Systematic Comparison of OWAS, RULA, and REBA Based on a Literature Review
Abstract
:1. Introduction
2. Materials and Methods
3. Results
3.1. General Characteristics
3.2. Application Fields
3.3. Risk Levels by Methods
3.4. Agreement Rates between Methods
3.5. Correlations between Methods
3.6. Inter- and Intra-Rater Reliability
3.7. Validation of the Three Methods
4. Discussion
5. Conclusions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Bhattacharya, A. Costs of occupational musculoskeletal disorders (MSDs) in the United States. Int. J. Ind. Ergon. 2014, 44, 448–454. [Google Scholar] [CrossRef]
- Ministry of Employment and Labor. The Analysis of Industrial Accidents; Ministry of Employment and Labor: Sejong, Korea, 2021.
- International Labour Organization (ILO). World Day for Safety and Health at Work, 28 April 2015: Global Trends on Occupational Accidents and Diseases. Available online: https://www.ilo.org/legacy/english/osh/en/story_content/external_files/fs_st_1-ILO_5_en.pdf (accessed on 20 May 2021).
- Kumar, S. Theories of musculoskeletal injury causation. Ergonomics 2001, 44, 17–47. [Google Scholar] [CrossRef] [PubMed]
- David, G.C. Ergonomic methods for assessing exposure to risk factors for work-related musculoskeletal disorders. Occup. Med. 2005, 55, 190–199. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hita-Gutiérrez, M.; Gómez-Galán, M.; Díaz-Pérez, M.; Callejón-Ferre, Á.-J. An overview of REBA method applications in the world. Int. J. Environ. Res. Public Health 2020, 17, 2635. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Roman-Liu, D.; Groborz, A.; Tokarski, T. Comparison of risk assessment procedures used in OCRA and ULRA methods. Ergonomics 2013, 56, 1584–1598. [Google Scholar] [CrossRef] [Green Version]
- McAtamney, L.; Corlett, E.N. RULA: A survey method for the investigation of work-related upper limb disorders. Appl. Ergon. 1993, 24, 91–99. [Google Scholar] [CrossRef]
- Hignett, S.; McAtamney, L. Rapid Entire Body Assessment (REBA). Appl. Ergon. 2000, 31, 201–205. [Google Scholar] [CrossRef]
- Karhu, O.; Kansi, P.; Kuorinka, I. Correcting working postures in industry: A practical method for analysis. Appl. Ergon. 1977, 8, 199–201. [Google Scholar] [CrossRef]
- Lowe, B.D.; Dempsey, P.G.; Jones, E.M. Ergonomics assessment methods used by ergonomics professionals. Appl. Ergon. 2019, 81, 102882. [Google Scholar] [CrossRef] [PubMed]
- Chiasson, M.; Imbeau, D.; Aubry, K.; Delisle, A. Comparing the results of eight methods used to evaluate risk factors associated with musculoskeletal disorders. Int. J. Ind. Ergon. 2012, 42, 478–488. [Google Scholar] [CrossRef]
- Genaidy, A.; Al-Shedi, A.; Karwowski, W. Postural stress analysis in industry. Appl. Ergon. 1994, 25, 77–87. [Google Scholar] [CrossRef]
- Gómez-Galán, M.; Pérez-Alonso, J.; Callejón-Ferre, Á.-J.; López-Martínez, J. Musculoskeletal disorders: OWAS review. Ind. Heal. 2017, 55, 314–337. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Sukadarin, E.H.; Deros, B.M.; Ghani, J.A.; Nawi, N.S.M.; Ismail, A.R. Postural assessment in pen-and-paper-based observational methods and their associated health effects: A review. Int. J. Occup. Saf. Ergon. 2016, 22, 389–398. [Google Scholar] [CrossRef] [PubMed]
- Takala, E.-P.; Pehkonen, I.; Forsman, M.; Hansson, G.-Å.; Mathiassen, S.E.; Neumann, W.P.; Sjøgaard, G.; Veiersted, K.B.; Westgaard, R.H.; Winkel, J. Systematic evaluation of observational methods assessing biomechanical exposures at work. Scand. J. Work Environ. Health 2010, 36, 3–24. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Roman-Liu, D. Comparison of concepts in easy-to-use methods for MSD risk assessment. Appl. Ergon. 2014, 45, 420–427. [Google Scholar] [CrossRef]
- Gómez-Galán, M.; Callejón-Ferre, Á.-J.; Pérez-Alonso, J.; Díaz-Pérez, M.; Carrillo-Castrillo, J.-A. Musculoskeletal risks: RULA bibliometric review. Int. J. Environ. Res. Public Health 2020, 17, 4354. [Google Scholar] [CrossRef]
- Joshi, M.; Deshpande, V. A systematic review of comparative studies on ergonomic assessment techniques. Int. J. Ind. Ergon. 2019, 74, 1–14. [Google Scholar] [CrossRef]
- Bartnicka, J. Knowledge-based ergonomic assessment of working conditions in surgical ward—A case study. Saf. Sci. 2015, 71, 178–188. [Google Scholar] [CrossRef]
- Choi, K.-H.; Kim, D.-M.; Cho, M.-U.; Park, C.-W.; Kim, S.-Y.; Kim, M.-J.; Kong, Y.-K. Application of AULA Risk Assessment Tool by Comparison with Other Ergonomic Risk Assessment Tools. Int. J. Environ. Res. Public Health 2020, 17, 6479. [Google Scholar] [CrossRef]
- Enez, K.; Nalbantoğlu, S.S. Comparison of ergonomic risk assessment outputs from OWAS and REBA in forestry timber harvesting. Int. J. Ind. Ergon. 2019, 70, 51–57. [Google Scholar] [CrossRef]
- Kee, D. An empirical comparison of OWAS, RULA and REBA based on self-reported discomfort. Int. J. Occup. Saf. Ergon. 2020, 26, 285–295. [Google Scholar] [CrossRef] [PubMed]
- Kee, D.; Karwowski, W. A comparison of three observational techniques for assessing postural loads in industry. Int. J. Occup. Saf. Ergon. 2007, 13, 3–14. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Kee, D.; Na, S.; Chung, M.K. Comparison of the Ovako Working Posture Analysis System, Rapid Upper Limb Assessment, and Rapid Entire Body Assessment based on the maximum holding times. Int. J. Ind. Ergon. 2020, 77, 102943. [Google Scholar] [CrossRef]
- Kong, Y.-G.; Lee, S.; Lee, K.-S.; Kim, D.M. Comparisons of ergonomic evaluation tools (ALLA, RULA, REBA and OWAS) for farm work. Int. J. Occup. Saf. Ergon. 2018, 24, 218–223. [Google Scholar] [CrossRef]
- Yazdanirad, S.; Khoshakhagh, A.H.; Habib, E.; Zare, A.; Zeinodini, M.; Dehghani, F. Comparing the effectiveness of three ergonomic risk assessment methods-RULA, LUBA, and NERPA-to predict the upper extremity musculoskeletal disorders. Indian J. Occup. Environ. Med. 2018, 22, 17–21. [Google Scholar] [PubMed]
- Burdorf, A.; Govaert, G.; Elders, L. Postural load and back pain of workers in the manufacturing of prefabricated concrete elements. Ergonomics 1991, 34, 909–918. [Google Scholar] [CrossRef]
- Domingo, J.R.T.; De Pano, M.T.S.; Ecat, D.A.G.; Sanchez, N.A.D.; Custodio, B.P. Risk Assessment on Filipino Construction Workers. Procedia Manuf. 2015, 3, 1854–1860. [Google Scholar] [CrossRef]
- Kee, D. Comparison of OWAS, RULA and REBA for assessing potential work-related musculoskeletal disorders. Int. J. Ind. Ergon. 2021, 83, 103140. [Google Scholar] [CrossRef]
- Massaccesi, M.; Pagnotta, A.; Soccetti, A.; Masali, M.; Masiero, C.; Greco, F. Investigation of work-related disorders in truck drivers using RULA method. Appl. Ergon. 2003, 34, 303–307. [Google Scholar] [CrossRef]
- Rathore, B.; Pundir, A.K.; Iqbal, R. Ergonomic risk factors in glass artware industries and prevalence of musculoskeletal disorder. Int. J. Ind. Ergon. 2020, 80, 103043. [Google Scholar] [CrossRef]
- Shuval, K.; Donchin, M. Prevalence of upper extremity musculoskeletal symptoms and ergonomic risk factors at a Hi-Tech company in Israel. Int. J. Ind. Ergon. 2005, 35, 569–581. [Google Scholar] [CrossRef]
- Kee, D.; Na, S.; Chung, M.K. Effect of External Load at Varying Hand Positions on Perceived Discomfort. Int. J. Occup. Saf. Ergon. 2013, 19, 3–14. [Google Scholar] [CrossRef] [Green Version]
- Winkel, J.; Mathiassen, S.E. Assessment of physical work load in epidemiologic studies: Concepts, issues and operational considerations. Ergonomics 1994, 37, 979–988. [Google Scholar] [CrossRef] [PubMed]
- Pal, A.; Dhara, P.C. Work Related Musculoskeletal Disorders and Postural Stress of the Women Cultivators Engaged in Uprooting Job of Rice Cultivation. Indian J. Occup. Environ. Med. 2018, 22, 163–169. [Google Scholar] [CrossRef]
- Isler, M.; Küçük, M.; Guner, M. Ergonomic assessment of working postures in clothing sector with scientific observation methods. Int. J. Cloth. Sci. Technol. 2018, 30, 757–771. [Google Scholar] [CrossRef]
- Cremasco, M.M.; Giustetto, A.; Caffaro, F.; Colantoni, A.; Cavallo, E.; Grigolato, S. Risk Assessment for Musculoskeletal Disorders in Forestry: A Comparison between RULA and REBA in the Manual Feeding of a Wood-Chipper. Int. J. Environ. Res. Public Health 2019, 16, 793. [Google Scholar] [CrossRef] [Green Version]
- Mukhopadhyay, P.; Jhodkar, D.; Kumar, P. Ergonomic risk factors in bicycle repairing units at Jabalpur. Work J. Prev. Assess. Rehabil. 2015, 51, 245–254. [Google Scholar] [CrossRef]
- Balaji, K.K.; Alphin, M. Computer-aided human factors analysis of the industrial vehicle driver cabin to improve occupational health. Int. J. Inj. Control. Saf. Promot. 2016, 23, 240–248. [Google Scholar] [CrossRef] [PubMed]
- Bhatia, A.; Singla, S. Ergonomic evaluation and customized design of kitchen. Int. J. Innov. Technol. Explor. Eng. 2019, 8, 1033–1039. [Google Scholar]
- Kulkarni, V.S.; Devalkar, R.V. Postural analysis of building construction workers using ergonomics. Int. J. Constr. Manag. 2019, 19, 464–471. [Google Scholar] [CrossRef]
- Sain, M.K.; Meena, M.L. Identifying musculoskeletal issues and associated risk factors among clay brick kiln workers. Ind. Health 2019, 57, 381–391. [Google Scholar] [CrossRef] [Green Version]
- Jones, T.; Kumar, S. Comparison of ergonomic risk assessments in a repetitive high-risk sawmill occupation: Saw-filer. Int. J. Ind. Ergon. 2007, 37, 744–753. [Google Scholar] [CrossRef]
- Jones, T.; Kumar, S. Comparison of ergonomic risk assessment output in a repetitive sawmill occupation: Trim-saw operator. Work J. Prev. Assess. Rehabil. 2008, 31, 367–376. [Google Scholar]
- Jones, T.; Kumar, S. Comparison of Ergonomic Risk Assessment Output in Four Sawmill Jobs. Int. J. Occup. Saf. Ergon. 2010, 16, 105–111. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Gallo, R.; Mazzetto, F. Ergonomic analysis for the assessment of the risk of work-related musculoskeletal disorder in forestry operations. J. Agric. Eng. 2013, XLIV, e147. [Google Scholar] [CrossRef]
- Garcia, P.P.N.S.; Polli, G.; Campos, J.A.D.B. Working postures of dental students: Ergonomic analysis using the Ovako Working Analysis System and rapid upper limb assessment. La Med. Del Lav. 2013, 104, 440–447. [Google Scholar]
- Noh, H.; Roh, H. Approach of Industrial Physical Therapy to Assessment of the Musculoskeletal System and Ergonomic Risk Factors of the Dental Hygienist. J. Phys. Ther. Sci. 2013, 25, 821–826. [Google Scholar] [CrossRef] [Green Version]
- Qutubuddin, S.M.; Hebbal, S.S.; Kumar, A.C.S. An ergonomic study of work related musculoskeletal disorder risks in Indian saw mills. IOSR J. Mech. Civ. Eng. 2013, 7, 7–13. [Google Scholar]
- Qutubuddin, S.M.; Hebbal, S.S.; Kumar, A.C.S. Ergonomic risk assessment using postural analysis tools in a bus body building unit. Ind. Eng. Lett. 2013, 3, 10–21. [Google Scholar]
- Sahu, S.; Moitra, S.; Maity, S.; Pandit, A.K.; Roy, B. A Comparative Ergonomics Postural Assessment of Potters and Sculptors in the Unorganized Sector in West Bengal, India. Int. J. Occup. Saf. Ergon. 2013, 19, 455–462. [Google Scholar] [CrossRef] [Green Version]
- Shanahan, C.J.; Vi, P.; Salas, E.A.; Reider, V.L.; Hochman, L.M.; Moore, A.E. A comparison of RULA, REBA and Strain Index to four psychophysical scales in the assessment of non-fixed work. Work J. Prev. Assess. Rehabil. 2013, 45, 367–378. [Google Scholar] [CrossRef]
- Ansari, N.A.; Sheikh, M.J. Evaluation of work Posture by RULA and REBA: A Case Study. IOSR J. Mech. Civ. Eng. 2014, 11, 18–23. [Google Scholar] [CrossRef]
- Mukhopadhyay, P.; Khan, A. The evaluation of ergonomic risk factors among meat cutters working in Jabalpur, India. Int. J. Occup. Environ. Health 2015, 21, 192–198. [Google Scholar] [CrossRef] [PubMed] [Green Version]
- Hussain, A.; Case, K.; Marshall, R.; Summerskill, S. Using Ergonomic Risk Assessment Methods for Designing Inclusive Work Practices: A Case Study. Hum. Factors Ergon. Manuf. 2016, 26, 337–355. [Google Scholar] [CrossRef] [Green Version]
- Chowdhury, N.; Aghazadeh, F.; Amini, M. Ergonomic assessment of working postures for the design of university computer workstations. Occup. Ergon. 2017, 13, 37–46. [Google Scholar] [CrossRef] [Green Version]
- nver-Okan, S.; Acar, H.H.; Kaya, A. Determination of work postures with different ergonomic risk assessment methods in forest nurseries. Fresenius Environ. Bull. 2017, 26, 7362–7371. [Google Scholar]
- Upasana; Vinay, D. Work posture assessment of tailors by RULA and REBA analysis. Int. J. Sci. Environ. Technol. 2017, 6, 2469–2474. [Google Scholar]
- Boulila, A.; Ayadi, M.; Mrabet, K. Ergonomics study and analysis of workstations in Tunisian mechanical manufacturing. Hum. Factors Ergon. Manuf. 2018, 28, 166–185. [Google Scholar] [CrossRef]
- Dev, M.; Bhardwaj, A.; Singh, S. Analysis of work-related musculoskeletal disorders and ergonomic posture assessment of welders in unorganized sector: A study in Jalandhar. Int. J. Hum. Factors Ergon. 2018, 5, 240–255. [Google Scholar] [CrossRef]
- Landekić, M.; Katuša, S.; Mijoč, D.; Šporčić, M. Assessment and Comparison of Machine Operators’ Working Posture in Forest Thinning. South-east Eur. For. 2018, 10, 29–37. [Google Scholar] [CrossRef]
- Li, X.; Han, S.; Gül, M.; Al-Hussein, M.; El-Rich, M. 3D Visualization-Based Ergonomic Risk Assessment and Work Modification Framework and Its Validation for a Lifting Task. J. Constr. Eng. Manag. 2018, 144, 4017093. [Google Scholar] [CrossRef]
- Joshi, M.; Deshpande, V.; Shukla, H. The investigation of ergonomic and energy intervention in roof sticks bending facility. Int. J. Mech. Prod. Eng. Res. Dev. 2019, 9, 220–225. [Google Scholar]
- Kalkis, H.; Roja, Z.; Bokse, K.; Babris, S.; Roja, I. Work posture load evaluation in medium size metal processing enterprise in Latvia. Agron. Res. 2019, 17, 1033–1040. [Google Scholar]
- Khan, I.A.; Deb, R.K. Postural analysis through RULA, REBA and QEC of vendors selling edible items at railway stations and in the trains. Int. J. Eng. Adv. Technol. 2019, 9, 7269–7277. [Google Scholar]
- Paini, A.D.C.; Lopes, E.D.S.; De Souza, A.P.; De Oliveira, F.M.; Rodrigues, C.K. Repetitive motion and postural analysis of machine operators in mechanized wood harvesting operations. CERNE 2019, 25, 214–220. [Google Scholar] [CrossRef]
- Vahdatpour, B.; Sayed-Mirramazani, M. Prevalence of Musculoskeletal Disorders and Postural Assessment during Endoscopy and Colonoscopy among Gastroenterologists in Isfahan City, Iran. Phys. Med. Rehabil. Electrodiagn. 2019, 1, 97–104. [Google Scholar] [CrossRef]
- Yaylı, D.; Çalışkan, E. Comparison of Ergonomic Risk Analysis Methods for Working Postures of Forest Nursery Workers. Eur. J. For. Eng. 2019, 5, 18–24. [Google Scholar] [CrossRef]
- Ijaz, M.; Ahmad, S.R.; Akram, M.; Khan, W.U.; Yasin, N.A.; Nadeem, F.A. Quantitative and qualitative assessment of musculoskeletal disorders and socioeconomic issues of workers of brick industry in Pakistan. Int. J. Ind. Ergon. 2020, 76, 102933. [Google Scholar] [CrossRef]
- Kamath, C.R.; Naik, N.; Bhat, R.; Mulimani, P.; Sinniah, A. Assessing the possibility of musculoskeletal disorders occurrence in the mechanical engineering laboratory operators of educational institutes. Int. J. Adv. Sci. Technol. 2020, 29, 6191–6197. [Google Scholar]
- Qureshi, A.M.; Solomon, D.G. Ergonomic Assessment of Postural Loads in Small- and Medium-Scale Foundry Units. J. Inst. Eng. India Ser. C 2021, 102, 323–335. [Google Scholar] [CrossRef]
- Widyanti, A. Validity and inter-rater reliability of postural analysis among new raters. Malays. J. Public Health Med. 2020, 1, 161–166. [Google Scholar] [CrossRef]
- De Bruijn, I.; Engels, J.; Van Der Gulden, J. A simple method to evaluate the reliability of OWAS observations. Appl. Ergon. 1998, 29, 281–283. [Google Scholar] [CrossRef]
- Kivi, P.; Mattila, M. Analysis and improvement of work postures in the building industry: Application of the computerised OWAS method. Appl. Ergon. 1991, 22, 43–48. [Google Scholar] [CrossRef]
- Mattila, M.; Karwowski, W.; Vilkki, M. Analysis of working postures in hammering tasks on building construction sites using the computerized OWAS method. Appl. Ergon. 1993, 24, 405–412. [Google Scholar] [CrossRef]
- Lins, C.; Fudickar, S.; Hein, A. OWAS inter-rater reliability. Appl. Ergon. 2021, 95, 103357. [Google Scholar] [CrossRef] [PubMed]
- Dockrell, S.; O’Grady, E.; Bennett, K.; Mullarkey, C.; Connell, R.M.; Ruddy, R.; Twomey, S.; Flannery, C. An investigation of the reliability of Rapid Upper Limb Assessment (RULA) as a method of assessment of children’s computing posture. Appl. Ergon. 2012, 42, 632–636. [Google Scholar] [CrossRef]
- Laeser, K.L.; Maxwell, L.E.; Hedge, A. The Effect of Computer Workstation Design on Student Posture. J. Res. Comput. Educ. 1998, 31, 173–188. [Google Scholar] [CrossRef]
- Breen, R.; Pyper, S.; Rusk, Y.; Dockrell, S. An investigation of children’s posture and discomfort during computer use. Ergonomics 2007, 50, 1582–1592. [Google Scholar] [CrossRef]
- Oates, S.; Evans, G.W.; Hedge, A. An Anthropometric and Postural Risk Assessment of Children’s School Computer Work Environments. Comput. Sch. 1998, 14, 55–63. [Google Scholar] [CrossRef]
- Lamarão, A.M.; Costa, L.D.C.M.; Comper, M.L.C.; Padula, R.S. Translation, cross-cultural adaptation to Brazilian- Portuguese and reliability analysis of the instrument Rapid Entire Body Assessment-REBA. Braz. J. Phys. Ther. 2014, 18, 211–217. [Google Scholar] [CrossRef] [Green Version]
- Schwartz, A.H.; Albin, T.J.; Gerberich, S.G. Intra-rater and inter-rater reliability of the rapid entire body assessment (REBA) tool. Int. J. Ind. Ergon. 2019, 71, 111–116. [Google Scholar] [CrossRef]
- Janowitz, I.L.; Gillen, M.; Ryan, G.; Rempel, D.; Trupin, L.; Swig, L.; Mullen, K.; Rugulies, R.; Blanc, P.D. Measuring the physical demands of work in hospital settings: Design and implementation of an ergonomics assessment. Appl. Ergon. 2006, 37, 641–658. [Google Scholar] [CrossRef] [PubMed]
- Kayis, B.; Kothiyal, K. A Multilevel Approach to Manual Lifting in Manufacturing Industries. Int. J. Occup. Saf. Ergon. 1996, 2, 251–261. [Google Scholar] [CrossRef] [PubMed]
- Olendorf, M.R.; Drury, C.G. Postural discomfort and perceived exertion in standardized box-holding postures. Ergonomics 2001, 44, 1341–1367. [Google Scholar] [CrossRef] [PubMed]
- Hellig, T.; Mertens, A.; Brandl, C. The interaction effect of working postures on muscle activity and subjective discomfort during static working postures and its correlation with OWAS. Int. J. Ind. Ergon. 2018, 68, 25–33. [Google Scholar] [CrossRef]
- Borg, G. Subjective Aspects of Physical and Mental Load. Ergonomics 1978, 21, 215–220. [Google Scholar] [CrossRef] [PubMed]
- Hellig, T.; Rick, V.; Mertens, A.; Nitsch, V.; Brandl, C. Investigation of observational methods assessing workload of static working postures based on surface electromyography. Work J. Prev. Assess. Rehabil. 2019, 62, 185–195. [Google Scholar] [CrossRef] [Green Version]
- van der Beek, A.J.; Mathiassen, S.E.; Windhorst, J.; Burdorf, A. An evaluation of methods assessing the physical demands of manual lifting in scaffolding. Appl. Ergon. 2005, 36, 213–222. [Google Scholar] [CrossRef]
- Waters, T.R.; Putz-Anderson, V.; Garg, A.; Fine, L.J. Revised NIOSH equation for the design and evaluation of manual lifting tasks. Ergonomics 1993, 36, 749–776. [Google Scholar] [CrossRef]
- Sector atlas. Work and Health in the Construction Industry, 1007; Arbouw Foundation: Amsterdam, The Netherlands, 1997. [Google Scholar]
- Fountain, L.J. Examining RULA’s Postural Scoring System with Selected Physiological and Psychophysiological Measures. Int. J. Occup. Saf. Ergon. 2003, 9, 383–392. [Google Scholar] [CrossRef] [PubMed]
- Corlett, E.N.; Bishop, R.P. A Technique for Assessing Postural Discomfort. Ergonomics 1976, 19, 175–182. [Google Scholar] [CrossRef]
- Kuorinka, I.; Jonsson, B.; Kilbom, A.; Vinterberg, H.; Biering-Sørensen, F.; Andersson, G.; Jørgensen, K. Standardised Nordic questionnaires for the analysis of musculoskeletal symptoms. Appl. Ergon. 1987, 18, 233–237. [Google Scholar] [CrossRef]
- Cornell University Ergonomics Web. Workplace Ergonomics Tools. Available online: http://www.ergo.human.cornell.edu/cutools.html (accessed on 20 May 2021).
- Shah, Z.A.; Amjad, A.; Ashraf, M.; Mushtaq, F.; Sheikkh, I.A. Prevalence of musculoskeletal problems and awkward posture in a Pakistani garments manufacturing industry. Malays. J. Public Health Med. 2016, 16, 75–79. [Google Scholar]
- Occupational Safety and Health Agency (KOSHA). Status of Musculoskeletal Disorders-Related Risky Tasks, 2004; Occupational Safety and Health Agency: Bucheon, Korea, 2005.
- Joshi, M.; Deshpande, V. Investigative study and sensitivity analysis of Rapid Entire Body Assessment (REBA). Int. J. Ind. Ergon. 2020, 79, 103004. [Google Scholar] [CrossRef]
- Madani, D.A.; Dababneh, A. Rapid entire body assessment: A literature review. Am. J. Eng. Appl. Sci. 2016, 9, 107–118. [Google Scholar] [CrossRef]
- Zetterberg, C.; Heiden, M.; Lindberg, P.; Nylén, P.; Hemphälä, H. Reliability of a new risk assessment method for visual ergonomics. Int. J. Ind. Ergon. 2019, 72, 71–79. [Google Scholar] [CrossRef]
- Joshi, M.; Deshpande, V. Identification of indifferent posture zones in RULA by sensitivity analysis. Int. J. Ind. Ergon. 2021, 83, 103123. [Google Scholar] [CrossRef]
Assessment Factors | Observation Strategy | Body Side Assessed | Risk Category | Strengths | Limitations | ||||||
---|---|---|---|---|---|---|---|---|---|---|---|
Posture | Force/External Load | Motion Repetition | Static Posture | Dynamic Loading ** | Coupling | ||||||
OWAS | Back, arms, legs | 3 categories | X * | X | X | X | Time sampling | Not specified | 4 action categories | Most rapid and easy to use Detailed leg posture classificaion | Postures of neck, elbow, and wrist, repetition, coupling, and static posture not included |
RULA | Upper arms, lower arms, wrist, neck, trunk, leg | 4 categories | O * | O | X | X | No detailed rules | Right or left side | 4 action levels | Rapid and easy to assess | Focused on upper limb posture Coupling not included Necessity to decide which side to observe |
REBA | Upper arms, lower arms, wrist, neck, trunk, leg | 3 categories (+1 adjusting factor) | O | O | O | O | Most common/prolonged/loaded postures | Right or left side | 5 action levels | Rapid and easy to assess | Necessity to decide which side to observe |
Study | Application Fields | Sample Size | Rank Order for Risk Levels | Remarks |
---|---|---|---|---|
Chiasson et al. [12] | Aerospace, food, appliances, musical instruments, tree nurseries, plastics, and composites | 567 tasks of 224 workstations in 18 plants | RULA > REBA | -3 risk levels -REBA has the ability to capture very awkward postures |
Enez and Nalbantoğlu [22] | Timber harvesting in forestry | 3119 postures of 58 workers | REBA > OWAS | 4 risk levels |
Kee [23] | Experimental environment | 48 experimental postures | RULA > REBA > OWAS | 4 risk levels |
Kee and Karwowski [24] | Iron and steel, electronics, automotive and chemical industries, general hospital | 301 postures | RULA > REBA > OWAS | The postures were classified and compared by industry, work type, and leg posture |
Kee et al. [25] | Experimental environment | 72 experimental postures | RULA > REBA = OWAS | -4 risk levels -Risk levels by OWAS and REBA were not significantly different |
Domingo et al. [29] | Construction | 14 postures | RULA > REBA | |
Kee [30] | Automotive and its parts manufacturing industry, construction | 209 postures | RULA > REBA > OWAS | 4 risk levels |
Pal and Dhara [36] | Uprooting job of rice cultivation | 2 postures of 112 women cultivators | RULA = REBA > OWAS | |
Isler et al. [37] | Clothing sector | 4251 postures for REBA4237 postures for OWAS | REBA = OWAS | -No significant differences |
Cremasco et al. [38] | Manual feeding of wood-chipper in forestry | 7 tasks | RULA > REBA | Based on normalized values for RULA grand and REBA scores |
Mukhopadhyay et al. [39] | Bicycle repairing | 9 activities | RULA = REBA = OWAS | -All activities were assessed as the highest postural loads (action category/level: 4) -OWAS was used but based on different coding system |
Balaji and Alphin [40] | Industrial vehicle driver cabin | Postures of 30 operators | RULA = REBA | -4 risk levels -No significant differences |
Bhatia and Singla [41] | Kitchen | Postures of 30 participants | RULA = REBA | -No significant differences |
Kulkarni and Devalkar [42] | 5 activities in construction | 30 workers | REBA > RULA | RULA assessed the activities as action level 3 or 4, and REBA as action level 4 |
Sain and Meena [43] | Clay brick kiln work | Postures of 154 workers | REBA > RULA | 4 tasks: spading, mold filling, mold evacuating, brick carrying |
Jones and Kumar [44] | Sawmill facility | 15 saw-filers | RULA > REBA | 3 risk levels |
Jones and Kumar [45] | Sawmill facility | 29 workers in four facilities | RULA > REBA | |
Jones and Kumar [46] | Sawmill facility | 87 sawmill workers | RULA > REBA | 3 risk levels |
Gallo and Mazzetto [47] | Forestry | 18 frames | REBA > OWAS | |
Garcia et al. [48] | Dental students | 283 procedures of 75 students | RULA > OWAS | |
Noh and Roh [49] | Dental hygienist | 5 simulated working postures of three dental hygienists | RULA > REBA | |
Qutubuddin et al. [50] | Saw mill | 110 workers | RULA > REBA | |
Qutubuddin et al. [51] | Automotive coach manufacturing | 38 workers | RULA > REBA | |
Sahu et al. [52] | Potter and sculptor | 10 working postures of 80 male potters’ and 50 clay sculptors | RULA > REBA | |
Shanahan et al. [53] | Rodworking in construction | 25 tasks | RULA > REBA | |
Ansari and Sheikh [54] | Small scale industry of India | 15 workers | RULA > REBA | |
Mukhopadhyay and Khan [55] | Meat cutters | 8 tasks | RULA > REBA | OWAS was used but based on different coding system |
Hussain et al. [56] | Furniture assembly | 705–706 postures of 12 participants | REBA > OWAS | 705 postures were used for REBA analysis and 706 postures for OWAS analysis |
Chowdhury et al. [57] | Computer workstation | 72 postures | RULA > REBA | |
Ünver-Okan et al. [58] | Forest nurseries | 10 works of 175 nurseries | RULA > REBA > OWAS | 3 risk levels |
Upasana and Vinay [59] | Tailors | 60 male tailors in 14 boutique shops | RULA > REBA | |
Boulila et al. [60] | Mechanical manufacturing | 3 operators’ postures | RULA > REBA | |
Dev et al. [61] | Welders | 5 postures | RULA > REBA | |
Landekić et al. [62] | Forest thinning | 248 postures for 3 machines: chainsaw, forwarder and harvester | REBA > OWAS | 4 risk levels |
Li et al. [63] | Lifting tasks | 13–18 postures according to 3 participants | RULA > REBA | |
Joshi et al. [64] | Roof stick bending of public transport buses | 7 processes | REBA > OWAS | |
Kalkis et al. [65] | Metal processing | 21 postures | RULA > REBA | |
Khan and Deb [66] | Vendors selling edible items | 8 vendors’ postures | RULA > REBA | |
Paini et al. [67] | Wood harvesting | 3 postures of 6 operators in tree cutting operations | RULA > REBA | |
Vahdatpour and Sayed-Mirramazani [68] | Gastroenterologists | 18 postures | RULA > OWAS | |
Yayli and Çalişkan [69] | Forest nursery | 104 forest nursery workers | RULA > REBA > OWAS | Based on hazardous ratios in working postures |
Ijaz et al. [70] | Brick industry | Postures of 8 activities | RULA > REBA | |
Kamath et al. [71] | Mechanical engineering laboratory | 5 postures | RULA > REBA | |
Qureshi and Solomon [72] | Foundry units | 210 postures | RULA > REBA |
OWAS and RULA | OWAS and REBA | RULA and REBA | |
---|---|---|---|
Chiasson et al. [12] | - | - | 73.7 (567) * |
Joshi and Deshpande [19] ** | 37.5 (20) | 36.4 (19) | 25.0 (44) |
Enez and Nalbantoğlu [22] | - | 29.1 (3119) | - |
Kee [23] | 16.7 (48) | 8.3 | 33.3 |
Kee and Karwowski [24] | 29.2 (301) | 54.8 | 48.2 |
Kee et al. [25] | 33.3 (72) | 52.8 | 29.2 |
Kee [30] | 17.7 (209) | 35.9 | 41.1 |
Pal and Dhara [36] | 50.0 (2) | 50.0 | 100.0 |
Cremasco et al. [38] | - | - | 85.7 (7) |
Kulkarni and Devalkar [42] | - | - | 66.7 (30) |
Jones and Kumar [46] | - | - | 66 (87) |
Gallo and Mazzetto [47] | - | 33.3 (18) | - |
Garcia et al. [48] | 0 *** (283) | - | - |
Noh and Roh [49] | - | - | 20.0 (5) |
Sahu et al. [52] | - | - | 60.0 (10) |
Ünver-Okan et al. [58] | 40.0 (10) | 50.0 | 50.0 |
Paini et al. [67] | - | - | 33.3 (3) |
Qureshi and Solomon [72] | - | - | 75.24 (105) |
Mean (±standard deviation) | 28.1 ± 15.9 | 39.0 ± 14.9 | 53.8 ± 23.9 |
OWAS and RULA | OWAS and REBA | RULA and REBA | |
---|---|---|---|
Chiasson et al. [12] | - | - | 0.67 * |
Kee [23] | 0.482 ** | 0.435 ** | 0.415 ** |
Kee and Karwowski [24] | 0.511 * | 0.487 ** | 0.468 ** |
Kee et al. [25] | 0.491 ** | 0.785 ** | 0.691 ** |
Kee [30] | 0.562 ** | 0.451 ** | 0.445 * |
Mean (±standard deviation) | 0.51 ± 0.04 | 0.54 ± 0.17 | 0.54 ± 0.13 |
Methods | Study | Applied Fields | No. of Raters | Intra-Rater Reliability | Inter-Rater Reliability |
---|---|---|---|---|---|
OWAS | Karhu et al. [10] | Steel industry | 4 | 70–100% | 23–88% for workers A and B; 74–99% for work-study engineer 1 and 2 |
de Bruijin et al. [73] | Nurses | 2 | 88–97% for 4 weeks’ interval; 83–100% for 3.5 months’ interval | 87–89% | |
Kivi and Mattila [74] | Building industry | 2 | - | -86% for the back; -94% for the arms; -85% for the leg; -94% for the force | |
Mattila et al. [75] | Building construction | 2 | - | -97% for the back postures; -100% for the arm postures; -98% for the leg postures; -97% for the whole body | |
Lins et al. [76] | Laboratory settings | 3 | - | -Over 98% (ĸ = 0.98) for whole body; -80–96% (ĸ = 0.85) for the upper body; -66–97% (ĸ = 0.85) for the legs | |
Widyanti [84] | Tofu, military equipment manufacturing, automotive maintenance and service, cracker, and milk processing | 50 | - | -% agreement: 57.07% -ĸ value: 0.39 | |
RULA | McAtamney and Corlett [8] | Keyboard operations, packing, sewing and brick sorting tasks | 120 | - | High consistency |
Dockrell et al. [77] * | Computer work environment | 6 | 0.27–0.86 for the action levels; 0.47–0.84 for the grand scores | -0.54–0.72 for the action levels; -0.50–0.77 for the grand scores | |
Laeser et al. [78] | Computer workstation | - | - | -Kendall’s W = 0.773; -r = 0.96 between the independent observers’ and the lead investigator’s scores | |
Breen et al. [79] | Computer workstation | 3 | - | 94.6% | |
Oates et al. [80] | Computer work environment | 1 | - | Ebel r = 0.73 | |
Widyanti [84] | Tofu, military equipment manufacturing, automotive maintenance and service, cracker, and milk processing | 50 | - | -% agreement: 58.25% -ĸ value: 0.20 | |
REBA | Hignett and McAtamney [9] | - | 14 | - | 62–85% (omitting the upper arm category) |
Lamarão et al. [81] | Textile industry, libraries, offices and supermarkets | 2 | 0.104–0.504 ** (15.09–69.81%) | 0.126–0.454 ** (5.66–66.03%) | |
Schwartz et al. [82] | Custodial tasks | 9 | 0.925 * | 0.54 ** | |
Jantowitz et al. [83] ** | Hospital settings | 2 | - | -0.54 for the upper body; -0.66 for the trunk/lower extremity; -<0.4 for the distal extremity | |
Widyanti [84] | Tofu, military equipment manufacturing, automotive maintenance and service, cracker, and milk processing | 50 | - | -% agreement: 50.14% -ĸ value: 0.26 |
Method | Study | Applied Fields | Sample Size | References Compared | Results |
---|---|---|---|---|---|
OWAS | Choi et al. [21] & Kong et al. [26] | Agriculture | 196 postures | -Subjective ergonomic expert’s evaluations | OWAS action category was in ‘moderate’ agreement with the experts’ assessments (ĸ = 0.538 and 0.501, respectively) * |
Kee [23] | Experimental conditions | 48 experimental postures | -Discomfort | OWAS action category was not significantly correlated with discomfort (r = −0.151, p > 0.10), and % capable at shoulder (r = −0.289, p > 0.05), but was correlated with % capable at trunk (r = −0.395, p < 0.01) | |
Kee et al. [25] | Experimental conditions | 72 experimental postures | -Discomfort -MHT | OWAS action category was not significantly correlated with discomfort and MHT (r = 0.125 (p > 0.10) and r = −0.151 (p > 0.10), respectively) | |
Burdorf et al. [28] | Concrete manufacturing | 1009 observations of 114 workers | -Prevalence of back pain | Average time spent working with a bent and/or twisted position of the back observed by the OWAS contributed to the prevalence | |
Kee [30] | Automotive and its parts’ manufacturing, and construction industries | 209 MSDs cases | -Association with MSDs | The OWAS action category was not significantly associated with MSDs (p > 0.10) | |
Vahdatpour and Say-ed Mirramazani [68] | Gastroenterologists | 18 postures | -Prevalence of MSDs | OWAS action level was not associated with the incidence of MSDs | |
Widyanti [84] | Tofu, military equipment manufacturing, automotive maintenance and service, cracker, and milk processing | 51 raters or postures in each industry | -Ratings between 50 new raters and an ergonomics expert for OWAS, RULA and REBA | Significant correlations between the ratings of the new raters and those of the expert for the OWAS (r = 0.802, p < 0.01) | |
Kayis and Kothiyal [85] | manual materials handling tasks in several manufacturing industries | 25 tasks | -L5/S1 compressive forces -Borg scale | Majority of the results of risk assessments (80%) were in agreement with one another | |
Olendorf and Drury [86] | Experimental conditions | 168 postures of 12 participants | -Perceived exertion -Body part discomfort measures | OWAS action levels and perceived exertion scores were associated | |
Hellig et al. [87] | Experimental conditions | 25 postures of 17 participants | -Ratings of perceived exertion (RPE), -Muscle activity | OWAS action levels were statistically significantly correlated with the RPE and back muscle activity | |
Hellig et al. [89] | Experimental conditions | 16 postures of 24 participants | -Muscle activity | OWAS action category was statistically significantly correlated with muscle activity (Spearman correlation coefficients: 0.17–0.55) | |
van der Beek et al. [90] | Scaffolding tasks | 26 workers | -Revised NIOSH lifting equation -Lifting guidelines for the Dutch construction industry (Arbouw method) -Rapid appraisal of the NIOSH lifting equation (practitioner’s method) | Ranks for 3 distinct scaffolding tasks determined by the OWAS was different from those determined by the other methods | |
RULA | McAtamney and Corlett [8] | Experimental conditions (VDU-based data-entry task) | 2 postures of 16 operators | -perceived pain, ache, and discomfort | RULA scores are sensitive to pain, ache, or discomfort |
Choi et al. [21] & Kong et al. [26] | Agriculture | 196 postures | -Subjective ergonomic expert’s evaluations | RULA action level was in ‘good’ and ‘moderate’ agreement with the experts’ assessments, respectively (ĸ = 0.599 and 0.627, respectively) * | |
Kee [23] | Experimental conditions | 48 experimental postures determined by hand positions and external loads | -Discomfort | RULA grand score was significantly correlated with discomfort (r = 0.554, p < 0.01), and % capable at trunk (r = −0.591, p < 0.01), but not with % capable at shoulder (r = −0.242, p < 0.05) | |
Kee et al. [25] | Experimental conditions | 72 experimental postures | -Discomfort -MHT | RULA grand score was significantly correlated with discomfort and MHT (r = 0.599 (p < 0.01) and r = −0.649 (p < 0.01), respectively) | |
Yazdanirad et al. [27] | Pharmaceutical and automotive and assembly industries | 210 workers | -Prevalence of subjective upper extremity musculoskeletal symptoms | RULA action levels were associated with the prevalence of the upper extremity MSDs | |
Domingo et al. [29] | Construction | 14 postures | -Subjective MSD symptoms | RULA scores had a negligible relationship with upper limb MSDs | |
Kee [30] | Automotive and its parts’ manufacturing, and construction industries | 209 MSDs cases | -Association with MSDs | RULA grand score and action level were significantly associated with MSDs (p < 0.01) | |
Massaccesi et al. [31] | Driving rubbish-collection and road-washing vehicles | 77 drivers’ postures | -Self-reported pain, ache, and discomfort | RULA trunk and neck scores were associated with pain, aches, and discomforts | |
Shuval and Donchin [33] | Software communication industry | 84 workers | -Prevalence of subjective upper extremity musculoskeletal symptoms | RULA hand/wrist scores were associated with the prevalence of the upper extremity symptoms | |
Vahdatpour and Say-ed Mirramazani [68] | Gastroenterologists | 18 postures | -Prevalence of MSDs | RULA score had a direct relationship with MSDs of the neck, upper back and knees | |
Breen et al. [79] | Computer use | 337 postures of 69 children | -Discomfort | Higher mean RULA grand score was correlated with discomfort | |
Widyanti [84] | Tofu, military equipment manufacturing, automotive maintenance and service, cracker, and milk processing | 51 raters or postures in each industry | -Ratings between 50 new raters and an ergonomics expert for OWAS, RULA and REBA | Significant correlations between the ratings of the new raters and those of the expert for the RULA (r = 0.799, p < 0.01) | |
Fountain [93] | Experimental conditions (typing task) | 3 postures of 20 participants | -EMG -Discomfort -Job attitude scores | RULLA risk level had a significant effect on perceived discomfort | |
REBA | Choi et al. [21] & Kong et al. [26] | Agriculture | 196 postures | -Subjective ergonomic expert’s evaluations | REBA action level was in ‘moderate’ agreement with the experts’ assessments (ĸ = 0.578 and 0.490, respectively) * |
Kee [23] | Experimental conditions | 48 experimental postures | -Discomfort | REBA score was significantly correlated with discomfort (r = 0.379, p < 0.01), and % capable at trunk (r = −0.609, p < 0.01), but not with % capable at shoulder (r = −0.272, p > 0.05) | |
Kee et al. [25] | Experimental conditions | 72 experimental postures | -Discomfort -MHT | REBA score was significantly correlated with discomfort and MHT (r = 0.352 (p < 0.01) and r = −0.465 (p < 0.01), respectively) | |
Domingo et al. [29] | Construction | 14 postures | -Subjective MSD symptoms | REBA scores had a weak relationship with entire body MSDs | |
Kee [30] | Automotive and its parts’ manufacturing, and construction industries | 209 MSDs cases | -Association with MSDs | REBA action level was significantly associated with MSDs (p < 0.01) | |
Rathore et al. [32] | Glass artware industry | 250 workers | -Prevalence of subjective musculoskeletal disorders | REBA scores and the musculoskeletal symptoms for the different body regions were significantly correlated | |
Widyanti [84] | Tofu, military equipment manufacturing, automotive maintenance and service, cracker, and milk processing | 51 raters or postures in each industry | -Ratings between 50 new raters and an ergonomics expert for OWAS, RULA and REBA | Significant correlations between the ratings of the new raters and those of the expert for the REBA (r = 0.790, p < 0.01) |
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. |
© 2022 by the author. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Share and Cite
Kee, D. Systematic Comparison of OWAS, RULA, and REBA Based on a Literature Review. Int. J. Environ. Res. Public Health 2022, 19, 595. https://doi.org/10.3390/ijerph19010595
Kee D. Systematic Comparison of OWAS, RULA, and REBA Based on a Literature Review. International Journal of Environmental Research and Public Health. 2022; 19(1):595. https://doi.org/10.3390/ijerph19010595
Chicago/Turabian StyleKee, Dohyung. 2022. "Systematic Comparison of OWAS, RULA, and REBA Based on a Literature Review" International Journal of Environmental Research and Public Health 19, no. 1: 595. https://doi.org/10.3390/ijerph19010595