Volume 16, Issue 1 (March 2018)                   Iranian Rehabilitation Journal 2018, 16(1): 11-16 | Back to browse issues page


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Khandan M, Vosoughi S, Poursadeghiyan M, Azizi F, Ahounbar E, Koohpaei A. Ergonomic Assessment of Posture Risk Factors Among Iranian Workers: An Alternative to Conventional Methods. Iranian Rehabilitation Journal 2018; 16 (1) :11-16
URL: http://irj.uswr.ac.ir/article-1-739-en.html
1- Department of Ergonomics, Faculty of Health, Qom University of Medical Sciences, Qom, Iran.
2- Department of Occupational Health Engineering, Faculty of Health, Iran University of Medical Sciences, Tehran, Iran.
3- Research Center in Emergency and Disaster Health, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
4- Work Health Research Centre, Qom University of Medical Sciences, Qom, Iran.
5- Substance Abuse and Dependence Research Center, University of Social Welfare and Rehabilitation Sciences, Tehran, Iran.
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1. Introduction
Inadequate body postures related to workstations is the primary cause of Musculoskeletal Disorders (MSDs) [1, 2]. American Bureau of Labor Statistics announced that in the United States of America, 44% of all reported occupational diseases were related to MSDs [3]. In Iran, studies are limited in this area [4]. In 1998, according to the Medical Commission of Tehran Social Security Organization, 14.4% of diseases that caused disabilities were MSDs [5]. Nouri et al., quoted Choobineh (2004) that the cost of MSDs in Iran in 2000 was 13.1% of Iranian government budget [6].
MSDs often engage multi-risk factors. The most important risk factors include vibration [7], poor posture, repetitive and excessive force, lifting and carrying [8-11]. The awkward posture is most important among various risk factors [12, 13]. Various studies have shown that the best strategy for the prevention of WMSDs is intervention aided by Multiple-Criteria Decision-Making (MCDM) techniques to reduce exposure to risk factors such as repetitive motions, excessive force, awkward postures, vibration and static activities [14-17]. This suggests that risk factors for MSDs must be considered and evaluated in the workstations [18, 19]. Also, risk assessment, training, consultation with workers, and prevention of fatigue must be noted [12, 20].
There are various tools to analyze risk factors or identify potentially hazardous jobs. These include observational methods, direct methods, self-declarations, and other psycho-physiological methods [21]. The objective measurement may result in the best description, but these methods are time-consuming, and also the evaluation of large groups is expensive. The tool must be user-friendly and flexible for a wide range of tasks with different complexities. On the other hand, studies demonstrated that experts tend to use descriptive words or use numbers only to describe situations, rather than an exact angle of body posture [21]. There are various methods such as QEC, OWAS, SI, OCRA, HAMA, and PLIBEL to assess the load/stress on body parts. However, Rapid Entire Body Assessment (REBA) and Rapid Upper Limb Assessment (RULA) are two other commonly used techniques to assess postures at work regards to economic reasons and ease of use. Also, Novel Ergonomic Postural Assessment (NERPA) method is one of the newest methods of postural assessment [22].
It is important to note that many variables between different countries, such as language, culture, and geography can change the output of the methods used [23]. In addition to variables such as gender, age, economic status, and body mass index, factors such as genetic, environmental, and cultural differences influence such disorders. MSDs are widespread among minority ethnic groups in the UK; this may reflect psychological, cultural, and social differences [24]. 
As another example, the Egyptian-born Americans are more prone to low back pain [25]. It can be hypothesized that the development of MSDs may be different in various populations. Therefore, it is necessary to evaluate the instruments prior to use in other communities. For instance, a tool like NERPA that is designed and tested in Spain needs to be validated in other countries. The aim of the current study was to validate NERPA by comparing it with two conventional methods of RULA and REBA. The results could be useful for occupational health experts, ergonomists and occupational medicine specialists in job assessment and prevention of MSDs.
2. Methods
The aim of this cross-sectional and descriptive-analytical study was to assess the validity of NERPA as a postural assessment method in industries of Iran within the year 2014. All operational staff (n=502) working in four industries including pharmaceutical, the publishing industry, drinks producer, and dairy were included. People with joint problems like arthritis, herniated disc, disc infection, and fracture in the spine, and other musculoskeletal problems and pains in various parts of the body were excluded from the current study. Finally, 455 workers were selected and enrolled in the study. Three posture evaluating methods named RULA, REBA and NERPA were used. NERPA was reported by Sanchez et al. in 2013 and is one of the latest postural assessment methods that try to make a better assessment of the situation. This method like many other pen-paper-based postural assessment methods uses a scoring system to express body states and reports them by numbers. Finally, it offers them in the form of four levels of corrective action [22]. 
At the first stage, working cycle was defined, and a cycle was captured in different directions by a camera. The videos/images were investigated further, and the various tasks have been analyzed. The tasks with higher frequencies were assessed by three mentioned methods. Furthermore, a demographic questionnaire was used to gather data about age, gender, and work experience. 
The results were collected and reported based on the approved ethical code of Qom University of medical sciences. Informed consent was prepared for all the participants as well as they were informed that inclusion and exclusion from the study were voluntary. All the information of participants kept confidential. Finally, the data were analyzed using kappa coefficient of the agreement through SPSS software version 20. Also, Spearman’s correlation test was used.
3. Results
General description

A total of 455 workers participated in this study, and 51.5% of them were aged 36-50 years (n=234), and 9.7% of them were >50 years. Majority of subjects had <10 years of work experience. Men represented 56.7% of participants and 43.3% (n=197) were women. Furthermore, only 2% of respondents have been working over 20 years at the same place. From the perspective of the industries, highest number of employees was in the dairy industry (38.02%) and lowest number of employees was in the drink production industry (10.99%). Detailed information on the numbers and percentages of the variables are presented in Table 1.
Comparing results of NERPA and RULA
Comparison between the level of risk assessed by RULA and NERPA has been tested using Spearman correlation coefficient and Kappa coefficient. Correlation between two methods with regards to corrective action levels was analyzed, and statistically significant (P<0.01) coefficient of 0.93 was obtained. Agreement between corrective actions levels of methods was also significant (P<0.01). Details of correlation and agreement coefficients are specified in Table 2. The highest agreement between two methods was achieved in the printing industry (coefficient 0.93) and the highest correlation was observed in the drink production industry. All coefficients were significant (P<0.01).
NERPA and REBA comparison
Comparison between levels of risk carried out by two methods of NERPA and REBA was performed by Spearman correlation and Kappa agreement coefficients. The correlation between outcomes of two methods was 0.744 (P<0.05). The agreement of corrective action levels of two methods was analyzed by kappa coefficient, however, no significant relationship was established. Also, the highest correlation was resulted in the drink production industry (0.78) and the lowest correlation was resulted in the dairy industry (0.50) (P<0.05).
4. Discussion
Currently, MSDs as a global challenge for occupational health and ergonomics specialists have crossed geographical boundaries and have become an international issue [26]. It should be noted that MSDs as the most severe consequences caused by work load, will lead to job restriction, loss of work time, reduced productivity and quality, poor quality of work life, and reduction in the retirement age [27-29]. These problems are prevalent among people in various occupations for e.g. in industries, organizations, healthcare sectors, and agricultural fields. Muscle pains as well as their related fatigue, can affect postural control and increase the risk of human errors [30, 31]  . 




 
Similar to other chronic diseases, MSDs have both occupational and non-occupational risk factors. Daily activities such as sports, driving, and work-family conflict, as well as smoking and obesity could influence ergonomic disorders [30]. Also age, sex, socio-economic status, and ethnicity can effect risk of injury. Therefore, it is crucial to apply best assessment method.
In this study, a comparison between the levels of risks involved was perfomed using the three methods (RULA and REBA as two reliable methods against NERPA as a novel method) aided by Spearman correlation and Kappa coefficients. Based on the statistical analysis, Spearman coefficient has demonstrated that the correlation between the assessed postures by NERPA and RULA in the investigated industries was significant. Our result revealed that the studied sectors had an excellent coefficient (0.92). Outcomes of REBA and NERPA methods demonstrated an acceptable correlation between the two methods (0.74). The correlation coefficient in four industries ranges from 0.78 to 0.51 that belong to drink production and dairy industries, respectively. Postures evaluated in the drink production industry by both RULA and REBA and comparing the results with NERPA had the highest correlation. The RULA method was in better correlation with NERPA which corroborates with the study conducted by Sanchez [22]. Some studies have been performed about comparison, correlation, or agreement of different postural evaluating methods such as RULA [32, 33], REBA [34], or both [3, 33, 35]. However, none of the studies compared NERPA with other evaluating methods.
Correlation between the results of two methods of REBA and RULA was tested and there a high correlation was observed between the final scores and the levels of corrective action of the two methods (0.871 and 0.821), respectively [3]. Chiasson et al. compared methods of QEC, FIOH, RULA, HAL, SI, REBA, OCRA, and EN1005-3 standard in various industries. The agreement of evaluation results at high-risk stations was reported for these methods [33]. In another study, Jones and Kumar evaluated the REBA, RULA, OCRA, HAL, and SI methods in the wood industry and found a complete agreement [35]. In a study performed in automobile assembly companies, outcomes of RULA and SI methods were compared and suggested a little agreement between results of the two methods, with a kappa coefficient of 0.11 [13].
5. Conclusion
Based on the results of the present study, it can be concluded that the correlation between corrective actions levels of NERPA and RULA is desirable. On the other hand, correlation between NERPA and REBA was acceptable. However, concurrent validity of NERPA comparing with REBA’s result, as a widely used method, has not been verified in the present study. For the establishment of NERPA inplace of REBA method to use in the industrial fields, further studies in larger populations as well as in more industries are essential. In summary, this study illustrated that applying a new NERPA method instead of RULA for the posture analysis of workers in manufacturing industries is possible.
Acknowledgements
This study was funded by Research Council of Qom University of Medical Sciences. Authors of this study wish to express their heartfelt gratitude to all the people who have helped in the implementation of this research, especially Qom University of Medical Sciences. It was funded by Qom University of medical sciences, as mentioned below.
Conflict of Interest 
There is no conflicts of interest to be declared.


References 
[1]Moradi M, Poursadeghiyan M, Khammar A, Hami M, Darsnj A, Yarmohammadi H. REBA method for the ergonomic risk assessment of auto mechanics postural stress caused by working conditions in Kermanshah (Iran). Annals of Tropical Medicine and Public Health. 2017; 10(3):589.

[2]Koohpaei A, Khandan M, Vosoughi S, Khammar A, Mobinizade V, Farrokhi M, et al. Industrial workers’ postures analysis by a new method named “loading on the upper body assessment” in Iran. Annals of Tropical Medicine and Public Health. 2017; 10(4):973-977. Available from: https://doi.org/10.4103/ATMPH.ATMPH_304_17

[3]Nasl Saraji J, Ghaffari M, Shahtaheri S. Survey of Correlation between Two Evaluation Method of Work Related Musculoskeletal Disorders Risk Factors REBA & RULA. Iran Occupational Health Journal. 2006; 3(2):25-32. 

[4]Khandan M, Sakhaei Z, Koohpaei AR. Surveying the relationship between musculoskeletal disorders and Occupational stress among Iranian truck drivers. Iran Occupational Health. 2016; 13(2):39-49.

[5]Dayani F, Sadeghi Naiini H, Bahrami M, Choopankareh V. Assessment of body work condition by RULA method in a motor vehicle industry in order to design an effective exoskeleton system. Iran Occupational Health. 2012; 8(4):36-47.

[6]Nouri J, Azadeh A, Mohammad Fam I. The evaluation of safety behaviors in a gas treatment company in Iran. Journal of Loss Prevention in the Process Industries. 2008; 21(3):319-25. Available from: https://doi.org/10.1016/j.jlp.2007.11.006

[7]Nassiri P, Koohpaei A, Zeraati H, Shalkouhi P. Research note evaluation of exposure to whole-body vibration and its health effects on train operators in tehran-andimeshk line, Iran. Journal of Low Frequency Noise Vibration and Active Control. 2009; 28(4):285-94. Available from: http://dx.doi.org/10.1260/0263-0923.28.4.285

[8]Poursadeghiyan M, Azrah K, Biglari H, Ebrahimi MH, Yarmohammadi H, Baneshi MM, et al. The effects of the manner of carrying the bags on musculoskeletal symptoms in school students in the city of Ilam, Iran. Annals of Tropical Medicine and Public Health. 2017; 10(3):600-5.

[9]Nadri H, Nadri A, Khanjani N, Nadri F, Roodbandi AJ. Evaluating the factors effective on musculoskeletal disorders among the employees of one of Qazvin’s governmental offices. Journal of Health and Development. 2013; 2(2):106-16.

[10]Khandan M, Ataei Manesh L, Eyni Z, Khosravi Z, Koohpaei A, Poursadeghiyan M. Relationship between Job content and Demographic Variables with Musculoskeletal Disorders among Nurses in a University Hospital, Qom Province, 2014. Jundishapur Journal of Health Sciences. 2016; 11:547-53. Available from: http://dx.doi.org/10.17795/jjhs-40491

[11]Nazari H, Hossaini Mahjoob H, Tapak L, Mortazavi SS. Prevalence of work-related musculoskeletal disorders and injuries in occupational and physical therapists and its comparison. Iranian Rehabilitation Journal. 2017; 15(1):31-6. Available from: https://doi.org/10.18869/nrip.irj.15.1.31

[12]Khandan M, Eyni Z, Manesh L, Khosravi Z, Biglari H, Koohpaei A. Relationship between musculoskeletal disorders and job performance among nurses and nursing aides in main educational hospital in Qom province, 2014. Research Journal of Medical Sciences. 2016; 10(4):307-12.

[13]Khandan M, Aligol MH, Shamsi M, Poursadeghiyan M, Biglari H, Koohpaei A. Occupational health, safety, and ergonomics challenges and opportunities based on the organizational structure analysis: A case study in the selected manufacturing industries in Qom Province, Iran, 2015. Annals of Tropical Medicine and Public Health. 2017; 10(3):606-11.

[14]Nassiri P, Koohpaei AR, Zeraati H, Jafari Shalkouhi P. Train passengers comfort with regard to whole-body vibration. Journal of Low Frequency Noise Vibration and Active Control. 2011; 30(2):125-36. Available from: https://doi.org/10.1260/0263-0923.30.2.125

[15]Khandan M, Koohpaei A. Assessment and analysis of ergonomics conditions based on TOPSIS in a manufacturing company. Iran Occupational Health. 2016; 13(5):98-108.

[16]Khandan M, Nili M, Koohpaei A, Mosaferchi S. Integrating the ergonomics techniques with multi criteria decision making as a new approach for risk management: An assessment of repetitive tasks-entropy case study. Journal of Research in Health Sciences. 2016; 16(2):85-9. PMID: 27497776

[17]Khandan M, Koohpaei AR, Nili M, Farjami Y. Occupational musculoskeletal disorders management using Fuzzy TOPSIS Assessment of Repetitive Tasks (ART). Work. 2017; 56(2):267-76. Available from: https://doi.org/10.3233/WOR-172491

[18]Burdorf A. The role of assessment of biomechanical exposure at the workplace in the prevention of musculoskeletal disorders. Scandinavian Journal of Work, Environment & Health. 2010; 36(1):1-2. PMID: 19967327. 

[19]Silverstein B, Clark R. Interventions to reduce work-related musculoskeletal disorders. Journal of electromyography and kinesiology: official journal of the International Society of Electrophysiological Kinesiology. 2004; 14(1):135-52. Available from: https://doi.org/10.1016/j.jelekin.2003.09.023

[20]Khandan M, Koohpaei A, Kohansal Aghchay M, Ebrahimi M, Khammar A. Assessing the Factors Predicting Work-Related Musculoskeletal Disorders Among Iranian Port’s Personnel Using Regression Model. Iranian Rehabilitation Journal. 2017; 15(4):309-16.

[21]Li G, Buckle P. Current techniques for assessing physical exposure to work-related musculoskeletal risks, with emphasis on posture-based methods. Ergonomics. 1999; 42(5):674-95. PMID: 10327891 

[22]Sanchez-Lite A, Garcia M, Domingo R, Angel Sebastian M. Novel Ergonomic Postural Assessment Method (NERPA) Using Product-Process Computer Aided Engineering for Ergonomic Workplace Design. PLoS ONE. 2013; 8(8):e72703. PMID: PMC3745403.

[23]Finch E. Physical rehabilitation outcome measures. 2nd edition. Lippincott: Williams & Wilkins; 2002.

[24]Allison TR, Symmons DP, Brammah T, Haynes P, Rogers A, Roxby M, et al. Musculoskeletal pain is more generalised among people from ethnic minorities than among white people in Greater Manchester. Annals of the Rheumatic Diseases. 2002; 61(2):151-6. PMID: 11796402

[25]  DL, Chown P, Kang MS. Cultural diversity in adolescent health care. Medical Journal of Australia. 2005; 183(8):436-8. PMID: 16225454

[26]Bulduk EÖ, Bulduk S, Süren T, Ovalı F. Assessing exposure to risk factors for work-related musculoskeletal disorders using Quick Exposure Check (QEC) in taxi drivers. International Journal of Industrial Ergonomics. 2014; 44(6):817-20. Available from:  https://doi.org/10.1016/j.ergon.2014.10.002

[27]Abadi AS, Mazlomi A, Saraji GN, Zeraati H, Hadian MR, Jafari AH. Effects of box size, frequency of lifting, and height of lift on maximum acceptable weight of lift and heart rate for male university students in Iran. Electronic Physician. 2015; 7(6):1365-71. PMID: 26516443 

[28]Khandan M, Roshan zamir S, Maghsoudipour M. [Survey of Workload and Job Satisfaction relationship in a Productive Company (Persian)]. Iran Occupational Health Journal. 2012; 9(1):30-36.

[29]Yarmohammadi H, Ziaei M, Poursadeghiyan M, Moradi M, Fathi B, Biglari H, et al. Evaluation of Occupational Risk Assessment of Manual Load Carrying Using KIM Method on auto mechanics in Kermanshah City in 2015. Research Journal of Medical Sciences, 2016; 10(3):116-119. Available from: http://dx.doi.org/10.3923/rjmsci.2016.116.119

[30]Punnett L, Wegman DH. Work-related musculoskeletal disorders: the epidemiologic evidence and the debate. Journal of Electromyography and Kinesiology: Official Journal of the International Society of Electrophysiological Kinesiology. 2004; 14(1):13-23. PMID: 14759746

[31]Barkhordari A, Jafari Nodoushan R, Vatani Shoaa J, Halvani GH, Salmani Nodoushan M. [Posture Evaluation Using OWAS, RULA, QEC Method in FERO-ALEAGE Factory Workers of Kerman (Persian)]. Occupational Medicine: Quarterly Journal of Shahid Sadoughi University of Medical Sciences. 2011; 2(1):14-9.

[32]Chiasson MÈ, Imbeau D, Aubry K, Delisle A. Comparing the results of eight methods used to evaluate risk factors associated with musculoskeletal disorders. International Journal of Industrial Ergonomics. 2012; 42(5):478-88. Available from: https://doi.org/10.1016/j.ergon.2012.07.003

[33]Motamedzade M, Ashuri MR, Golmohammadi R, Mahjub H. Comparison of ergonomic risk assessment outputs from rapid entire body assessment and quick exposure check in an engine oil company. Journal of Research in Health Sciences. 2011; 11(1):26-32. PMID: 22911944

[34]Jones T, Kumar S. Comparison of ergonomic risk assessment output in four sawmill jobs. International Journal of Occupational Safety and Ergonomics. 2010; 16(1):105-11. Available from: https://doi.org/10.1080/10803548.2010.11076834

[35]Drinkaus P, Sesek R, Bloswick D, Bernard T, Walton B, Joseph B, et al. Comparison of ergonomic risk assessment outputs from Rapid Upper Limb Assessment and the Strain Index for tasks in automotive assembly plants. Work. 2003; 21(2):165-72. PMID: 14501094 
Article type: Original Research Articles | Subject: Ergonomics
Received: 2017/06/1 | Accepted: 2017/10/18 | Published: 2018/03/1

References
1. Moradi M, Poursadeghiyan M, Khammar A, Hami M, Darsnj A, Yarmohammadi H. REBA method for the ergonomic risk assessment of auto mechanics postural stress caused by working conditions in Kermanshah (Iran). Annals of Tropical Medicine and Public Health. 2017; 10(3):589.
2. Koohpaei A, Khandan M, Vosoughi S, Khammar A, Mobinizade V, Farrokhi M, et al. Industrial workers' postures analysis by a new method named "loading on the upper body assessment" in Iran. Annals of Tropical Medicine and Public Health. 2017; 10(4):973-977. Available from: [DOI:10.4103/ATMPH.ATMPH_304_17]
3. Nasl Saraji J, Ghaffari M, Shahtaheri S. Survey of Correlation between Two Evaluation Method of Work Related Musculoskeletal Disorders Risk Factors REBA & RULA. Iran Occupational Health Journal. 2006; 3(2):25-32.
4. Khandan M, Sakhaei Z, Koohpaei AR. Surveying the relationship between musculoskeletal disorders and Occupational stress among Iranian truck drivers. Iran Occupational Health. 2016; 13(2):39-49.
5. Dayani F, Sadeghi Naiini H, Bahrami M, Choopankareh V. Assessment of body work condition by RULA method in a motor vehicle industry in order to design an effective exoskeleton system. Iran Occupational Health. 2012; 8(4):36-47.
6. Nouri J, Azadeh A, Mohammad Fam I. The evaluation of safety behaviors in a gas treatment company in Iran. Journal of Loss Prevention in the Process Industries. 2008; 21(3):319-25. Available from: [DOI:10.1016/j.jlp.2007.11.006]
7. Nassiri P, Koohpaei A, Zeraati H, Shalkouhi P. Research note evaluation of exposure to whole-body vibration and its health effects on train operators in tehran-andimeshk line, Iran. Journal of Low Frequency Noise Vibration and Active Control. 2009; 28(4):285-94. Available from: http://dx.doi.org/10.1260/0263-0923.28.4.285 [DOI:10.1260/0263-0923.28.4.285]
8. Poursadeghiyan M, Azrah K, Biglari H, Ebrahimi MH, Yarmohammadi H, Baneshi MM, et al. The effects of the manner of carrying the bags on musculoskeletal symptoms in school students in the city of Ilam, Iran. Annals of Tropical Medicine and Public Health. 2017; 10(3):600-5.
9. Nadri H, Nadri A, Khanjani N, Nadri F, Roodbandi AJ. Evaluating the factors effective on musculoskeletal disorders among the employees of one of Qazvin's governmental offices. Journal of Health and Development. 2013; 2(2):106-16.
10. Khandan M, Ataei Manesh L, Eyni Z, Khosravi Z, Koohpaei A, Poursadeghiyan M. Relationship between Job content and Demographic Variables with Musculoskeletal Disorders among Nurses in a University Hospital, Qom Province, 2014. Jundishapur Journal of Health Sciences. 2016; 11:547-53. Available from: http://dx.doi.org/10.17795/jjhs-40491 [DOI:10.17795/jjhs-40491]
11. Nazari H, Hossaini Mahjoob H, Tapak L, Mortazavi SS. Prevalence of work-related musculoskeletal disorders and injuries in occupational and physical therapists and its comparison. Iranian Rehabilitation Journal. 2017; 15(1):31-6. Available from: [DOI:10.18869/nrip.irj.15.1.31]
12. Khandan M, Eyni Z, Manesh L, Khosravi Z, Biglari H, Koohpaei A. Relationship between musculoskeletal disorders and job performance among nurses and nursing aides in main educational hospital in Qom province, 2014. Research Journal of Medical Sciences. 2016; 10(4):307-12.
13. Khandan M, Aligol MH, Shamsi M, Poursadeghiyan M, Biglari H, Koohpaei A. Occupational health, safety, and ergonomics challenges and opportunities based on the organizational structure analysis: A case study in the selected manufacturing industries in Qom Province, Iran, 2015. Annals of Tropical Medicine and Public Health. 2017; 10(3):606-11.
14. Nassiri P, Koohpaei AR, Zeraati H, Jafari Shalkouhi P. Train passengers comfort with regard to whole-body vibration. Journal of Low Frequency Noise Vibration and Active Control. 2011; 30(2):125-36. Available from: [DOI:10.1260/0263-0923.30.2.125]
15. Khandan M, Koohpaei A. Assessment and analysis of ergonomics conditions based on TOPSIS in a manufacturing company. Iran Occupational Health. 2016; 13(5):98-108.
16. Khandan M, Nili M, Koohpaei A, Mosaferchi S. Integrating the ergonomics techniques with multi criteria decision making as a new approach for risk management: An assessment of repetitive tasks-entropy case study. Journal of Research in Health Sciences. 2016; 16(2):85-9. PMID: 27497776 [PMID]
17. Khandan M, Koohpaei AR, Nili M, Farjami Y. Occupational musculoskeletal disorders management using Fuzzy TOPSIS Assessment of Repetitive Tasks (ART). Work. 2017; 56(2):267-76. Available from: [DOI:10.3233/WOR-172491]
18. Burdorf A. The role of assessment of biomechanical exposure at the workplace in the prevention of musculoskeletal disorders. Scandinavian Journal of Work, Environment & Health. 2010; 36(1):1-2. PMID: 19967327. [DOI:10.5271/sjweh.2882] [PMID]
19. Silverstein B, Clark R. Interventions to reduce work-related musculoskeletal disorders. Journal of electromyography and kinesiology: official journal of the International Society of Electrophysiological Kinesiology. 2004; 14(1):135-52. Available from: [DOI:10.1016/j.jelekin.2003.09.023]
20. Khandan M, Koohpaei A, Kohansal Aghchay M, Ebrahimi M, Khammar A. Assessing the Factors Predicting Work-Related Musculoskeletal Disorders Among Iranian Port's Personnel Using Regression Model. Iranian Rehabilitation Journal. 2017; 15(4):309-16. [DOI:10.29252/nrip.irj.15.4.309]
21. Li G, Buckle P. Current techniques for assessing physical exposure to work-related musculoskeletal risks, with emphasis on posture-based methods. Ergonomics. 1999; 42(5):674-95. PMID: 10327891 [DOI:10.1080/001401399185388] [PMID]
22. Sanchez-Lite A, Garcia M, Domingo R, Angel Sebastian M. Novel Ergonomic Postural Assessment Method (NERPA) Using Product-Process Computer Aided Engineering for Ergonomic Workplace Design. PLoS ONE. 2013; 8(8):e72703. PMID: PMC3745403.
23. Finch E. Physical rehabilitation outcome measures. 2nd edition. Lippincott: Williams & Wilkins; 2002.
24. Allison TR, Symmons DP, Brammah T, Haynes P, Rogers A, Roxby M, et al. Musculoskeletal pain is more generalised among people from ethnic minorities than among white people in Greater Manchester. Annals of the Rheumatic Diseases. 2002; 61(2):151-6. PMID: 11796402 [DOI:10.1136/ard.61.2.151] [PMID] [PMCID]
25. DL, Chown P, Kang MS. Cultural diversity in adolescent health care. Medical Journal of Australia. 2005; 183(8):436-8. PMID: 16225454 [PMID]
26. Bulduk EÖ, Bulduk S, Süren T, Ovalı F. Assessing exposure to risk factors for work-related musculoskeletal disorders using Quick Exposure Check (QEC) in taxi drivers. International Journal of Industrial Ergonomics. 2014; 44(6):817-20. Available from: [DOI:10.1016/j.ergon.2014.10.002]
27. Abadi AS, Mazlomi A, Saraji GN, Zeraati H, Hadian MR, Jafari AH. Effects of box size, frequency of lifting, and height of lift on maximum acceptable weight of lift and heart rate for male university students in Iran. Electronic Physician. 2015; 7(6):1365-71. PMID: 26516443 [PMID] [PMCID]
28. Khandan M, Roshan zamir S, Maghsoudipour M. [Survey of Workload and Job Satisfaction relationship in a Productive Company (Persian)]. Iran Occupational Health Journal. 2012; 9(1):30-36.
29. Yarmohammadi H, Ziaei M, Poursadeghiyan M, Moradi M, Fathi B, Biglari H, et al. Evaluation of Occupational Risk Assessment of Manual Load Carrying Using KIM Method on auto mechanics in Kermanshah City in 2015. Research Journal of Medical Sciences, 2016; 10(3):116-119. Available from: http://dx.doi.org/10.3923/rjmsci.2016.116.119
30. Punnett L, Wegman DH. Work-related musculoskeletal disorders: the epidemiologic evidence and the debate. Journal of Electromyography and Kinesiology: Official Journal of the International Society of Electrophysiological Kinesiology. 2004; 14(1):13-23. PMID: 14759746 [DOI:10.1016/j.jelekin.2003.09.015] [PMID]
31. Barkhordari A, Jafari Nodoushan R, Vatani Shoaa J, Halvani GH, Salmani Nodoushan M. [Posture Evaluation Using OWAS, RULA, QEC Method in FERO-ALEAGE Factory Workers of Kerman (Persian)]. Occupational Medicine: Quarterly Journal of Shahid Sadoughi University of Medical Sciences. 2011; 2(1):14-9.
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