JIANG Ping, DONG Yidan, JIN Xu, JIANG Nanyu, PENG Yu, HUANG Wenchu, HE Lihua. Influencing factors for work-related musculoskeletal disorders among assembly workers in four manufacturing enterprises[J]. Journal of Environmental and Occupational Medicine, 2022, 39(6): 593-599. DOI: 10.11836/JEOM21569
Citation: JIANG Ping, DONG Yidan, JIN Xu, JIANG Nanyu, PENG Yu, HUANG Wenchu, HE Lihua. Influencing factors for work-related musculoskeletal disorders among assembly workers in four manufacturing enterprises[J]. Journal of Environmental and Occupational Medicine, 2022, 39(6): 593-599. DOI: 10.11836/JEOM21569

Influencing factors for work-related musculoskeletal disorders among assembly workers in four manufacturing enterprises

  • 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.

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