatigue and increase the risk of WMSDs (26–29). Therefore, it was crucial to implement ergonomic interventions, such as adjusting workstations, providing rest breaks, and rotating tasks, to reduce the risk of WMSDs.

Exercise was found to be a protective factor for WMSDs, which was consistent with previous studies (30, 31). Exercise can improve muscle strength and flexibility, reduce fatigue, and prevent WMSDs (32, 33). Workers who never exercised had the highest prevalence of WMSDs, while those who exercised 2–3 times per month and 1–2 times per week had lower odds of WMSDs, which suggested that even moderate levels of exercise can be beneficial for preventing WMSDs.

However, it was not easily to engage in physical exercise, even if it was only mild exercise, which was benefit to prevent the occurrence of WMSDs.

To the best of our knowledge, this is the first study to illustrated the prevalence of WMSDs among the emerging manufacturing enterprises workers and to explore the risk factors in large samples in Beijing, China. The current study illustrated that workers in the emerging manufacturing enterprises were at high risk of WMSDs although whose labor load was not as strong. Work load risk factors of siting for long, carry objects, uncomfortable positions were associated with the risk of WMSDs, while the demographic and habits of female, age, educational level, and sports were also associated with the happen of WMSDs. Therefore, ergonomic interventions, including implement ergonomic interventions to address work load risk factors such as prolonged sitting, carrying heavy objects, and uncomfortable positions, could be applied in the workplace. In addition, providing training and education programs to raise awareness among workers about the importance of maintaining good posture, using proper body mechanics, and adopting ergonomic practices probably be benefit to reshape the WMSDs, which can help them understand the risks associated with WMSDs and learn preventive measures. By implementing these measures, it is possible to reduce the prevalence of WMSDs among workers in emerging manufacturing enterprises and improve their overall musculoskeletal health.

This study had notable strengths due to its large sample size. Nevertheless, it was important to acknowledge several limitations that were present in this study. First, the study was conducted based on a cross-sectional design, which limited the ability to establish causality between risk factors and WMSDs. Second, the study relied on self-reported data, which may be subject to recall bias and social desirability bias. There may be inaccuracies when participants recalled WMSD or not over a year. In addition, some participants tended to exaggerate the severity of WMSDs when they were dissatisfied with the enterprises. Third, only three types of industries workers in Beijing were included, especially the disproportionally small sample size of the electronics group, which may limit the generalizability of the findings to other regions and industries in China and other regions. Forth, the data were collected online since the epidemic of COVID-19, while the information bias was common for that. Therefore, it is necessary to further verify the conclusions of this study.

This study provides important insights into the prevalence and risk factors of WMSDs among manufacturing workers in Beijing, China. The high prevalence of WMSDs and the identified risk factors highlight the need for targeted prevention measures, such as ergonomic interventions and exercise. In addition, there is currently a lack of objective and reliable diagnostic methods for WMSDs. It is necessary to conduct research in the future to address this gap.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving humans were approved by the Medical Ethics Committee of the Beijing Institute of Occupational Disease Prevention and Treatment. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.

XD: Conceptualization, Formal analysis, Methodology, Writing – original draft. ZG: Data curation, Methodology, Software, Writing – review & editing. NL: Supervision, Writing – original draft. MB: Data curation, Investigation, Methodology, Writing – review & editing. FJ: Supervision, Writing – review & editing. HW: Supervision, Writing – review & editing. XZ: Project administration, Writing – original draft. BL: Resources, Supervision, Writing – review & editing. DN: Supervision, Writing – review & editing. TL: Project administration, Resources, Writing – original draft. TX: Project administration, Writing – original draft. JL: Funding acquisition, Supervision, Writing – review & editing. TY: Conceptualization, Funding acquisition, Investigation, Resources, Supervision, Writing – original draft, Writing – review & editing.