Skip to main content

Effect of Body Mass Index on work related musculoskeletal discomfort and occupational stress of computer workers in a developed ergonomic setup

Abstract

Background

Work urgency, accuracy and demands compel the computer professionals to spend longer hours before computers without giving importance to their health, especially body weight. Increase of body weight leads to improper Body Mass Index (BMI) may aggravate work related musculoskeletal discomfort and occupational-psychosocial stress. The objective of the study was to find out the effect of BMI on work related musculoskeletal discomforts and occupational stress of computer workers in a developed ergonomic setup.

Methods

A descriptive inferential study has been taken to analyze the effect of BMI on work related musculoskeletal discomfort and occupational-psychosocial stress. A total of 100 computer workers, aged 25-35 years randomly selected on convenience from software and BPO companies in Bangalore city, India for the participation in this study. BMI was calculated by taking the ratio of the subject's height (in meter) and weight (in kilogram). Work related musculoskeletal discomfort and occupational stress of the subjects was assessed by Cornell University's musculoskeletal discomfort questionnaire (CMDQ) and occupational stress index (OSI) respectively as well as a relationship was checked with their BMI.

Results

A significant association (p < 0.001) was seen among high BMI subjects with their increase scores of musculoskeletal discomfort and occupational stress.

Conclusion

From this study, it has been concluded that, there is a significant effect of BMI in increasing of work related musculoskeletal discomfort and occupational-psychosocial stress among computer workers in a developed ergonomic setup.

Peer Review reports

Background

Work related Musculoskeletal Disorders (WMSD) are the class of musculoskeletal disorders that include damage of tendons, tendon sheaths, and synovial lubrication of tendon sheaths, and related to bones, muscles, nerves of hands, wrists, elbows, shoulders, neck and back. Other commonly used terms include Ergonomic Disorders, Cumulative Trauma Disorders (CTD) and Repetitive Strain Injuries. These disorders develop gradually over a period of week, months or even years due to repeated exertions and movements of the body. These musculoskeletal disorders belong to a collection of health problems that are more prevalent among the working class than general population [1]. Work related musculoskeletal disorders constitute a major source of employee disability and lost wages. Thus, active surveillance of WMSD should continue an essential component in an ergonomic program used to control WMSD and reduce human suffering, lost workdays and wages, and compensation claims.

The changes brought about by the development of Video Display Terminal (VDT) technology may have contributed to the increase in CTD associated with VDT use. Office workers in United States have experienced an increase in CTD since 1986 [2]. Additional factors, such as increased awareness on the part of office workers and physicians as well as better recording of CTDs may also have contributed to this increased incidence [3]. Musculoskeletal symptoms and impairment affect approximately 29.7 to 32.6% of the population of the United States, and low back pain is the most frequent disorder to be involved. The incidence of neck disorders as a source of musculoskeletal impairment or disability is second to lower back disorders [4].

Pressure on soft tissues caused by external surfaces termed as contact stress or strain. Psychosocial stress is defined as organizational or interpersonal factors resulting in increased actual or perceived stress [5]. Stress in office work of VDT operators has two components: the first is associated with introducing new technology inherent in the use of VDT; the second is associated with the job demands and job position. The stress contributed by new technology is often transient. Electronic monitoring, however, is a technology related stress that may not be transient. Electronic monitoring has been used in jobs as diverse as truck drivers, nurses and telephone operators [6]. Occupational-psychosocial Stress (OS) in VDT operators may be related more to the total job and organizational structure than the VDT themselves. Some research has reported that job level is a better indicator of stress than VDT use [7] for example, those with better jobs are more likely to be able to set their own priorities. OS has been linked to jobs that include rigid work procedures, lack of social support, monotony and insecurity. Many individuals in their jobs express dissatisfaction with their position.

Many factors have already been identified that cause WMSD and OS. Ergonomic workstation helps in the reduction of WMSD and stress as well as throws an opportunity to have better work performance for better and faster industrial production. However, another factor is the overweight or obesity, which influences the WMSD and OS even in a developed ergonomic setup. The current study will help in providing information of awareness of overweight and effect of overweight on sustained work in an upright position as well as to quantify different dimensional work related musculoskeletal discomfort and occupational stress of computer professionals with correlation to their body mass indices in a developed ergonomic setup.

Materials & method

Inclusions

Subjects with the age group between 21 to 35 years, working in a developed ergonomic setup (i.e. Computer workstation: ergonomic design and anthropometric data of workers [812]; Monitor size: 17 inches, position of monitor: arms length distance (20-26 inches) with 10-20 degree tilt (as per individual preference), top of the viewing screen is at eye level when the user is sitting in an upright position (Bifocal wearers may need to lower the monitor to a couple of inches), viewing angle 40 degree with reduced glare, keyboard position: flat or neutral, mouse kept at side of key board, document holder (if required): preferably, at side of the monitor, Chair with 5 point base with casters, 15-22 inches adjustable seat height, (for individual convenience) feet rest flat on floor (footrest used if necessary), Seat size: 16.9 inches depth, 17.7 inches width, angle 0-4 degree with a waterfall front edge. Backrest size: 17.7 inches high, 14.2 inches width, adjustable lumbar support; 5.9 to 9.8 inches, backrest tilt/recline: adjustable 15 degree forward and backward (as per user preference), angle between backrest and seat pan: 90 degree or greater, arm rest: 10 inches high, 9.5 inches length, 2 inches width, removable/ height-adjustable arm rest (as per individual preference), well padded armrests, not used for slouch, Table: height of the table: 30 inches (for better leg room below the keyboard and mouse tray), height of key board and mouse tray: 26.5 inches below elbow height, Knee room: height (26 inches), width (20 inches), depth (15 inches). Anthropometric data of workers: head in straight/erect position, shoulders: relaxed (bilateral), shoulder abduction angle is less than 20 degree for working with mouse, shoulder-elbow angle: 90 degree, wrist in neutral position (fore arm and hand in a straight line, hip-torso angle: 90 degree, thigh-leg angle: 90 degree, leg-foot angle: 90 degree) as well as checked with OSHA Ergonomic Solutions: Computer Workstations eTool - Evaluation Checklist [13], those present during data collection, educational qualification - professional degree and above in engineering and computer science (upper-I socioeconomic status) [1416], work experience of more than one year and willingness towards participation have been included for study.

Exclusions

Part-time workers, subjects suffering from chronic illness and those underwent major surgery, eye problems, post-traumatic stiff joints, fixed deformity, weakness and paralysis were excluded.

Procedure

Subjects were selected by simple random sampling based on inclusion and exclusion criteria along with fulfillment of OSHA Ergonomic Solutions: Computer Workstations eTool - Evaluation Checklist [13] with a written consent signed by them for participation in this study. All the respondents completed the questionnaires anonymously, recording their individual ID number. No expenditure was inflicted on the cases, and all the personal records were considered confidential. The study was started after receiving approval from the institutional ethical committee. Body Mass Index (BMI) [17] was calculated by taking the ratio of the subject's height (in meter) and weight (in kilogram) i.e. (weight/ (height)2. Work related musculoskeletal discomfort was assessed by Cornell University's Musculoskeletal Discomfort Questionnaire (CMDQ) [18, 19] and occupational-psychosocial stress (role overloads, role ambiguity, etc.) was assessed by Occupational Stress Index (OSI) [20, 21] and the score was taken for calculation. The association was checked between different body mass indices and the scores of musculoskeletal discomfort and the occupational stress index.

Data Analysis

The data was analyzed for statistical significance by using the statistical package of social science (SPSS 11.0 Systat 8.0) software. The effect of BMI on WMSD and OS was analyzed by ANOVA. Separate Chi square analysis was done to associate BMI with OSI scores. Also a multivariate discriminant functional analysis was done to predict the BMI based on the study parameters (WMSD & OS) and OSI components.

Results

Maximum 60% of subjects were noted in the age group of 31-35 years with involvement of WMSD and OS (Table 1), whereas 64% of subjects were noted in high BMI group (Table 2). Maximum CMDQ score was noted in the overweight group (Mean, 46.23) followed by normal weight group (Mean, 26.13) and underweight group (Mean, 11.00), because overweight may contribute to increasing work related musculoskeletal disorders due to more weight loads on tissues. Significant association of BMI with CMDQ score (F = 136.137, P < 0.001; Table 3 & Figure 1) and OSI score (F = 422.295, P < 0.001; Tables 4 and 5 & Figure 2) has been found in this study. This shows that, high BMI group perceives a high level of WMSD and OS. Multivariate Discriminant Function Analysis was done to predict the BMI based on two parameters (Table 6). It has been noted that as the BMI increases, the CMDQ score significantly increases (P < 0.001), and OSI score also increases (P < 0.001). A Multivariant discriminant function analysis was done to predict the BMI over OSI sub components in which significance (P < 0.001; Table 7) has been seen with the role overload, unreasonable group pressure, responsibility and strenuous working conditions only.

Table 1 Subject distribution with their age group
Table 2 Body Mass Index (BMI) distribution (kg/m2)
Table 3 Association of Body Mass Index (BMI) with Work related Musculoskeletal Discomfort (CMDQ Score)
Figure 1
figure1

Association of Body Mass Index (BMI) with Work Related Musculoskeletal Discomfort (CMDQ Score).

Table 4 Association of Body Mass Index with Occupational-psychosocial Stress (OSI score)
Table 5 Association of Occupational-psychosocial Stress with Body Mass Index
Figure 2
figure2

Association of Body Mass Index (BMI) with Occupational-psychosocial Stress (using OSI score).

Table 6 Multivariate discriminant function analysis to predict the BMI based on two study parameters
Table 7 Multivariate Discriminant function analysis to predict the BMI based on OSI components

Discussion

Computer worker's health is foremost important for better productivity of any IT or BPO Company. Correct ergonomic setup, frequent rest, stretching and strengthening exercises may reduce few degrees of physiological and psychological load in the body, but at the same time importance has to be given for reduction of body weight in their sedentary working life otherwise it might lead to serious work related musculoskeletal disorders and occupational-psychosocial stress in due course of time.

An effort has been made here to find out the influence of BMI over CMDQ and OSI scores of the subjects in a developed ergonomic setup (Computer workstation: ergonomic design and anthropometric data of workers) [812]. In this study, 100 computer workers of different BMI were randomly selected (those who have given consent for participation) with fulfillment of OSHA Ergonomic Solutions: Computer Workstations eTool - Evaluation Checklist [13].

Evaluation of WMSD has already been studied by many authors in different Indian cities on computer professionals [2225]. The CMDQ [18, 19] is a reliable and valid tool, which has been taken here for investigation as well as already been used in foreign [26, 27] and Indian [24] studies for measurement of WMSD of computer professionals. The WMSD also has been studied in various other occupations in Indian population [2839].

In this study, maximum percentage of subjects was noted in the age group of 31-35 years as well as under high BMI. Computer workers with high BMI were found to be at risk with more WMSD and occupational-psychosocial stress, because over weight could be the factor to contribute in increasing of physiological and mechanical load on tissues. Relative disk pressure is being experienced during sitting with various inclinations of the back support. Intra-diskal pressure of the nucleus pulposus acts as a load transducer and indicates the magnitude of axial loading on the spinal column and the increased pressure indicates a greater muscular effort in maintaining the posture and hence a larger stress on spinal column [40].

Overweight yields a decreased postural stability and potentially negative impact on control of upper limb movements but its effect on control of balance imposes constraints on goal-directed movements. From a clinical perspective, obese individuals might be less efficient and more at risk of injuries than normal individuals in a large number of work tasks and daily activities especially requiring upper limb movements performed from an upright position [41].

Here increased CMDQ score was significantly associated with high BMI (P < 0.001, F = 136.137). Hence, high BMI has a definite influence in increasing WMSD even in a developed ergonomic setup. The finding inferred that high BMI computer professionals were prone to musculoskeletal disorder at work. This could be because of the body tissues are with stress load due to increased BMI which contributes to musculoskeletal discomforts. In support of this finding Shiri et al. [42] confirmed about the association between weight-related factors and the prevalence of Low Back Pain. Sjolie [43] too reported a significant correlation between high BMI and low back pain due to lesser flexibility, especially poor hip mobility. Furthermore, longer the time period they spent before the computer, higher the tissue load they receive on different body parts, which may further aggravate in case of high BMI. In addition, IJmaker et al. [44] confirmed an incidence of WMSD in different body parts of office workers due to their long time exposure to the computers. The time factor was dependent on speed and accuracy of work, which could be slow in case of high BMI computer professionals forcing them to experience more WMSD.

Occupation related psychosocial stress among working population is drastically increasing worldwide. Stress at work has become an integral part of everyday life. OSI with its 12 sub-components has been used in this study for evaluation of occupational-psychosocial stress (or occupational stress) among computer workers. OSI developed by Srivastava and Singh [20, 21] has been commonly used for research in Indian context [4551].

Overweight has got an impact on occupational-psychosocial stress. Because of repetitive movements of upper limbs, completion of a certain task in a stipulated time period, competition with fellow colleagues put the overweight and obese workers in a major occupational stress. The overweight impact may contribute in functional strength of the body in a continuous sedentary task where the ability of performance compromised to some extent. In a study Riddiford et al. [52] has reported that obese children spent significantly more time periods during all transfer phases of the chair raising task compare to non-obese children and thereby lower limb functionality in young obese children was impeded, when they move their greater body mass against gravity. Here it has been found that overweight workers face moderate to severe occupational stress as compared to their moderate built colleagues in a stressful work environment.

Stress in office work of VDT operators are due to introduction of new technology, inherent in the use of VDT, job demands and job position. Stress in VDT operators may be related more to the total job and organizational structure than to VDT themselves. Job's level is a better indicator of stress than VDT use, for example, those with better jobs are more likely to be able to set their own priorities. Stress has been linked to jobs that include rigid work procedures, lack of social support, monotony and insecurity. In this study psychosocial factors have been checked among computer workers from a single socioeconomic status (i.e. upper I) [1416] with high professional qualification, high earning and well to do family background. It helped in unbiased assessment of occupational-psychosocial stress claiming the impact of different BMI, since there were no other levels of socioeconomic status included.

Role over load, unreasonable group pressure, responsibility for persons, strenuous working condition has been found significant (P < 0.001) association with high BMI. This could be due to the competitive task required day by day in growing industries where the overweight computer professionals face such difficulties in stressful computing job. Previous research has focused on overall association between occupational stress and BMI. Sedentary office workers in a stressful job with high BMI will have more eating behavior, thereby they are more prone to have a weight gain which leads to obesity as reported by Kivimaki et al. [53] adding further occupational stress. In contrast, the weak association also has been seen between BMI and Occupational Stress of aggravated scores as reported by Kouvonen et al. [54].

Here, the increased OSI score has been significantly associated with high BMI (P < 0.001, F = 422.295) computer workers in a developed ergonomic setup. Hence, high BMI has a definite influence in increasing occupational-psychosocial stress. This study is confirmed by Ostry et al. [55] exploring the significant association exists between BMI and Occupational-Psychosocial Stress.

Conclusion

It can be concluded by stating that, there is a significant effect of BMI in increasing of WMSD and occupational-psychosocial stress. This study provides the insight to the Clinicians and Ergonomists about the relationship between BMI and WMSD, occupational stress in order to formulate well designed training program to avoid overweight for making the computer professionals fit at their sedentary work and free from occupational injury and stress.

Suggestion

Further study is required to find out the effect of BMI on followings:

  1. 1)

    Equal number of male and female population can be taken for the study.

  2. 2)

    Visual problems can be taken into consideration separately

  3. 3)

    Mental stress can be added along with occupational stress.

Abbreviations

BMI:

Body Mass Index

WMSD:

Work-related Musculoskeletal Discomforts

OS:

Occupational-psychosocial Stress

OSI:

Occupational Stress Index

VDT:

Video Display Terminal.

References

  1. 1.

    Saldana Norka: Active survillence of work related musculoskeletal disorders: Occupational Ergonomics, Theory and Application. Marcel Dekker Inc. 1996, 490.

    Google Scholar 

  2. 2.

    Bureau of Labor Statistics: BLS Report on survey of occupational injuries and illness in 1990 (press release USDC-91-600), and unpublished BLS analyses for finance, insurance and real estate workers: US Department of labor. 1991, Washington DC

    Google Scholar 

  3. 3.

    Franklin J: Quoted in labor department: Half of all job illnesses are RSIs. VDT News. 1991, 8 (1): 7-8.

    Google Scholar 

  4. 4.

    Cunningham LS, Kelsey JL: Epidemiology of musculoskeletal impairment and associated disability. Am J Public Health. 1984, 74 (6): 574-579. 10.2105/AJPH.74.6.574.

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  5. 5.

    Brophy M, Grant C: Office Ergonomics: Occupational Ergonomics, Theory and Applications. Marcel Dekker, Inc. 1996, New York

    Google Scholar 

  6. 6.

    Danann S, Moavero T: Stories of Mistrust and Manipulation: The Electronic Manitoring of the American Workforce, 9 to 5 Working Women Education Fund, Cleveland. 1990

    Google Scholar 

  7. 7.

    Smith MJ, Cohan BGF, Stammerjoh LW: An investigation of health complaints and job stress in video display operations. Human Factors. 1981, 23: 387-400.

    CAS  PubMed  Google Scholar 

  8. 8.

    Computer ergonomics guide, Cal/OSHA Consultation Service, Research and Education Unit, Division of Occupational Safety and Health, California Department of Industrial Relations. 2005, http://www.dir.ca.gov/dosh/dosh_publications/computerergo.pdf. accessed on 27.9.2007

  9. 9.

    Alan Hedge: ANSI/HFES 100-2007, workstation & chair checklist, Cornell University, Dept. Design & Environmental Analysis, Ithaca, NY 14850, USA. http://ergo.human.cornell.edu/studentdownloads/ANSIHFES100_2007CHAIR%20CHECKLIST.pdf. accessed on 27.9.2007

  10. 10.

    Ergonomic seating guide: Haworth, Inc: 2008, 10.08. http://www.haworth.com/en-us/Knowledge/Workplace-Library/Documents/Ergonomic-Seating-Guide.pdf. accessed on 27.11.2008

  11. 11.

    Karen Jcobs: Ergonomic strategies- computer keyboard, mice, monitors, Ergonomics for therapists. Mosby. 2008, 425-427. 3

    Google Scholar 

  12. 12.

    Bhattacharya Amit, James D McGlothlin: computer workstation ergonomic design: Occupational Ergonomics, Theory and Application. Marcel Dekker Inc. 1996, 788.

    Google Scholar 

  13. 13.

    OSHA Ergonomic Solutions: Computer Workstations eTool-Evaluation checklist: http://www.osha.gov/SLTC/etools/computerworkstations/pdffiles/checklist1.pdf accessed on 27.07.2007

  14. 14.

    Kumar N, Shekhar C, Kumar P, Kundu AS: Kupuswamy's socioeconomic status scale-updating for 2007. Indian Journal Paediatrics. 2007, 74 (12): 1131-32.

    CAS  Google Scholar 

  15. 15.

    Kupuswamy B: Manual of socioeconomic status (urban). 1981, Manasayan, Delhi

    Google Scholar 

  16. 16.

    Mishra D, Singh HP: Kuppuswamy's socioeconomic status scale- A revision. Indian Journal Paediatrics. 2003, 70 (3): 273-274. 10.1007/BF02725598.

    CAS  Article  Google Scholar 

  17. 17.

    Bethesda: Executive summary of clinical guidelines on identification, evaluation, and treatment of overweight, obesity in adults. Arch Intern Med. 1998, 158: 1855-10.1001/archinte.158.17.1855.

    Article  Google Scholar 

  18. 18.

    Hedge A, Marimoto S, McCrobie D: Effect of keyboard tray geometry on upper body posture and comfort with the use of CMDQ (Cornell university musculoskeletal discomfort questionnaire). Ergonomics. 1999, 42 (10): 1333-1349. 10.1080/001401399184983.

    CAS  Article  PubMed  Google Scholar 

  19. 19.

    Oguzhan Erdinc, Kubilay Hot, Murat Ozkaya: Cross-cultural adaptation, validity and reliability of Cornell musculoskeletal discomfort questionnaire (CMDQ) in Turkish language. Research report, Turkish Air force Academy. Department of industrial engineering, Istanbul, turkey. 2008

    Google Scholar 

  20. 20.

    Srivastava AK, Singh AP: Manual of Occupational Stress Index: Dept. of Psychology. Banaras Hindu University. Manovigyanik Parikshan Sansthan. 1981

    Google Scholar 

  21. 21.

    Srivastava AK, Singh AP: Construction and standardization of an Occupational Stress Index: A pilot study. Indian journal of clinical psychology. 1981, 8: 133-136.

    Google Scholar 

  22. 22.

    Sharma AK, Khera S, Khadekar J: Computer related health problems among IT professionals in Delhi. Indian journal of community medicine. 2006, 31 (1): 36-38. 10.4103/0970-0218.54936.

    Article  Google Scholar 

  23. 23.

    Dinesh Bhanderi, Choudhary SK, Lata Parmar, Vikas Doshi: A study of occurrence of musculoskeletal discomfort in computer operators. Indian journal of community medicine. 2008, 33 (1): 65-66. 10.4103/0970-0218.39252.

    Article  Google Scholar 

  24. 24.

    Shirley Telles, Manoj Dash, Naveen KV: Effect of yoga on musculoskeletal discomfort and motor functions in professional computer users. Work. 2009, 33: 297-306.

    Google Scholar 

  25. 25.

    Sharan D, Parijat P, Sasidharan AP, Ranganathan R, Mohandoss M, Jose J: Workstyle Risk Factors for Work Related Musculoskeletal Symptoms Among Computer Professionals in India. J Occup Rehabil. 2011

    Google Scholar 

  26. 26.

    Menzel Nancy, Brooks Stuart, Bernard Thomas, Nelson Audrey: The physical workload of nursing personnel: association with musculoskeletal discomfort. International Journal of Nursing Studies. 2004, 41 (8): 859-867. 10.1016/j.ijnurstu.2004.03.012.

    Article  PubMed  Google Scholar 

  27. 27.

    Mircea Fagarasanu, Shrawan Kumar: Musculoskeletal symptoms in support staff in a large telecommunication company. Work. 2006, 27 (2): 137-142.

    Google Scholar 

  28. 28.

    Gangopadhyay S, Das B, Das T, Ghosal G: An ergonomic study on posture-related discomfort among preadolescent agricultural workers of West Bengal, India. Int J Occup Saf Ergon. 2005, 11 (3): 315-22.

    Article  PubMed  Google Scholar 

  29. 29.

    Pradhan CK, Thakur S, Chowdhury AR: Physiological and subjective assessment of food grain handling workers in West Godavari district, India. Ind Health. 2007, 45 (1): 165-9. 10.2486/indhealth.45.165.

    Article  PubMed  Google Scholar 

  30. 30.

    Gangopadhyay S, Ghosh T, Das T, Ghoshal G, Das BB: Prevalence of Upper Limb Musculo Skeletal Disorders among Brass Metal Workers in West Bengal, India. Ind Health. 2007, 45 (2): 365-70. 10.2486/indhealth.45.365.

    Article  PubMed  Google Scholar 

  31. 31.

    Gangopadhyay S, Das B, Ghoshal G, Das T, Ghosh T, Ganguly R, Samato K: The prevalence of musculoskeletal disorders among prawn seed collectors of sunderbans. J Hum Ergol (Tokyo). 2008, 37 (2): 83-90.

    Google Scholar 

  32. 32.

    Mohan GM, Prasad PS, Mokkapati AK, Venkataraman G: Development of risk assessment tool for foundry workers. Work. 2008, 31 (4): 405-16.

    PubMed  Google Scholar 

  33. 33.

    Khan AA, O'Sullivan L, Gallwey TJ: Effects of combined wrist deviation and forearm rotation on discomfort score. Ergonomics. 2008, 17: 1-22.

    Google Scholar 

  34. 34.

    Khan AA, O'Sullivan L, Gallwey TJ: Effects of combined wrist flexion/extension and forearm rotation and two levels of relative force on discomfort. Ergonomics. 2009, 52 (10): 1265-75. 10.1080/00140130903040208.

    Article  PubMed  Google Scholar 

  35. 35.

    Mukhopadhyay P, O'Sullivan LW, Gallwey TJ: Upper limb discomfort profile due to intermittent isometric pronation torque at different postural combinations of the shoulder-arm system. Ergonomics. 2009, 52 (5): 584-60. 10.1080/00140130802396438.

    Article  PubMed  Google Scholar 

  36. 36.

    Ghosh T, Das B, Gangopadhyay S: Work-related Musculoskeletal Disorder: An Occupational Disorder of the Goldsmiths in India. Indian J Community Med. 2010, 35 (2): 321-5. 10.4103/0970-0218.66890.

    Article  PubMed  PubMed Central  Google Scholar 

  37. 37.

    Gangopadhyay S, Ghosh T, Das T, Ghosal G, Das B: Effect of working posture on occurrence of musculoskeletal disorders among the sand core making workers of West Bengal. Cent Eur J Public Health. 2010, 18 (1): 38-42.

    PubMed  Google Scholar 

  38. 38.

    Gangopadhyay S, Das B, Das T, Ghosal G, Ghosh T: An ergonomics study on posture-related discomfort and occupational-related disorders among stone cutters of West Bengal, India. Int J Occup Saf Ergon. 2010, 16 (1): 69-79.

    Article  PubMed  Google Scholar 

  39. 39.

    Mukhopadhyay P, Srivastava S: Evaluating ergonomic risk factors in non-regulated stone carving units of Jaipur. Work. 2010, 35 (1): 87-99.

    PubMed  Google Scholar 

  40. 40.

    Eastman Kodak Co: Human Factor Section: Ergonomics for people at work. Van Norstrand Reinhold, New York. 1996

    Google Scholar 

  41. 41.

    Berrigan F, Simoneau M, Trembley A, Hue O, Teasdale N: Influence of obesity on accurate and rapid arm movement performed from a standing posture. Int J Obes. 2006, 30 (12): 1750-57. 10.1038/sj.ijo.0803342.

    CAS  Article  Google Scholar 

  42. 42.

    Shiri R, Solovieva S, Husgafvel-Pursiainen K, Taimela S, Saarikoski LA, Hupponen R, Viikari J, Raitakati OT, Viikari-Juntura E: The association between obesity and prevalence of low back pain in young adults: the cardiovascular risk in young Finns study. Am J Epidemiol. 2008, 167 (9): 1110-9. 10.1093/aje/kwn007.

    Article  PubMed  Google Scholar 

  43. 43.

    Sjolie AN: Low back pain in adolescent is associated with poor hip mobility and high body mass index. Scand J Med Sc in Sport. 2004, 14 (3): 168-75. 10.1111/j.1600-0838.2003.00334.x.

    Article  Google Scholar 

  44. 44.

    IJmker S, Blatter BM, van der Beek AJ, van Mechelen W, Bongers PM: Perspective research on musculoskeletal disorders in office workers (PROMO): study protocol. BMC Musculoskeletal Disorder. 2006, 5 (7): 55.

    Article  Google Scholar 

  45. 45.

    Vempati RP, Shirley Telles: Baseline of occupational stress levels and physiological responses to a two day stress management program. Journal of Indian Psychology. 2000, 18 (1&2): 33-37.

    Google Scholar 

  46. 46.

    Jain KK, Fauzia Jabin, Vinita Mishra, Naveen Gupta: Job satisfaction as related to organizational climate and occupational stress: A case study of Indian Oil. International Review of Business Research Papers. 2007, 3 (5): 193-208.

    Google Scholar 

  47. 47.

    Adhikari R: Presented in National Yoga Week in Morarjee Desai National Institute of Yoga, New Delhi. Effect of yoga practices on occupational stress among army personnels. 2008

    Google Scholar 

  48. 48.

    Meena Kumari: Personality and occupational stress differentials of female school teachers in Haryana. Journal of Indian Academy of Applied Psychology. 2008, 34 (2): 251-257.

    Google Scholar 

  49. 49.

    Bakhshi R, Sudha N, Sandhu P: Impact of Occupational Stress on Home Environment:An Analytical Study of Working Women of Ludhiana City. J Hum Ecol. 2008, 23 (3): 231-235.

    Google Scholar 

  50. 50.

    Sandeep Kumar, Singh AP: Stress and job attitude: Role of work culture. Indian Journal of Social Science Researches. 2009, 6 (2): 38-47.

    Google Scholar 

  51. 51.

    Lovy Sarikwal, Sunil Kumar: An international study of work stress with types of workers. 2010, In proceedings of ASBBS Annual conference, Los Vegas, 17 (1): 142-145.

    Google Scholar 

  52. 52.

    Riddiford-Harland DL, Steele JR, Bour LA: Upper and lower limb functionality: are these compromised in obese children. Int J Pediatr Obes. 2006, 1 (1): 42-49. 10.1080/17477160600586606.

    Article  PubMed  Google Scholar 

  53. 53.

    Kivimaki M, Head J, Feeeie JE, Shipley MJ, Brunner E, Vahtera J, Marmot MG: Work stresss, Weight gain and Weight loss: evidence of bidirectional effect of job strain on body mass index in the Whitehall II study. Int J Obes. 2006, 30 (6): 982-7. 10.1038/sj.ijo.0803229.

    CAS  Article  Google Scholar 

  54. 54.

    Kouvonen A, Kivimaki , Cox SJ, Cox T, Vahtera J: Relationship between work stress and body mass index among 45,810 female and male employees. Psychosom Med. 2005, 67 (4): 577-83. 10.1097/01.psy.0000170330.08704.62.

    Article  PubMed  Google Scholar 

  55. 55.

    Ostry AS, Radi S, Louie AM, LaMontagne AD: Psychosocial and working conditions in relation to body mass index in representative sample of Australian workers. BMC Public Health. 2006, 2 (6): 53.

    Article  Google Scholar 

Download references

Acknowledgements

We acknowledge the contribution of Dr. Suresh and Dr. Subramaniam (Biostatisticians, Indian council of medical research) towards the data analysis.

Author information

Affiliations

Authors

Corresponding author

Correspondence to Jasobanta Sethi.

Additional information

Competing interests

The authors declare that they have no competing interests.

Authors' contributions

Authors JS and VI have made substantial contributions to conception and design, acquisition of data, analysis and interpretation of data, JS and JSS have been involved in drafting the manuscript, revising it critically for important intellectual content, and all the authors read and approved the final manuscript.

Authors’ original submitted files for images

Below are the links to the authors’ original submitted files for images.

Authors’ original file for figure 1

Authors’ original file for figure 2

Rights and permissions

This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Reprints and Permissions

About this article

Cite this article

Sethi, J., Sandhu, J.S. & Imbanathan, V. Effect of Body Mass Index on work related musculoskeletal discomfort and occupational stress of computer workers in a developed ergonomic setup. BMC Sports Sci Med Rehabil 3, 22 (2011). https://doi.org/10.1186/1758-2555-3-22

Download citation

Keywords

  • Body Mass Index
  • High Body Mass Index
  • Discriminant Function Analysis
  • Occupational Stress
  • Computer Worker