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Susceptibility Of Chronic Obstructive Pulmonary Disease Among Bike Riders In Bangalore Using Bode Index

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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.
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Int J Physiother 2015; 2(3) Page | 557
1Barnali Bhattacharjee
2Pravin Aaron
3Subin Solomen
4Prabhu .C .G
CORRESPONDING AUTHOR
1Barnali Bhattacharjee, M.P.T.
Senior Lecturer,
College of Physiotherapy and Medical
Sciences,
Guwahati-781021, India.
Int J Physiother. Vol 2(3), 557-562, June (2015) ISSN: 2348 - 8336
ABSTRAC T
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.
DOI: 10.15621/ijphy/2015/v2i3/67031
www.ijphy.org
2Professor and Principal,
Padmashree Institute of Physiotherapy,
Bangalore
3Professor,
Padmashree Institute of Physiotherapy,
Bangalore.
4Professor,
Hosmat Hospital Educational Institutions,
Bangalore. India.
Received 24th May 2015, revised 03rd June 2015, accepted 06th June 2015
Int J Physiother 2015; 2(3) Page | 558
INTRODUCTION
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
systemic effects.9
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.
METHODOLOGY
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
pain, asthma.
Procedure:
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
number.
OUTCOME MEASURES
Measurements were taken for all the subjects. To
calculate BODE index measurements such as BMI,
FEV1, Exercise capacity and Dyspnea were
measured.
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=<35%.
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.
1
Breathless only with strenuous exercise.
2
Short of breath when hurrying on the
level or up a slight hill
3
Slower than most people of the same age
on a level surface or have to stop when
walking at own pace on the level
4
Stop for breath walking 100 meters or
after walking a few minutes at own pace
on the level
5
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.
0
1
2
3
score
BMI
>21
<21
FEV1
>65%
50-
64%
36-
49%
<35%
MMRC
1-2
3
4
5
6MWD
>350m
250-
349m
150-
249m
<149m
TOTAL
Based on the above quartile the subjects
susceptible for COPD were calculated. The higher
the score the more susceptible are the subjects for
COPD.
Statistical Methods
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.
RESULTS
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
BODE index.
Table 1: Basic Variables of the Bike Riders under
Study
Variable
Range
Mean
SD
Age
25-40
32.51
4.44
BMI
13.82-39.62
24.75
4.47
FEV1
50.0-100
89.70
11.16
6MWD
115-368
272.82
52.79
MMRC
1-4
1.95
0.744
BODE
0-7
1.64
1.40
Hours of
bike riding
2-10
4.32
1.74
Table 2: Correlation between the basic variables
in the study.
Variable
BMI
FEV1
6MWD
MMRC
BODE
Hours of
bike
riding
-
0.177
NS
-
0.626**
-
0.729**
-
0.432**
0.745**
**Correlation significant at 0.05 level; NS: Not
significant
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.
Hours
of bike
riding
Stages of COPD
Total
Chi square
value, df &
p value
Stage 1
Stage 2
Stage 3
n
o
%
n
o
%
n
o
%
X2=47.192,
df=8
P < 0.05
Significant.
So, more
than 4
hours of
bike riding
may be
prone for
COPD.
2 hrs
and
below
8
9.2
0
0
0
0
8
3hrs
32
36.
8
0
0
0
0
32
4hrs
22
25.
3
1
14.
3
0
0
23
5 hrs
13
18.
4
2
28.
6
1
11.
1
16
6 hrs
and
above
9
10.
3
4
57.
1
8
88.
9
21
Total
84
87.
0
7
4.0
9
8.0
100
Figure 1: Scattered graph
Hours of bike riding
121086420
BODE
8
6
4
2
0
-2
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
BODE=0.909+0.571×5=3.764=4
Figure 2: BODE index according to stages
Figure 3: BODE index distribution
DISCUSSION
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
0
10
20
30
40
50
60
70
80
90
stage1 stage2 stage3 stage4
84
79
0
Score
0
10
20
30
40
50
60
70
80
90
100
Stage 0 stage 1 Stage 2 Stage 3
84
14
0 0
95
50 0
87
760
8
64
24
4
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.
CONCLUSION
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
COPD.
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
occupational demand.”
Acknowledgement
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
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Citation
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.
... [12] Body-mass, airflow Obstruction, Dyspnea, and Exercise (BODE) index is also used for severity staging in COPD patients, but it is not known whether treatment can be tailored according to the BODE index. [13] Bhattacharjee et al. [14] conducted a study to find out the susceptibility of chronic obstructive pulmonary disease among bike riders in Bangalore using BODE index and concluded that more than 4 h of bike riding is associated with the chances of developing COPD even in nonsmokers; therefore, there is significant susceptibility of COPD among bike riders in Bangalore. ...
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The purpose of this study is to clarify the changes in the small airways associated with reduced forced expiratory volume in one second (FEV1). We compared the structure of the membranous and respiratory bronchioles of resected lungs from 111 patients with a normal predicted FEV1 to the structure of these airways from 45 patients with an FEV1 reduced below the 95% confidence limits for height and age. Membranous and respiratory bronchioles of less than 2 mm in internal diameter were counted and their diameter and wall thickness were measured. The data show that there were more membranous bronchioles of internal diameter less than 0.4 mm in patients with reduced FEV1. The walls of membranous bronchioles were not increased in thickness but there was an increase in the ratio of wall thickness to lumen diameter. The wall thickness of respiratory bronchioles was increased in the obstructed group and there was also an increase in the ratio of wall thickness to lumen diameter in these airways. We conclude that the patients with obstructive lung disease have a greater increase in wall thickness than can be explained by a reduction in airway support due to emphysema and suggest that the airways obstruction in these patients is due to thickening of the wall and narrowing of the lumen by a chronic inflammatory process.
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Reliable information on causes of death is essential to the development of national and international health policies for prevention and control of disease and injury. Medically certified information is available for less than 30% of the estimated 50.5 million deaths that occur each year worldwide. However, other data sources can be used to develop cause-of-death estimates for populations. To be useful, estimates must be internally consistent, plausible, and reflect epidemiological characteristics suggested by community-level data. The Global Burden of Disease Study (GBD) used various data sources and made corrections for miscoding of important diseases (eg, ischaemic heart disease) to estimate worldwide and regional cause-of-death.patterns in 1990 for 14 age-sex groups in eight regions, for 107 causes. Preliminary estimates were developed with available vital-registration data, sample-registration data for India and China, and small-scale population-study data sources. Registration data were corrected for miscoding, and Lorenz-curve analysis was used to estimate cause-of-death patterns in areas without registration. Preliminary estimates were modified to reflect the epidemiology of selected diseases and injuries. Final estimates were checked to ensure that numbers of deaths in specific age-sex groups did not exceed estimates suggested by independent demographic methods. 98% of all deaths in children younger than 15 years are in the developing world. 83% and 59% of deaths at 15-59 and 70 years, respectively, are in the developing world. The probability of death between birth and 15 years ranges from 22.0% in sub-Saharan Africa to 1.1% in the established market economies. Probabilities of death between 15 and 60 years range from 7.2% for women in established market economies to 39.1% for men in sub-Saharan Africa. The probability of a man or woman dying from a non-communicable disease is higher in sub-Saharan Africa and other developing regions than in established market economies. Worldwide in 1990, communicable, maternal, perinatal, and nutritional disorders accounted for 17.2 million deaths, non-communicable diseases for 28.1 million deaths and injuries for 5.1 million deaths. The leading causes of death in 1990 were ischaemic heart disease (6.3 million deaths), cerebrovascular accidents (4.4 million deaths), lower respiratory infections (4.3 million), diarrhoeal diseases (2.9 million), perinatal disorders (2.4 million), chronic obstructive pulmonary disease (2.2 million), tuberculosis (2.0 million), measles (1.1 million), road-traffic accidents (1.0 million), and lung cancer (0.9 million). Five of the ten leading killers are communicable, perinatal, and nutritional disorders largely affecting children. Non-communicable diseases are, however, already major public health challenges in all regions. Injuries, which account for 10% of global mortality, are often ignored as a major cause of death and may require innovative strategies to reduce their toll. The estimates by cause have wide Cls, but provide a foundation for a more informed debate on public-health priorities.
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The American Thoracic Society recently recommended that chronic obstructive pulmonary disease be staged on the basis of the percentage of predicted FEV1. To examine 1) the relation between the american Thoracic Society system for staging chronic obstructive pulmonary disease and health-related quality of life and 2) the effect of self-reported comorbid conditions on health-related quality of life. Cross-sectional study. Outpatient clinics of respiratory departments of four hospitals and one primary health care center in spain. 321 consecutive male patients with chronic obstructive pulmonary disease. Functional respiratory impairment, FEV1, respiratory symptoms, and health-related quality of life. Respiratory symptoms and health-related quality of life were measured by using the Spanish version of the St. George's Respiratory Questionnaire and the Nottingham Health Profile. Patient scores on the St. George's Respiratory Questionnaire were moderately to strongly associated with disease staging (r = 0.27 to 0.51). Compared with reference values, values for health-related quality of life for patients with stage I disease were substantially higher on the St. George's Respiratory Questionnaire (6 and 34; p < 0.001) and values for impairment were significantly greater in stage 1 patients with comorbid conditions (19 and 36; P = 0.001). At least one concomitant chronic condition was found in 84% of study patients. Comorbid conditions only partly influenced the observed pattern of deterioration of health-related quality of life with worsening stages of disease. Staging criteria for chronic obstructive pulmonary disease based on percentage of predicted FEV1 separated groups of patients with varying degrees of impairment in health-related quality of life. Contrary to expectations, even patients with mild disease showed substantially compromised health-related quality of life. Comorbid conditions influenced the relation between chronic obstructive pulmonary disease and health-related quality of life.