Advanced Search

Preplanned Studies: Incidence and Risk Factors of the Upper-Limb Musculoskeletal Disorders Among Occupational Groups in Key Industries — China, 2018–2021

View author affiliations
  • Summary

    What is already known about this topic?

    The burden of illness and economic losses due to upper-limb work-related musculoskeletal disorders (UL-WMSDs) is high; thus, they have become a major global public health problem. At present, the epidemiological characteristics of UL-WMSDs in China's occupational population are still unknown.

    What is added by this report?

    The incidence of UL-WMSDs among key occupational groups in China is 22.5%, with distinct occupational characteristics.

    What are the implications for public health practice?

    This study has primarily determined the occurrence and potential risk factors of UL-WMSDs in key industries in China and provided data support for recommending prevention and control of the occurrence of such diseases in key industries in China, and in facilitating the addition into the China’s List of Legal Occupational Diseases.

  • loading...
  • Funding: Funded by the Project of Occupational Health Risk Assessment and the National Occupational Health Standard Formulation of the National Institute of Occupational Health and Poison Control (Project No. 131031109000160004). National Key R&D Program of China (2022YFC2503205)
  • [1] Kuorinka I, Jonsson B, Kilbom A, Vinterberg H, Biering-Sørensen F, Andersson G, et al. Standardised Nordic questionnaires for the analysis of musculoskeletal symptoms. Appl Ergon 1987;18(3):233 − 7. http://dx.doi.org/10.1016/0003-6870(87)90010-XCrossRef
    [2] Salvendy G. Handbook of human factors and ergonomics. 4th ed. Hoboken: John Wiley & Sons. 2012. https://onlinelibrary.wiley.com/doi/book/10.1002/9781118131350.https://onlinelibrary.wiley.com/doi/book/10.1002/9781118131350
    [3] Jia N, Zhang HD, Ling RJ, Liu YM, Li G, Ren ZL, et al. Investigation on work-related musculoskeletal disorders — China, 2018-2019. China CDC Wkly 2020;2(18):299 − 304. http://dx.doi.org/10.46234/ccdcw2020.077CrossRef
    [4] Jia N, Zhang HD, Ling RJ, Liu YM, Li G, Ren ZL, et al. Epidemiological data of work-related musculoskeletal disorders—China, 2018-2020. China CDC Wkly 2021;3(18):383 − 9. http://dx.doi.org/10.46234/CCDCW2021.104CrossRef
    [5] Govaerts G, Tassignon B, Ghillebert J, Serrien B, De Bock S, Ampe T, et al. Prevalence and incidence of work-related musculoskeletal disorders in secondary industries of 21st century Europe: a systematic review and meta-analysis. BMC Musculoskelet Disord 2021;22(1):751. http://dx.doi.org/10.1186/s12891-021-04615-9CrossRef
    [6] Bouffard J, Yang C, Begon M, Côté J. Sex differences in kinematic adaptations to muscle fatigue induced by repetitive upper limb movements. Biol Sex Differ, 2018;9(1):17. http://dx.doi.org/10.1186/s13293-018-0175-9CrossRef
    [7] Seidler A, Bolm-Audorff U, Petereit-Haack G, Ball E, Klupp M, Krauss N, et al. Work-related lesions of the supraspinatus tendon: a case-control study. Int Arch Occup Environ Health 2011;84(4):425 − 33. http://dx.doi.org/10.1007/s00420-010-0567-6CrossRef
    [8] Muslim K, Nussbaum MA. Musculoskeletal symptoms associated with posterior load carriage: An assessment of manual material handling workers in Indonesia. Work 2015;51(2):205 − 13. http://dx.doi.org/10.3233/WOR-141853CrossRef
    [9] Rodriguez AC, Barrero LH. Job rotation: effects on muscular activity variability. Appl Ergon 2017;60:83 − 92. http://dx.doi.org/10.1016/j.apergo.2016.11.005CrossRef
  • TABLE 1.  Prevalence of upper-limb musculoskeletal disorders in key industries or occupational groups in China, 2018–2021 (n=72,029).

    Industry/working groupNumber
    Upper-limb musculoskeletal disorders
    npi (%)p' (%)
    Total72,02918,19325.322.5
    Animal husbandry2466225.240.8
    Biopharmaceutical manufacturing28511540.436.8
    Civil aviation1,35642031.032.5
    Healthcare industry6,9612,52036.231.5
    Ferrous metal smelting and rolling1,92144423.129.9
    Cement, lime, and gypsum manufacturing1932211.425.4
    Nonferrous metal smelting and rolling processing industry2,36469629.425.0
    Computer, communication industry, and other electronic equipment manufacturing8,9102,22925.023.3
    Automobile manufacturing21,5985,73026.522.0
    Toy manufacturing33314142.320.4
    Automobile repair and maintenance80214518.119.2
    Footwear industry7,1231,84425.918.2
    Coal mining, and washing3,46180423.217.3
    Shipping and related device manufacturing3,49388625.416.7
    Railway transportation equipment manufacturing96518619.316.7
    Agriculture2435221.416.5
    Road transportation1,31722817.316.1
    Construction1,47620614.015.2
    Power, heat, gas, water production, and supply5918213.913.5
    Furniture manufacturing8,2411,37116.612.0
    Petrochemical industry150106.74.0
    Chi-square test1203.6
    P value0
    Note: pi: actual age-specific prevalence rate, p': standardized prevalence rate.
    Download: CSV

    TABLE 2.  Univariate analysis of factors of upper-limb musculoskeletal disorders among occupational groups in key industries in China, 2018–2021.

    VariableUpper-limb musculoskeletal disorders
    Number of workersCasePercentage (%)OR (95% CI)
    Individual risk factors
     Gender
    Men49,07911,05022.51
    Women22,9507,14331.11.555 (1.502–1.611)*
     Age (years)
    <257,9091,85823.51
    25–29,5827,49525.31.105 (1.043–1.171)*
    35–19,7685,26926.71.184 (1.114–1.258)*
    45–11,3852,85725.11.091 (1.020–1.167)*
    55–3,38571421.10.871 (0.790–0.960)*
     Length of service (years)
    <219,1384,14321.61
    2–14,5493,61724.91.198 (1.138–1.260)*
    4–9,1792,33225.41.233 (1.163–1.307)*
    6–6,7901,78126.21.287 (1.207–1.372)*
    8–22,3736,32028.21.425 (1.362–1.491)*
     Educational level
    Junior high school21,3654,81022.51
    Senior high school26,6326,58624.71.131 (1.084–1.180)*
    University degree14,3653,77626.31.227 (1.169–1.289)*
    Graduate degree9,6673,02131.31.564 (1.483–1.651)*
     Body mass index (BMI)
    <18.56,6811,72525.81
    18.5–48,32312,28425.40.979 (0.924–1.038)
    25–17,0254,18424.60.936 (0.877–0.999)
     Smoking
    No43,74311,60026.51
    Occasionally13,0342,80021.50.758 (0.723–0.795)*
    Frequently15,2523,79324.90.917 (0.879–0.957)*
     Physical exercise
    No21,6195,87727.21
    Occasionally38,0739,44324.80.883 (0.851–0.918)*
    Frequently12,3372,87323.30.813 (0.772–0.856)*
    Workplace risk factor
    Standing often at work
    No11,0382,81625.51
    Yes60,99115,37725.20.984 (0.940–1.031)
     Sitting often at work
    No30,8507,79225.31
    Yes41,17910,40125.31 (0.967–1.035)
     Squatting or kneeling often at work
    No41,7769,82823.51
    Yes30,2538,36527.71.242 (1.201–1.285)*
     Lifting heavy loads (more than 5 kg)
    No25,0915,76423.01
    Yes46,93812,42926.51.208 (1.165–1.252)*
     Lifting heavy loads (more than 20 kg)
    No38,8859,18923.61
    Yes33,1449,00427.21.205 (1.165–1.247)*
     Exerting great force on the upper limbs or hands
    No11,9082,18618.41
    Yes60,12116,00726.61.614 (1.535–1.696)*
     Use of vibration tools at work
    No43,85510,08723.01
    Yes28,1748,10628.81.352 (1.307–1.399)*
     Maintaining the same posture at a high frequency
    No13,7281,92714.01
    Yes58,30116,26627.92.370 (2.251–2.495)*
     Trunk posture
    Trunk straight24,0514,44118.51
    Bending slightly at the trunk38,39810,50227.41.662 (1.598–1.729)*
    Bending heavily at the trunk9,5803,25033.92.267 (2.149–2.391)*
     Always turning around with the trunk
    No25,5125,32720.91
    Yes46,51712,86627.71.449 (1.397–1.502)*
     Always bending and twisting with the trunk
    No40,6708,31320.41
    Yes31,3599,88031.51.790 (1.731–1.852)*
     Always making the same movement with the trunk
    No28,4885,03117.71
    Yes43,54113,16230.22.020 (1.947–2.096)*
     Always bending the wrist up and down
    No25,3444,43117.51
    Yes46,68513,76229.51.973 (1.899–2.049)*
     Wrist is in a bent posture for a prolonged time
    No40,4557,50318.51
    Yes31,57410,69033.92.248 (2.172–2.326)*
     Wrist is often placed on the edge of hard and angular objects
    No45,9459,73321.21
    Yes26,0848,46032.41.786 (1.726–1.848)*
     Always pinching/grasping some objects/tools
    No16,3962,64316.11
    Yes55,63315,55028.02.019 (1.929–2.113)*
     Working above the shoulder level
    No59,21114,80425.01
    Yes12,8183,38926.41.078 (1.032–1.126)*
    Work organization factors
    Often working overtime34,0787,49222.01
    No37,95110,70128.21.394 (1.347–1.442)*
    Yes
     Abundant resting time
    No38,30312,57932.81
    Yes33,7265,61416.60.408 (0.394–0.423)*
     Deciding on an independent rest time
    No57,74115,34626.61
    Yes14,2882,84719.90.687 (0.657–0.719)*
     Staff shortage
    No38,9678,00320.51
    Yes33,06210,19030.81.724 (1.666–1.783)*
     Doing the same job nearly every day
    No8,5791,41516.51
    Yes63,45016,77826.41.820 (1.715–1.932)*
     Job rotation
    No34,6429,45727.31
    Yes37,3878,73623.40.812 (0.785–0.840)*
    Abbreviation: COR=Crude odds ratio; CI=confidence interval.
    * P<0.05.
    Download: CSV

    TABLE 3.  Multivariate logistic regression model predicting the risk factors of upper-limb musculoskeletal disorders among occupational groups in key industries in China, 2018–2021.

    VariableCoefficientWald χ2aOR95% CIP value
    Maintaining the same posture at a high frequency0.270418.7981.3101.277–1.3450.000
    Use of vibration tools at work0.14853.1341.1601.114–1.2070.000
    Working above the shoulder level0.07610.5151.0791.030–1.1300.001
    Length of service0.071117.2841.0731.060–1.0870.000
    Exerting great force on the upper limbs or hands0.0664.6751.0681.006–1.1340.031
    Lifting heavy loads (more than 20 kg)0.0567.4301.0581.016–1.1020.006
    Job rotation−0.10517.0660.9000.857–0.9460.000
    Note: North China: Beijing, Tianjin; East China: Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Jiangxi; Central China: Hubei; South China: Guangdong; Southwest China: Sichuan, Chongqing, Guizhou, Yunnan, Northwest China: Shanxi, Ningxia; Northeast China: Liaoning.
    Abbreviation: aOR=adjusted odds ratio; CI=confidence interval.
    Download: CSV

Citation:

通讯作者: 陈斌, bchen63@163.com
  • 1. 

    沈阳化工大学材料科学与工程学院 沈阳 110142

  1. 本站搜索
  2. 百度学术搜索
  3. 万方数据库搜索
  4. CNKI搜索
Turn off MathJax
Article Contents

Article Metrics

Article views(3741) PDF downloads(52) Cited by()

Share

Related

Incidence and Risk Factors of the Upper-Limb Musculoskeletal Disorders Among Occupational Groups in Key Industries — China, 2018–2021

View author affiliations

Summary

What is already known about this topic?

The burden of illness and economic losses due to upper-limb work-related musculoskeletal disorders (UL-WMSDs) is high; thus, they have become a major global public health problem. At present, the epidemiological characteristics of UL-WMSDs in China's occupational population are still unknown.

What is added by this report?

The incidence of UL-WMSDs among key occupational groups in China is 22.5%, with distinct occupational characteristics.

What are the implications for public health practice?

This study has primarily determined the occurrence and potential risk factors of UL-WMSDs in key industries in China and provided data support for recommending prevention and control of the occurrence of such diseases in key industries in China, and in facilitating the addition into the China’s List of Legal Occupational Diseases.

  • 1. National Institute of Occupational Health and Poison Control, Chinese Center for Disease Control and Prevention, Beijing Municipality, China
  • 2. Chongqing Center for Disease Control and Prevention, Chongqing Municipality, China
  • 3. Hubei Provincial Hospital of Integrated Chinese & Western Medicine, Wuhan City, Hubei Province, China
  • 4. Guangzhou Twelfth People’s Hospital Affiliated to Guangzhou Medical University, Guangzhou City, Guangdong Province, China
  • 5. Liaoning Provincial Health Service Center, Shenyang City, Liaoning Province, China
  • 6. Shanghai Center for Disease Control and Prevention, Shanghai Municipality, China
  • 7. Shandong Academy of Occupational Health and Occupational Medicine, Jinan City, Shandong Province, China
  • 8. Jiangsu Provincial Center for Disease Control and Prevention, Nanjing City, Jiangsu Province, China
  • 9. Civil Aviation Medical Center, Civil Aviation Administration of China, Beijing Municipality, China
  • 10. Guizhou Province Occupational Disease Prevention and Control Hospital, Guiyang City, Guizhou Province, China
  • 11. Tianjin Occupational Disease Prevention and Control Hospital, Tianjin Municipality, China
  • 12. Tianjin Center for Disease Control and Prevention, Tianjin Municipality, China
  • 13. Beijing Center for Disease Control and Prevention, Beijing Municipality, China
  • 14. Fujian Province Occupational Disease and Chemical Poisoning Prevention and Control Center, Fuzhou City, Fujian Province, China
  • 15. Guangdong Province Hospital for Occupational Disease Prevention and Treatment, Guangzhou City, Guangdong Province, China
  • 16. Hubei Provincial Center for Disease Control and Prevention, Wuhan City, Hubei Province, China
  • 17. Zhejiang Provincial Center for Disease Control and Prevention, Hangzhou City, Zhejiang Province, China
  • 18. Institute of Occupational Medicine of Jiangxi, Nanchang City, Jiangxi Province, China
  • 19. Ningxia Hui Autonomous Region Center for Disease Control and Prevention, Yinchuan City, Ningxia Province, China
  • 20. Sichuan Provincial Center for Disease Control and Prevention, Chengdu City, Sichuan Province, China
  • 21. Shanxi Provincial Center for Disease Control and Prevention, Xian City, Shanxi Province, China
  • 22. Yunnan Provincial Center for Disease Control and Prevention, Kunming City, Yunnan Province, China
  • Corresponding author:

    Zhongxu Wang, wangzx@niohp.chinacdc.cn

  • Funding: Funded by the Project of Occupational Health Risk Assessment and the National Occupational Health Standard Formulation of the National Institute of Occupational Health and Poison Control (Project No. 131031109000160004). National Key R&D Program of China (2022YFC2503205)
  • Online Date: December 16 2022
    Issue Date: December 16 2022
    doi: 10.46234/ccdcw2022.227
  • Upper limb work-related musculoskeletal disorders (UL-WMSDs) are the most common after lower back pain and have been included in the list of occupational diseases by the International Labor Organization (ILO). In recent years, WMSDs have been widespread among the Chinese occupational populations, leading to job replacement and long-term sick leave. It is difficult to add UL-WMSDs to China’s List of Legal Occupational Diseases because data on the occurrence of UL-WMSDs and their relationship with specific works are lacking. Therefore, this study included a large sample to conduct an epidemiological investigation and research into the occurrence of UL-WMSDs in key industry populations in different regions of China. The results showed the standardized incidence of UL-WMSDs in crucial industries or occupational groups in China is 22.5%. The risk of UL-WMSDs changes with the length of service, type of work, work posture, work organization, and other factors. The results may provide data support for recommending the prevention and control of such diseases and their inclusion in China’s List of Legal Occupational Diseases.

    The research data included in this study were obtained from seven China regions (North, East, Central, South, Southwest, Northwest, and Northeast China), and included data from 21 industries or operations, such as automobile manufacturing, furniture manufacturing, and the footwear industry. In this study, we used a stratified cluster sampling method; the workers on duty were the study participants. The inclusion criteria for subjects were employed for more than a year. The exclusion criteria were as follows: patients with congenital spinal deformity and those with non-WMSDs due to trauma, infectious diseases, and malignant tumors. This study has been reviewed by the Medical Ethical Review Committee of the Occupational Health and Poison Control at the Chinese Center for Disease Control and Prevention.

    To conduct this survey, experts used the Ergonomic Evaluation and Analysis System of WMSDs provided by the Department of Occupational Protection and Ergonomics of the National Institute of Occupational Health and Poison Control of the Chinese Center for Disease Control and Prevention was used to investigate the incidence of WMSDs and its influencing factors in participants from key industries or occupational groups in different regions of China. The system includes four other sub-systems: an electronic ergonomics survey and evaluation tool for remote operation site, a real-time data monitoring system, a data transmission network, and a background data terminal. This study's survey tool (the Chinese electronic version of the musculoskeletal disorders questionnaire) was one of the built-in questionnaires in the system, namely. This electronic questionnaire system was based on the Nordic Musculoskeletal Disorders Questionnaire (NMQ) and Dutch Musculoskeletal Questionnaire (DMQ) (1-2). After appropriate modification, it was shown to have good reliability and validity, and can be used for Chinese occupational populations. After the survey data were exported from the backend database, they were statistically processed using SPSS 20.0 statistical software (version 20.0, SPSS Inc, Chicago, IL, USA). Based on China’s population composition data, the standardized incidence rate of upper-limb musculoskeletal disorders was calculated using the direct method. The single-factor analysis of WMSDs adopts the χ2 test method, multivariate analysis was performed using an unconditional logistic regression model.

    Till date, 72,029 valid questionnaires have been received. Table 1 shows that the standardized rate of UL-WMSDs in key industries or occupational groups in China was 22.5%, and the standardized rates differed significantly between different industries (P<0.05). The standardized incidence rates (ranked from the highest to the lowest) in the top five industries were animal husbandry (40.8%), biopharmaceutical product manufacturing (36.8%), civil aviation (32.5%), healthcare industry (31.5%), ferrous metal smelting and rolling processing industry (29.9%).

    Industry/working groupNumber
    Upper-limb musculoskeletal disorders
    npi (%)p' (%)
    Total72,02918,19325.322.5
    Animal husbandry2466225.240.8
    Biopharmaceutical manufacturing28511540.436.8
    Civil aviation1,35642031.032.5
    Healthcare industry6,9612,52036.231.5
    Ferrous metal smelting and rolling1,92144423.129.9
    Cement, lime, and gypsum manufacturing1932211.425.4
    Nonferrous metal smelting and rolling processing industry2,36469629.425.0
    Computer, communication industry, and other electronic equipment manufacturing8,9102,22925.023.3
    Automobile manufacturing21,5985,73026.522.0
    Toy manufacturing33314142.320.4
    Automobile repair and maintenance80214518.119.2
    Footwear industry7,1231,84425.918.2
    Coal mining, and washing3,46180423.217.3
    Shipping and related device manufacturing3,49388625.416.7
    Railway transportation equipment manufacturing96518619.316.7
    Agriculture2435221.416.5
    Road transportation1,31722817.316.1
    Construction1,47620614.015.2
    Power, heat, gas, water production, and supply5918213.913.5
    Furniture manufacturing8,2411,37116.612.0
    Petrochemical industry150106.74.0
    Chi-square test1203.6
    P value0
    Note: pi: actual age-specific prevalence rate, p': standardized prevalence rate.

    Table 1.  Prevalence of upper-limb musculoskeletal disorders in key industries or occupational groups in China, 2018–2021 (n=72,029).

    The influencing factors of UL-WMSDs were divided into individual, work type, and work organization factors. The univariate analysis results (Table 2) show that gender, age, length of service, educational level, smoking status, sports, and other individual-level factors were significantly associated with the occurrence of UL-WMSDs (P<0.05). The incidence of UL-WMSDs in women was higher than that in men. The risk of UL-WMSDs increased with the length of service and educational level. The risk of UL-WMSDs in smoking and physical exercise groups was significantly lower than in the control group. Maintaining the same posture at a high frequency, always making the same movement with the trunk, always pinching/grasping some objects/tools, wrist is in a bent posture for a prolonged time, and other factors such as work type correlated significantly with the occurrence of UL-WMSDs (P<0.05). Frequent overtime work, staff shortages, and doing the same job nearly every day are positively correlated with the occurrence of UL-WMSDs, and the difference is statistically significant (P<0.05).

    VariableUpper-limb musculoskeletal disorders
    Number of workersCasePercentage (%)OR (95% CI)
    Individual risk factors
     Gender
    Men49,07911,05022.51
    Women22,9507,14331.11.555 (1.502–1.611)*
     Age (years)
    <257,9091,85823.51
    25–29,5827,49525.31.105 (1.043–1.171)*
    35–19,7685,26926.71.184 (1.114–1.258)*
    45–11,3852,85725.11.091 (1.020–1.167)*
    55–3,38571421.10.871 (0.790–0.960)*
     Length of service (years)
    <219,1384,14321.61
    2–14,5493,61724.91.198 (1.138–1.260)*
    4–9,1792,33225.41.233 (1.163–1.307)*
    6–6,7901,78126.21.287 (1.207–1.372)*
    8–22,3736,32028.21.425 (1.362–1.491)*
     Educational level
    Junior high school21,3654,81022.51
    Senior high school26,6326,58624.71.131 (1.084–1.180)*
    University degree14,3653,77626.31.227 (1.169–1.289)*
    Graduate degree9,6673,02131.31.564 (1.483–1.651)*
     Body mass index (BMI)
    <18.56,6811,72525.81
    18.5–48,32312,28425.40.979 (0.924–1.038)
    25–17,0254,18424.60.936 (0.877–0.999)
     Smoking
    No43,74311,60026.51
    Occasionally13,0342,80021.50.758 (0.723–0.795)*
    Frequently15,2523,79324.90.917 (0.879–0.957)*
     Physical exercise
    No21,6195,87727.21
    Occasionally38,0739,44324.80.883 (0.851–0.918)*
    Frequently12,3372,87323.30.813 (0.772–0.856)*
    Workplace risk factor
    Standing often at work
    No11,0382,81625.51
    Yes60,99115,37725.20.984 (0.940–1.031)
     Sitting often at work
    No30,8507,79225.31
    Yes41,17910,40125.31 (0.967–1.035)
     Squatting or kneeling often at work
    No41,7769,82823.51
    Yes30,2538,36527.71.242 (1.201–1.285)*
     Lifting heavy loads (more than 5 kg)
    No25,0915,76423.01
    Yes46,93812,42926.51.208 (1.165–1.252)*
     Lifting heavy loads (more than 20 kg)
    No38,8859,18923.61
    Yes33,1449,00427.21.205 (1.165–1.247)*
     Exerting great force on the upper limbs or hands
    No11,9082,18618.41
    Yes60,12116,00726.61.614 (1.535–1.696)*
     Use of vibration tools at work
    No43,85510,08723.01
    Yes28,1748,10628.81.352 (1.307–1.399)*
     Maintaining the same posture at a high frequency
    No13,7281,92714.01
    Yes58,30116,26627.92.370 (2.251–2.495)*
     Trunk posture
    Trunk straight24,0514,44118.51
    Bending slightly at the trunk38,39810,50227.41.662 (1.598–1.729)*
    Bending heavily at the trunk9,5803,25033.92.267 (2.149–2.391)*
     Always turning around with the trunk
    No25,5125,32720.91
    Yes46,51712,86627.71.449 (1.397–1.502)*
     Always bending and twisting with the trunk
    No40,6708,31320.41
    Yes31,3599,88031.51.790 (1.731–1.852)*
     Always making the same movement with the trunk
    No28,4885,03117.71
    Yes43,54113,16230.22.020 (1.947–2.096)*
     Always bending the wrist up and down
    No25,3444,43117.51
    Yes46,68513,76229.51.973 (1.899–2.049)*
     Wrist is in a bent posture for a prolonged time
    No40,4557,50318.51
    Yes31,57410,69033.92.248 (2.172–2.326)*
     Wrist is often placed on the edge of hard and angular objects
    No45,9459,73321.21
    Yes26,0848,46032.41.786 (1.726–1.848)*
     Always pinching/grasping some objects/tools
    No16,3962,64316.11
    Yes55,63315,55028.02.019 (1.929–2.113)*
     Working above the shoulder level
    No59,21114,80425.01
    Yes12,8183,38926.41.078 (1.032–1.126)*
    Work organization factors
    Often working overtime34,0787,49222.01
    No37,95110,70128.21.394 (1.347–1.442)*
    Yes
     Abundant resting time
    No38,30312,57932.81
    Yes33,7265,61416.60.408 (0.394–0.423)*
     Deciding on an independent rest time
    No57,74115,34626.61
    Yes14,2882,84719.90.687 (0.657–0.719)*
     Staff shortage
    No38,9678,00320.51
    Yes33,06210,19030.81.724 (1.666–1.783)*
     Doing the same job nearly every day
    No8,5791,41516.51
    Yes63,45016,77826.41.820 (1.715–1.932)*
     Job rotation
    No34,6429,45727.31
    Yes37,3878,73623.40.812 (0.785–0.840)*
    Abbreviation: COR=Crude odds ratio; CI=confidence interval.
    * P<0.05.

    Table 2.  Univariate analysis of factors of upper-limb musculoskeletal disorders among occupational groups in key industries in China, 2018–2021.

    Abundant resting time, deciding on an independent rest time and job rotation are the protective factor of UL-WMSDs. The results of the multiple logistic regression showed that the influencing factors of UL-WMSDs were maintaining the same postures at a high frequency, use of vibration tools at work, working above shoulder level, length of service (in years), exerting great force on the upper limbs or hands, lifting of heavy loads (more than 20 kg) and job rotation, according to the odds ratio (OR). The last item, job rotation, is a protective factor (Table 3).

    VariableCoefficientWald χ2aOR95% CIP value
    Maintaining the same posture at a high frequency0.270418.7981.3101.277–1.3450.000
    Use of vibration tools at work0.14853.1341.1601.114–1.2070.000
    Working above the shoulder level0.07610.5151.0791.030–1.1300.001
    Length of service0.071117.2841.0731.060–1.0870.000
    Exerting great force on the upper limbs or hands0.0664.6751.0681.006–1.1340.031
    Lifting heavy loads (more than 20 kg)0.0567.4301.0581.016–1.1020.006
    Job rotation−0.10517.0660.9000.857–0.9460.000
    Note: North China: Beijing, Tianjin; East China: Shanghai, Jiangsu, Zhejiang, Fujian, Shandong, Jiangxi; Central China: Hubei; South China: Guangdong; Southwest China: Sichuan, Chongqing, Guizhou, Yunnan, Northwest China: Shanxi, Ningxia; Northeast China: Liaoning.
    Abbreviation: aOR=adjusted odds ratio; CI=confidence interval.

    Table 3.  Multivariate logistic regression model predicting the risk factors of upper-limb musculoskeletal disorders among occupational groups in key industries in China, 2018–2021.

    • This study was an occupational health risk assessment investigation established by the Chinese Center for Disease Control and Prevention from January 2018 to December 2023. It is the largest population survey on WMSDs in China so far. It aimed to include a large sample to conduct an epidemiological survey and research into the occurrence of UL-WMSDs in critical industries or occupational groups in different regions of China. This aim was to determine the occurrence and distribution characteristics of WMSDs in key sectors in China. Furthermore, we explored the epidemic rule and identified the influencing factors of WMSDs.

      Moreover, our study provided big data to support the inclusion of WMSDs in crucial industries in China’s List of Legal Occupational Diseases. The study published relevant reports in China CDC Weekly in 2020 and 2021, respectively (3-4). The data reported in this paper were those collected until 2021. Hence, they only described the occurrence of UL-WMSDs and analyzed the relevant influencing factors.

      The survey results show that the standardized rate of UL-WMSDs in key industries or occupational groups in China was 22.5%. A survey (5) on musculoskeletal diseases related to work during the second industrial revolution in the 21st century in Europe shows a prevalence of upper limb musculoskeletal diseases between 4% and 26%, similar to our survey results. The survey found a significantly different incidence of WMSDs among different industries and showed that WMSDs were related to the work type and work organization factors, with prominent occupational characteristics. This study found that animal husbandry and biopharmaceutical product manufacturing had the highest upper limb musculoskeletal diseases among the industries, with an incidence of more than 35%. The survey found that the operation mode in the above two industries occurred during the assembly line operation, and workers’ hands, wrists, and elbows needed quick and repetitive activity. At the end of each operation cycle, there was little or very short rest time. Research shows that (6) prolonged, repeated exertion may lead to local muscle fatigue and, if left unrecovered for a long time, causes musculoskeletal disorders easily. The risk factors of UL-WMSDs can be divided into individual-level, work type, and work organization factors. The results of this study showed that, in terms of individual-level factors, gender, age, length of service, educational level, smoking status, and sports were all related to the occurrence of UL-WMSDs (P<0.05). Of these, length of service remained a significant variable in univariate and multivariate logistic regression analyses. In terms of the work type factors, repetitive work in the same posture at a high frequency, use of vibration tools at work, working above shoulder level, exerting great force on the upper limbs or hands, lifting of heavy loads (more than 20 kg) are all risk factors of UL-WMSDs. A large number of scholarly articles have confirmed the above results. A population-based case-control study found (7) a dose-response relationship between the cumulative duration of work with highly elevated arms (positioned above shoulder level) and ruptures of the supraspinatus tendon.

      The results of this study show that the risk of UL-WMSDs will increase when handling objects that weigh over 20 kg. Some studies have also confirmed (8) that the occurrence of UL-WMSDs is positively correlated with the weight of the object being carried (load mass). This may be related to manual handling without the use of auxiliary tools. The heavier the load of moving objects, the harder it is for workers to carry them, resulting in increased hand pain. In terms of work organization factors, the results of this study show that job rotation is a protective factor of UL-WMSDs. Previous studies also support this view. A study showed that (9) the implementation of job rotation can help increase the variability of muscle activities, particularly in upper extreme muscles and can reduce the burden of occupational injury.

      Although this study is a population survey with a large sample used to clarify the epidemiological characteristics and risk factors of UL-WMSDs in critical sectors or occupational groups in China, the following limitations still exist. First, the current study’s design makes it difficult to determine the temporal relationship between the antecedents and consequences and infer the causal relationship between the risk factors and the occurrence of UL-WMSDs. Second, this study used questionnaires to obtain information about the respondents’ illnesses in the past year. Since it is easy to forget the past, report and recall bias could have occurred.

      In conclusion, the standardized incidence of UL-WMSDs in key industries or occupational groups in China is 22.5%. UL-WMSDs have recognized occupation-related characteristics, and their risk factors change with the length of service, type of work, work posture, work organization, and other factors. Given this, it is suggested to continue to carry out special epidemiological investigation and research on a large sample of the occupational population in key industries nationwideand establish a database of factors related to musculoskeletal disorders among occupational population in key industries in China, to provide extensive data support for listing UL-WMSDs to relevant regions in China’s List of Legal Occupational Diseases.

    • 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, 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, Guangdong Province Hospital for Occupational Disease Prevention and Treatment, and Institute of Occupational Medicine of Jiangxi.

Reference (9)

Citation:

Catalog

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return