Musculoskeletal disorders among insurance office employees: A case study

Abstract

BACKGROUND:

Insurance employees in India are overworked, and their jobs demand prolonged sitting hours in the office; this can lead to musculoskeletal disorders through consistent stress on the musculoskeletal system. The present study includes implications for the reduction of work-related musculoskeletal disorders to minimise sick leaves and medical expenses.

OBJECTIVE:

This study aimed to determine the prevalence of musculoskeletal disorder-related issues among employees working in insurance offices and to analyse the association of pain symptoms with risk factors including demographic, occupational and psychosocial factors.

METHODS:

The study included 400 employees from different insurance offices. Data were collected using a questionnaire about pain, a flexibility test (sit-and-reach test) and a video-based analysis of working postures using the Rapid Upper Limb Assessment (RULA) method.

RESULTS:

The prevalence of work-related musculoskeletal symptoms was the highest in the neck (57.2%), shoulders (38.5%), upper back (28.5%) and lower back (46.2%).

CONCLUSIONS:

A high persistence of musculoskeletal symptoms was observed in the neck, lower back, upper back and shoulders; the presence of these symptoms was strongly associated with predominant factors: assumed awkward posture, body mass index, job demand, RULA score and infrequent rest breaks. Additional research is required for testing the effect of interventions involving stretching exercises and/or installation of ergonomic workstations.

Keywords

BMI occupational factors psychosocial work factors RULA

1 Introduction

Musculoskeletal disorders (MSDs) are considered to be a major health issue and one of the most common and expensive work-related issues arising among a range of occupations worldwide [1, 2]. Extensive research has been conducted on MSDs in various professions such as office workers, bus drivers, nurses, cleaners and sewing machine operators [3 –7]. Musculoskeletal symptoms are common among office workers, and there has been a drastic increase in the duration of work, including computer work, in the modern occupational setting [8]. Working in an office environment is widely accepted to be associated with the occurrence of musculoskeletal disorders that occur especially in the neck, upper extremity and lower back [9 –11]. In terms of individual effects, MSDs in office employees can lead to limited ability and efficiency, lowered self-esteem, weak group communication, absenteeism, lowered productivity, poor quality of work and, consequently, loss of job [12 –16]. To improve employee health and reduce sick leaves, physical and mental health in the workplace requires attention [17, 18].

Researchers have examined the relationship between occupational factors and MSDs [19]. Insurance companies have been utilising computers in the workplace for some time owing to its various advantages including an increase in productivity. Previous studies have reported a strong association of working at computer terminals using keyboards with the occurrence of a range of MSDs, which affect the back, neck and upper extremities. Various activities performed by office employees include not only documentation and computer work but also physical activities such as twisting, bending, reaching, carrying and climbing stairs. The main risk factors for the development of MSDs are activities involving repetitive movements, physical effort and/or awkward postures [20 –22]. Other identified risk factors responsible for musculoskeletal pain symptoms include long working hours, poor office ergonomics, static postures and repetitive work [23, 24]. Specifically, awkward sitting postures lead to an increase in intra-disc pressure [25, 26]. Issues of discomfort associated with sitting at work for long periods of time are associated with bad postural habits [27]. These issues are collectively responsible for back and shoulder pain that cause discomfort, subsequently leading to difficulties in concentrating on and performing work [28]. Consequently, MSDs can lead to a severe decline in work performance [3], which can have serious organisational implications. Although previous studies have investigated occupational stress among insurance office employees [29, 30], only a few have examined MSDs in allied fields [15 , 31]. However, the insurance office employees may be more prone to MSDs due to prolonged sitting hours along with incorrect posture. The posture related assessment among insurance office employees is found unexplored as far as the literature reviewed. Therefore, the present study attempted to analyze the work postures among Indian insurance office employees by using Rapid Upper Limb Assessment (RULA). The prevalence of MSDs is investigated with respect to the various associated factors i.e. demographic, occupational and psychosocial factors.

2 Methods

This study was conducted among office employees of different insurance companies located in Punjab (India). A random sample was taken from employees (men and women) who were interested in participating in this study. We visited insurance companies, and questionnaires were completed via interviews with the employees. We sampled office employees who usually sit and work, primarily with a computer, telephone, calculator, and paper.

2.1 Study population

The sample selection has been carried out on the basis of recommended maximum sample size (n = 400) at±5% precision [32]. The study population consisted of 400 office workers from different insurance companies in Punjab and primarily consisted of adults aged >25 years. Participants were mainly managers (sales and operations), customer care workers, accountants, telephone operators, computer experts and development officers. Because the questionnaire enquired regarding incidents in the past year, only workers who had completed at least one year in their current positions were eligible for inclusion in the study. All participants signed a consent form to participate in the study which has been approved by the Ethics Committee of Research (ECR) at Dr B R Ambedkar national Institute of Technology, Jalandhar [Ref. no. NITJ/IP/ECR/232].

2.2 Study design and data collection

This study employed a self-administered questionnaire that asked questions about the participants’ demographic characteristics, physical, occupational and psychosocial risk factors, general health status, physical flexibility and existence of MSDs using Cornell’s University musculoskeletal disorder questionnaire. The questionnaire also included a video-based analysis of working postures using the Rapid Upper Limb Assessment (RULA) method. Data collection included recording videos of the actual work and postures adopted by employees. The flexibility of the lower back and hamstring muscles was assessed using the score on the sit-and-reach test [33] using a sit-and-reach box.

Demographic information collected included gender, age, marital status, family members and average monthly income. Body mass index (BMI) of each participant was calculated on the basis of actual measurement of height (m) and weight (kg) using a stadiometer and a weighing machine, respectively.

Occupational physical factors included the length of service (1–5, 6–10, 11–15 and >15 years) and prolonged sitting. Participants were asked about the frequency of rest breaks at work (once every <2 h, once every 2–4 h or once every >4 h). Information regarding commuting time (number of hours per day the participant spent travelling to/from work) was also collected.

Psychosocial factors were assessed via the Health and Safety Executive Standards Management indicator tool (HSE, 2004), which included job demand, job control, supervisor support, colleague support, and relationship with colleagues, role in organisation and changes at work. In addition, two psychosocial factors - wages and workplace layout/environment were also investigated because these are not covered by the HSE tool.

Finally, MSDs were measured using a Cornell University work related musculoskeletal disorder questionnaire (CMDQ). Respondents were asked to report the musculoskeletal symptoms experienced in the previous year and to specify whether this pain was partly or solely work-related.

2.2.1 RULA

To evaluate physical exposure to work-related musculoskeletal risk, RULA was applied. RULA is a universal and most referred tool for the work posture analysis for individuals using workstations for their job. It enables to investigate the risk level of upper limb disorder [34]. In this study, all participants had identical muscle and force scores because their daily office tasks required negligible resistance.

Ergo Master software was used to calculate the participant’s RULA scores by incorporating pictures or images of the job task being analysed or redesigned. Details, including angular positions from the captured image for the upper and lower arms, wrists, wrist twist, neck, trunk, and legs were entered into the Ergo Master Wizard. In addition, muscle and force scores were used to calculate a grand body posture score (RULA score). Similarly, all scores were calculated to produce a final grand score (RULA score).

2.3 Statistical analysis

Backward stepwise linear regression was performed to test the significance of demographic, occupational and psychosocial factors on MSDs in different body regions; a significance level of p < 0.05 was used. Odds ratios (OR) with 95% confidence intervals were calculated as a measure of association. Data analysis was conducted using the SPSS for Windows version 17.0 statistical package.

3 Results

The findings of this study revealed that MSDs were highly prevalent in the study population. Table 1 shows the demographic factors of the participants. Almost one-third of participants (34.1%) were >45 years old, and majority participants were above normal BMI out of which 55% were overweight (25<BMI<30) and 8.8% obese (BMI >30). Table 2 shows participant distribution according to occupational factors such as the number of working hours per day, rest break frequency and daily commuting hours. The RULA score was calculated using Ergo master software for a sample of 90 employees who had a high discomfort score. The overall average RULA score of the selected sample was found to be 4.09, which indicated an intermediate level of risk; therefore, further investigation is needed and changes may be required in terms of ergonomic interventions.

Table 1
Distribution of the subjects in different categories according to explanatory variables (n = 400)

Demographic Factors N %

Age

<30 years 79 19.8

31–35 years 105 26.4

36–40 years 40 9.9

41–45 years 40 9.9

>45 years 136 34.1

Company-

Public 242 60.4

Private 158 39.6

Gender-

Male 343 85.7

Female 57 14.3

Marital Status-

Married 347 86.8

Unmarried 48 12.1

Others 4 1.1

BMI-

Underweight (<18.5 kg/m²) 31 7.8

Normal (18.5–25 kg/m²) 114 28.5

Overweight (25.1–30 kg/m²) 220 55.0

Obese (>30 kg/m²) 35 8.8

Demographic Factors	N	%
Age
<30 years	79	19.8
31–35 years	105	26.4
36–40 years	40	9.9
41–45 years	40	9.9
>45 years	136	34.1
Company-
Public	242	60.4
Private	158	39.6
Gender-
Male	343	85.7
Female	57	14.3
Marital Status-
Married	347	86.8
Unmarried	48	12.1
Others	4	1.1
BMI-
Underweight (<18.5 kg/m²)	31	7.8
Normal (18.5–25 kg/m²)	114	28.5
Overweight (25.1–30 kg/m²)	220	55.0
Obese (>30 kg/m²)	35	8.8

Table 2

Distribution of the subjects in different categories according to occupational factors (n = 400)

Occupational Factors	N	%
Length of service
1–5 years	84	20.9
6–10 years	132	33.0
11–15 years	35	8.8
>15 years	149	37.4
Frequency of rest break
Once in 2 h	141	35.2
Once in 2–4 h	114	28.6
Once in 4–6 h	141	35.2
Once in >6 h	4	1.1
Environment of work place:
AC	365	91.2
Non-AC	35	8.8
Nature of job-
Office operations	334	83.5
Marketing operations	66	16.5
Monthly income level (Rs)
Up to 25000	114	28.6
25000–50000	149	37.4
50000–100000	132	33.0
>100000	4	1.1
Daily travelling hours
<1 h	229	57.1
1–2 h	110	27.5
3–4 h	48	12.1
>4 h	13	3.3

As shown in Table 3, MSDs were the most prevalent in the neck (57.2%) and lower back (46.2%). Other affected regions were the shoulders (38.5%) and upper back (28.5%). Table 4 shows the association of various individual, demographic, occupational and psychosocial factors with self-reported neck, shoulder, upper back and lower back pain. The following risk factors were significantly associated with reported neck pain: BMI, length of service (6–10 and >15 years), rest frequency (once every 4–6 h), daily commuting (>1, 1–2 and 3–4 h), assumed awkward posture, physical flexibility, RULA score and job demand. The following risk factors were significantly associated with reported shoulder pain: assumed awkward posture, physical flexibility, supervisor support, relationship with colleagues and wages.

Table 3

Prevalence of MSD in different body regions of insurance office employees (n = 400)

Body Region	N	%
Neck	229	57.25
Shoulder	154	38.5
Upper back	114	28.5
Upper arm	26	6.5
Lower back	185	46.25
Forearm	31	7.75
Wrist	53	13.25
Butt	4	1
Thigh	35	8.75
Knee	75	18.75
Lower leg	110	27.5

Table 4

Statistical association of risk factors with self-reported neck, shoulder, upper back and lower back pain

Parameters	Neck				Shoulder				Upper Back				Lower back
	p-value	O.R	Lower	Upper	p-value	O.R	Lower	Upper	p-value	O.R	Lower	Upper	p-value	O.R	Lower	Upper
Age
<30 years	0.539	0.246	0.0254	4.521	0.543	0.342	0.0219	5.164	0.422	0.357	0.045	2.946	0.136	0.528	0.021	1.816
31–35 years	0.381	0.430	0.065	2.839	0.572	0.608	0.108	3.426	0.413	0.468	0.076	2.888	0.016^*	0.033	0.002	.531
36–40 years	0.946	0.918	0.077	11.003	0.468	0.438	0.047	4.068	0.067^*	0.069	0.004	1.210	0.061	0.048	0.002	1.157
41–45 years	0.375	0.346	0.033	3.617	0.502	0.463	0.049	4.380	0.328	0.298	0.026	3.371	0.013^*	0.014	0.000	.404
>45 years	0.202	0.237	0.026	2.166	0.124	0.179	0.020	1.605	0.127	0.152	0.014	1.708	0.029^*	0.027	0.001	.694
Gender (Male)	0.613	0.710	0.188	2.677	0.361	1.885	0.483	7.353	0.783	1.259	0.244	6.483	0.975	0.974	0.192	4.934
Marital status	0.759	0.720	0.088	5.877	0.730	0.689	0.083	5.736	0.535	0.461	0.040	5.311	0.469	0.353	0.021	5.913
Children	0.859	1.079	0.468	2.488	0.626	1.241	0.521	2.957	0.795	1.139	0.427	3.038	0.461	1.514	0.502	4.567
BMI	0.027^*	1.153	1.016	1.310	0.060	1.142	0.995	1.310	0.009^*	1.275	1.064	1.529	0.000^*	1.542	1.238	1.922
Length of service
1–5 years	0.582	0.546	0.0287	26.548	0.131	2.253	0.134	14.352	0.466	0.939	0.024	3.421	0.078	0.046	0.0246	0.854
6–10 years	0.036^*	36.094	1.795	725.845	0.146	4.183	0.607	28.822	0.469	0.474	0.063	3.568	0.011^*	0.076	0.011	.552
11–15 years	0.772	1.541	0.083	28.702	0.999	0.000	0.000	–	0.321	0.249	0.016	3.890	0.044^*	0.064	0.004	.930
>15 years	0.019^*	2.291	0.120	43.722	0.646	0.540	0.039	7.464	0.024^*	0.100	0.005	1.883	0.081^*	0.107	0.009	1.322
Rest break frequency
once in 2 h	0.460	0.652	0.0239	3.219	0.252	4.548	3.146	16.246	0.978	0.591	0.128	4.294	0.477	1.361	0.0627	5.297
once in 2–4 h	0.119	4.694	0.671	32.812	0.070	0.196	0.033	1.145	0.893	0.886	0.153	5.123	0.265	0.410	0.086	1.964
once in 4–6 h	0.028^*	2.680	0.456	15.749	0.075	0.216	0.040	1.166	0.028^*	0.688	0.120	3.954	0.039^*	1.372	0.294	6.396
Environment of workplace (AC)	0.533	3.177	0.084	119.850	0.421	2.348	0.293	18.804	0.563	2.031	0.184	22.433	0.248	0.215	0.016	2.918
Nature of job (Office operations)	0.878	1.175	0.149	9.256	0.652	1.483	0.268	8.205	0.787	0.766	0.110	5.331	0.310	0.390	0.063	2.406
Income
<Rs 25000/month	0.607	0.526	0.428	5.217	0.927	0.001	0.000	–	0.463	0.534	0.021	3.104	0.191	1.376	0.861	3.247
Rs 25000–50000	0.284	0.256	0.021	3.094	0.498	0.489	0.062	3.862	0.109	4.962	0.700	35.156	0.031^*	7.620	1.202	48.316
50000–100000	0.743	0.631	0.040	9.922	0.595	0.538	0.055	5.290	0.255	3.717	0.388	35.634	0.089	6.627	0.750	58.518
>100000	1.000	0.000	0.000	–	1.000	0.000	0.000	–	1.000	0.000	0.000	–	1.000	0.000	0.000	–
Daily travelling hours
>1 h	0.024^*	4.259	2.187	15.246	0.623	3.573	0.437	6.346	0.630	3.243	1.021	5.628	0.299	4.627	0.681	9.376
1–2 h	0.007^*	11.537	1.951	68.237	0.405	1.911	0.416	8.782	0.279	0.430	0.093	1.981	0.526	1.594	0.377	6.737
3–4 h	0.019^*	26.191	1.728	396.929	0.492	2.039	0.268	15.544	0.373	0.348	0.034	3.551	0.046^*	11.040	0.933	130.644
>4 h	0.620	4.077	0.016	1045.846	0.313	12.873	0.090	1833.377	0.999	0.000	0.000	–	0.617	2.291	0.089	58.976
Mean assumed posture	0.000^*	109.838	10.151	1188.472	0.000^*	22.615	4.240	120.636	0.001^*	27.417	4.123	182.337	0.000^*	37.717	5.362	265.305
Mean workplace layout	0.516	1.880	0.280	12.627	0.756	0.776	0.156	3.845	0.582	0.605	0.101	3.619	0.481	0.535	0.094	3.045
flexibility	0.003^*	0.883	0.813	.959	0.005^*	0.888	0.818	0.964	0.201	0.949	0.877	1.028	0.000^*	0.836	0.766	.912
RULA score	0.049^*	0.690	0.466	1.021	0.179	0.771	0.528	1.127	0.031^*	0.977	0.661	1.444	0.044^*	0.885	0.596	1.314
Job demand	0.048^*	3.248	0.876	12.043	0.988	1.009	0.298	3.421	0.036^*	1.949	0.468	8.116	0.037^*	0.782	0.208	2.941
Job control	0.205	0.310	0.051	1.892	0.737	0.733	0.120	4.467	0.459	0.505	0.083	3.083	0.477	1.839	0.343	9.853
Supervisor support	0.241	0.573	0.226	1.454	0.015^*	0.292	0.108	0.788	0.205	0.540	0.208	1.400	0.158	2.032	0.759	5.443
Colleague support	0.116	0.414	0.138	1.244	0.909	0.938	0.313	2.815	0.606	0.731	0.223	2.402	0.920	1.058	0.349	3.206
Relationship with colleague	0.083	2.441	0.891	6.686	0.033^*	3.187	1.099	9.243	0.360	1.634	0.570	4.683	0.872	0.921	0.340	2.494
Role in organisation	0.097	0.269	0.057	1.271	0.220	0.370	0.076	1.812	0.106	0.237	0.041	1.359	0.110	0.268	0.054	1.344
Changes at work	0.113	4.104	0.716	23.533	0.180	3.438	0.565	20.930	0.432	1.993	0.357	11.114	0.675	0.705	0.137	3.623
Wages	0.970	1.010	0.610	1.670	0.008^*	0.467	0.267	0.818	0.212	0.695	0.392	1.230	0.167	0.685	0.401	1.171
Work environments	0.107	2.906	0.795	10.620	0.285	2.018	0.558	–	0.026^*	0.210	0.053	0.830	0.083	0.333	0.096	1.153

^*Level of significance at ‘p’ <0.05; The bold fonts under the parameter column refers to the sub categories.

The association of various individual, demographic, occupational and psychosocial factors with self-reported upper back pain are shown in Table 4. The following risk factors were significantly associated with reported upper back pain: age (31–35 and >41 years), BMI, length of service (>15 years), rest frequency (once every 4–6 h), assumed awkward posture, RULA score, job demand and work environment. Finally, the following risk factors were significantly associated with reported lower back pain: age (31–35 and >41 years), BMI, length of service (6–15 years), rest frequency (once every 4–6 h), low income (Rs 25,000–50,000), daily commuting (3–4 h), assumed awkward posture, physical flexibility, RULA score and job demand.

4 Discussion

The MSD symptoms were found highest in neck followed by lower back, shoulders and upper back body region among the surveyed employees of insurance companies. However, Habib et al. [35] investigated the MSDs among paper office workers and reported lower back pain as the most prevalent followed by neck pain. The existence of high level of neck pain in the present study may have been due to long hours spent working on the computer or completing other office work, which takes its toll on the neck over time, and length of service.

Likewise, high job demand and long working hours increase sitting time in the office, reducing the physical movement of office employees, leading to increased BMI and reduced physical flexibility. The increase in length of service (>15 years) and less frequent rest breaks (once every 4–6 h) were strongly associated with neck pain because both effects the neck due to increased working time. Continuous work without rest breaks also affects an employee’s posture, which in turn affects neck posture [36]. The acquired posture reported by respondents was incorrect and was strongly associated (OR = 27.4) with neck pain. This is logical because the neck tends to assume an inclined position when one engages in long periods of office work. Daily commuting also had an effect on the musculoskeletal pain that was significantly associated with daily commuting for >1 h, as found in this study.

The high occurrence of shoulder pain is also related to the awkward posture assumed due to the high desks used in the workplace. Physical factors, such as acquired posture and flexibility and psychosocial factors such as supervisor support, relationship with colleagues and wages lead to job stress and were significantly associated with reported shoulder pain in the study findings, which is in accordance with a previous study [37] where workers who reported high job stress were more likely to develop shoulder symptoms.

The high prevalence of upper back problems could be attributed to the prolonged awkward posture of this region and less frequent use of backrests during working hours. Posture and RULA scores were strongly associated with upper back problems, which may be explained by the fact that with a long length of service (>15 years) and high job demand, back pain occurs due to overwork and incorrect back posture [38].

Numerous studies have reported a significant relationship between MSDs and individual risk factors such as BMI [39, 40]. The current study also found a significant and strong association of BMI and physical flexibility with lower back pain. Moreover, Shariat et al. [31] reported similar findings related to the association between BMI and lower back pain among Malaysian office workers. This may be due to high occupational workload, which leads to excessive sitting duration that restricts body movement and flexibility, which in turn leads to increased BMI, contributing to incorrect body posture that affects the lower back. In support of this, an earlier study [41] also reported a significant correlation between high BMI and lower back pain; this was due to lower flexibility, especially the poor movement of the lower body. Daily commuting for 3–4 h was also significantly associated with neck and lower back pain.

Neck pain was strongly and significantly associated with the length of service (6–10 and >15 years). Similarly, lower back pain was significantly associated with length of service (6–10 and 11–15 years). There was a significant association between longer length of service (>15 years) and lower back pain (p = 0.081). These results may be due to several factors; for instance, older office employees who developed lower back pain may have changed professions due to their pain, and those who remained in the profession may have been those who never experienced lower back pain or experienced it at one point but have since recovered and learnt to prevent pain from occurring [42].

BMI assumed awkward posture and rest break frequency of once every >4 h are the factors that contributed most to MSDs, affecting the neck, upper back, shoulders and lower back. Additionally, RULA score was high for the majority of participants and was associated with neck, upper back, and lower back pain. These results revealed that there was a significant linear association between RULA risk level and measure of reported symptoms in the lower back; this finding corresponds with that of previous studies [43, 44].

High job demand and longer length of service (6–15 years) were also associated with lower back pain, which likely results from continuous sitting in an incorrect posture with less frequent rest periods (once in every 4–6 h). IJmker [45] confirmed the incidence of work-related MSDs in different body parts among office workers due to long duration of computer exposure. Similarly, people with low income and high job demand tend to develop more stress, which is associated with back pain [34]. In addition, Cho et al. [46] conducted a similar study on Taiwan office workers and reported a significant association between high job demand and lower back pain. Finally, uncomfortable daily commute of >3 h is associated with lower back pain.

It is also important to note that our study was a questionnaire-based self-reported survey, and the occurrence of work-related MSDs among employees working in different positions with the same level of hazards may be very different due to their different attitudes and perceptions.

Overall, the results of this study revealed a high prevalence of MSDs, especially in the neck and lower back, among insurance office employees. Various risk factors were recognised, some of which showed statistically significant associations with pain at all four major body regions analysed. The occurrence of neck pain observed in the previous year, as reported in this study, was much higher than that reported by office workers in U.K (26%) [47] and somewhat higher than that in a sample of office workers in New Zealand (51%) [48]. In contrast, the prevalence rates of lower back and shoulder pain reported herein were closer to those reported in the studies of New Zealand and UK. The neck was the most common region of pain, which is in accordance with several other studies conducted among office workers [3 , 23].

The results obtained in the present study indicate that 43% of office employees surveyed were at high and very high (action levels 3 and 4 of RULA) [34] risk levels according to the risk assessment of work-related MSDs (assessed via RULA). In other words, the tasks performed and working conditions in the insurance office environment were conducive to the development of work-related MSDs. Ergonomic interventions are, therefore, necessary for improving working conditions and decreasing the likelihood of developing MSDs. From this viewpoint, uncomfortable postures can be alleviated with stretching exercises and ergonomic workstation design.

4.1 Limitations of study

In the present study, there are some limitations. The scope of this study is limited to Punjab region only; therefore, generalizability of the results may not be applicable across the country. The insurance companies did not provide any data related to the employees who may have left their jobs or remained absent due to MSDs complaints; therefore, the study provided instantaneous observation rather than past data. Moreover, the work-related musculoskeletal disorder questionnaire merely evaluated the MSD risk factors rather than a diagnosis.

5 Conclusion

A high persistence of musculoskeletal symptoms was reported in the neck, shoulders, upper and lower back of insurance office employees. The results suggested that the musculoskeletal symptoms in these four regions are strongly associated with awkward posture. BMI, job demand, RULA score and rest break frequency of once every 4–6 h were associated with neck, upper back, and lower back pain. Reduced flexibility was associated with neck, shoulder and lower back pain, and a daily commuting time of 3–4 h was associated with neck and lower back pain. The study recommends conducting some regular awareness programmes to educate the employees regarding the ergonomic aspects of working in office workstations.

Conflict of interest

None to report.

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