Global systematic review of biomechanical and ergonomic assessment outcomes among urban transit operators

Authors

DOI:

https://doi.org/10.35816/jiksh.v15i2.331

Keywords:

ergonomics, musculoskeletal disorders, occupational health, whole-body vibration

Abstract

Introduction: Urban transit operators, including bus drivers, train operators, and metro personnel, are chronically exposed to biomechanical stressors and ergonomic hazards predisposing them to musculoskeletal disorders (MSDs), whole-body vibration (WBV)-related spinal pathology, and psychosocial morbidity. To systematically identify, critically appraise, and synthesise biomechanical and ergonomic assessment outcomes among urban transit operators worldwide.

Research Methodology: This systematic review followed the PRISMA 2020 guidelines and used the PICOS framework. English-language studies published between 2000 and 2024 were retrieved from PubMed, Medline, Embase, Scopus, Global Health, and Google Scholar. Quality appraisal employed the JBI Critical Appraisal Checklist for Analytical Cross-Sectional Studies. Narrative synthesis was applied due to methodological heterogeneity, which precluded meta-analysis.

Results: Of 312 identified records, 45 Cross-Sectional studies from 23 countries (n = 12,859 workers) met the inclusion criteria. Bus drivers comprised 52% of the study population. The predominant outcome domain was MSDs (31%), followed by WBV exposure (24%), psychosocial and fatigue outcomes (18%), postural risk (11%), ergonomic risk assessment (9%), and occupational injuries (9%). Low back pain (LBP) prevalence ranged from 43% to 78%. WBV exposures frequently exceeded the 0.5 m/s² Exposure Action Value under EU Directive 2002/44/EC. Quality appraisal rated 60% of studies as low risk, 31% as moderate risk, and 9% as high risk of bias.

Conclusion: Urban transit operators represent a high-risk occupational group for biomechanical and ergonomic hazards. Standardised longitudinal studies, objective exposure assessment, and equitable geographic representation are urgently needed to inform globally applicable prevention guidelines.

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References

Adhaye, A. M., Jolhe, D. A., Loyte, A. R., Devarajan, Y., & Thanappan, S. (2023). Biomechanical investigation of tasks concerning manual materials handling using response surface methodology. Scientific Reports, 13(1). https://doi.org/10.1038/s41598-023-43645-2

Arippa, F., Leban, B., Fadda, P., Fancello, G., & Pau, M. (2021). Trunk sway changes in professional bus drivers during actual shifts on long-distance routes. Ergonomics, 65(5), 762–774. https://doi.org/10.1080/00140139.2021.1991002

Bassani, G., Filippeschi, A., & Avizzano, C. A. (2021). A Dataset of Human Motion and Muscular Activities in Manual Material Handling Tasks for Biomechanical and Ergonomic Analyses. IEEE Sensors Journal, 21(21), 24731–24739. https://doi.org/10.1109/jsen.2021.3113123

Batool, Z., Younis, M. W., Yasir, A., Rehman, A. U., Dilawar, M., Yasin, M., Hamza, M., Shahzad, S., Ali, M. S., Jamil, A., & Asghar Khan, M. H. (2021). Effects of safety pattern, cabin ergonomics, and sleep on work-related stress and burnout of city and transit bus drivers in Lahore, Pakistan. Ergonomics, 65(5), 704–718. https://doi.org/10.1080/00140139.2021.1983029

Bovenzi, M., & Schust, M. (2021). A prospective cohort study of low-back outcomes and alternative measures of cumulative external and internal vibration load on the lumbar spine of professional drivers. Scandinavian Journal of Work, Environment & Health, 47(4), 277–286. https://doi.org/10.5271/sjweh.3947

Brosche, J., Wackerle, H., Augat, P., & Lödding, H. (2024). Individualized workplace ergonomics using motion capture. Applied Ergonomics, 114, 104140. https://doi.org/10.1016/j.apergo.2023.104140

Chand, A., & Bhasi, A. B. (2023). Anthropometric Assessment of Heavy-Duty Driver Postures Using RULA Method. Transactions of the Indian National Academy of Engineering, 8(4), 617–623. https://doi.org/10.1007/s41403-023-00420-z

Cheng, Z., Luo, B., Chen, C., Guo, H., Wu, J., & Chen, D. (2024). Study on Static Biomechanical Model of Whole Body Based on Virtual Human. Sensors, 24(20). https://doi.org/10.3390/s24206504

Fan, X., Lind, C. M., Rhen, I.-M., & Forsman, M. (2021). Effects of Sensor Types and Angular Velocity Computational Methods in Field Measurements of Occupational Upper Arm and Trunk Postures and Movements. Sensors, 21(16), 5527. https://doi.org/10.3390/s21165527

Gupta, N., Bjerregaard, S. S., Yang, L., Forsman, M., Rasmussen, C. L., Rasmussen, C. D. N., Clays, E., & Holtermann, A. (2022). Does occupational forward bending of the back increase long-term sickness absence risk? A 4-year prospective register-based study using device-measured compositional data analysis. Scandinavian Journal of Work, Environment & Health, 48(8), 651–661. https://doi.org/10.5271/sjweh.4047

Hota, S., & Tewari, V. K. (2024). A Machine Learning–Based Ergonomic Assessment of Wireless Hand Control System for Lower‐Limb Disabled Tractor Operators and Abled Female Agricultural Workers. Journal of Field Robotics, 42(4), 1344–1360. https://doi.org/10.1002/rob.22458

Hota, S., Tewari, V. K., & Chandel, A. K. (2023). Workload Assessment of Tractor Operations with Ergonomic Transducers and Machine Learning Techniques. Sensors, 23(3). https://doi.org/10.3390/s23031408

Kearney, J., Muir, C., Salmon, P., & Smith, K. (2024). Rethinking paramedic occupational injury surveillance: A systems approach to better understanding paramedic work-related injury. Safety Science, 172, 106419. https://doi.org/10.1016/j.ssci.2024.106419

Khamaisi, R. K., Perini, M., Morganti, A., Placci, M., Grandi, F., Peruzzini, M., & Botti, L. (2024). An innovative integrated solution to support digital postural assessment using the TACOs methodology. Computers and Industrial Engineering, 194. https://doi.org/10.1016/j.cie.2024.110376

Kia, K., Park, J., Chan, A., Srinivasan, D., & Kim, J. H. (2025). Vertical-dominant and multi-axial vibration associated with heavy vehicle operation: Effects on dynamic postural control. Applied Ergonomics, 122, 104402. https://doi.org/10.1016/j.apergo.2024.104402

Kibria, M. G., Parvez, M. S., Saha, P., & Talapatra, S. (2023). Evaluating the ergonomic deficiencies in computer workstations and investigating their correlation with reported musculoskeletal disorders and visual symptoms among computer users in Bangladeshi university. Heliyon, 9(11), e22179. https://doi.org/10.1016/j.heliyon.2023.e22179

Kim, I.-J. (2023). An ergonomic focus evaluation of work-related musculoskeletal disorders amongst operators in the UAE network control centres. Heliyon, 9(10), e21140. https://doi.org/10.1016/j.heliyon.2023.e21140

Korshøj, M., Svendsen, S. W., Hendriksen, P. F., Gupta, N., Holtermann, A., Andersen, J. H., Dalbøge, A., & Frost, P. (2022). Agreement between an expert-rated mini job exposure matrix of occupational biomechanical exposures to the lower body and technical measurements or observation: a method comparison study. BMJ Open, 12(12), e064035. https://doi.org/10.1136/bmjopen-2022-064035

Lin, P. C., Chen, Y. J., Chen, W. S., & Lee, Y. J. (2022). Automatic real-time occupational posture evaluation and select corresponding ergonomic assessments. Scientific Reports, 12(1). https://doi.org/10.1038/s41598-022-05812-9

Lind, C. M., Abtahi, F., & Forsman, M. (2023). Wearable Motion Capture Devices for the Prevention of Work-Related Musculoskeletal Disorders in Ergonomics—An Overview of Current Applications, Challenges, and Future Opportunities. Sensors, 23(9), 4259. https://doi.org/10.3390/s23094259

Lolli, F., Coruzzolo, A. M., Forgione, C., Peron, M., & Sgarbossa, F. (2024). Auto-AzKNIOSH: an automatic NIOSH evaluation with Azure Kinect coupled with task recognition. Ergonomics, 68(10), 1718–1734. https://doi.org/10.1080/00140139.2024.2433027

Marín, J., & Marín, J. J. (2021). Forces: A motion capture-based ergonomic method for the today’s world. Sensors, 21(15). https://doi.org/10.3390/s21155139

Nie, H., Hu, M., & Yin, F. (2021). Ergonomics Analysis of Bus Seat Based on Jack. In 2021 IEEE 12th International Conference on Software Engineering and Service Science (ICSESS) (pp. 266–269). IEEE. https://doi.org/10.1109/icsess52187.2021.9522169

Petrovic, M., Vukicevic, A. M., Djapan, M., Peulic, A., Jovicic, M., Mijailovic, N., Milovanovic, P., Grajic, M., Savkovic, M., Caiazzo, C., Isailovic, V., Macuzic, I., & Jovanovic, K. (2022). Experimental Analysis of Handcart Pushing and Pulling Safety in an Industrial Environment by Using IoT Force and EMG Sensors: Relationship with Operators’ Psychological Status and Pain Syndromes. Sensors, 22(19), 7467. https://doi.org/10.3390/s22197467

Prauzek, M., Dolezal, J., Urbanek, T., Prycl, D., Macurova, L., Lhotska, L., & Konecny, J. (2025). Integration of Wearable Electromyography Sensors With Cloud-Based Analytics for Biomechanical Overload Monitoring and Ergonomic Evaluation. IEEE Access, 13, 179886–179900. https://doi.org/10.1109/access.2025.3621836

Sabino, I., Fernandes, M. do C., Antunes, A., Monteny, A., Mendes, B., Caldeira, C., Guimarães, I., Grazina, N., Probst, P., Cepeda, C., Quaresma, C., Gamboa, H., Nunes, I. L., & Gabriel, A. T. (2025). Ergo4Workers: A User-Centred App for Tracking Posture and Workload in Healthcare Professionals. Sensors, 25(18), 5854. https://doi.org/10.3390/s25185854

Salehi, M., Park, J., Srinivasan, D., & Kim, J. H. (2025). Simulation-based biomechanical assessment of a passive back support exoskeleton: Comparison of various support levels during a sustained forward bending task. Applied Ergonomics, 129, 104620. https://doi.org/10.1016/j.apergo.2025.104620

Seo, H., Pham, H. T. T. L., Golabchi, A., Seo, J., & Han, S. (2023). A case study of motion data-driven biomechanical assessment for identifying and evaluating ergonomic interventions in reinforced-concrete work. Developments in the Built Environment, 16, 100236. https://doi.org/10.1016/j.dibe.2023.100236

Shakourisalim, M., Wang, X., Beltran Martinez, K., Golabchi, A., Krell, S., Tavakoli, M., & Rouhani, H. (2024). A comparative study of biomechanical assessments in laboratory and field settings for manual material handling tasks using extractor tools and exoskeletons. Frontiers in Bioengineering and Biotechnology, 12. https://doi.org/10.3389/fbioe.2024.1358670

Silva, R. L. A., Alves, K. G., da Costa, J. Â. P., Ochoa, A. A. V., Yamada, R. N. J., Michima, P. S. A., Leite, G. de N. P., & Lima, Á. A. S. (2025). Computer Simulation of Whole-Body Vibration in Port Container Handling Machine Operators. Sensors, 25(20), 6346. https://doi.org/10.3390/s25206346

Su, J.-M., Chang, J.-H., Indrayani, N. L. D., & Wang, C.-J. (2023). Machine learning approach to determine the decision rules in ergonomic assessment of working posture in sewing machine operators. Journal of Safety Research, 87, 15–26. https://doi.org/10.1016/j.jsr.2023.08.008

Suzianti, A., Sabrina, G., Ardi, R., & Fathia, S. N. (2022). Designing a sustainable digital control room for public transport: a comprehensive human performance measurement model. Production & Manufacturing Research, 10(1), 160–175. https://doi.org/10.1080/21693277.2022.2064932

Toner, J., Rickards, J., Seaman, K., & Kuruganti, U. (2021). Alteration in HDEMG Spatial Parameters of Trunk Muscle Due to Handle Design during Pushing. Sensors, 21(19), 6646. https://doi.org/10.3390/s21196646

Tröster, M., Eckstein, S., Kennel, P., Kopp, V., Benkiser, A., Bihlmeier, F., Daub, U., Maufroy, C., Dendorfer, S., Fritzsche, L., Schneider, U., & Bauernhansl, T. (2026). Person-specific evaluation method for occupational exoskeletons – Biomechanical body heat map. Applied Ergonomics, 132, 104671. https://doi.org/10.1016/j.apergo.2025.104671

Valentim, D. P., Comper, M. L. C., Sandy Medeiros Rodrigues Cirino, L., da Silva, P. R., Padilha Alonso Gomes, M., Martins da Silva, A., & Padula, R. S. (2024). Observational methods for the analysis of biomechanical exposure in the workplace: a systematic review. Ergonomics, 68(10), 1561–1582. https://doi.org/10.1080/00140139.2024.2427864

Vujica Herzog, N., Buchmeister, B., Jaehyun, P., & Kaya, O. (2024). Enhancing workplace safety and ergonomics with motion capture systems: Present state and a case study. Advances in Production Engineering & Management, 19(3), 333–346. https://doi.org/10.14743/apem2024.3.510

Yin, W., Chen, Y., Reddy, C., Zheng, L., Mehta, R. K., & Zhang, X. (2023). Flexible sensor-based biomechanical evaluation of low-back exoskeleton use in lifting. Ergonomics, 67(2), 182–193. https://doi.org/10.1080/00140139.2023.2216408

Yusriyanto, & Asran. (2026). Impact of PPE availability and safety training on occupational health implementation in rural construction projects: a cross-sectional study. Jurnal Ilmiah Kesehatan Sandi Husada, 14(1), 114–122. https://doi.org/10.35816/jiksh.v14i1.316

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Published

15-07-2026

How to Cite

Setyo Nugroho, B. Y., Pramitasi, R., Asfawi, S., & Ashraf Fauzi, M. (2026). Global systematic review of biomechanical and ergonomic assessment outcomes among urban transit operators. Jurnal Ilmiah Kesehatan Sandi Husada, 15(2), 422–435. https://doi.org/10.35816/jiksh.v15i2.331

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