Indian Institute of Foreign Trade
Kolkata Campus
Consumer Behaviour
“Report on the Study of the Effects of Anti-Tobacco activities on the
Smoking Behaviour and Attitude of Young People”
Submitted to: Prof. Saikat Banerjee
Date: 8th March, 2011
Submitted by
Group 3
Aditya Adavi – (04)
Arnav Mathur – (10)
Piyush Agarwal – (24)
Saurabh Mitra – (33)
Shashank Kyatanavar – (34)
Siddharth Deswal – (38)
Sukesh Chande – (40)
Ankur Gupta – (48)
Vedvyas – (49)
Contents
Executive Summary..........................................................................................................................3
Introduction.....................................................................................................................................4
Research Approach...........................................................................................................................5
Methodology....................................................................................................................................6
Target Sample...................................................................................................................................6
Sample Size.......................................................................................................................................6
Analysis............................................................................................................................................8
Chi Square Test..................................................................................................................................8
Age Group......................................................................................................................................8
Employed vs. Student...................................................................................................................10
Economic Status...........................................................................................................................12
Residence.....................................................................................................................................14
Smoking Age................................................................................................................................16
Paired Difference Test.....................................................................................................................18
Findings and Conclusion.................................................................................................................19
2
Executive Summary
It is a very well-known fact that consumption of tobacco is injurious to health. But still a lot
of people continue to consume tobacco in some form or the other (cigarettes and bidis beings some
of the most common forms). The number of smokers in India has been on the rise for quite some
time now. To counter this and to make the public aware of the adverse effects of smoking and other
forms of consumption of tobacco, the government of India came out with a few anti-tobacco
campaigns such as the ban on public smoking, pictorial warnings on all tobacco products etc. But the
effectiveness of these campaigns has been a major question mark.
Our main purpose of carrying out this study is to find out if these campaigns have brought
about any changes in the smoking behaviour of the youth. For instance we would like to see if the
ban on public smoking has actually caused someone to reduce the number of cigarettes smoked or
maybe even quit smoking altogether.
The research was carried out on the smoking youth segment. By youth we mean individuals
in the age range of 17 to 35 years. We received 130 responses which were analysed using the chi-
square test and the paired difference test.
3
Introduction
The practice of burning and inhaling tobacco smoke is referred to as smoking. The active
substances such as nicotine provide pleasure to the smokers. The most common method of smoking
today is through cigarettes, primarily industrially manufactured but also hand-rolled from loose
tobacco and rolling paper. Other smoking implements include pipes, cigars, bidis, hookahs,
vaporizers and bongs. The harmful effects/ diseases caused by smoking include vascular stenosis,
lung cancer, heart attacks and chronic obstructive pulmonary disease.
In response to these the government has resorted to various anti-tobacco activities which
include:
Ban on public smoking
o India imposed a ban on smoking in public spaces on 2nd October 2010 .
No ads on smoking
o Tobacco advertising has been banned in India from 1 st May 2004.
Pictorial and graphical warnings on cigarette packs
o The pictorial warning on cigarette and tobacco products highlighting
adverse effects of smoking and using tobacco products have been
implemented from 31st May 2009.
Government taxes
o Excise duty on cigarettes went up by 10-18% in February 2010.
Our main focus would be on the youth segment. We classify the youth segment as the
people aged between 17 and 35 years. Through this study we aim to find out the effects
that the above mentioned anti-tobacco activities have had on the smoking behaviour of the
youth in India.
4
Research Approach
To carry out the research we need to perform a certain set of activities. This research can be
broadly classified into two activities:
Pilot Survey:
o This stage of the research includes observing the behaviour of the people smoking
as well as approaching them and asking a few questions related to their smoking as
well as any anti-tobacco activities that they might be aware of. The results from this
pilot survey help us in the formulation of the questionnaire which will be used in the
next stage of the research.
Data Collection and Analysis
o Based on the answers obtained from the respondents in the pilot survey, the
questionnaire is formed which is then used to collect data from a sample. This data
will then be analysed using the chi-square test and the paired difference test in
order to find out if these anti-tobacco activities have had any effect on the smoking
behaviour of the youth.
5
Methodology
As mentioned earlier, our main focus is on the youth segment. That is, people aged between
17 and 35 years. We make sure that the age of the respondents does not exceed 35 years and we
also make sure that the respondents are people who consume tobacco in some form (cigarettes,
bidis etc.)
This study had been done by conducting a survey with smokers (consumers of tobacco)
directly (primary data) through a questionnaire (to get direct information). Hence the data that has
been used for the analysis is purely primary data.
Target Sample
The sample consists of smokers aged between 17 and 35 years.
Sample Size
130 samples have been collected to analyse and reach a conclusion i.e. a sample size of 130.
The data collected, has been divided into different sub groups based on various factors. The groups
formed are based on:
Age Group
o 17-21
o 22-25
o 26-30
o 31-35
Whether they are employed or a student
o Employed
o Student
Economic Status
o Low
o Middle
6
o Rich
Residence
o Home
o Away from home (hostel, PG, rented place in the same city or a different one etc.)
Smoking age
o Less than 1 year
o 1-3 years
o 3-5 years
o More than 5 years
By dividing the sample into the above mentioned groups we can find out for each of the anti-tobacco
activity if it has any dependence on the factors (age group, economic status, residence, etc.). For
example we can test if the effect of the ban on public smoking and the age group are independent of
each other.
Apart from the Chi-Square tests, we have also made use of the paired difference tests to measure
the overall effect of the anti-tobacco activities. To perform this test we have asked the respondents
the approximate number of cigarettes that they used to smoke before they were aware of the anti-
tobacco activities and the number of cigarettes that they smoke as of now.
By obtaining this data we can find out if there is any difference in the number of cigarettes smoked
before and after the introduction of the anti-tobacco activities. This would give us an idea about the
effects that these campaigns have had on the smokers. No change in the number would mean that
the campaigns did not result in any reduction of any sort.
7
Analysis
Chi Square Test
As mentioned above data collected has been divided into many groups based on various factors. Let
us look at each of those factors individually.
Age Group
Effect of Ban on Public Smoking
Effect of Ban on Public Smoking
Reduced Not Reduced
17-21 1 3
22-25 20 54
Age Group
26-30 11 26
31-35 9 6
Reduced refers to the number of people who say that the Ban on Public Smoking has caused them to
reduce the number of cigarettes that they smoked. For instance, in the age group 17 -21, out of the
4 respondents, only one has reduced his cigarette consumption because of the ban on public
smoking.
H0: There is no dependence between the effect of ban on public smoking and the age group
H1: There is dependence between the effect of ban on public smoking and the age group
Test Statistic
Chi-Square 6.46037789
p-value 0.09123827
0.05
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
Effect of Ban on Promotion of Tobacco
Effect of Ban on Promotion of Tobacco
Reduced Not Reduced
17-21 1 3
22-25 10 64
Age Group
26-30 5 31
31-35 2 13
H0: There is no dependence between the effect of ban on promotion of tobacco and the age group
H1: There is dependence between the effect of ban on promotion of tobacco and the age group
8
Test Statistic
Chi-Square 0.42339231
p-value 0.93536891
0.05
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
Effect of Pictorial Warning
Effect of Pictorial warnings
Reduced Not Reduced
17-21 1 3
22-25 19 55
Age Group
26-30 7 29
31-35 5 10
H0: There is no dependence between the effect of pictorial warnings and the age group
H1: There is dependence between the effect of pictorial warning and the age group
Test Statistic
Chi-Square 1.16965032
p-value 0.76029224
0.05
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
Effect of Increase in Tax
Effect of Increase in Tax
Reduced Not Reduced
17-21 1 3
22-25 16 58
Age Group
26-30 8 26
31-35 4 11
H0: There is no dependence between the effect of increase in tax and the age group
H1: There is dependence between the effect of increase in tax and the age group
Test Statistic
Chi-Square 0.20675893
p-value 0.97649087
0.05
9
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
Employed vs. Student
Effect of ban on public smoking
Effect of Ban on Public Smoking
Reduced Not Reduced
Employed 28 52
Employed or Student
Student 13 37
H0: There is no dependence between the effect of ban on public smoking and whether they are
employed or a student
H1: There is dependence between the effect of ban on public smoking and whether they are
employed or a student
Test Statistic
Chi-Square 0.77509249
p-value 0.37864625
0.05
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
Effect of ban on promotion of tobacco
Effect of Ban on Promotion of Tobacco
Reduced Not Reduced
Employed 12 68
Employed or Student
Student 6 44
H0: There is no dependence between the effect of ban on promotion of tobacco and whether they
are employed or a student
H1: There is dependence between the effect of ban on promotion of tobacco and whether they are
employed or a student
Test Statistic
Chi-Square 0.04876612
p-value 0.82522439
0.05
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
10
11
Effect of Pictorial Warnings
Effect of Pictorial warnings
Reduced Not Reduced
Employed 21 59
Employed or Student
Student 11 39
H0: There is no dependence between the effect of pictorial warnings and whether they are
employed or a student
H1: There is dependence between the effect of pictorial warnings and whether they are employed
or a student
Test Statistic
Chi-Square 0.11425781
p-value 0.73534779
0.05
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
Effect of Increase in Tax
Effect of Increase in Tax
Reduced Not Reduced
Employed 16 64
Employed or Student
Student 13 37
H0: There is no dependence between the effect of increase in tax and whether they are employed
or a student
H1: There is dependence between the effect of increase in tax and whether they are employed or a
student
Test Statistic
Chi-Square 0.33981308
p-value 0.55993714
0.05
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
12
Economic Status
Effect of ban on Public Smoking
Effect of Ban on Public Smoking
Reduced Not Reduced
Low 1 8
Economic Status Middle 18 34
Rich 22 47
H0: There is no dependence between the effect of ban on public smoking and the economic status
H1: There is dependence between the effect of ban on public smoking and the economic status
Test Statistic
Chi-Square 1.97114424
p-value 0.37322564
0.05
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
Effect of ban on promotion of tobacco
Effect of Ban on Promotion of Tobacco
Reduced Not Reduced
Low 0 9
Economic Status Middle 7 45
Rich 11 58
H0: There is no dependence between the effect of ban on promotion of tobacco and the economic
status
H1: There is dependence between the effect of ban on promotion of tobacco and the economic
status
Test Statistic
Chi-Square 1.70696026
p-value 0.42593006
0.05
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
13
Effect of Pictorial Warnings
Effect of Pictorial warnings
Reduced Not Reduced
Low 0 9
Economic Status Middle 15 37
Rich 17 52
H0: There is no dependence between the effect of pictorial warnings and the economic status
H1: There is dependence between the effect of pictorial warnings and the economic status
Test Statistic
Chi-Square 3.44038838
p-value 0.17903138
0.05
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
Effect of Increase in Tax
Effect of Increase in Tax
Reduced Not Reduced
Low 0 9
Economic Status Middle 16 36
Rich 13 56
H0: There is no dependence between the effect of increase in tax and the economic status
H1: There is dependence between the effect of increase in tax and the economic status
Test Statistic
Chi-Square 5.2109094
p-value 0.07386954
0.05
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
14
Residence
Effect of Ban on Public Smoking
Effect of Ban on Public Smoking
Reduced Not Reduced
Home 12 25
Residence
Away 29 64
H0: There is no dependence between the effect of ban on public smoking and the place of residence
H1: There is dependence between the effect of ban on public smoking and the place of residence
Test Statistic
Chi-Square 0.00501107
p-value 0.94356578
0.05
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
Effect of Ban on Promotion of Tobacco
Effect of Ban on Promotion of Tobacco
Reduced Not Reduced
Home 4 33
Residence
Away 14 79
H0: There is no dependence between the effect of ban on promotion of tobacco and the place of
residence
H1: There is dependence between the effect of ban on promotion of tobacco and the place of
residence
Test Statistic
Chi-Square 0.12295273
p-value 0.72585382
0.05
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
15
Effect of Pictorial Warnings
Effect of Pictorial warnings
Reduced Not Reduced
Home 9 28
Residence
Away 23 70
H0: There is no dependence between the effect of pictorial warnings and the place of residence
H1: There is dependence between the effect of pictorial warnings and the place of residence
Test Statistic
Chi-Square 0.03133452
p-value 0.85949615
0.05
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
Effect of Increase in Tax
Effect of Increase in Tax
Reduced Not Reduced
Home 8 29
Residence
Away 21 72
H0: There is no dependence between the effect of increase in tax and the place of residence
H1: There is dependence between the effect of increase in tax and the place of residence
Test Statistic
Chi-Square 0.01320807
p-value 0.9085035
0.05
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
16
Smoking Age
Effect of Ban on Public Smoking
Effect of Ban on Public Smoking
Reduced Not Reduced
Less than 1 yr 12 19
1-3 yrs 9 15
Smoking Age
3-5 yrs 8 23
more than 5 yrs 12 32
H0: There is no dependence between the effect of ban on public smoking and the smoking age
H1: There is dependence between the effect of ban on public smoking and the smoking age
Test Statistic
Chi-Square 1.97592198
p-value 0.5774192
0.05
The p-value obtained by performing the Chi-square test is coming out be greater than the value.
Therefore we cannot reject the null hypothesis.
Effect of Ban on Promotion of Tobacco
Effect of Ban on Promotion of Tobacco
Reduced Not Reduced
Less than 1 yr 12 19
1-3 yrs 3 21
Smoking Age
3-5 yrs 0 31
more than 5 yrs 3 41
H0: There is no dependence between the effect of ban on promotion of tobacco and the smoking
age
H1: There is dependence between the effect of ban on promotion of tobacco and the smoking age
Test Statistic
Chi-Square 22.9055278
p-value 0.000042
0.05
The p-value obtained by performing the Chi-square test is coming out be less than the value.
Therefore we reject the null hypothesis. And we can observe that people who have started smoking
recently (smoking age < 1 year) are the ones who have reduced smoking after a ban has been placed
on the promotion on tobacco.
17
Effect of Pictorial Warnings
Effect of Pictorial warnings
Reduced Not Reduced
Less than 1 yr 13 18
1-3 yrs 10 14
Smoking Age
3-5 yrs 2 29
more than 5 yrs 7 37
H0: There is no dependence between the effect of pictorial warnings and the smoking age
H1: There is dependence between the effect of pictorial warnings and the smoking age
Test Statistic
Chi-Square 16.0810027
p-value 0.00109143
0.05
The p-value obtained by performing the Chi-square test is coming out be less than the value.
Therefore we reject the null hypothesis. And we can observe that people who have started smoking
recently (smoking age < 1 year) are the ones who have reduced smoking after the pictorial warnings
on the cigarette packs have been in place.
Effect of Increase in Tax
Effect of Increase in Tax
Reduced Not Reduced
Less than 1 yr 12 19
1-3 yrs 6 18
Smoking Age
3-5 yrs 6 25
more than 5 yrs 5 39
H0: There is no dependence between the effect of increase in tax and the smoking age
H1: There is dependence between the effect of increase in tax and the smoking age
Test Statistic
Chi-Square 8.10901502
p-value 0.04381161
0.05
The p-value obtained by performing the Chi-square test is coming out be less than the value.
Therefore we reject the null hypothesis. And we can observe that people who have started smoking
recently (smoking age < 1 year) are the ones who have reduced smoking after there has been an
increase in the price of the cigarettes due to an increase in tax.
18
Paired Difference Test
In the questionnaire we have asked to respondents to give the approximate number of
cigarettes that they smoked before and after they were aware of the anti-tobacco activities. We
have used these answers to find out if the campaigns have been successful in causing a reduction in
the number of cigarettes smoked or not. The analysis is shown below.
Evidence
Size 130 n Assumption
Average Difference -0.06154 m D Populations Normal
Stdev. of Difference 2.36497 s D
Note: Difference has been defined as
Test Statistic -0.2967 t Sample1 - Sample2
df 129
Hypothesis Testing At an a of
Null Hypothesis p -value 5%
H0: m 1 - m 2 = 0 0.7672 Do not Reject H0
The data obtained has been analysed using the paired difference test with the hypothesis as:
H0: The difference in the means is equal to zero
H1: The difference in the means in not equal to zero
At a = 0.05, since the p-value is coming out to be greater than the value we do not reject the null
hypothesis.
Therefore we can say that there hasn’t been any significant change in the number of cigarettes
smoked before and after being aware of the anti-tobacco campaigns. In short that means that the
campaigns have had no effect on the smoking behaviour of the youth.
19
Findings and Conclusion
From the results obtained after performing the chi-square tests and the paired difference
test, we have found out the following:
The effect that the anti-tobacco activities have had is the same:
o Over different age groups
o Whether the respondents are employed or students
o Over people from different economic status
o Whether the respondents stay at home or away from home
The effect that has been observed is that these activities have not caused in any sort of
reduction in the number of cigarettes smoked. The number of people who have reduced
smoking after being exposed to these campaigns is very less compared to the number of
people who have not reduced.
The effect that the anti-tobacco activities have had is dependent on the smoking age of the
respondent.
o This means that those who are new to smoking (smoking age < 1 year) and the ones
who can be influenced with the help of these campaigns. Once people turn in
experienced smokers, these campaigns do not seem to affect them.
And from the paired difference test we can conclude that the anti-tobacco activities have
not resulted in any change in the smoking behaviour of the youth in India. The average
number is cigarettes smoked before and after being aware of the campaigns remains the
same.
And from the finding of the survey we can come to a few conclusions:
The anti-tobacco activities/ campaigns introduced by the government have not been
successful in causing a reduction in the average number of cigarettes smoked.
20
People who are new to smoking are the ones that can be influenced by these campaigns.
Therefore the government and the NGOs should target the younger population (schools and
colleges) to make these campaigns more effective.
21
