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Approximately 1.71 billion people worldwide suffer from musculoskeletal diseases (MSDs) (1), and this number is expected to increase in the coming decades. The prevention and control of MSDs have attracted global attention. With economic transformation, industrial upgrading, and rapid industrialization in China, new technologies, processes, and materials are widely used, leading to the emergence of new occupational hazards such as MSDs. The Healthy China Action (2019–2030) includes the prevention and control of MSDs caused by adverse ergonomic factors in occupational health protection actions. The National Health Commission of the People’s Republic of China is studying the inclusion of MSDs in the Classification and Catalogue of Occupational Diseases and plans to include them in statutory occupational disease management. To provide a solid database for this policy's implementation, the Institute of Occupational Health and Poisoning Control of the China CDC conducted a nationwide risk assessment project from 2018 to 2023. This project focused on studying MSDs caused by adverse ergonomic factors, particularly addressing previous data gaps, such as the lack of comprehensive epidemiological data on the prevalence and risk factors of MSDs in occupational settings and the under-representation of lower extremity MSDs (LE-MSDs) in research. However, lower extremity MSDs (LE-MSDs, including hip/thigh, knee, and ankle/foot) have not received sufficient attention in MSD research and prevention. This may be due to several factors, including a historical focus on upper body MSDs, less recognition of the impact of LE-MSDs on the ability to work and the associated economic burden, and the complexity of diagnosing and attributing LE-MSDs to specific occupational hazards. The global disease burden survey reveals that LE-MSDs have become one of the leading causes of global disabilities (2). Therefore, this paper focuses on the distribution of LE-MSDs and related influencing factors in key industries or worker populations in China. This study found that the standardized prevalence rate of LE-MSDs in key industries or occupational groups in China is 17.7%. Individual, work type, and work organization factors may impact LE-MSDs. This study provides data support for China in formulating relevant preventive countermeasures and strategies for MSDs and revising occupational disease classifications and catalogues.
Data for this study were obtained from 7 regions in China: North, East, Central, South, Southwest, Northwest, and Northeast. These regions encompass 9 national economic industries: agriculture, forestry, animal husbandry, fishery, mining, manufacturing, electricity, heat, gas, and water production and supply; construction; wholesale and retail; transportation, warehousing, and postal services; residents’ services, repairs, and other services; and health and social work.
This study used stratified random sampling to select representative industries closely related to work-related MSD (WMSD) occurrence from the above-mentioned areas. Samples were drawn according to the following principle: 1–2 large enterprises, 2–4 medium-sized enterprises, and 5–7 small enterprises (all enterprises with insufficient numbers were included). Subsequently, all workers who met the inclusion and exclusion criteria were selected as participants by stratified cluster sampling. Inclusion criteria were workers with >1 year of service. Exclusion criteria were congenital spinal deformity and non-work-related MSDs due to trauma, infectious diseases, and malignant tumors. This study was reviewed by the Medical Ethical Review Committee of Occupational Health and Poison Control at the Chinese Center for Disease Control and Prevention, and all participants provided informed consent.
In this survey, the “Ergonomic Evaluation and Analysis System of WMSDs” (3) developed by the Department of Occupational Protection and Ergonomics of the National Institute of Occupational Health and Poison Control of the China CDC was used to investigate the occurrence and influencing factors of WMSDs in key industries or among workers in different regions of China. The survey tool was a questionnaire built into this system, namely, the electronic questionnaire system of the Chinese version of the Musculoskeletal Disorders Questionnaire. This questionnaire was based on the Nordic Musculoskeletal Questionnaire (NMQ) and the Dutch Musculoskeletal Disorders Questionnaire (4). After appropriate modification, it has demonstrated good reliability and validity and can be used for occupational populations in China. The survey adopted a 1:N format; one investigator organized N respondents to scan the Quick Response(QR) code of the electronic questionnaire and answer the questions online. Upon completion, questionnaires were directly submitted and uploaded to a cloud database. After export, data were analyzed using SPSS 26.0 (version 26.0; Armonk, NY, USA). The prevalence of LE-MSDs in key industries in China is expressed by the age-standardized prevalence rate based on age composition data (18–60 years old) from the seventh national census. Univariate analysis of LE-MSDs used the χ2 test, and multivariate analysis used unconditional logistic regression. This study adopted the US National Institute for 0ccupational Safety and Health(NIOSH) criteria (3) for LE-MSDs in the United States: discomfort symptoms such as hurt, pain, stiffness, burning, numbness, or tingling, and at the same time: 1) discomfort in the past year; 2) discomfort began after starting the current job; 3) no past accident or sudden injury (in the area of discomfort); and 4) discomfort occurring monthly or lasting more than 1 week was judged as an MSD.
By the end of 2023, 88,609 valid questionnaires were received. Table 1 shows that the standardized prevalence of LE-MSDs in key industries or workers in China was 17.7%, and there were statistically significant differences among industries (P<0.05). The 5 industries with the highest standardized prevalence rates were toy manufacturing (29.0%), medical personnel (25.5%), automobile manufacturing (23.2%), nonferrous metal smelting and rolling processing (22.5%), and coal mining and washing (20.9%).
Industry/working group Number Lower extremity musculoskeletal disorders n pi p' 95% CI Total 88,609 16,387 18.5 17.7 0.182–0.187 Automobile manufacturing 21,759 5,317 24.4 23.2 0.239–0.250 Computer, communication industry, and other electronic equipment
manufacturing10,638 1,540 14.5 15.4 0.138–0.151 Furniture manufacturing 9,004 1,242 13.8 12.4 0.131–0.145 Footwear industry 7,100 1,036 14.6 15.2 0.138–0.154 Medical staff 7,011 1,899 27.1 25.5 0.260–0.281 Ferrous metal smelting and rolling 3,494 620 17.7 16.3 0.165–0.190 Electrical machinery and equipment manufacturing industry 3,434 343 10.0 9.7 0.090–0.110 Shipping and related device manufacturing 3,431 723 21.1 19.6 0.197–0.224 Coal mining and washing 3,356 735 21.9 20.9 0.205–0.233 Metal products industry 3,195 374 11.7 10.6 0.106–0.128 Nonferrous metal smelting and rolling processing industry 2,312 596 25.8 22.5 0.240–0.276 Road transportation 2,296 254 11.1 14.3 0.098–0.123 Biopharmaceutical product manufacturing 1,738 233 13.4 13.5 0.118–0.150 Railway transportation equipment manufacturing 1,674 220 13.1 12.3 0.115–0.148 Construction 1,434 137 9.6 10.2 0.080–0.111 Civil aviation flight attendants 1,341 270 20.1 18 0.180–0.223 Non-ferrous metal mining and dressing industry 1,225 171 14.0 13.7 0.120–0.159 Comprehensive retail industry 1,086 156 14.4 13.8 0.123–0.165 Food manufacturing industry 828 137 16.5 15.7 0.140–0.191 Automobile repair and maintenance 777 109 14.0 14 0.116–0.165 Toy manufacturing 325 79 24.3 29 0.196–0.290 Animal husbandry 245 48 20.3 20.3 0.146–0.246 Agriculture 239 76 31.8 17.6 0.259–0.377 Cement, lime, and gypsum manufacturing 194 19 9.8 20.4 0.056–0.140 Petrochemical industry 150 8 5.3 4.5 0.017–0.090 Chemical raw materials and chemical products manufacturing industry 95 8 8.4 8.4 0.027–0.141 Handling and warehousing industry 92 7 7.6 6.3 0.021–0.131 Power, heat, gas, water production, and supply 86 20 23.3 18.3 0.141–0.324 Packaging, decoration and other printing industries 50 10 8.1 7.6 0.085–0.315 Chi-square test 1,899.9 P P<0.001 Note: pi: actual crude prevalence rate, p': standardised prevalence rate.
Abbreviation: CI=confidence interval.Table 1. Incidence of lower extremity musculoskeletal disorders in key industries or occupational groups in China, 2018–2023. (n=88,609).
Individual, work type, and work organization factors may affect LE-MSD prevalence. Univariate analysis (Table 2) identified statistically significant (P<0.05) factors, which were then included as independent variables in a multivariate logistic regression analysis. The results showed that repeatedly performing the same movements with the lower limbs and ankles [odds ratio (OR)=1.394, 95% confidence interval (CI): 1.325–1.467] was associated with the highest risk of LE-MSDs. Other risk factors included frequently standing at work, job rotation, working in the same postures at a high pace, repetitive trunk movements, staff shortages, frequent overtime work, trunk posture, frequent trunk bending and twisting, prolonged knee bending, frequent squatting or kneeling at work, and exerting significant force with the upper limbs or hands. Protective factors against LE-MSDs included physical exercise, year of investigation, stretching or changing leg posture, frequent sitting at work, and sufficient rest time. Further details are presented in Table 3.
Variables lower extremity musculoskeletal disorders Number of workers Case Percentage (%) COR (95% CI) Individual risk factors Gender Men 59,989 11,287 18.8 1 Women 28,620 5,100 17.8 0.936 (0.902, 0.970)* Age (years) <25 14,349 2,854 19.90 1 25–34 34,336 6,845 19.90 1.003 (0.955, 1.053) 35–44 22,172 3,827 17.30 0. 840 (0.796, 0.887)* 45–54 13,417 2,180 16.20 0.781 (0.735, 0.831)* ≥55 4,335 681 15.70 0.751 (0.685, 0.823)* Working age (years) <2 22,029 3,534 16.00 1 2–3 17,155 3,204 18.70 1.202 (1.140, 1.267)* 4–5 11,268 2,041 18.10 1.158 (1.090, 1.229)* 6–7 8,414 1,609 19.10 1.237 (1.159, 1.321)* ≥8 29,743 5,999 20.20 1.322 (1.263, 1.384)* Education level Junior high school 27,912 4,067 14.60 1 Senior high school 32,301 6,422 19.90 1.455 (1.394, 1.519)* University degree 27,157 5,740 21.10 1.571 (1.503, 1.642)* Graduate degree 1,239 158 12.80 0.857 (0.723, 1.016) Body mass index (BMI) <18.5 7,219 1,426 19.80 1 18.5–24 59,030 10,627 18.00 0.892 (0.839, 0.949)* ≥25 22,360 4,334 19.40 0.977 (0.914, 1.044) Smoking No 55,882 9,981 17.90 1 Occasionally 15,446 2,741 17.70 0.992 (0.947, 1.040) Frequently 17,281 3,665 21.20 1.238 (1.186, 1.291)* Physical exercise No 27,057 5,400 20.00 1 Occasionally 46,152 8,440 18.30 0.898 (0.864, 0.932)* Frequently 15,400 2,547 16.50 0.795 (0.755, 0.837)* Workplace risk factor Standing often at work No 14,322 1,468 10.20 1 Yes 74,287 14,919 20.10 2.200 (2.079, 2.239)* Sitting often at work No 37,986 8,212 21.60 1 Yes 50,623 8,175 16.10 0.698 (0.675, 0.722)* Squatting or kneeling often at work No 53,516 8,064 15.10 1 Yes 35,093 8,323 23.70 1.752 (1.694, 1.813)* Lift heavy loads (more than 5 kg) No 32,171 4,436 13.80 1 Yes 56,438 11,951 21.20 1.680 (1.618, 1.744)* Lift heavy loads (more than 20 kg) No 48,825 7,540 15.40 1 Yes 39,784 8,847 22.20 1.566 (1.513, 1.620)* Exerting great force on upper limbs or hands No 15,302 1,610 10.50 1 Yes 73,307 14,777 20.20 2.147 (2.033, 2.268)* Use vibration tools at work No 55,729 8,639 15.50 1 Yes 32,880 7,748 23.60 1.680 (1.624, 1.739)* Working in the same postures at a high pace No 18,294 1,828 10.00 1 Yes 70,315 14,559 20.70 2.352 (2.234, 2.477)* Trunk posture Trunk straight 30,837 4,158 13.50 1 Bend slightly with your trunk 46,971 8,991 19.10 1.519 (1.459, 1.581)* Bend heavily with your trunk 10,801 3,238 30.00 2.747 (2.606, 2.895)* Always turn around with your trunk No 33,138 3,951 11.90 1 Yes 55471 12,436 22.40 2.135 (2.054, 2.219)* Always bend and twist with your trunk No 51,769 6,915 13.40 1 Yes 36,840 9,472 25.70 2.245 (2.169, 2.324)* Always make the same movements with your trunk No 44,006 5,262 12.00 1 Yes 44,603 11,125 24.90 2.447 (2.360, 2.536)* Wrists in bent posture for a prolonged time No 37,186 5,150 13.80 1 Yes 51,423 11,237 21.90 1.739 (1.678, 1.803)* Stretch or change leg posture No 20,031 3,885 19.40 1 Yes 68,578 12,502 18.20 0.927 (0.890, 0.964)* Keep your knees bent for a prolonged time No 60,893 9,627 15.80 1 Yes 27,716 6,760 24.40 1.718 (1.659, 1.779)* Lower limbs and ankles often do the same movements repeatedly No 54,101 7,448 13.80 1 Yes 34,508 8,939 25.90 2.190 (2.116, 2.266)* Work organization factors Often work overtime 45,009 6,400 14.20 1 No 43,600 9,987 22.90 1.792 (1.731, 1.856)* Yes Abundant resting time No 43,384 11,274 26.00 1 Yes 45,225 5,113 11.30 0.363 (0.350, 0.376)* Decide the rest time independently No 69,214 13,757 19.90 1 Yes 19,395 2,630 13.60 0.632 (0.604, 0.662)* Staff shortage No 50,002 6,925 13.80 1 Yes 38,607 9,462 24.50 2.020 (1.951, 2.090)* Do the same job almost every day No 10,530 1,278 12.10 1 Yes 78,079 15,109 19.40 1.737 (1.634, 1.847)* Job rotation No 37,537 5,693 15.20 1 Yes 51,072 10,694 20.90 1.481 (1.430, 1.535)* Abbreviation: COR=crude odds ratio; CI=confidence interval.
* P<0.05.Table 2. Univariate analysis of lower extremity musculoskeletal disorders among occupational groups in key industries in China, 2018–2023.
Variable Coefficient Wald χ2 AOR 95% CI P Lower limbs and ankles often do the same movements repeatedly 0.332 165.193 1.394 1.325, 1.467 0.000 Standing often at work 0.314 63.367 1.368 1.267, 1.478 0.000 Job rotation 0.303 160.727 1.353 1.292, 1.418 0.000 Working in the same postures at a high pace 0.269 42.494 1.309 1.207, 1.419 0.000 Always make the same movements with your trunk 0.266 81.385 1.305 1.232, 1.383 0.000 Staff shortage 0.242 101.516 1.274 1.215, 1.335 0.000 Often work overtime 0.179 57.432 1.196 1.142, 1.253 0.000 Trunk posture 0.13 51.972 1.139 1.099, 1.180 0.000 Always bend and twist with your trunk 0.122 19.711 1.13 1.070, 1.192 0.000 Keep your knees bent for a prolonged time 0.11 17.996 1.117 1.061, 1.175 0.000 Squatting or kneeling often at work 0.107 17.31 1.113 1.058, 1.171 0.000 Exerting great force on upper limbs or hands 0.106 6.739 1.112 1.026, 1.204 0.009 Use vibration tools at work 0.093 14.345 1.097 1.046, 1.151 0.000 Education level 0.087 36.535 1.091 1.061, 1.123 0.000 Body mass index (BMI) 0.077 13.989 1.08 1.037, 1.124 0.000 Working age (years) 0.06 66.734 1.062 1.047, 1.077 0.000 Physical exercise −0.056 11.116 0.945 0.915, 0.977 0.001 Investigation year −0.104 195.421 0.901 0.888, 0.914 0.000 Stretch or change leg posture −0.122 20.834 0.886 0.840, 0.933 0.000 Sitting often at work −0.258 112.274 0.773 0.737, 0.810 0.000 Abundant resting time −0.548 465.856 0.578 0.550, 0.608 0.000 Always make the same movements with your trunk −2.739 1129.345 0.065 0.055, 0.076 0.000 Abbreviation: AOR=adjusted odds ratio; CI=confidence interval. Table 3. Multivariate logistic regression model predicting the risk factors of lower extremity musculoskeletal disorders among occupational groups in key industries in China, 2018–2021.
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Since 2018, the Institute of Occupational Health and Poisoning Control of the China Center for Disease Control and Prevention has organized provincial and municipal centers for disease control and prevention and occupational prevention institutes to conduct occupational health risk assessments of MSDs caused by adverse ergonomic factors in key industries and operations in different regions of China. This project was reported in China Weekly in 2020, 2021, and 2022 (5–7). The data used in this paper are current to the end of 2023, describe only the occurrence of LE-MSDs, and analyze the related influencing factors.
This study found that the standardized rate of LE-MSDs in key industries or workers in China was 17.7%. In 2015, the European Agency for Safety and Health (EU-OSHA) (8) conducted an MSD survey across 28 countries in the European Union using the NMQ. This survey reported a 29% rate of self-reported LE-MSDs. It also showed that the occurrence of LE-MSDs varied across industries, suggesting that working environments and methods differ. This finding is consistent with the results of the present survey in China.
This study showed that prolonged standing and frequent, repetitive lower limb and ankle movements are high-risk factors for LE-MSDs. Research shows that prolonged standing increases venous pressure in the lower limbs, which may lead to obstructed blood return and venous hypertension (9). Persistent venous hypertension not only increases muscle load but also causes poor circulation and insufficient oxygen supply, ultimately leading to muscle fatigue and injury. A laboratory review of prolonged standing and MSDs indicated that standing for 40 minutes can be regarded as the exposure limit for prolonged standing (10). In addition to work type, this study found that individual and work organization factors cannot be ignored in relation to LE-MSDs. Studies show that obesity significantly increases the burden on the lower limb musculoskeletal system (11). Excess weight places more stress on joints and bones, which can easily cause inflammation, cartilage wear, and muscle injury, particularly in the weight-bearing knee and hip joints. Obesity accelerates tissue degeneration and injury. A survey of female hospital cleaners working under two different organizational models found that the group with more beneficial psychosocial factors (e.g., sufficient staffing, adequate rest time, and fewer shifts) had better musculoskeletal health (12). A cross-sectional survey of European working conditions also indicated that good work organization is vital to preventing LE-MSDs (13). This aligns with our findings. The following factors may explain this situation. First, frequent overtime and insufficient staffing may lead to prolonged work under high pressure. This continuous physical labor increases the burden on the lower limbs, increasing the risk of LE-MSDs. Additionally, performing the same job almost daily means a lack of variety and restricted movement, leading to the overuse of specific muscle groups and increased musculoskeletal stress due to fixed postures. Conversely, adequate rest time allows employees to recover physically and relieve muscle tension. Short rests promote blood circulation, reduce muscle fatigue, and help prevent MSDs. Self-determination of rest time provides employees with greater flexibility, enabling them to adjust their work rhythm to their physical needs, positively affecting work conditions and MSD prevention. Implementing a shift system helps break the monotony of work. Varying work hours and task assignments reduce the continuous load on specific muscle groups, thereby reducing the risk of MSDs. Therefore, to protect employee health, companies should consider arranging reasonable working hours, providing sufficient rest opportunities, and implementing shift systems to mitigate MSD risks for employees engaged in the same job long-term.
This study has some limitations. First, as a cross-sectional study, it is subject to recall bias. The study relies on participants' memories of work-related musculoskeletal diseases in the past year, which may be inaccurate. Workers with mild or habitual pain may forget some medical histories and individual cognitive differences can exacerbate inconsistencies in memory quality. Second, causality is uncertain. Although the study identifies related risk factors, the cross-sectional design cannot determine the sequence of variables. Therefore, it is unclear whether working conditions cause the disease or if conditions change after illness onset, which hinders the formulation of effective prevention strategies. In summary, the standardized prevalence rate of LE-MSDs in key industries and occupational groups in China was 17.7%. The five industries or occupational groups with the highest prevalence rates of LE-MSDs are toy manufacturing, medical personnel, automobile manufacturing, nonferrous metal smelting and rolling processing, and coal mining and washing, demonstrating clear occupational characteristics. In addition to occupational factors, such as prolonged standing, personal and work organization factors must also be considered. Therefore, it is necessary to strengthen the dissemination and education of ergonomics knowledge for professionals. These efforts could include improving workbench design, implementing regular rest and activity breaks, and creating personalized exercise prescriptions tailored to the specific needs of the occupational population to reduce the impact of LE-MSDs in China.
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All the participants involved in this study, from Chongqing, Shanghai, Jiangsu, Zhejiang, Tianjin, Beijing, Hubei, Ningxia Hui Autonomous Region, Sichuan, Shaanxi and Yunnan Provincial Centers for Disease Prevention and Control, Hubei Provincial Hospital of Integrated Chinese and Western Medicine, Guangzhou Twelfth People’s Hospital Affiliated to Guangzhou Medical University, Liaoning Provincial Health Supervision Center, Shenyang, Liaoning, China, Guizhou Province Occupational Disease Prevention and Control Hospital, Shandong Academy of Occupational Health and Occupational Medicine, Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Civil Aviation Medical Center of China Civil Aviation Administration, Tianjin Occupational Disease Prevention and Control Hospital, Fujian Province Occupational Disease and Chemical Poisoning Prevention and Control Center, and Institute of Occupational Medicine of Jiangxi.
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