Musculoskeletal Disorder and Their Predisposing Factors Among Garment Workers in Bangladesh: A Clinical Study

Md. Mubdiul Haque¹, Mohammad Mohinul Islam^2*

¹Educo Bangladesh
²Bangladesh Shishu (Children) Hospital and Institute, Dhaka, 1207, Bangladesh

*Correspondence author: Mohammad Mohinul Islam, Bangladesh Shishu (Children) Hospital and Institute, Dhaka, 1207, Bangladesh and Assistant Professor, Dhaka College of Physiotherapy (DCPT), Bangladesh; Email: mohinphysio@gmail.com

Citation: Haque MM, et al. Musculoskeletal Disorder and Their Predisposing Factors Among Garment Workers in Bangladesh: A Clinical Study. Jour Clin Med Res. 2025;6(3):1-12.

Copyright^© 2025 by D’Annuncio V, et al. All rights reserved. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Table 1: Sociodemographic characteristics.

Anthropometric Measurement

Most of the respondents (50%) belonged to 145-155 cm, 34.5% belonged to 155-165 cm and only 15.5% were 165-175 cm height, respectively. The Table 2 showed that 69.1% of respondents were 45-60 kg, according to 29.1% belonged to 61-75 kg and only 1.8% were >75 kg, respectively. This table shows that the majority of 81.8% of respondents BMI were 18.5-24.9, followed by 18.2% of respondents had a BMI of 25-29.9.

Table 2: Anthropometric measurements.

Job-Related Information

As the Table 3 showed, 28.2% of respondents were 1-8 hours their working in garment factories, according to 71.8% worked 8-12 hours. The mean working hours were Mean=9.49; (SD=±0.993). overtime working hours are higher.

Table 3: Distribution of respondents by regular working hours.

As the Table 4 showed, 70.9% did this work for 1-10 years, according to 29.1% did work 10-20 years.

Table 4: Distribution of the respondents by duration of work in RMG (in years).

Table 5 shows that almost all garment workers (4.5%) were working on their ironing section, followed by 16.4% in were finishing section, 7.3% in were knitting section, 7.3% dyeing section, 15.5% quality section, 24.5% in were sewing section, 10% in were printing section,10.9% were cutting section 3.6% were other section.

Table 5: Distribution of the respondents by name of section.

Predisposing Factors of Musculoskeletal Disorders Among the Participants

The risk of developing musculoskeletal disorder pain was almost 32.7% of respondents. There were 1-8 hours and 17.3% were 8-12 hours, by the daily time spent sitting at work and the not applicable respondent was 50.0%. The risk of developing musculoskeletal disorder pain was almost 46.4% of respondents reported 1-8 hours and 36.4% reported 8-12 hours due to daily standing at work. And the not applicable respondent was 17.3. Regarding the study, it has been shown that about 72.7% of respondents by heavy physical duty (lifting). The risk of developing musculoskeletal disorders among respondents was 47.3% sometimes with the increase in the amount of perceived stress. Those who never stress (14.5%) participate in groups respectively. And never any stress, 14.5, all the time very little, 14.8%.

Distribution of the Respondents by Suffering from Other Co-Existing Diseases

The table shows that 16.4% of respondents were not suffering from a common co-existing disease. Among them, 25.5% suffered common cold, 18.2% suffered from skin allergies, 11.8% suffered from fungal infection, 5.5% suffered from asthma and a small percentage suffered from co-morbidities.

Extended Nordic Musculoskeletal Questionnaire (NMQ-E) for Musculoskeletal Disorder

Considering the pain in different parts of the 9-body region, 23.6% had neck according to 12.7% had shoulder, 6.4% upper back, 3.6% had elbow 7.3%, 3.6% wrist/hand, 29.1% lower back, 0.9% Hips/thigh, 10.9% knees and 9.1% ankles/foot (Table 6).

Table 6: Distribution of respondents by pattern of body region pain.

Association Between BMI and Lifting Objects/People During Work

A chi-square test for independence with α=0.05 was used to assess whether the BMI was related to lifting objects/people during work. The chi-square test is statistically significant, χ² (1, N=110)=6.366, p<0.05, with a phi coefficient of 0.241, indicating a moderate relationship. As seen in the figure, a normal BMI is more likely to lift objects/people than an overweight (Fig. 1).

Figure 1: Association between BMI and lifting objects/people during work.

Association Between Actual Regular Working Hours with Daily Sitting Hours

A chi-square test for independence with α=0.05 was used to assess whether the actual regular work hour was related to the daily sitting hours. The chi-square test is statistically significant, χ² (1, N=110)=8.985, p<0.05, with a phi coefficient of 0.404, indicating a strong relationship. As seen in the figure, actual regular-hour overtime is more likely sitting hours than during regular working hours (Fig. 2).

Figure 2: Association between actual regular working hours with daily sitting hours.

Association Between Actual Regular Working Hours with Daily Standing Hours

 A chi-square test for independence with α=0.05 was used to assess whether the actual regular work hour was related to the daily standing hour. The chi-square test is statistically significant, χ² (1, N=110)=25.56, p<0.05, with coefficient of 0.530, indicating a strong relationship. As seen in the Fig. 3 actual regular-hour over time is more likely standing hours than a regular working hour.

Figure 3: Association between actual regular working hours with daily standing hours.

Discussion

Garment workers mostly work in a sitting posture and they hold their posture sincerely due to the nature of their work and its importance. Prolonged sitting makes people discomfort and leads to musculoskeletal disorders. In Bangladesh, most of the garment workers are early adult and their physical capacity is higher than other age. So, they can compensate for the problem. When this population is under threat of musculoskeletal disorders, then it’s alarming. It was observed in the present study that the mean age of the respondents was 21.89 (SD± 3.899) years. The majority of the respondents (28.8%) were between 19-20 years. Only 22.3% were above 25 years and almost all were Muslim (91.2%) except one who belonged to the Hindu Community. It was observed in the present study that 110 participant’s 38% (n=42) participants were male and 62% (n=68) were female. The female was the highest number of the respondents. It was observed in the present study that the mean age of the respondents was 29.94 (SD± 6.571) years. Among 110 participants, less than 18-30 years is 59.1% (n=65), 39.1% (n=43) were in the age between 30-45 years and 1.8% (n=2) were in the age of more than 30 years. The 18-30-year group had the highest percentage. Most of the respondents were Muslim (94.5%), followed by Hindu (4.5%) and Buddhist (0.9%).

Most of the respondents, 90.9% of garment workers, were married, 8.2% were unmarried and the rest 0.9% were divorced. among 110 respondents, 0.9% (n=1) have the below SSC educational level, 78.2% (n=86) have the SSC educational level, 20% (n=22) have the HSC educational level and 0.9% (n=1) have the graduate educational level. SSC’s educational level has the highest number of participants. This finding correlates with LFS findings, that people with no or little education had a high labour force participation rate (Rahman, 2014). Husband /father occupation of the respondent’s day labourer 8.2% (n=9), cultivator 6.4% (n=7), rickshaw puller 9.1% (n=10), garment worker 19.1% (n=21), Small business 13.6% (n=15), Service 6.4% (n=7) and not applicable 37.3% (n=41). Wife /father occupation of the respondent’s: Garments worker 13.6% (n=15), Small business 3.6% (n=4), Service 1.8% (n=2, Housewife 18.2%(n=20) and not applicable 62.7% (n=69). The epidemiology showed that underprivileged populations are working in the garment factory.

RMG is placing second place for Job facilities for many unskilled labourers coming from rural areas seeking work. Without prior knowledge, many labourers handled heavy loads which are monotonous, continuous and prolonged. Without proper protective equipment and inappropriate ergonomic provisions, their health is vulnerable. This study aimed to determine the WMSDs and risk factors among RMG workers and find out the association and correlation with pain among different predefined variables in Bangladesh. Musculoskeletal Disorders (MSDs) are a significant health concern in the workplace, particularly in industries that require repetitive motions and sustained physical activity, such as garment manufacturing.

The risk of developing musculoskeletal disorder pain was almost 32.7% of respondents. There were 1-8 hours and 17.3% were 8-12 hours of daily sitting at work. And the not applicable respondent was 50.0%. The risk of developing musculoskeletal disorder pain was almost 46.4% of respondents reported 1-8 hours and 36.4% reported 8-12 hours due to daily standing at work. And the not applicable respondent was 17.3. It regards 72.7% of respondents by heavy physical duty (lifting). The risk of developing musculoskeletal disorders among respondents was 47.3% sometimes with the increase in the amount of perceived stress. Those who never stress (14.5%) participate in the group, respectively. And never any stress, 14.5, all the time, very little, 14.8%.

Co-morbid diseases have been associated with musculoskeletal disorder pain [12]. 16.4% of respondents were not suffering from common co-existing diseases. Among them, 25.5% were suffering from the common cold, 18.2% suffered skin allergies, 11.8% suffered from fungal infection and 5.5% had asthma and a small percentage had another co-existing disease. In our study, among 110 respondents, 9-body region, 23.6% had a neck according to 12.7% had a shoulder, 6.4% upper back, 3.6% had an elbow 7.3%, 3.6% wrist/hand, 29.1% lower back, 0.9% had Hips/thigh, 10.9% knees and 9.1% ankles/foot. Initial ages of trouble arise in 6.4% below 18 years of age, according to 64.5% in here age range 18-30 years, 28.2% in here age range 30-40 years and 0.9% above 40 years 0.9%. Due to trouble among 110 respondents, 5.5% (n=6) are hospitalized and the rest of 94.5% (n=104) did not require hospitalisation. Due to trouble changing jobs/duties among 110 respondents, 16.4% (n=18) changed jobs/duties and the rest of the majority, 83.6% 9(n=92) did not need it. Trouble (ache, pain or discomfort) lasted 4 weeks among 110 respondents; 73.6% (n=81) felt it and 26.4% (n=29) did not experience it. Trouble (ache, pain or discomfort) today, among 110 respondents, 92.7% (n=102) experience it and the rest of 7.3% (n=8) do not experience it. Preventing from work (home or away from home) among 110 respondents, 31.8% (n=35) faced it and the rest of the majority, 68.2% (n=75) did not face it. Among 110 respondents who received doctor, physiotherapist, chiropractor or other treatment, 93.6% (n=103) and the rest of not receive any treatment, 6.4% (n=7).

Among 110 respondents who received medication, 87.3% (n=96) and the rest of 12.7% (n=14) did not. Most of the respondents received treatment, 93.6% (n=103). The rest of 2.7%(n=3) do not receive treatment due to lack of money, 1.8% (n=2) due to distance from health facilities and another 1.8% (n=2) due to expenditure for treatment. Among 110 respondents taking sick leave for trouble, 61.8% (n=68) and the rest 38.2% (n=42) did not. The majority of more than half (56.4%) of respondents had 1-6 days of leave last 12 months, followed by 40.0% who had 7-12 days in the last 12 months and 0.9% had more than 12 days of leave last year. And the rest of the 2.7% had no leave last 12 months. Most of the respondents (50%) belonged to 145-155 cm, 34.5% belonged to 155-165 cm and only 15.5% were 165-175 cm in height, respectively. 69.1% of respondents were 45-60kg, according to 29.1% belonged to 61-75 kg and only 1.8% were >75 kg, respectively. The majority of 81.8% of respondents’ BMI was 18.5-24.9, followed by 18.2% of respondents were 25-29.9. There was a relationship between the BMI was related to lifting objects/people during work. 72.7% of respondents by heavy physical duty (lifting). The findings are statistically moderately significant. χ² (1, N=110) =6.366, p<0.05 with phi co-efficient of 0.241. Relationship between hours spent sitting and participants with regular duty hours. The risk of developing musculoskeletal disorder pain was almost 32.7% of respondents reported 1-8 hours and 17.3% reported 8-12 hours due to daily sitting at work. The findings show a statistically strong relationship. χ² (1, N=110) =8.985, p<0.05 with phi co-efficient of .404. Regular-hour overtime is more likely sitting hour than regular working hours. Relationship between hours spent standing and participants with regular duty hours. The risk of developing musculoskeletal disorder pain was almost 46.4% of respondents reported 1-8 hours and 36.4% reported 8-12 hours due to daily standing at work. The findings show a statistically strong relationship. Here, χ² (1, N=110) =25.56, p<0.05 with phi co-efficient of 0.530. Actual regular-hour overtime is more likely to be standing hours than regular working hours. Interestingly, a study of Sri Lankan garment workers found a relatively low prevalence of musculoskeletal disorders, with few sewing machine operators reporting neck or upper extremity pain. This is surprising, given that the garment industry generally experiences some of the highest rates of neck and shoulder pain compared to other manufacturing sectors [11-25]. In Bangladesh, the garment sector plays a crucial role in the economy, employing a large portion of the workforce, with a significant number of workers being women. Despite its economic importance, the industry is notorious for its poor working conditions, which include prolonged standing, repetitive motions, inadequate seating arrangements and poor ergonomics, all of which contribute to the development of musculoskeletal disorders [13-48].

Strength of the Study

The study was implemented in one of the biggest garment factories in Bangladesh. So, it was generated the quality data. The data collector was trained before starting data collection, so they have given very nice output. The ethical issues were maintained properly.

Limitations of the Study

It was a single-centred study which was not sufficient to get all aspects information. Due to a self-funded study, it was not possible to get data from multiple centres.

Conclusion and Recommendations

The range of health issues faced by garment workers, especially the high incidence of musculoskeletal problems, is alarming. It is essential to take measures to revise their wages and improve working conditions to enhance their socioeconomic status. Additionally, providing counselling for alcohol and tobacco addiction is crucial, along with educating workers about disease prevention and the importance of personal hygiene. In the ready-made garment sector of Bangladesh, a significant number of female workers continue their employment despite suffering from various diseases and illnesses, as they have no alternative means of support. The growth and development of this sector heavily rely on female workers, who are its primary contributors. It is important to recognize that unhealthy workers cannot sustain a healthy economy. Health issues among workers significantly impact the competitive strength of the garment sector in the global market, as they greatly reduce productivity. To identify workers at high risk of poor outcomes, factors associated with chronic low back pain can be utilized. These factors include recovery expectations, interactions with healthcare providers, self-reported pain and physical limitations and the physical demands of the job. Screening workers based on these factors can help pinpoint those at high risk of long-term or permanent disability. There is conflicting evidence regarding the association of the female gender with musculoskeletal disorders, particularly in occupations like nursing and jobs requiring heavy physical labour. Participation in physical activities more than three times a week is protective against lower back pain. It is essential to maintain a balance between prolonged sitting, standing and walking, as excessive amounts of any of these can contribute to the development of musculoskeletal pain. Additionally, stress is associated with musculoskeletal pain, which may also be linked to other chronic diseases.

Conflict of Interest

The authors declared no potential conflicts of interest with respect to the research, authorship and/or publication of this article.

Financial Disclosure

This research did not receive any grant from funding agencies in the public, commercial or not-for-profit sectors.      

Consent To Participate

The authors certify that they have obtained all appropriate patient consent.

Data Availability and Consent of Patient

Data is available for the journal. Informed consents were not necessary for this paper.

Author’s Contribution

All authors contributed equally for this paper.

Acknowledgment

None.

References

1. Alam MA, Hasan MA, Sultana S. Musculoskeletal disorders among readymade garment workers: Prevalence, impact and risk factors. Int J Occup Saf Health. 2019;9(2):71-7.
2. Anema JR, van der Beek AJ, Knol DL. Effective interventions for low back pain in the workplace. J Occup Rehabil. 2007;17(3):327-36.
3. sg. Global statistics on work-related musculoskeletal disorders. World Health and Safety Council. 2018.
4. Niu S. Musculoskeletal symptoms among garment and textile workers: A study on prevalence and risk factors. J Occup Health. 2010;53(2):103-9.
5. Rahman MS. Work-related musculoskeletal disorders among garment workers in Bangladesh: Causes and impact on health. Int J Ergon. 2020;32(2):215-25.
6. Islam SM, Rahman MS, Siddiquee MS. Impact of occupational factors on the health and productivity of garment workers in Bangladesh. Int J Occup Med. 2019;50(4):239-47.
7. Hossain MS, Sultana R, Rahman M. Prevalence of musculoskeletal disorders in garment workers in Bangladesh: An exploration of risk factors. J Occup Health Saf. 2021;40(1):32-42.
8. Shams A, Hossain M, Rahman M. Neck and back pain among garment workers: A study of prevalence and contributing factors. Bangladesh J Ergon. 2022;14(1):98-108.
9. Rahman MS, Islam M. Factors contributing to musculoskeletal disorders in the garment industry of Bangladesh. Occup Health Saf Rev. 2021;5(2):65-72.
10. World Health Organization. Occupational health: Musculoskeletal disorders in small-scale industries. WHO. 2012.
11. Jahan S, Islam M, Hossain M. Musculoskeletal disorders in garment workers in Dhaka, Bangladesh: A cross-sectional study. J Occup Health Psychol. 2015;18(2):118-27.
12. Dionne CE, Desrosiers ME, Bourbonnais R. The impact of lumbar spine surgery on the long-term disability of workers. J Occup Rehabil. 2006;16(2):231-41.
13. Saha M, Dasgupta S, Butt A. Health risks in the garment industry: The case of Bangladesh. Int J Ind Health. 2010;48(4):315-24.
14. Anderson GBJ. Epidemiology of low back pain: A review of the literature. Spine. 1999;24(16):1739-48.
15. Anderson L. Musculoskeletal disorders in industrialized countries: Prevalence and costs. J Occup Health. 1999;41(2):143-52.
16. Anette S, Carlsson M, Bengtsson E. Work-related musculoskeletal disorders among female sewing machine operators: A longitudinal study. Ergonomics. 2016;59(6):849-60.
17. Ann L. Work-related musculoskeletal disorders: A review of the literature and analysis of data from the U.S. Department of Labor. J Occup Health. 2016;58(2):123-32.
18. Anthony J. Musculoskeletal disorders and their effects on work-related health and productivity. J Occup Health. 2003;45(4):235-45.
19. Anthony W. Economic impact of musculoskeletal conditions: The health care costs and productivity loss. J Occup Health Psychol. 2003;8(1):88-96.
20. Beaudart C, Reginster JY, Rizzoli R. Prevalence and burden of musculoskeletal disorders in the world. Nat Rev Rheumatol. 2018;14(9):588-96.
21. Behrens V, Kallenbach M, Stuebner H. Occupational health risks and ergonomic challenges in the textile industry. Int J Ind Ergon. 1994;14(4):247-55.
22. Bongers PM, de Winter CH, Kompier MA, Hildebrandt VH. Psychosocial factors at work and musculoskeletal disorders. Scand J Work Environ Health. 1993;19(3):173-81.
23. Bongers PM, Kremer AM, Laak MR. Psychosocial and physical risk factors for musculoskeletal disorders in the workplace. Occup Med. 2002;52(3):191-8.
24. Cohen SP, Buvanendran A, Nalamachu S. Treatment of musculoskeletal pain: The role of ergonomics and injury prevention. Clin J Pain. 2008;24(7):604-15.
25. Hartvigsen J, Hancock MJ, Kongsted A, Louw Q, Ferreira M, Genevay S. What low back pain is and why we need to pay attention. Lancet. 2018;391(10137):2356-67.
26. Hasan M, Islam S, Rahman M. Prevalence of musculoskeletal disorders among garment workers: A cross-sectional study. J Occup Saf Health. 2023;20(4):55-62.
27. Hossain M, Rahman M, Sultana S. Musculoskeletal pain and discomfort among readymade garment workers: An analysis of lower back pain prevalence and risk factors. Occup Med J. 2018;11(2):92-8.
28. Hush JM, Cameron KA, O’Neill S. Sleep disturbances in patients with chronic low back pain. J Pain Res. 2009;2:111-8.
29. Jaiswal R. Musculoskeletal disorders among workers in the textile industry: Prevalence, risk factors and impact. J Occup Med Health. 2021;14(2):63-70.
30. Jaiswal A, Prasad N. Prevalence of musculoskeletal disorders in textile workers: A case study of silk saree workers in Bhadohi, Uttar Pradesh. Int J Occup Health. 2021;19(4):109-15.
31. Lombardo JR. Musculoskeletal disorders among workers in the manufacturing industry: Prevalence and risk factors. Occup Med. 2011;61(5):329-36.
32. Maharjan A, Shrestha P, Thapa S. Musculoskeletal disorders among garment workers in Rupendehi district of Nepal. J Occup Saf Health. 2020;12(3):103-10.
33. Marty MA, Feiner M, Jafari P. Work loss and disability from musculoskeletal disorders in workers. J Occup Health Psychol. 2008;13(3):240-8.
34. Montreuil S, Tellier C. Work-related musculoskeletal disorders in the textile sector: An analysis of the factors involved. Ergonomics. 1996;39(3):347-56.
35. Nag PK, Desai SK, Nag A. Occupational health problems in the textile industry. Indian J Occup Health. 1992;16(2):42-9.
36. Nabi M, Hasan M, Islam T. Musculoskeletal disorders among female workers in non-OSH-compliant garment factories. Int J Occup Saf Health. 2021;15(1):45-50.
37. Ohlsson K, Attewell R, Nordander C. Repetitive work tasks and their association with musculoskeletal injuries among female industrial workers. Scand J Work Environ Health. 1995;21(2):123-9.
38. Pincus T, McCracken LM, DeCosta G. Cognitive-behavioral therapy for chronic pain: The effectiveness of a psychological approach. Br J Pain. 2002;14(1):8-13.
39. Rahman MS, Siddiquee MS. Ergonomics and musculoskeletal disorders in Bangladesh’s garment industry: The influence of work environment and job demands. Occup Med Health. 2018;38(1):24-32.
40. Wood RJ. Musculoskeletal disorders among garment workers in North America: A longitudinal study of injuries and interventions. J Text Appar. 2014;10(3):121-34.
41. Wood RJ. Evaluation of a health program for garment workers in the United States. New School University Health Policy Research Center. 2014.
42. Singh V. Health problems among garment workers: The role of occupational hazards and working conditions. Int J Text Sci. 2009;16(3):205-13.
43. Sudha R, Meenaxi D. Musculoskeletal disorders and working conditions in the garment industry: A study of Indian workers. J Health Saf. 2014;20(2):100-10.
44. Tiwari R, Pathak M, Zodpey SP. A cross-sectional study on the prevalence of low back pain among textile workers. J Occup Health. 2003;45(4):256-62.
45. Tucer MG, Kocyigit H, Sayan S. Depression in patients with chronic low back pain. J Pain Res. 2009;5:89-93.
46. Van Tulder MW, Koes BW. The burden of low back pain. Best Pract Res Clin Rheumatol. 1995;9(4):723-32.
47. Walker BF. The prevalence of low back pain: A systematic review of the literature. J Spinal Disord Tech. 2000;13(3):200-8.
48. Walker BF. Low back pain: A review of the evidence for management. Eur Spine J. 2003;12(2):96-104.