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Predictive Factors of Short-Term Related Musculoskeletal Pain in the Automotive Industry

Author

Listed:
  • Ana Assunção

    (Biomechanics and Functional Morphology Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, 1499-002 Cruz Quebrada-Dafundo, Portugal)

  • Vera Moniz-Pereira

    (Biomechanics and Functional Morphology Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, 1499-002 Cruz Quebrada-Dafundo, Portugal)

  • Carlos Fujão

    (Volkswagen Autoeuropa—Industrial Engineering & Lean Management, Quinta da Marquesa, 2954-024 Palmela, Portugal)

  • Sarah Bernardes

    (Biomechanics and Functional Morphology Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, 1499-002 Cruz Quebrada-Dafundo, Portugal)

  • António P. Veloso

    (Biomechanics and Functional Morphology Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, 1499-002 Cruz Quebrada-Dafundo, Portugal)

  • Filomena Carnide

    (Biomechanics and Functional Morphology Laboratory, CIPER, Faculdade de Motricidade Humana, Universidade de Lisboa, 1499-002 Cruz Quebrada-Dafundo, Portugal)

Abstract

To determine the short-term associations between biomechanical risk factors and musculoskeletal symptoms in the upper limbs and low back in an automotive company, a longitudinal study with a follow-up of 4 days was conducted in a sample of 228 workers of the assembly and paint areas. Data were analyzed using generalized estimating equations, calculating the crude and adjusted model for age, sex, seniority, and intensity of pain at baseline. The interactions found were the same for both models. Workers were divided in low-risk and high-risk group for posture, force, exposure, percentage of cycle time with the arm at/above shoulder level, and with the trunk flexed or/and strongly flexed. The predictive factors showed by time × group effect were found between pain intensity on the left shoulder for posture (β = 0.221, p < 0.001), percentage of time with the trunk flexed (β = 0.136, p = 0.030) and overall exposure (β = 0.140, p = 0.013). A time × group interactions were observed, namely between neck pain and posture (β = 0.218, p = 0.005) and right wrist and force (β = 0.107, p = 0.044). Workers in the high-risk group were more prone to report unfavorable effects on their self-reported musculoskeletal pain, across a workweek when exposed to specific risk factor, being posture important to neck, right wrist and left shoulder pain.

Suggested Citation

  • Ana Assunção & Vera Moniz-Pereira & Carlos Fujão & Sarah Bernardes & António P. Veloso & Filomena Carnide, 2021. "Predictive Factors of Short-Term Related Musculoskeletal Pain in the Automotive Industry," IJERPH, MDPI, vol. 18(24), pages 1-12, December.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:24:p:13062-:d:699878
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    Citations

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    Cited by:

    1. Linghao Ni & Fengqiong Chen & Ruihong Ran & Xiaoping Li & Nan Jin & Huadong Zhang & Bin Peng, 2022. "A Deep Learning-Based Model for Predicting Abnormal Liver Function in Workers in the Automotive Manufacturing Industry: A Cross-Sectional Survey in Chongqing, China," IJERPH, MDPI, vol. 19(21), pages 1-14, November.
    2. Nafiseh Mollaei & Carlos Fujao & Luis Silva & Joao Rodrigues & Catia Cepeda & Hugo Gamboa, 2022. "Human-Centered Explainable Artificial Intelligence: Automotive Occupational Health Protection Profiles in Prevention Musculoskeletal Symptoms," IJERPH, MDPI, vol. 19(15), pages 1-27, August.

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