Prevalance Of Work Related Low Back Pain Among The Information Technology Professionals In India – A Cross Sectional Study

Abstract

Objective: To study the prevalence of Work Related Low Back Pain (WRLBP) as one of the major Work-related Musculoskeletal Disorders (WMSD‘s) amongst the Information Technology (IT) Professionals in India. Study Design: As it was intended to study the factors that cause the low back pain in IT establishments, Cross sectional study design was adopted. Materials and Methods: IT Professionals (N=400) working at two IT companies located in Coimbatore city of India were used for initial screening of this study. Cornell Musculoskeletal Discomfort Questionnaire was administered to capture the factors pertaining to the occurrence of Low Back Pain (LBP). Univariate Exploratory Analysis was employed to study the factors among the employees reported with Low Back Pain. Simple percentages and Means were employed to study the factors. The means between the groups with and without Back Pain were tested using Independent t- test. Results: It was inferred that 54% (N=162) male employees and 42% (N=98) female employees have reported LBP. Having considered all the subjects participated in the study, the percentage of employees with Low Back Pain is 51%. Conclusion: The study thus concludes that the Low Back Pain is the major Work Related Musculoskeletal Disorder among the IT Professionals studied. When demographic factors were analyzed, the study suggests life style changes along with therapeutic intervention. Hence appropriate prevention and intervention strategies should be employed to create a healthier working scenario and thereby improve productivity.

Full text

INTERNATIONAL JOURNAL OF SCIENTIFIC & TECHNOLOGY RESEARCH VOLUME 2, ISSUE 7, JULY 2013 ISSN 2277-8616
80
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Prevalance Of Work Related Low Back Pain
Among The Information Technology Professionals
In India – A Cross Sectional Study
P Shahul Hameed
ABSTRACT: Objective: To study the prevalence of Work Related Low Back Pain (WRLBP) as one of the major Work-related Musculoskeletal Disorders
(WMSD‘s) amongst the Information Technology (IT) Professionals in India. Study Design: As it was intended to study the factors that cause the low back
pain in IT establishments, Cross sectional study design was adopted. Materials and Methods: IT Professionals (N=400) working at two IT companies
located in Coimbatore city of India were used for initial screening of this study. Cornell Musculoskeletal Discomfort Questionnaire was administered to
capture the factors pertaining to the occurrence of Low Back Pain (LBP). Univariate Exploratory Analysis was employed to study the factors among the
employees reported with Low Back Pain. Simple percentages and Means were employed to study the factors. The means between the groups with and
without Back Pain were tested using Independent t- test. Results: It was inferred that 54% (N=162) male employees and 42% (N=98) female employees
have reported LBP. Having considered all the subjects participated in the study, the percentage of employees with Low Back Pain is 51%. Conclusion:
The study thus concludes that the Low Back Pain is the major Work Related Musculoskeletal Disorder among the IT Professionals studied. When
demographic factors were analyzed, the study suggests life style changes along with therapeutic intervention. Hence appropriate prevention and
intervention strategies should be employed to create a healthier working scenario and thereby improve productivity.
Keywords: Work-related Musculoskeletal Disorders (WMSD‘s), Low Back Pain in Information Technology Professionals, India; Posture and Back Pain.
————————————————————
INTRODUCTION
The prevalence of Work-related Musculoskeletal Disorders
(WMSD‘s) is increasing among Computer users throughout
the world (Luis et al., 2003; Arun Vijay., 2013). The
Information Technology (IT) Industry boom in India, since
the last two decades, has led to an increased use of
Computer Devices and peripherals. Approximately 76% of
Computer professionals from India reported
musculoskeletal discomfort in various epidemiological
studies (Talwar R et al., 2009; Bhanderi D et al., 2007;
Sharma A et al., 2006 & Bakhtia CS et al., 2003). There are
several risk factors associated with the development of
work related Musculoskeletal Disorders among the workers
who use Computer extensively at their workplace. All the
risk factors can be divided into two major categories (World
Health Organization, 1985). One is occupational and other
in non–occupational/personal. Among the occupational
factors, repetition, force, awkward/static postures, duration
of exposure and vibration are identified as major risk
factors. As the IT Professionals are exposed to such
different risk factors and therefore it is expected that they
are prone to develop Work related Musculoskeletal
Discomfort (Wahlstrom J 2005). Hence, the workers
involved in the IT profession will have high prevalence of
Work-related Musculoskeletal Disorders and that may be
associated with work style as one of the risk factors in the
development of musculoskeletal discomfort (DeepakSharan
et al., 2011). The aim of this study is to identify Work
related risk factors that may be associated with the onset or
exacerbation of WMSD‘s in Indian IT Professionals.
Epidemiological studies report that the lifetime incidence of
Low Back Pain (LBP) in Industrial workers to be
approximately 60% (Sevensson and Anderson, 1983; Lee
et al, 2001).
Among the occupations which are prone to Musculoskeletal
Disorders, Video Display Terminal workers are prominent.
Video Display Terminal workers are particularly susceptible
to the development of musculoskeletal symptoms, with
prevalence as high as 50% (Gerr and Marcus, 2001).
Various factors contribute to Back Pain in Information
TechnologyProfessionals and these factors include
Individual risk factors, Work-related physical risk factors
such as poor posture, Work related psycho-social factors
and Occupational risk factors. The identification of
appropriate risk factors is of vital importance in preventing
the recurrence of this health issue. Among the various
types of industry workers, the working environment of IT
Professionals is unique. A number of studies have
suggested that prolonged sitting could be a risk factor for
the development of Low-Back Pain (Corlett, 2006; pope et
al., 2002). Thus the study of discomfort in relation to
prolonged sitting may reveal important aspects of the
transition between discomfort and pain. Discomfort is
considered to be related with sitting postural changes
(Fenety and walker, 2002; Vergara and page, 2002; Liao
and Drury, 2000) and it had been reported a positive
relationship between discomfort and the frequency of
postural changes during computer work. The presence and
severity of Low Back Pain is associated with several socio-
demographic factors. Among them, sex, age, education
level, smoking and occupation are more prominent.
Andersson et al., (1998) found that smokers were more
likely to suffer from Musculoskeletal injuries than people
who never smoke. Pain, specifically in the Lower Back had
been increasing depending on the daily cigarette
consumption. Obesity has also been found to be a cause of
back pain (Peltonen et al., 2003). Physical Inactivity, Inferior
fitness and nutrition levels are common characteristics of
smokers and obese individuals. Stress, Pain behavior,
Depressive mood, cognitive functioning are the
Psychosocial risk factors at work. Perceived high pressure
on time and workload, low job control, job dissatisfaction,
monotonous work, and low support from coworkers and
management appear to independently increase the risk of
____________________
P Shahul Hameed, Thanthai Rover College of
Physiotherapy, Perambalur-621212, Tamilnadu, India.
shahul.pt@gmail.com

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hospitalization of back disorders with a low-control job
compared with a high-control job. Occupational risk factors
and low back pain are hampered by the difficulties of
measuring specific exposures. The two major occupational
risk factors for Low Back pain symptoms are static muscle
load (Bernard, 1997; Hedman and Fernie, 1997) and flexed
curvature of the lumbar spine, both of which are involved in
seated work tasks (Wilder et al., 1988; Chaffin and
Andersson, 1990; Bernard, 1997). In this article, the term
Work related Low Back Pain was narrowed down to the
symptoms such as ache, pain, and discomfort in the Low
Back region which arise mainly due to Work activities. The
term ‗IT professional‘ is applied to those who belong to the
software development and programming personnel only.
Thus, the objective is to study the prevalence of Work
Related Low Back Pain as one of the major Work-related
Musculoskeletal Disorders among the Information
Technology professionals in India.
METHODS
STUDY DESIGN
As it was intended to study the factors that cause the Low
Back Pain in IT establishments, Cross sectional study
design was adopted.
SUBJECTS
The total number of Software Professionals (N=400)
working in two different Multinational Information
Technology companies in Coimbatore, Tamilnadu were
formed the population of this study. Out of which only those
who reported to have low back pain as indicated in the
Cornell musculoskeletal discomfort questionnaire was
selected for analyzing the risk factors contributing to its
occurrence. Subjects who satisfied the following criteria
were selected:
(i) Software professionals of both sexes aged
between 25 and 40 years who are working on day
shift.
(ii) The duration of working hours were also taken into
consideration which is fixed as at least 5 hours a
day or 25 hours per week.
(iii) Further, the Software professionals who are
working in other service domains of Information
Technology Industry including support services are
excluded.
Accordingly, a total of 302 Male employees and 98 female
employees were recruited for this study thus constituting
the male: female ratio of 3:1. Such ratio is proportionate to
the gender specific distribution of the work force in the IT
Organization.
METHODOLOGY
The Demographic Data Information Sheet and the Cornell
Musculoskeletal discomfort questionnaires along with
consent form were distributed with prior approval from the
Human Resource Department and with proper intimation to
the respective Head of the Department to get their full
cooperation and support. A presentation was done to all the
participants about the questionnaire and doubts were
clarified before the distribution of the Questionnaires. The
Work Related Musculoskeletal Disorders of the subjects
was assessed by Cornell University‘s musculoskeletal
discomfort questionnaire (CMDQ) (JasobantaSethi et al.,
2011). The Questionnaire was used to identify the number
of subjects who had pain in Low Back region with respect to
other body regions. Even though, the prevalence of all the
musculoskeletal disorders was captured through the
Questionnaire, the objective of this study is capturing the
prevalence of Low Back Pain.
DATA ANALYSIS AND RESULTS
This part deals with the work related risk factors of Low
Back Pain in Software Professionals. Univariate
Exploratory Analysis was employed to study the factors
among the employees reported with Low Back Pain.
Simple percentages and Means were employed to study
the factors. It is inferred from the Table No.1, 50% of
subjects reported Lower back pain, 16% of subjects
reported Neck Pain and 11% percentage of subjects
reported shoulder pain, 7% reported upper back pain and
5% reported wrist and hand symptoms. The mean scores
between the groups with and without Low Back pain were
tested using Independent t-test. The Table 2 shows the
prevalence of Low Back Pain in which 203 (51%)
employees reported low back pain (LBP). Correspondingly,
out of the 302 male employees, 54% (N=162) employees
reported LBP and out of all the female employees, 42%
(N=41) reported LBP. With respect to the distribution of
age among male subjects, 72% were between the ages of
21 to 30. 26% of them were between the age group of 31
to 40. With respect to the distribution of age among female
subjects, 90% were between the ages of 21 to 30. 10% of
them were between the age group of 31 to 40. The mean
age of all the employees is 28.04 years. The mean age of
those who complained of LBP is 28.39 years and that of
who did not report LBP is 27.68 years. This difference is
statistically insignificant at 5% level (Independent t-
test).With respect to the working hours of subjects with low
back pain, 22% of subjects were working less than 40
hours and 71% of them were working 41 to 50 hours a
week. Only 7% of the subjects were working more than 50
hours per week. The mean Work Hours per week of all the
employees is 45.57 hours. The mean Work Hours per
week of those who complained of LBP is 46.4 hours and
that of who did not report LBP is 44.72 hours. This
difference is statistically significant at 5% level
(Independent t-test). It is relevant to note here that those
who had LBP have put in more hours of work per week.
With respect to the Body Mass index of the subjects with
Low back pain, 38% were at normal level and 49% of
subjects were overweight. Only 13% of were obese as
indicated in the BMI over 30. The mean BMI of all the
employees is 25.23. The mean BMI of those who
complained of LBP is 26.29 and that of who did not report
LBP is 24.13. This difference is statistically significant at
5% level (Independent t-test). With respect to the
distribution of Waist-Hip Ratio (W-H ratio) of male subjects,
77% was less than 0.95. 15% of them were between the
Waist-Hip ratio group of 0.96 to 1.0. With respect to the
distribution of Waist-Hip Ratio of female subjects, 7% was
less than 0.80. 37% of them were between the Waist-Hip
ratio group of 0.81 to 0.85. 56% of them were more than
0.86. The mean W-H ratio of the 400 employees is 0.90.
The mean W-H ratio of those who complained of LBP is

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0.91 and that of who did not report LBP is 0.88. This
difference is statistically significant at 5% level
(Independent t-test). The higher BMI and W-H Ratio of
those reported LBP can be attributed to the sedentary life
style of the employees.Table 3&4 shows that Levene‘s
Test for Equality of Variances and Independent t-Test for
Equality of Means of different variables contributing to Low
Back pain in Software Professionals respectively.
Table-01: Categorization of Musculoskeletal disorders
in different body regions
Complaint Region
Total number of subjects
percentage
Hip
Knee
Lower back
Lower leg
Neck
Shoulder
Thigh
Upper arm
Upper back
Wrist
16
16
203
2
64
43
6
0
29
21
4
4
50
1
16
11
2
0
7
5
Total
400
100.00
Table-02: Description of Individual Factors contributing
to Low Back Pain in the Software Professionals
S.No
Parameters
/Variables
N
Mean
Std.
Deviation
1.
Age
203
28.39
3.13
2.
Working Hours
46.40
4.78
3.
BMI
26.03
3.42
4.
Waist Hip Ratio
0.904
0.06
Table-03: Levene’s Test for Equality of Variances
Variables
Levene’s Test for Equality of
Variances
F
Sig.
Age
20.997
0.00
Work Hours per
week
1.859
0.17
BMI
7.610
0.01
W-H Ratio
11.737
0.00
*F ratio is calculated with equality of variance assumed
Table-04: Independent t-Test for Equality of Means of
different variables contributing to Low Back pain in
Software Professionals
Variables
Equality
Assumpt
ion
t-Test for Equality of Means
t
df
Sig.
(2-
tailed
)
Mean
Differe
nce
Age
Equal
variances
assumed
1.63
8
398
0.102
0.709
Equal
variances
not
assumed
1.62
8
332.41
4
0.104
0.709
Work
Hours per
week
Equal
variances
assumed
3.10
9
398
0.002
1.683
Equal
variances
not
assumed
3.10
9
374.48
4
0.002
1.683
BMI
Equal
variances
assumed
5.44
6
398
0.000
2.164
Equal
variances
not
assumed
5.42
5
367.18
8
0.000
2.164
W-H
Ratio
Equal
variances
assumed
3.72
1
398
0.000
0.022
Equal
variances
not
assumed
3.73
3
385.59
6
0.000
0.022
* Significant at 0.05 level
DISCUSSION ON FINDINGS
The term ―Software Profession‖ is a wide area of concern in
which there are various categories of work in the
Information Technology sector. Thus, in this study, the term
―Software Professionals‖ is applied to those belonging to
the Software Design and Development Division only.
Besides this, certain criteria was fixed for including the
subjects into this study to achieve homogeneity of the
samples which includes age (i.e. 25- 40 years), and the
duration of working hours (at least5 hours a day or 25 hours
per week). Previous studies have cited four hours per day
as being a critical time for the development of
Musculoskeletal Disorders in employees working with
Visual Display Units (Rossignol et al, 1987). The present

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study is the documentation of the prevalence of Work
Related Low Back Pain among the Information Technology
Professionals. The presence of Computer in the workplace
leads to a set of peculiar characteristics of the workstation
which require the workers to stay in a static posture for long
periods. Back pain usually occurs due to sprains and
strains in the back as an outcome of static or an awkward
posture. Sedentary workers often complain of back pain
due to bad and awkward postures. Injuries occur due to
inactivity and static postures (Namrata Arora Charpe,
2009). WMSD‘s among the Informational Technology
professional is a common area of concern worldwide. This
study analyzes the limited work related risk factors of Low
Back Pain thus concluding that the risk factors are Age,
Working hours, Body Mass Index and Waist-Hip ratio. Total
number of (N=400) subjects was taken to analyze the work
related risk factors in the field of Software Profession.
Several studies carried out on Computer workers in India
reveals a high prevalence of Musculoskeletal discomfort
among Information Technology (IT) workers (Bakhtiar C.S.
and Vijaya R.S., 2003; Bhanderi D., 2007; Arun Vijay,
2013). Long working hours, Static postures, Poor office
Ergonomics, and repetitive nature of work were identified as
some of the risk factors leading to pain and discomfort
(Talwar R., 2009). Studies have also shown that the IT
professionals were exposed to such different risk factors
and therefore, it is expected that they are prone to develop
work related musculoskeletal discomfort (Wahlstrom J.
2005). The response (dependent) variables adopted in this
research was the presence or absence of Low Back Pain.
The factors such as Age, Working hours, Body Mass Index
and Waist-Hip ratio variables were analyzed to investigate
to what extent these factors might be the risk factors for
triggering Low Back Pain. Following the descriptive analysis
of the study, a Univariate Exploratory Model was used to
demonstrate the risk factors. From the analysis, it was
inferred that among the total number of subjects (N=400) in
the organization, 50% (N=203) of them reported Low Back
Pain (LBP). Similarly out of the 302 male subjects 54%
(N=162) reported LBP and out of 98 female subjects 42%
(N=41) of them have reported LBP. The mean Working
Hours per week of those who complained of LBP is 46.4
hours and that of who did not report LBP is 44.72 hours.
This difference is statistically significant at 5% level
(Independent t-test). It is relevant to note that those who
had LBP have put in more hours of work per week. Thus,
the finding of the present study supports the number of
hours spent on repeated activities at work was associated
with the prevalence of back pain (H-R Guo, 2002). The
association between Obesity and Low back pain may be
causal, in both cross-sectional and cohort studies (Rahman
Shiri et al., 2009). Several possible mechanisms can
explain this association. First, obesity could increase the
mechanical load on the spine by causing a higher
compressive force or increased shear on the lumbar spine
structures during various activities. Secondly, obese people
may also be more liable to incur accidental injuries (Hu HY,
Chou YJ, Chou P, et al. 2009). Thirdly, obesity may cause
low back pain through systemic chronic inflammation.
Obesity is associated with increased production of
cytokines and acute-phase reactants and with activation of
pro-inflammatory pathways (Tilg H, Moschen AR. 2006),
which in turn, may lead to pain (Karppinen J, 2007). Finally,
population-based studies have shown a stronger
association of abdominal obesity than generalized obesity
with low back pain (Han TS, Schouten JS, Lean ME, et al.
1997 and Shiri R, et al 2008). In this study, the mean BMI of
those who complained of LBP is 26.29 and that of who did
not report LBP is 24.13. This difference is statistically
significant at 5% level (Independent t-test). Waist-hip ratio
is one of the most commonly used anthropometric
measures to indicate a central obesity pattern (Perry AC et
al., 1998). In this study the mean Waist Hip ratio of those
who complained of LBP is 0.91 and that of who did not
report LBP is 0.88. This difference is statistically significant
at 5% level (Independent t-test).
CONCLUSION
The study concludes that the Low Back Pain is the major
Work Related Musculoskeletal Disorder among the IT
Professionals. In this study, more than 50% of them
reported Low Back Pain. Neck pain, Shoulder, Upper back
and wrist are the next most frequent types of
Musculoskeletal Disorders. When demographic factors are
analyzed, this study suggests that strategies incorporating
life style changes along with work modification as the best
option. Thus, the present study is a wakeup signal to both
the Information Technology professionals and the Human
Resource personnel to understand the health problems of
the software professionals working in IT industries.
Appropriate preventions and intervention strategies must be
emphasized to ensure a healthier working atmosphere and
thereby improve productivity of the IT Employees.
SCOPE FOR FURTHER RESEARCH
1. Future studies could estimate association between
the frequency of Work Related Musculoskeletal
disorders and various psychosocial factors such as
high stress, low control and limited social support
in the Software professionals. These factors should
be taken into consideration while designing
intervention strategies to reduce Work Related Low
Back Pain Problems.
2. The present study was conducted on particular
population of Information Technology Professionals
who are working in the Software developmental
divisions only. Similar studies can be conducted on
other divisions of IT Profession to find out the
occurrence of work related Low back Pain
problems.
3. A similar study can be conducted on wider age
group to find out the age impact on the occurrence
of musculoskeletal disorders.
ACKOWNLEDGEMENTS
The author acknowledges Dr. Alagesen, Professor and
Head, FGAPEdY, Ramakrishna Mission Vivekananda
University, Coimbatore, India for his guidance and support
towards the completion of this article. The author expressed
his gratitude to Dr. Balasubramanian, Joint Director,
Department of Economics and Statistics, Chennai, India for
his statistical inputs. The technical inputs given by Dr. S.

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Arun Vijay, Professor, KG College of Physiotherapy,
Coimbatore, India is also duly acknowledged.
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