Content uploaded by Subin Solomen
All content in this area was uploaded by Subin Solomen on Jul 08, 2015
Content may be subject to copyright.
Int J Physiother 2015; 2(3) Page | 557
4Prabhu .C .G
1Barnali Bhattacharjee, M.P.T.
College of Physiotherapy and Medical
Int J Physiother. Vol 2(3), 557-562, June (2015) ISSN: 2348 - 8336
Background: Air pollution as a trigger for exacerbation of COPD has been recognized for more than 50
years. Nowadays, in the cities like Bangalore, most of the people need to ride the bike for their
occupational demand and move around. The purpose of this study is to find out the prediction of COPD
using the BODE index in motor bike riders in Bangalore.
Methods: An exploratory cross sectional study has been done on 100 subjects who uses motor bike as
their mode of transport for their occupational demand, to study the hours of bike riding with the
chances of COPD based on BODE index.
Results: Analysis using spearman rank correlation found that there is statistically significant correlation
(p < 0.05) between hours of bike riding and the BODE index. Chi square test found that more than 4
hours of bike riding was associated with the chances of COPD.
Conclusion: Based on the result, it is concluded that more than 4 hours of bike riding is associated with
the chances of developing COPD even in non-smokers. Therefore there is significant susceptibility of
COPD among bike riders in Bangalore.
Key words: COPD, BODE Index, Air pollution, BMI, Bike riders, Exercise Capacity.
2Professor and Principal,
Padmashree Institute of Physiotherapy,
Padmashree Institute of Physiotherapy,
Hosmat Hospital Educational Institutions,
Received 24th May 2015, revised 03rd June 2015, accepted 06th June 2015
Int J Physiother 2015; 2(3) Page | 558
Chronic obstructive pulmonary disease is defined
as a disease state characterized by airflow
limitation that is not fully reversible. The airflow
limitation is usually both progressive and
associated with an abnormal inflammatory
response of the lungs to noxious particles or gases.1
Some of the risk factors for COPD are well known
and include smoking, occupational exposure, air
pollution.2 Tobacco smoking is established as a risk
factor, but emerging evidence suggest other risk
factors that are associated with COPD in non
smokers.3 Studies have shown that even non
smokers are prone for the development of COPD.
Mild, moderate, severe COPD is possible in non
smokers. Although the majority of COPD occurs in
current or former smokers the disease also occurs
in persons who have never smoked.4
Air pollution as a trigger for exacerbation of COPD
has been recognized for >50 years. The recent
dramatic increase in motor vehicle traffic has
produced a relative increase in the levels of newer
pollutants such as ozone and fine particulate air
pollution <10 micro meter in diameter. Numerous
epidemiological studies has shown association
between the level of these air pollutants and
adverse health effects such as exacerbation of
airway disease and even death from respiratory
and cardiovascular cause.5 The minute particles in
the air pollution leads to various pathological
changes in the lung. COPD comprises pathological
changes in four different compartment of the
lungs, central airways, peripheral airways, lung
parenchyma and pulmonary vasculature, which
are variably present in the individual with the
disease.6,7,8 The different pathogenic mechanism
produces the pathological changes which in turn
give rise to the following changes: mucus
hypersecretion and ciliary dysfunction, airflow
limitation and hyperinflation, gas exchange
abnormalities, pulmonary hypertension and
Nowadays in Bangalore most of the profession
requires riding bike for their occupation. Too much
of exposure to the pollution gives rise to various
respiratory ailments. All the pathological changes
in the lungs may later after some years lead to the
development of COPD. The risk of death in
patients with COPD is often graded with the use of
a single pathological variable the forced expiratory
volume in one second (FEV1)1,10,11,12. However other
risk factors such as presence of hypoxaemia or
hypercapnia, a short distance walked in a fixed
time, a high degree of functional breathlessness
and a low BMI are also associated with an increased
risk of death12
Recently BODE (body mass index, airflow
obstruction, dyspnea and exercise capacity) index
a multidimensional grading system was shown to
be a better predictor than FEV1 in predicting the
risk of death among patient with COPD.12.13 BODE
index is a multidimensional grading system to
assess severity in COPD, that incorporates four
factors known to be the independent predictor of
survival in this disease: the body mass index(B), the
degree of airflow obstruction(O), functional
dyspnea (D) and exercise capacity(E)13 The BODE
index has being used as it is a better predictor of
the risk of death from any cause and respiratory
cause than GOLD (Global initiative for Obstructive
Lung Disease) alone.12 Also due to larger inter
individual variability FEV1 does not seem to be
adequate as a basis for individual management
plan in rehabilitation.14 GOLD is unidimensional
but BODE is multidimensional.15
There are no studies done till now to find the
influence of air pollution in bike riders who are non
smokers but are susceptible to COPD due to their
exposure to air pollution for occupational demand.
Therefore the purpose of this study is to find the
prediction of COPD based on BODE index in bike
riders who uses it for their occupational demand.
An exploratory cross sectional study done on 100
subjects who uses bike as their mode of transport
for their occupational demand. The ethical
clearance was obtained from ethical committee of
Padmashree institute of Physiotherapy, Bangalore.
Subjects were recruited from Bangalore Urban
Community and study measurements procedure
was conducted at Padmashree Clinic, Bangalore.
Subjects included were non smoker bike riders for
more than 5 years with minimum of 1 hour riding
per day in Bangalore, between ages 25-40 years.
Subjects were excluded with hypertension, joint
Subjects who joined companies where workers had
to travel more in bikes for their occupational
demand were approached. 100 subjects were
selected based on inclusion criteria once the
subject agrees to participate in the study, an
informed written consent was taken from the
subjects. A questionnaire was distributed to all the
people who used bike as their mode of transport.
The questionnaire included person’s name age,
occupation, smoker/non smoker, reason for using
bike, duration of using bike, routine areas and
places covered in Bangalore, approximate distance
and time covered each day. Contact information
Int J Physiother 2015; 2(3) Page | 559
was included including address and phone
Measurements were taken for all the subjects. To
calculate BODE index measurements such as BMI,
FEV1, Exercise capacity and Dyspnea were
1. BMI: According to WHO Body Mass Index
(BMI) is a simple index of weight-for-height that
is commonly used to classify underweight,
overweight and obesity in adults. It is defined
as the weight in kilograms divided by the
square of the height in metres (kg/m2). For
example, an adult who weighs 70kg and whose
height is 1.75m will have a BMI of 22.9. BMI =
70 kg / (1.75 m2) = 70 / 3.06 = 22.9. Subjects
height and weight were calculated. Weight was
measured using the weighing machine. Height
was measured using the stadiometer.
Calculation: BMI=weight in kg/height in m2
2. FEV1: FEV1 predicted value was measured
using the PFT as per the American thoracic
society are 0= >65%; 1=50-64; 2= 36-49%;
3. Exercise Capacity: Distance walked was
measured by the 6 min walk test as per the
standards outlined by the American thoracic
society. Interpretation: 0=>350m; 1= 250-
349m; 2=150-249m; 3=<149m.
4. Dyspnea: Dyspnea was graded by MMRC.
MMRC Dyspnea Scale
Breathless only with strenuous exercise.
Short of breath when hurrying on the
level or up a slight hill
Slower than most people of the same age
on a level surface or have to stop when
walking at own pace on the level
Stop for breath walking 100 meters or
after walking a few minutes at own pace
on the level
Too breathless to leave the house
5. BODE INDEX: Stage 1: BODE index 0-2; Stage
2: BODE index 3-4; Stage 3: BODE index 5-7;
Stage 4: BODE index 8-10.
Based on the above quartile the subjects
susceptible for COPD were calculated. The higher
the score the more susceptible are the subjects for
Descriptive statistical analysis presented as mean
± SD. Significance is assessed at 5 % level of
significance with p value was set at 0.05 (1tailed
Hypothesis). Chi square test has been used to find
out the association between the hours of bike riding
and COPD. Spearman rank correlation has been
used to find out the relationship between the hours
of bike riding with BODE index. Linear regression
analysis was done to predict BODE index score
from hours of bike riding. The statistical analysis
was performed by using SPSS version 17. Alpha
value was set at 0.05. Microsoft word and excel has
been used to generate graphs, tables.
The correlation between the hours of bike riding
and COPD showed that there is significant
association of COPD with hours of bike riding. As
the hours of bike riding increases the BODE index
also increases. Chi square test shows that more
than 4 hours of bike riding is prone for developing
COPD. The scatterd graph shows an upward trend
which means there is significant positive
correlation between the hours of bike riding and
Table 1: Basic Variables of the Bike Riders under
Table 2: Correlation between the basic variables
in the study.
**Correlation significant at 0.05 level; NS: Not
Received 17th March 2015, revised 27th March 2015, accepted 08th April 2015
Int J Physiother 2015; 2(3) Page | 560
Table 3: Association between the hours of bike
riding and stages of COPD.
Stages of COPD
value, df &
P < 0.05
Figure 1: Scattered graph
Hours of bike riding
Graph shows a significant positive correlation
between hours of bike riding and the BODE index.
Table 6: Regression equation of scores of BODE on
hours of bike riding
BODE=0.909+0.571×Hours of bike riding
Eg. If hours of riding=5, then
Figure 2: BODE index according to stages
Figure 3: BODE index distribution
The purpose of this study was to find out with the
help of BODE index the number of bike riders who
are non smokers, but are susceptible to COPD due
to exposure to air pollution for their occupational
demand. The main objective of the study was to
find out the association between bike riders and
BODE index, relationship between hours of bike
riding and BODE index and how many hours of
bike riding can be prone for COPD.
Majority of the subjects that is 84 fell in stage 1.
However in stage 2 and stage 3 the number of
subjects were 7 and 9 respectively and stage 4 being
0. Majority of the subjects that is 32 rode bike for 3
hours. 22 subjects for 4 hours,16 for 5 hours and 21
for more than 6 hours.
Analysis about relationship between hours of bike
riding and BODE index shows that as hours of bike
riding increases the BODE index also increases.
Results shows that more than 4 hrs of bike riding is
prone for COPD.
Result has shown statistically significant positive
correlation of MMRC of dyspnea with hours of bike
riding. It may have increased due to decreased
exercise tolerance or susceptibility of the subjects
with COPD. Study done by Loredana Stendardi et.,
al shows that Respiratory muscle function and its
relationship to metabolic and cardiopulmonary
variables during exercise identify some of the
factors that limit exercise performance in patients
with COPD 16.
Result shows statistically significant negative
correlation of 6MWD with hours of bike riding.
Since all were non smokers, this may be due to
pollution. Factors like BMI may influence 6MWD
but it can be ruled out as BMI was generalized. So
decreased distance walked can be due to their
susceptibility to COPD. The 6MWD used in this
study is limited to 350 meter instead of the usual
stage1 stage2 stage3 stage4
Stage 0 stage 1 Stage 2 Stage 3
BMI FEV1 MMRC 6MWD
Int J Physiother 2015; 2(3) Page | 561
500 to 600 meters. It could be due to the
susceptibility of the cases with COPD. Previous
study has shown that the distance walked by COPD
patients is limited approximately to 350 meter.
Study done by Hatem F S Al Ameri shows that
overall the average 6MWD for 129 patients with
respiratory disease was 341±70m.The mean
distance walked for men was 390±75 m ,which was
significant at (p< 0.001)more than distance walked
by women(mean 305±57m).17
Result has shown statistically significant negative
correlation of FEV1 with hours of bike riding. Since
subjects were non smokers it can be due to their
exposure to air pollution for their occupational
demand. Study done by Bijendra Kumar Binawara
et.al shows that the FEV1 were decreased in study
group both in smokers and non-smokers which
were statistically highly significant in age group of
up to 40 years in non-smokers18. But due to larger
inter individual variability FEV1 does not seem to
be adequate as a basis for individual management
plan in rehabilitation.14 So BODE index has been
used in this study and it has shown statistically
significant positive correlation with hours of bike
riding. Result also has shown significant
association of bike riding with BODE index. Since
all the subjects were healthy non smokers, the
association can be due to their susceptibility to
CODP in future.
Based on the findings it signifies that there is
susceptibility of COPD among the bike riders in
Bangalore and more than 4 hours of bike riding is
prone to develop COPD in future.
Limitation of the study are that the data taken was
completely subjective which may influence the
study. Covering areas always may not be always
polluted. So hours of bike riding and COPD may
vary. 6MWD was done only 1 time, so less distance
covered may give high BODE index. No data about
hip, knee or ankle pain was taken as it was
completely subjective. Alpha trypsin deficiency
was not ruled out which is a genetic factor
associated with COPD. Wearing helmet with front
glass on was not taken into consideration which
may influence the study.
Further Research Recommendation: Incidence of
COPD in bike riders, a cohort study can be done.
6MWD should be done with practice. Can be done
in auto drivers, traffic police to know their chances
of developing COPD due to their exposure to air
pollution for their occupational demand.
Based on the statistical analysis performed, it is
concluded that there is significant effect of bike
riding and COPD in Bangalore. The higher BODE
index suggests that even non smokers who are
exposed to pollution mostly due to their
occupational demand are susceptible of getting
Based on this outcome it can be concluded that
“There will be significant susceptibility of COPD
among bike riders in Bangalore who are exposed to
more than 4 hours of bike riding for their
Authors were expressing their sense of gratitude’s
to the people who helped and encouraged them for
the guidance and completion of this study. I
sincerely acknowledge my indebtedness to Dr.
Vinod Babu. K, Assistant Professor in
Physiotherapy, KTG College of Physiotherapy,
Bangalore and Dr. Kritica Boruah, Lecturer in
Physiotherapy, College of Physiotherapy and
Medical Sciences, Guwahati, for their keen
interest, suggestions and guidance.
Conflicts of interest: None
Source of Funding: self
1. Pauwell R A, Buist S, Calverly PMA, Christine R
Sussane Sh. Global Stategy For The Diagnosis,
Management, And Prevention Of
COPD.NHBL/WHO Global Initiative For
Chronic Obstructive Pulmonary Disease,
Workshop Summary. Am J Respir Crit Care
2. Pavord ID, Yousaf N, Birring SS. Chronic
obstructive pulmonary disease in non-smokers.
Lancet. 2009 Dec 12;374(9706):1964; author
3. Sudeep Salvi, Peter J Bernes. Chronic
obstructive pulmonary disease in non-
4. Carolyn E Behrendt. Mild Moderate To Severe
COPD In Non-Smokers. Chest. 2005;
5. William Mac Nee, Kenneth Donaldson.
Exacerbation of COPD. Chest.2000;117:390s-
6. Stephen I Rennard. Inflammation And Repair
Process In COPD. Am J Resp Crit Care.
1999;160(5 Pt 2):S12-6.
7. Victor I V O Peinade etal. Inflammatory
Reaction In Pulmonary Muscular Arteries Of
Patient With COPD. Am J Resp Crit Care.
1999;159(5 Pt 1):1605-11
Int J Physiother 2015; 2(3) Page | 562
8. Marina Saetta: Airway Inflammation In COPD.
J Allergy Clin Immunol. 2003;112(5):819-27.
9. Matsuba K, Ikeda T, Shirakusa T. The Changes
In Airways Associated With Reduced Fev1.
Rinsho Byori.. 1990; 38(4):411-4.
10. Murray CJL, Lopez AD. Mortality By Cause For
Eight Regions Of The World: Global Burden Of
Disease Study. The Lancet. 1997;
11. Ferrer M, Alonso J, Morera J, et al. Chronic
obstructive Pulmonary disease stage and
health-related quality of life. Ann Intern
Med.1997; 127: 1072–1079.
12. Bartolome R Celli Etal. The Bode Mass Index,
Airflow Obctruction, Dyspnea And Exercise
Capacity Index In COPD.N Eng J Med. 2004;
13. Kian-Chung Ong, Arul Earnest And Suat-Jin Lu.
A Multidimentional Grading System(Bode
Index)As A Predictor Of Hospitalization For
COPD. Chest. 2005; 128(6):3810-3816.
14. Rosaline J Hiojsmans, Arnold DE ,Nick N H T,
Ten Hacken, Renata V M Straver,Alex J Vant
Hul;The Clinical Utiliy Of The Gold
Classification Of COPD Disease Severity In
Pulmonary Rehabilitation. Resp Med. 2008;
15. Fagerello etal: BODE Index And GOLD Staging
As Predictor Of 1 Year Exacerbation Risk In
COPD. Am J Med Sc. 2010; 339(1):10-14.
16. Loredana Stendardi, Barbara Binazzi, Giorgio
Scano. Exercise dyspnea in patients with
COPD. International Journal of COPD.
17. Hatem FS Al Ameri. Six Minute Walk Test In
Respiratory Diseases:A University Hospital
Experience. Annals Of Thoracic
18. Bijendra Kumar Binawara, Sushila Gahlot,
Kamlesh Chandra Mathur, Ashok Kakwar,
Reshu Gupta, Rajnee. Pulmonary Function
Tests In Three Wheeler Diesel taxi Drivers In
Bikaner City. Pak J Physiol. 2010;6(1):28-31.
Bhattacharjee, B., Aaron, P., Solomen, S., & Gowda, P. (2015). SUSCEPTIBILITY OF CHRONIC
OBSTRUCTIVE PULMONARY DISEASE AMONG BIKE RIDERS IN BANGALORE USING BODE
INDEX. International Journal of Physiotherapy, 2(3), 557-562.