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Musculoskeletal health and mental well-being of occupational two-wheeler delivery drivers from Mumbai metropolitan region
*For correspondence: suparnakhera@hotmail.com
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How to cite this article: Khera S, Lokras S, NP K, Gitte SV. Musculoskeletal health and mental well-being of occupational two-wheeler delivery drivers from Mumbai metropolitan region. Indian J Med Res. 2026;164:153-5. doi: 10.25259/IJMR_3592_2025
Abstract
Considering the surge of urban gig drivers, 111 two-wheeler delivery riders (ages 18–40) in Panvel, MMR were assessed using NMQ and GHQ-12. High (87.3%) prevalence of musculoskeletal disorders primarily in the lower back (68%), significantly correlating with age (P<0.0086) and weight carried (P<0.0001) were observed. Additionally, 42.3% reported psychological distress (GHQ-12≥3), significantly associated with weight carried (P=0.0329), distance travelled (P=0.041), work hours (P=0.006) and the number of body parts affected by musculoskeletal disorders (P=0.0007). In conclusion, this occupational group faces a high risk of early-onset musculoskeletal disorders and long-term disability. Consequently, stakeholders must establish regulatory guidelines for this emerging sector.
Keywords
General Health Questionnaire-12 (GHQ-12)
Gig drivers
Musculoskeletal disorders (MSDs)
Nordic Musculoskeletal Questionnaire (NMQ)
Occupational two-wheeler delivery drivers
Psychological distress
In the dynamic landscape of modern urban consumerism, app-based delivery systems have caused a surge in occupational two-wheeler delivery professionals commonly known as Gig drivers. Their work involves handling heavy loads, repeated bending, twisting, and prolonged driving in static postures, making them vulnerable to musculoskeletal disorders (MSDs).1-4 Additionally, time-pressured deliveries and traffic stress contribute to mental distress affecting quality of life.5 Though there is ample literature available on four-wheeler drivers, limited studies are retrievable on health challenges faced by occupational two-wheeler drivers, especially in the Indian context.1,3,4 Recognising this evidence gap, an exploratory community-based cross-sectional study was conducted in Panvel block of Raigad district on food and ration delivery riders aged 18 to 40 yr from February to August 2023, to estimate the prevalence and profile of musculoskeletal disorders and perceived mental health status with possible contributing factors. A sample size of 111 was determined based on an estimated 50% musculoskeletal disorders prevalence and 9% relative error. The consenting participants with at least six months of experience and three hours of daily work were identified through approaching the only e-commerce hub available and nearby popular outlets frequently visited by occupational two-wheeler drivers.
The data were collected via a semi-structured questionnaire to assess demographic and work-related information and the widely used Nordic Musculoskeletal Questionnaire (NMQ)6 for musculoskeletal health and General Health Questionnaire-12 (GHQ-12)7 for mental health. For the (GHQ-12) caseness scoring method (0-0-1-1) was used to dichotomise the score, resulting in a cutoff of 3 or higher signifying psychological distress. Microsoft Excel 2022 and R Studio 4.3.1. was used for data entry and analysis.
Of the 111 respondents, 109 (98%) were male, with 63 (67%) aged 20–30 yr (Mean age: 29.3±5.4). The mean employment duration was 28.4±18.3 months. Most 95 (85%) worked 10+ hours daily, and 101 (91%) worked at least six days a week. Majority of the respondents, 69 (62.2%), used motorcycles, and 42 (37.8%) used scooters for the delivery of goods. Riders covered a mean daily distance of 160.7±58.5 km, averaging 20–25 trips/day. About 66 (59.5%) carried loads of 5 kg or more per trip. Despite these demands, 91 (82%) expressed job satisfaction.
Musculoskeletal health
In the past 12 months, 97 (87.3%) of respondents reported experiencing musculoskeletal discomfort, with 37 (38.1%) reporting discomfort in the past seven days ( Table). Lower back pain was the most commonly reported site, affecting 76 (68.5%) of respondents, followed by upper back 57 (51.4%), shoulder and wrists/hands pain [38 (34%)]. The pattern of body parts affected was observed to be similar for the last 12 months and the last 7 days ( Table). Full-time workers 84 (76%) and motorcycle riders (57%) were more affected than part-time or scooter riders, suggesting the ergonomic demands of motorcycles requiring greater flexion of the spine and neck causing high prevalence of back pain. Around 79.37% of the respondents who had musculoskeletal disorders in the last 12 months were between the ages of 20 and 30 yr. Age was significantly associated with musculoskeletal disorders (Chi-square test (P value <0.01). Respondents with musculoskeletal disorders were older (Mean: 30.3 yr) than those without (Mean: 22.9 yr) [Odds ratio (OR)=1.51. at 95% Confidence interval (CI) at 95%, P<0.001]. Furthermore, as age increased, the number of affected body regions also increased (Spearmen correlation P=0.013 at 95% CI 95%). While chronic (12-month) pain increased significantly with age from the 20-30 yr age group to the 31-40 yr age group, from 79.3 to 97.92%, acute (7-day) pain was identical across both age groups at 33%. This indicates that while older workers face higher rates of chronic issues, acute discomfort affects all riders equally, regardless of age.
| Regions | Had trouble, discomfort, numbness in last 12 months, n (%) | During the last 12 months have you been prevented from carrying out normal activities (e.g. job, housework, hobbies) because of this trouble, n (%) | During the last 12 months have you seen a physician for this condition, n (%) | Had trouble, discomfort, numbness in last 7 days, n (%) | ||||
|---|---|---|---|---|---|---|---|---|
| Yes | No | Yes | No | Yes | No | Yes | No | |
| Neck | 31 (28) | 80 (72) | 0 (0) | 31 (28) | 2 (2) | 29 (26) | 6 (5) | 25 (22) |
| Shoulder | 38 (34) | 73 (65) | 10 (9) | 28 (25) | 4 (4) | 34 (31) | 13 (12) | 25 (22) |
| Upper back | 57 (51) | 54 (49) | 14 (13) | 43 (39) | 9 (8) | 48 (15) | 19 (17) | 38 (15) |
| Elbow | 12 (11) | 99 (89) | 2 (2) | 10 (9) | 0 (0) | 12 (11) | 4 (4) | 8 (7) |
| Wrist/hands | 38 (34) | 73 (66) | 11 (10) | 27 (24) | 2 (2) | 36 (32) | 9 (8) | 29 (26) |
| Lower back | 76 (68) | 35 (31) | 26 (23) | 50 (45) | 13 (12) | 63 (57) | 30 (28) | 46 (41) |
| Hips/thighs | 30 (27) | 81 (73) | 9 (8) | 21 (19) | 4 (4) | 26 (23) | 10 (9) | 20 (18) |
| Knees | 19 (17) | 92 (83) | 4 (4) | 15 (13) | 2 (2) | 17 (15) | 6 (5) | 13 (12) |
| Ankles/feet | 32 (29) | 79 (71) | 6 (5.4) | 26 (23) | 2 (2) | 30 (27) | 9 (8) | 23 (21) |
MSD, musculoskeletal disorder
A moderate positive association was found between the weight carried and the number of affected body regions affected by musculoskeletal disorders (Kendall Tb=0.3249 P< 0.0001).
The prevalence (87.3%) of musculoskeletal disorders in our study was comparable to findings by Afridi et al,8 unlike Li et al9 (54.9%). Lower back pain was the most common site affected in our study, consistent with findings by Binoosh1 and Mukerjee et al.4 The association between age and musculoskeletal disorders in our study was similar to findings by Bovenzi et al.10
A total of 47 (42.3%) of the respondents obtained a GHQ-12 score of 3 or above, indicating psychological distress. The mean score of GHQ-12 was 2.44, and the median was 1, exhibiting a skewness where a large minority (25%) of respondents reported high levels of distress (total GHQ-12 score of 4 or higher), undermining the vulnerable subgroup experiencing significant distress. Among those identified as experiencing psychological distress, 32 (68%) drove scooters, 43 (91%) worked six to seven days a week, 29 (61%) > 20 trips per day, 42 (88%) worked more than 10 h per day, and 22 (46%) travelled more than 160 km daily with 22 (32%) carrying loads of more than 10 kg per trip. Contrary to the musculoskeletal disorders, psychological distress showed significant positive correlation with distance travelled (P = 0.0413 (tb= 0.1488) and daily hours of work (Tb = 0.2009, P= 0.0060) and average weight carried (Kendall’s Tau-b Tb=0.3249 P< 0.0001) consistent with findings by Useche et al11 and Kieling et al.12 Prolonged waits in traffic, pressure of multiple and timely deliveries, irritant clients, uncertainty about job continuity may be contributing to psychological stress.
While the mere presence of musculoskeletal disorders did not cause psychological distress in itself, the extent of the musculoskeletal problems, as determined by the number of anatomical regions affected, was significantly associated with the mental wellbeing of respondents. (Kendall tau Tb=0.2500; P=0.0007) as also observed by a systematic review by Rezaei et al.13 Chronic pain often triggers anxiety and sleep disturbances, which further exacerbates musculoskeletal disorders.11-13
In conclusion, the growing workforce of occupational two-wheeler drivers faces a heightened risk of developing musculoskeletal disorders and significant psychological morbidity at a young age, warranting an in-depth study to understand their occupational health needs. Policymakers need to timely formulate regulatory work guidelines, develop preplacement and periodic screening mechanisms, ensure employers support, and bring them under the ambit of organised services to provide healthful work environments and mitigate future disease burdens.
Acknowledgement
The authors acknowledge Dr. Suchitra Surve, MPH student for her valuable technical suggestions.
Author contributions
SK: Study conceptualisation and design, detailed data analysis and interpretation, manuscript writing; SL: Acquisition of data, preliminary data analysis; KNP: Study design, citations; SVG: Study design, manuscript writing. All authors have read and approved the final printed version of the manuscript.
Financial support and sponsorship
None.
Conflicts of Interest
None.
Use of Artificial Intelligence (AI)-Assisted Technology for manuscript preparation
The authors confirm that there was no use of AI-assisted technology for assisting in the writing of the manuscript and no images were manipulated using AI.
References
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