ABSTRACT
Background:
Musculoskeletal disorders (MSDs) significantly affect global health, with a high prevalence among software professionals due to prolonged sedentary behaviour and suboptimal ergonomic practices. In India, limited research exists on the burden and ergonomic challenges of MSDs in the IT sector, necessitating this study.
Materials and Methods:
An analytical cross-sectional study was conducted among 200 software professionals employed in multinational companies in India. Data were collected over 6 months using an online self-administered questionnaire comprising sociodemographic details, ergonomic practices and the Nordic Musculoskeletal Questionnaire (NMQ). Purposive sampling and snowball techniques ensured participant diversity. Descriptive statistics summarized data, while logistic regression identified significant predictors of MSDs.
Results:
The prevalence of MSDs was 72% during last 12 months with the lower back (66.7%) and neck (56.9%) being the most affected regions. Women were at a significantly lower risk (OR = 0.403, P = 0.049), while overweight individuals faced higher risks (OR = 2.84, P = 0.011). Prolonged work hours (≥8 hours/day) were a significant predictor (OR = 3.175, P = 0.004). Ergonomic challenges included inadequate workstation setups, with only 65% having a dedicated workspace and 45% receiving ergonomic training. Coping strategies included stretching exercises (61%) and over-the-counter medications (49.3%).
Conclusion:
The study highlights a significant burden of MSDs among Indian software professionals, emphasizing the need for workplace interventions focusing on ergonomic training, improved workstation design, and awareness about early medical consultation. Future research should assess the efficacy of these strategies to mitigate MSD risks and enhance occupational health outcomes.
Keywords: Ergonomics, musculoskeletal disorders, Nordic musculoskeletal questionnaire, software professionals
Introduction
Musculoskeletal disorders (MSDs) constitute a significant global health issue, affecting millions of individuals across diverse occupational domains. According to the report by the World Health Organization (WHO), it is estimated that approximately 1.71 billion individuals worldwide suffer from musculoskeletal disorders, with 50-70% of these cases comprising workers from various professional fields.[1] Musculoskeletal conditions significantly limit mobility and dexterity, leading to early retirement from work, lower levels of well-being and reduced ability to participate in society.
Among this demographic, software professionals are particularly susceptible to work-related musculoskeletal disorder (WMSDs) due to the inherent characteristics of their occupation, which frequently involves extended durations of sedentary behaviour and repetitive movements associated with computer use. WMSDs have a significant impact on employees and organizations, leading to sickness absence and reduced productivity, negatively affecting the quality of life of the working population.[2,3] It not only affect the health of workers but also includes economic and social costs creating burden on the health system. Studies indicate that MSDs contribute for a significant portion of lost workdays globally, leading to an estimated annual cost of billions of dollars in healthcare expenses and lost productivity.[4,5]
The rising trend of remote work after the COVID-19 pandemic further intensifies these challenges, as numerous employees may be deprived of ergonomic resources or appropriate guidance concerning the maintenance of proper posture during prolonged computer usage. This transition has been correlated with an increase in MSDs.
Despite the growing recognition of MSDs as a critical occupational health issue, there is a notable gap in research focusing on software professionals in India. Factors such as prolonged static postures, repetitive strain injuries from keyboard use, and inadequate workstation setups contribute significantly to the risk of developing MSDs. The high stress environment of software professionals often leads to neglect of physical health. Furthermore, the lack of tailored prevention and management strategies for this group highlights a crucial gap in current occupational health practices.
Addressing this issue requires urgent attention and collaborative efforts from researchers, employers, and policymakers alike. With limited research focusing on the ergonomic factors contributing to these disorders within the Indian IT sector, there is an urgent need to explore how workplace environments influence musculoskeletal health. Without understanding these dynamics, effective preventive strategies cannot be developed or implemented. Therefore, this study was planned to evaluate the burden of MSDs among software professionals in India and identifying ergonomic challenges among software professionals.
Objectives of the study
To assess the burden of musculo skeletal disorders among software professionals.
To assess ergonomic factors responsible for these disorders.
Materials and Methods
Study design
Analytical cross-sectional study.
Study setting and population
The study was conducted among software professionals employed in multinational companies in India and meeting the inclusion criteria. The data were collected in 6 months from May to October 2024 through an online self-administered questionnaire.
Inclusion criteria
Software professionals working in the IT industry for at least 1 year.
Individuals spending a minimum of 6 hours per day using a computer.
Exclusion criteria
Participants with postural deformities.
History of injury, trauma, or surgery involving the spine in the past year.
Pregnancy.
Sample size determination
The sample size for the study was calculated using the following formula:
Based on the findings of the previous study[6] which reported the prevalence of musculoskeletal disorders among software professionals as 66%, relative error 10%, 95% confidence interval, the sample size was calculated to be 198.
Sampling method
Participants were recruited using non-probability purposive sampling and the snowball technique. Initial recruitment was started with a small group of software professionals who meet the inclusion criteria. These individuals were approached through social media platforms (LinkedIn, WhatsApp). Then, each recruited participant was asked to share the survey link with their colleagues or other software professionals they know who also meet the inclusion criteria. Regularly tracking of the responses was done, and participants were encouraged to refer others until the desired sample size was reached.
Data collection tools and procedure
Data were collected using a structured, online, self-administered questionnaire comprising two parts: Section I consisting of questions addressing sociodemographic characteristics and workplace ergonomic practices; and Section II used to assess prevalence of MSDs using The Nordic Musculoskeletal Questionnaire.[7]
The questionnaire was distributed online via social media platforms, and data collection was continued until the required sample size is achieved. The primary outcome was the prevalence of musculoskeletal disorders and associated ergonomic challenges. Informed consent was taken before participation and ethical clearance has been obtained from the Institutional ethics committee vide letter no ELMC and H/R-cell/2024/174 dated 5/4/2024.
Statistical analysis
Data were analysed using the Statistical Package for Social Sciences (SPSS) version 22. Descriptive statistics summarize demographic characteristics and prevalence rates of MSDs. Inferential statistics was conducted using logistic regression to assess associations between various factors and MSD prevalence. A P value <0.05 was considered statistically significant.
Results
The study comprised of 200 software professionals including 153 (76.5%) males and 47 (23.5%) females with a mean age of 30.6 years (SD ± 4.5). Body Mass Index (BMI) using WHO criteria ranged from 17 to 39.1, with a mean of 26.1 (SD ± 5.5). Participants reported professional experience ranging from 1 to 20 years, with a mean of 6.1 years (SD ± 3.7). Daily working hours ranged from 6 to 13 hours, averaging 8.8 hours (SD ± 1.7). 64 (32%) participants were working permanently from home and 58 (29%) exclusively form the office. Rest 78 (39%) were working in the hybrid mode. The summary of descriptive statistics for demographic variables collected from study participants are shown in Table 1.
Table 1.
Descriptive statistics of demographic variables
| Variable | Minimum | Maximum | Median | Mean±SD* |
|---|---|---|---|---|
| Age (in years) | 22 | 44 | 30 | 30.6±4.5 |
| BMI (kg/m2) | 17 | 39.1 | 25.8 | 26.1±5.5 |
| Experience in years | 1 | 20 | 5 | 6.1±3.7 |
| Working hours per day | 6 | 13 | 8 | 8.8±1.7 |
*SD=Standard deviation
The study assessed various ergonomic practices among participants. Only 130 (65%) of participants reported a dedicated workplace who were working from home either permanently or in hybrid mode. A majority, 194 (97%), reported adequate lighting in their office or workplace for their tasks. 121 (61%) indicated that their workstations featured adjustable monitors (height and/or tilt) and 98 (49%) had adjustable desk heights. 50% of participants used a footrest. Only 91 (45.5%) workers had access to ergonomic training or guidance in their workplace. Majority of participants (85%) reported taking breaks every 2-3 hours, whereas 15% took breaks after longer durations [Figure 1].
Figure 1.
Ergonomic practices of the software professionals
In this study using standardised Nordic Musculoskeletal Questionnaire (NMQ) during previous 12 months work related MSD was reported by 144 (72%) of the participants while during last 7 days reported by 116 (58%) individuals. Lower back was the most commonly affected region, with 96 participants (66.7%) reporting symptoms. This was followed by the neck, with 82 participants (56.9%) experiencing discomfort, and the shoulder, with 64 participants (44.4%) reporting symptoms. Other regions included the elbow, with 44 participants (30.5%); the upper back, with 42 participants (29.2%). Less commonly reported regions included the hips, (12.5%) knees (22.2%); and ankles (13.9%). Over the last 7 days, the lower back continued to show the highest prevalence, with 72 participants (62%) reporting symptoms, followed by the neck, with 69 participants (59.4%), and the shoulder, with 51 participants (43.9%) [Table 2].
Table 2.
Prevalence of MSD with respect to the body locations among study participants
| Region | Symptoms in last 12 months (n=144) | Symptoms in last 7 days (n=116) | ||
|---|---|---|---|---|
|
|
|
|||
| No. | % | No. | % | |
| Neck | 82 | 56.9 | 69 | 59.4 |
| Shoulder | 64 | 44.4 | 51 | 43.9 |
| Elbow | 44 | 30.5 | 32 | 27.6 |
| Wrist/hand | 26 | 18 | 15 | 13 |
| Upper back | 42 | 29.2 | 29 | 25 |
| Lower back | 96 | 66.7 | 72 | 62 |
| One/both hips | 18 | 12.5 | 8 | 7 |
| One/both knee | 32 | 22.2 | 12 | 10.3 |
| One or both ankles | 20 | 13.9 | 7 | 3.5 |
Association of various risk factors classified as Physiological like Age, Gender, BMI and Ergonomic factors such as working hours per day, experience in the industry, frequency of breaks was assessed using logistic regression. Participants aged ≥ 30 years were more likely to experience musculoskeletal disorders (MSD), though the association was not statistically significant (OR = 2.497, 95% CI: 0.836-7.461; P = 0.101). Females exhibited a significantly lower risk of MSD compared to males (OR = 0.403, 95% CI: 0.163-0.996; P = 0.049), while overweight individuals were at a significantly higher risk (OR = 2.84, 95% CI: 1.230-5.018; P = 0.011). Ergonomic factors also influenced MSD risk, with participants having ≥8 years of experience showing increased odds, though this was not statistically significant (OR = 2.28, 95% CI: 0.582-8.950; P = 0.236). Working ≥8 hours per day significantly increased the likelihood of MSD (OR = 3.175, 95% CI: 1.454-6.931; P = 0.004). Regular breaks every 2-3 hours were associated with lower odds of MSD compared to longer break intervals, though this association was not significant (OR = 1.25, 95% CI: 0.418-3.713; P = 0.692) [Table 3].
Table 3.
Predictors of MSD among software professionals
| Variables | Category | Total | With MSD | Without MSD | OR | 95% CI | P | |
|---|---|---|---|---|---|---|---|---|
| Physiological factors | Age | <30 | 114 | 71 | 43 | 1 | - | - |
| ≥30 | 86 | 73 | 13 | 2.497 | 0.836-7.461 | 0.101 | ||
| Gender | Male | 153 | 113 | 40 | 1 | - | - | |
| Female | 47 | 31 | 16 | 0.403 | 0.163-0.996 | 0.049 | ||
| BMI | Normal | 84 | 50 | 34 | 1 | - | - | |
| Overweight | 116 | 94 | 22 | 2.84 | 1.230-5.018 | 0.011 | ||
| Ergonomic factors | Experience in years | <8 | 139 | 88 | 51 | 1 | - | - |
| ≥8 | 61 | 56 | 5 | 2.28 | 0.582-8.950 | 0.236 | ||
| Working hours per day | <8 | 102 | 62 | 41 | ||||
| ≥8 | 98 | 82 | 15 | 3.175 | 1.454-6.931 | 0.004 | ||
| Break frequency | Taking break 2-3 h | 170 | 120 | 50 | 1 | - | - | |
| Longer break duration | 30 | 24 | 6 | 1.25 | 0.418-3.713 | 0.692 |
The coping mechanisms for work-related musculoskeletal discomfort among software professionals (n = 144) revealed diverse strategies, with many participants employing multiple approaches. Stretching exercises were the most commonly reported method, used by 88 professionals (61%). Over-the-counter pain medications followed, utilized by 71 individuals (49.3%). Ergonomic aids were used by 52 participants (36.1%), and 48 (33.3%) coped by taking off from work. Treatment from physiotherapists or chiropractors was sought by 44 professionals (30.5%), while hot/cold therapy was adopted by 37 (26%). Seeking medical advice was reported by 35 respondents (24.2%), and 28 participants (19.4%) relied on other methods such as sleeping to distract themselves from pain, doing some relaxation techniques like meditation and reducing work load [Table 4].
Table 4.
Coping mechanism for work-related musculoskeletal discomfort used by software professionals (n=144)
| Coping mechanism (Multiple response) | No. | % |
|---|---|---|
| Over the counter pain medication | 71 | 49.3 |
| Stretching exercises | 88 | 61 |
| Hot/cold therapy | 37 | 26 |
| Using ergonomic aids | 52 | 36.1 |
| Seeking medical advice | 35 | 24.2 |
| Taking off from work | 48 | 33.3 |
| Taking treatment from physiotherapist/chiro practitioner | 44 | 30.5 |
| Others | 28 | 19.4 |
Discussion
The current study explored the prevalence of work related musculoskeletal disorders (MSDs) and their associated risk factors among IT professionals through a cross-sectional design. The findings revealed an MSD prevalence rate of 72% during last 12 months among the participants which is in alignment with the findings of other studies where MSD prevalence ranges from 67% to 70%.[8,9,10] This notably high prevalence signifies the urgent need for effective interventions in this sector. A much higher percentage (91%) is shown by another study conducted in a software company, Kolkata by Basu et al.[11] This variability is supported by literature review focusing on IT professionals which quoted that the prevalence of musculoskeletal symptoms is not uniform across different studies.[12]
In this study 76.5% participants were males while 23.5% were females which is consistent with other studies showing male predominance in this sector.[6,13] However Saleem et al.[10] reported higher percentage of females in their population in their study population with 57.6% males and 42.4% females.
In the current study, most commonly region affected was lower back (66.7%) followed by neck (56.9%). Kumar et al.[14] in their a similar pattern of musculoskeletal disorders with predominant involvement of neck (61.9%), lower back (52.9%) and shoulder (37.7%). Similar distribution of pain was also reported by various other studies.[15,16,17,18]
Studies shows that working more than 52 hours per week significantly raises the risk of upper and lower limb pain in both male and female workers.[19] In our research, working more than eight hours per day was identified as a significant predictor of MSDs reinforcing the need for interventions aimed at reducing work hours or implementing regular breaks. Our results indicated that individuals with higher Body Mass Index (BMI) were at increased risk for MSDs which is aligning with findings from another study that have established a link between obesity and musculoskeletal pain.[20] Similar results were also seen in a prospective study where Age, Body Mass Index (BMI), working hours and work-style were positively correlated (r < 0.01) with the presence of WRMSDs, as higher the age and BMI, increased working hours and higher work-style score showed higher prevalence of WRMSD.[21]
The ergonomic challenges faced by software professionals are critical in understanding the high incidence of MSDs. A study conducted in Ahmedabad (Gujarat) identified poor workstation ergonomics as a significant risk factor, with many participants reporting inadequate setup leading to discomfort and pain.[6] The Rapid Office Strain Assessment (ROSA) tool used in their research highlighted that poorly designed workstations were associated with higher prevalence rates of MSDs. In the present study it was observed that only 65% had a dedicated workspace and 49% had adjustable desk heights. 61% participants stated that their workstations featured adjustable monitors (height and/or tilt). Another study revealed poor office ergonomics (54%), lack of keyboard tray (25%), lack of mouse tray (35%), lack of foot rest (60%), improper monitor height (80%) as the major self-reported risk factors.[22]
In this study 45% had access to ergonomic training or guidance in their workplace. However, the another study revealed that only 32.03% and 32.31% of participants became aware of computer ergonomics only after the occurrence of musculoskeletal and visual problems, respectively.[13] Thus lack of ergonomic knowledge and practice among software professionals suggests the need of educational interventions which will be helpful in reducing the work related Musculo skeletal discomfort.
In our study stretching (61%) and over the counter pain medication (49.3%) came out to be most common coping mechanism used by participants against MSD. These results are in concordance another study which reported self-stretching (69%), taking more frequent micro breaks (51%) and adjustment of work stations by 24% participants.[8] In the current study only 21% of participants sought medical advice for their symptoms. The relatively low rate of professional medical consultation despite high prevalence indicates a potential gap in healthcare-seeking behaviour among this population. This underscores the need of generating awareness for seeking timely medical help which could prevent further complications and improve outcome.
Conclusion
The findings from our study highlight the significant burden of MSD sand underscore the urgent need for targeted interventions to address this among software professionals. These interventions should focus on improving ergonomic practices, reducing work hours, and enhancing awareness about health-seeking behaviour. Future research should aim to evaluate the effectiveness of such interventions in reducing the burden of MSDs within this vulnerable population.
Limitations
The study may be subject to reporting bias due to the self-administered nature of the questionnaire. The use of nonprobability sampling may limit generalizability.
Author contributions
RC: Concepts, design, definition of intellectual content, literature search, data acquisition, data analysis, statistical analysis, manuscript preparation, manuscript editing, manuscript review. SA: Concepts, design, definition of intellectual content, literature search, data acquisition, statistical analysis, manuscript preparation, manuscript editing, manuscript review. SR, AS, JM: Concepts, design, definition of intellectual content, statistical analysis, manuscript preparation, manuscript editing, manuscript review.
Ethical approval
Ethical clearance has been obtained from the Institutional ethics committee vide letter no ELMC and H/R-cell/2024/174 dated 5/4/2024.
Conflicts of interest
There are no conflicts of interest.
Funding Statement
Nil.
References
- 1.World Health Organization. Musculoskeletal conditions. 2019. [[Last accessed on 2025 Jan 20]]. Available from: https://www.who.int/news-room/fact-sheets/detail/musculoskeletal-conditions .
- 2.Doğrul Z, Mazican N, Turk M. The prevalence of work-related musculoskeletal disorders (WRMSDs) and related factors among occupational disease clinic patients. Int Arch Public Health Community Med. 2019;3:030. [Google Scholar]
- 3.Chandralekha K, Joseph M, Joseph B. Work-related musculoskeletal disorders and quality of life among staff nurses in a tertiary care hospital of Bangalore. Indian J Occup Environ Med. 2022;26:178–82. doi: 10.4103/ijoem.ijoem_25_22. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Chen N, Fong DYT, Wong JYH. Health and economic outcomes associated with musculoskeletal disorders attributable to high body mass index in 192 countries and territories in 2019. JAMA Netw Open. 2023;6:e2250674. doi: 10.1001/jamanetworkopen.2022.50674. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Gorasso V, Van der Heyden J, De Pauw R, Pelgrims I, De Clercq EM, De Ridder K, et al. The health and economic burden of musculoskeletal disorders in Belgium from 2013 to 2018. Popul Health Metr. 2023;21:4. doi: 10.1186/s12963-023-00303-z. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 6.Panchal S, Viramgami AP, Pingle S. Prevalence and determinants of musculoskeletal disorders among information technology sector employees of Ahmedabad, Gujarat. J Compr Health. 2020;8:28–32. [Google Scholar]
- 7.Kuorinka I, Jonsson B, Kilbom A, Vinterberg H, Biering-Sorensen F, Andersson G, et al. Standardised Nordic questionnaires for the analysis of musculoskeletal symptoms. Appl Ergon. 1987;18:233–7. doi: 10.1016/0003-6870(87)90010-x. [DOI] [PubMed] [Google Scholar]
- 8.Swetha NB, Ranganath TS, Shibi S, Shireen N. Cross-sectional study of visual and musculoskeletal disorders among the information technology professional workers in Bengaluru South, Karnataka, India. Int J Community Med Public Health. 2016;3:2781–5. [Google Scholar]
- 9.Kothapalli M. Prevalence of self-reported work-related musculoskeletal symptoms among software employees in Hyderabad, India. Int J Res Rev. 2022;9:69–73. [Google Scholar]
- 10.Saleem M, Priya S, Govindarajan R, Balaji E, Anguraj JD, Shylendra Babu PG, et al. A cross-sectional study on work-related musculoskeletal disorders among software professionals. Int J Community Med Public Health. 2015;2:367–72. [Google Scholar]
- 11.Basu R, Dasgupta A, Ghosal G. Musculoskeletal disorders among video display terminal users: A cross-sectional study in a software company, Kolkata. J Clin Diagn Res. 2014;8:JC01–4. doi: 10.7860/JCDR/2014/9480.5252. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 12.Singh RM, Borkar P. Prevalence of work-related musculoskeletal disorders among IT professionals in India: A literature review. Int J Res Med Sci. 2020;8:3765–71. [Google Scholar]
- 13.Thekdi KP, Patel JP, Macwana JJ. Role of ergonomics in occupational health problems of information technology professionals of Ahmedabad City. Indian J Public Health Res Dev. 2024;15:451–6. [Google Scholar]
- 14.Kumar M, Dutta S, Saha I, Saha A, Prasanth K. A study on musculoskeletal morbidity among professionals in information technology hub, Salt Lake City, Kolkata. Biomed Res. 2019;30:914–6. [Google Scholar]
- 15.Vijay A. Work-related musculoskeletal health disorders among the information technology professionals in India: A prevalence study. Int J Manage Res Bus Strat. 2013;2:118–28. [Google Scholar]
- 16.Moom K, Sing P, Moom N. Prevalence of musculoskeletal disorder among computer bank office employees in Punjab (India): A case study. Proce Mfg. 2015;3:6624–31. [Google Scholar]
- 17.Hameed S. Prevalence of work related low back pain among the information technology professionals in India-A cross sectional study. Int J Sci Technol Res. 2013;2:80–5. [Google Scholar]
- 18.Mohanty P, Singh A, Pattnaik M. Risk factors responsible for musculoskeletal pain among computer operators. EC Ortho. 2017;6:15–31. [Google Scholar]
- 19.Amiri S. Longer working hours and musculoskeletal pain: A meta-analysis. Int J Occup Saf Ergon. 2022;29:1–16. doi: 10.1080/10803548.2022.2036488. [DOI] [PubMed] [Google Scholar]
- 20.Mohan V, Inbaraj R, George E, Norman G. Prevalence of complaints of arm, neck, and shoulders among computer professionals in Bangalore: A cross-sectional study. J Fam Med Prim Care. 2019;8:171–7. doi: 10.4103/jfmpc.jfmpc_253_18. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Sharan D, Rajkumar JS. 643 Risk factors for the development of work related musculoskeletal disorders among information technology professionals. Occup Environ Med. 2018;75:A149–50. [Google Scholar]
- 22.Sharan D, Ajeesh PS, Rameshkumar R, Jose J. Risk factors, clinical features and outcome of treatment of work related musculoskeletal disorders in on-site clinics among IT companies in India. Work. 2012;41:5702–4. doi: 10.3233/WOR-2012-0924-5702. [DOI] [PubMed] [Google Scholar]

