Contents
CHAPTER1 ..................................................................................................................................................... 3
INTRODUCTION ............................................................................................................................................. 3
1.0 Introduction ........................................................................................................................................ 3
1.1 Background ......................................................................................................................................... 3
1.2 Problem statement ............................................................................................................................. 6
1.3 Significance of the study ..................................................................................................................... 7
1.4 Objectives............................................................................................................................................ 8
1.5 Research hypothesis ........................................................................................................................... 8
1.6 Conclusion ........................................................................................................................................... 8
CHAPTER 2 .................................................................................................................................................... 9
LITERATURE REVIEW ..................................................................................................................................... 9
2.0 Introduction ........................................................................................................................................ 9
2.1 Theoretical literature review .............................................................................................................. 9
2.1.2 Rational addiction theory............................................................................................................. 9
2.1.3 Social psychological theories ..................................................................................................... 10
2.1.4 Expectancy-value theories of attitude and behavior change .................................................... 11
2.1.5 Health Belief Model ................................................................................................................... 12
2.2 Empirical literature ........................................................................................................................... 12
2.3 Conclusion ......................................................................................................................................... 14
CHAPTER 3 .................................................................................................................................................. 15
METHODOLOGY .......................................................................................................................................... 15
3.0 INTRODUCTION ................................................................................................................................. 15
3.1 Model specification ........................................................................................................................... 15
3.2 Justification for the Choice of Variables ........................................................................................... 16
3.2.1 Smoker/nonsmoker ................................................................................................................... 16
3.2.2 Level of education ...................................................................................................................... 16
3.2.3 Occupation ................................................................................................................................. 17
3.2.4 Income level ............................................................................................................................... 17
3.2.5 Social background ...................................................................................................................... 17
1
3.2.6 Age ............................................................................................................................................. 18
3.2.7 Gender ........................................................................................................................................ 18
3.2.8 Advertising ................................................................................................................................. 18
3.3 Diagnostic Tests ................................................................................................................................ 18
3.3.1 Multicollinearity ......................................................................................................................... 19
3.3.2 Heteroskedasticity...................................................................................................................... 19
3.4 DATA SOURCES ................................................................................................................................. 19
3.5 Conclusion ......................................................................................................................................... 22
REFERENCES ............................................................................................................................................ 23
2
CHAPTER1
INTRODUCTION
1.0 Introduction
Tobacco smoking is one of the most preventable risk factor for mortality in Zimbabwe and the
world. Tobacco smoking has been recognized as an addictive habit because most smokers find it
difficult to stop smoking when they start. Its harmful effects on human health can be evidenced
for both active and passive smokers. In a report which was published in 2008 on tobacco use
and control, co-published by the American Cancer Society, the World Health Organization
(WHO) and the International Union Against Cancer (UICC) 2008 estimates that while about half
of current tobacco deaths occurs in developing countries like Zimbabwe, that number is expected
to rise to more than 70% by 2020. It lends further support to the evidence that tobacco industry is
increasingly targeting women in developing countries, the largest remaining untapped market for
cigarettes. Thus tobacco's cancer burden is increasingly being shifted to developing countries
like Zimbabwe. Apart from urgent need for increasing people's awareness of tobacco smoke
harmful effects on human health, enforcement of health care workers' education in the field of
smoking cessation methods and primary prevention of tobacco use are also necessary. This has
triggered the author to try and identify the determinants of tobacco smoking so that this will help
in the primary prevention and cessation of tobacco smoking in Zimbabwe.
1.1 Background
In Zimbabwe, as in many parts of Africa, cigarette smoking is growing. According to a survey
on tobacco smoking by WHO carried out in 2008, Africa is expected to double its tobacco
consumption in 9 years if current trends continue. The surge in smoking is seen in young people
under the age of 20 that constitute the majority of the continents population. According a survey
carried out in 2005 by Zimbabwe Stepwise there is a high prevalence of modifiable risk factors
of non-communicable diseases. It also reveals that current tobacco consumption is very high
especially among males. The survey noted that current Tobacco consumption was 33 percent in
males and 5 percent in females and tobacco smoking is considered a major cause of quite a
number of cancers (MoHCW publication on non communicable diseases prevention and control
2013). Across Africa, it is estimated men constitute of 70-85 percent of smokers (WHO 2008).
3
For many, smoking starts at a young age. It starts with peer pressure, being exposed to second
hand smoking, having parents and best friends who smoke. While it‟s almost taboo for women to
smoke, the habit is slowly picking up among young women who regard it as a fashion statement.
Cigarette consumption which was at 6 328 billion sticks in 2009, is estimated to have declined to
6 319 billion sticks in 2010 due to consumption reduction in other parts of the world which was
in turn offset by growth in Asia (TIMB 2011).
According to a UNICEF survey carried out in 2004 tobacco kills more than 14,000 people each
day – nearly 6 million people each year globally. Included in this death toll are some 600,000
non-smokers who are exposed to second-hand smoke. In 2004, children accounted for 31% of
these deaths. Almost half of children regularly breathe air polluted by tobacco smoke. There are
more than 4,000 chemicals in tobacco smoke, of which at least 250 are known to be harmful, and
more than 50 are known to cause cancer.
In Zimbabwe according to Tobacco Atlas (2004) about 3% of deaths in males is due to diseases
caused by tobacco smoking whilst in women about 1% of deaths is due to diseases caused
tobacco smoking. About 20,9% youths between the age of 13 And 15 are exposed to secondhand
smoking and thus are likely to be affected by diseases caused by tobacco smoking (tobacco atlas
2009). According to the national cancer registry (2011), around 7 000 cancer cases are recorded
each year in Zimbabwe and the epidemic is on the increase. Close to 60% of new cancer cases
recorded in Zimbabwe are HIV-related while the other significant burden is largely due to
tobacco smoking. This means that approximately 40% of such cases are due to tobacco smoking.
Tobacco is the single most preventable cause of death in the world today but very few countries
in Africa just like Zimbabwe have tobacco control acts to protect citizens from adverse effects of
smoking, second hand smoking and the rate of new addictions. According to the ZDHS statistics
of 2010 to 2011 prevalence of smoking habits is higher in rural areas than in cities. This is
probably due to lack of knowledge and access to information on the effects of tobacco smoking
and also it was noted that man are the major smokers of tobacco. The ZDHS (2010-2011) also
showed that smoking was more prevalent on those whose ages range from 25-49, followed by
those from 15-24 and those who range from 50 and above.
4
Smoking tobacco is a major cause of cardiovascular diseases, chronic obstructive pulmonary
disease (COPD), lung cancer, chronic bronchitis and asthma. According to a publication by the
ministry of health and child welfare recently (2013) chronic obstructive lung diseases, especially
asthma, are one of the more frequently seen conditions in outpatient clinics. In both adults and
children, asthma has become a disease of public health concern. Asthma and the Acute
Respiratory tract Infections (ARI) contribute significantly to the high levels of morbidity,
mortality and disability, particularly among the under 5 years in Zimbabwe. ARI itself is a major
cause of deaths in children under five years. In 2006, new acute respiratory tract infections cases
accounted for 37 percent of all outpatient diseases. There were 148322 new cases for under five
years giving an incidence rate of 394 per 1000 in 2006 (MoHCW publication on non
communicable diseases 2013).
Most of the above mentioned diseases are due to a substance found in tobacco known as
nicotine. Asthma on average causes about 662 deaths per year in Zimbabwe, oesophagus cancer
causes about 631 deaths( 0.37%),and lung cancer on average causes about 258 deaths ( 0.15%)
these diseases are in the top 50 causes of deaths in Zimbabwe( health profile Zimbabwe
published by Who 2010). Tobacco smoking also influences the development of other cancers
that develop in different body organs like the pharynx, larynx, oesophagus, stomach, pancreas,
uterus, cervix, kidney, ureter and bladder. Tobacco smoking also has harmful effects on
reproduction and pregnancy that it results in reduced fertility, low birth weight, increased risk of
ectopic pregnancy and increased risk of spontaneous abortion. In Zimbabwe deaths caused by
low birth weight which can also be due to tobacco smoke are on average 4225( about 2.49% of
total deaths) and ranked the 8th major cause of death in Zimbabwe (WHO health profile for
Zimbabwe 2010). Tobacco smoking also causes many other health disorders that include dental
and peridental diseases.
Dr John Hill, a London physician, reported an increase of lip cancer in pipe smokers as long ago
as 1761. Sir Percival Pott reported cancer of the scrotum in chimney sweeps in 1777, which he
attributed correctly to lodgment of soot in the rugose scrotal skin. This type of cancer was
virtually eliminated by simple personal hygiene. Later, many chemicals were proved to be
carcinogenic and hence many cancers became avoidable by taking more care when dealing with
them and the best solution was to avoid use by all means possible.
5
Zimbabwe as a developing country focus has been more urgent on problems such as
malnutrition, h.i.v/a.i.d.s, and infectious diseases caused due to poor living conditions( for
example recent outbreaks of cholera and typhoid). Thus there is less or no statistics available for
the past years, on the diseases caused by tobacco smoking as well as deaths due to these diseases.
Thus the ministry of health and child welfare was focusing mainly on communicable diseases.
Zimbabwean health services, as Chapman and Richardson (1990) said about Papua New Guinea,
which is also a developing country like Zimbabwe, “typically accord low priority to smoking
control” (pg. 537). Indeed smoking control policies and programmes in Zimbabwe are virtually
nonexistent. As one observer of the Zimbabwean tobacco industry poignantly quips: “the closest
thing in Zimbabwe that resembles any anti-tobacco activity is the anti tobacco air sanitizer cans
sold in supermarkets.” This can also be noted by little or no information at all recorded on the
diseases and deaths due to tobacco smoking. Also there are less awareness campaigns on the
consequences due to tobacco smoking. The author thinks this is mainly due to the fact that the
effect of tobacco smoking are only noticed in the long run thus why countries like Zimbabwe
focus more on infectious diseases whose effect are noticed in the very short run.
Cigarette advertising continues unabated as there are no restrictive regulations and this has
resulted in B.A.T., through their flagship Kingsgate cigarette brand, and also Madison,
establishing themselves as sponsors of the country‟s premier soccer league at certain points and
time. However it should be noted that the act of sponsoring is not bad but in the process of doing
that emphasis should also be made on all the bad effects of tobacco smoking rather than jus focus
on increasing sales.
Thus, in the continuous stark absence of any active anti-tobacco legislation, it appears that
mainly economic factors such as price and income levels as well as socio-cultural factors such as
one‟s background, level of education, employment status and many others may have a significant
impact on tobacco smoking.
1.2 Problem statement
Tobacco smoking kills more than 14,000 people each day – nearly 6 million people each year
globally (UNICEF Survey 2004). Included in this death toll are some 600,000 non-smokers who
are exposed to second-hand smoke. In 2004, children accounted for 31% of these deaths
(UNICEF Survey 2004). Almost half of children regularly breathe air polluted by tobacco
6
smoke. Half of these deaths occur in developing countries like Zimbabwe and they are expected
to rise to 70% by 2020. In Zimbabwe according to the national cancer registry (2011), around 7
000 cancer cases are recorded each year in Zimbabwe and the epidemic is on the increase. Close
to 60% of new cancer cases recorded in Zimbabwe are HIV-related while the other significant
burden is largely due to tobacco smoking. This means that approximately 40% of such cases are
due to tobacco smoking. The Zimbabwe‟s ministry of health and child welfare recently published
that chronic obstructive lung diseases, especially asthma, are one of the more frequently seen
conditions in outpatient clinics in both adults and children. Asthma and the Acute Respiratory
tract Infections (ARI) contribute significantly to the high levels of morbidity, mortality and
disability, particularly among the under 5 years in Zimbabwe. ARI itself is a major cause of
deaths in children under five years. In 2006, new acute respiratory tract infections cases
accounted for 37 percent of all outpatient diseases. There were 148322 new cases for under five
years giving an incidence rate of 394 per 1000 in 2006 (MoHCW publication on non
communicable diseases 2013). Also the world health organization health profile on Zimbabwe
(2010) shows that approximately at least 3.1% of the total deaths in Zimbabwe are due to
diseases caused by tobacco smoking which also fall in the top 20 causes of mortality in
Zimbabwe. This has prompted the author to carry out an investigation on the determinants of
tobacco smoking so as to help stop tobacco smoking at its roots and help reduce the increasing
numbers of deaths caused by tobacco smoking.
1.3 Significance of the study
In this study the author argues that for there to be an effective reduction in the deaths and all
other problems caused by tobacco smoking the major determinants of tobacco smoking have to
be identified. Identifying the determinants of tobacco smoking will help policy makers and all
the relevant authorities to come up with better solutions to help stop tobacco smoking at its
primary stages as well as cessation of those already smoking. That is if the determinants are
known measures will be put in place to ensure reduction of tobacco smoking. Also the researcher
has found that literature in this particular area has not been widely available and it is against this
basis to add some literature on this subject. The few available studies have been mainly
concentrated in developed countries and thus the author has decided to add more literature basing
on information and conditions of developing countries like Zimbabwe. Also most of the
literature available focused more on youths and only socio-cultural determinants, but this study
7
will investigate from the youths to adults and will also consider all possible determinants for
tobacco smoking.
1.4 Objectives
 Identify the determinants of tobacco smoking
 Evaluate the impact of the determinants on smoking
 Give policy recommendations to government and all the relevant authorities
1.5 Research hypothesis
Factors such as income level, occupation, level of education, advertising, age, gender, social
background and price influence tobacco smoking behavior.
1.6 Conclusion
The role of the study is to try and find the major determinants of tobacco smoking behavior in
Kadoma, Zimbabwe.
8
CHAPTER 2
LITERATURE REVIEW
2.0 Introduction
The empirical models of smoking initiation and cessation are based on the economic theory of
demand assuming existence of an individual‟s utility function. An individual utility from
consuming cigarettes depends on the number of cigarettes, utility derived from other goods, and
individual tastes. An individual maximizes his or her utility subject to a budget constraint, which
is comprised of the price of cigarettes, income, and the prices of all other goods. This constrained
maximization determines the demand function for cigarettes where cigarette consumption is
related to the price of cigarettes, prices of related goods, income, and individual‟s tastes.
2.1 Theoretical literature review
Economists use a broad definition of price that includes not only monetary value of a product,
but also the time and other costs associated with the purchase and the use of a product. For
example, restrictions on smoking impose additional costs on smokers in the form of discomfort,
limitations, and a possibility of fines for smoking in restricted areas. Similarly, limits on youth
access to tobacco may raise the time and potential legal costs associated with smoking by
minors, and new information on the health consequences of tobacco consumption can raise the
perceived long-term costs of smoking.
2.1.2 Rational addiction theory
Economists model human behavior by assuming that individuals act in their own best interest.
Agents are described as maximizing utility and are believed to make rational choices consistent
with their preferences, given their beliefs. Also Economists try to describe or explain tobacco
smoking behavior using rational addiction models, which build on earlier analysis in which the
individual‟s past consumption patterns affect present choices (for example see Pollack, (1970)
and Stigler and Becker, (1977)). Becker and Murphy in their addiction analysis of 1988 they
assumed that agents choose an over life consumption path to maximize expected utility and show
that addiction is consistent with rational behavior.
9
Another theory of addiction is the „multiple selves‟ approach that embodies competing
preferences. In these models a smoker would have one „self‟ who wants to smoke competing
against her non-smoker „other self‟.
2.1.3 Social psychological theories
In social psychological theories we find what are known as proximal factors or determinants of
tobacco smoking these tend to be behaviorally specific, and we also have distal factors these tend
to be relatively global and stable underlying influences on behavior, for example, depression,
optimism, and general social support. The key differentiating characteristics among these factors,
however, is that distal ones are posited to influence behavior less immediately and to exert their
influence through proximal ones.
Proximal determinants
Proximal determinants are grounded in extant social psychological theories, including the theory
of planned behavior (Ajzen, 199 l), theory of triadic influence (Flay & Petraitis, 1994), and
social cognitive theory (Bandura, 1997). While there are more substantive differences in the
organization and terminology of proximal constructs within those models (Fishbein et al., 2001),
view five constructs as comprising these models‟ most important behavioral antecedents. These
central constructs, as applied to smoking, are self-efficacy which means perceived behavioral
control to resist smoking, attitudes (that is either positive or negative expectancies) toward
smoking, social norms (subjective norms) surrounding smoking, impediments (environmental
barriers) to smoking, and intention (proximal goals) to smoke.
There are several ways in which the central proximal determinants could impact one‟s smoking
behavior. For example, if an individual does not believe that he or she could resist the temptation
to smoke (i.e., has low self-efficacy to resist smoking); he/she may be more likely to smoke or to
act on peer influence to smoke. Positive attitudes toward smoking could impact tobacco initiation
as well. If an individual believes that smoking leads to positive gain, they may engage in
smoking in order to attain the perceived desirable consequences. Perceived risks or dangers
surrounding tobacco smoking, which can be considered a form of negative expectancies
attitudes, could also affect tobacco smoking in that one is more likely to smoke if he/she does not
recognize the harmful consequences of that behavior. Also, social norms surrounding smoking
10
could influence one to smoke tobacco or not. Some individuals are more likely to smoke if they
experience environmental cues that are accepting or encouraging of smoking for example,
believing that parents or peers approve of smoking. Also if one does not encounter
environmental barriers or any other restrictions to smoking for example, if they have easy access
to cigarettes, too much exposure to smoking habits and opportunities to smoke anywhere they
want, they may be more likely to initiate and subsequently engage in regular smoking.
Distal determinants
Distal determinants though believed to be less strongly associated to smoking behavior, they are
considered important because distal determinants may influence proximal determinants of
smoking. Such distal influences of smoking primarily correspond to constructs representative of
theories in personality (broadly defined) and social development. For example, strong
relatedness to parents (a distal determinant) may impact smoking by fostering youth
understanding of parental norms against smoking (a proximal determinant), or by creating a
home environment where smoking would be a more difficult behavior for an individual to
engage in (thereby increasing restrictions to smoking, another proximal factor). Likewise, a
number of theories suggest that bonding with conventional role models in the family or
educational setting (versus bonding with deviant peers) influences smoking outcomes, in part, by
creating a social environment (e.g., peer norms) with less favorable views toward smoking.
2.1.4 Expectancy-value theories of attitude and behavior change
There is also what is known as the Expectancy-value theories of attitude and behavior change.
Like the other recent theories it also implicitly assumes that individuals have control over their
choices and that they base their choices on information available to them. The expectancy-value
models include two components as predictors of attitudes, or in the case of decision models,
behavioral choice. The two components are expectancy that is the likelihood that the decision is
associated with a particular outcome and a value, that is, the positive or negative valence
associated with that outcome. The core assumption of expectancy-value models is that people
strive to maximize the perceived benefits and minimize the perceived costs associated with
performing a behavior.
11
In the medical literature it is suggested that addictions are „diseases‟ arising out of biological
predispositions. This approach places the choice about using addictive substances beyond the
individual‟s control that is one will not be able to control one‟s level of addiction or cannot avoid
addiction. Some Psychologists describe addictions using what are known as „primrose path‟
theories. In this view individuals are lured into addiction either because the latent costs are
initially hidden or because of a faulty reasoning process.
2.1.5 Health Belief Model
One of the most influential models in the health area and from my own opinion in determining
one‟s smoking behavior is the Health Belief Model (HBM), which says that the cognitive
activities in response to messages pertain to formulating beliefs about health risks and the healthprotective qualities of certain behaviors. To preserve one‟s health, modification of behavior may
take place. The HBM assumes that self destructive behavior, such as smoking, occurs when
individuals do not have adequate information about the health risks posed by their behavior, fail
to understand their vulnerability to the consequences of their behavior, fail to understand that
avoiding the behavior will reduce health risks, or encounter other informational barriers to
behavior change. To encourage smoking cessation, the HBM, and expectancy-value models in
general, suggest strengthening the individual‟s perception of the risk and severity of the
consequences of smoking and of their physical vulnerability to those consequences. At the same
time, a persuasive message should try to reduce the perceived benefits of continued smoking as
well as the barriers to changing the behavior, perhaps by increasing necessary skills to quit or
perceived self-efficacy that quitting is possible and beneficial.
2.2 Empirical literature
Friis et al (2006) made their investigations on the socio-cultural determinants of tobacco use
among Cambodian Americans. They tried to explain the role of cultural factors needed to be
considered when designing appropriate smoking cessation strategies for Cambodian Americans
12
using a sample size of 119. They used the SPSS to analyze their data which was obtained by
distributing questionnaires. The principal outcomes measured were cigarette smoking and
tobacco use. Other variables included reasons for smoking, traditional uses of tobacco, stress
factors related to smoking and the perceived health effects of smoking. Predisposing, reinforcing
and enabling factors associated with tobacco-use behaviors included peer group influences,
smoking adopted as a coping method, tobacco used for medicinal purposes and smoking
practiced within cultural traditions. The frequency of smoking was four times higher among
males than among females. The results showed that the main socio-cultural factors that induced
smoking tobacco were: traditions and practices that integrate smoking with the Cambodian
American social environment, smoking as a coping mechanism and tobacco used for medicinal
purposes.
Maskarinec at al (2005) attempted to explain the ethnic differences in trends and determinants of
cigarette smoking in Hawaii. They calculated odds ratios and 95% confidence intervals by using
polytomous logistic regression to explore determinants of smoking, while controlling for
clustering by study.
Carvajal et al (2004) investigated on the theory based determinants of youth smoking: a multiple
influence approach. They tested a broad array of determinants of smoking grounded in general
social psychological theories, as well as personality and social development theories. They used
the multiple regression model, univariate logistic regression model and the multivariate logistic
regression model. They concluded that intention to smoke, positive and negative attitudes toward
smoking, impediments to smoking, self-efficacy to resist smoking, parent norms, and academic
success most strongly predicted current smoking. Also parental relatedness, maladaptive coping
strategies, depression, and low academic aspirations most strongly predicted susceptibility to
smoking for those who had not yet smoked a cigarette.
13
Smet et al (1999) investigated on the determinants of smoking behavior among adolescents in
Semarang, Indonesia. A random sample of schools in Semarang (population at that time was 1.5
million) was obtained using a stratified sampling procedure (strata based on type of school and
district). A total of 149 schools were selected. Within the schools 186 classes were selected and
their investigations were based only on male adolescents mainly targeting the following ages 11,
13, 15, and 17 year olds. The students from the selected schools answered questionnaires.
Logistic regression was used to investigate the outcome and the results showed that the smoking
behavior of best friends was the most powerful determinant of smoking, and this proved to be
consistent across all age groups. Best friends‟ attitudes towards smoking and older brothers‟
smoking behavior were also found to be important determinants of smoking by respondents.
2.3 Conclusion
Literature has shown that tobacco smoking just like any other goods and commodities is
influenced by ones desire to maximize utility which in this case is derived from one achieving
his or her expectancies due to smoking if positive to him or her. If the expectancies are negative
then one will reduce smoking so as not to reduce utility and thus these expectancies are the ones
that influences‟ ones smoking behavior. Thus it is also shown that the availability of information
plays a vital role on ones‟ decision to smoke. Proximal and distal determinants have shown to
have major influence on tobacco smoking and most empirical studies have proved to be
consistent with theory.
14
CHAPTER 3
METHODOLOGY
3.0 INTRODUCTION
This chapter will contain the specification of the econometric model used and the justification of
the variables basing on the literature review contained in the previous chapter. Data collection
methods are also shown since the research uses primary data. This chapter also contains
diagnostic tests that will be carried out in the next chapter.
3.1 Model specification
Previously different models were used mainly due to the different types of data used by the
different researchers. Some researchers used the multivariate logistic regression models,
polytomous logistic regression and multiple regression analysis model which was used by
Carvajal et al (2004). In order to measure the parameters of the determinants for tobacco
smoking the author is going to adopt the multiple regression analysis model which was also used
by Carvajal et al (2004). According to Maddala multiple regression is when a model has two or
more explanatory variables. The model will have the function
Sm = f (Edu; Occ; Inc; Ag; Adv; Sb; G)
The model will be specified as follows
Sm = β0 + β1 Edu + β2Occ + β3Inc + β4Ag + β5Adv + β6Sb + β7G + ε
Were:
Sm is a dummy showing whether one is a smoker or non smoker
Edu is a dummy variable showing the level of education
Occ is dummy variable showing whether one is employed or not and the type of
employment
15
Inc shows the income level of the respondent
Ag
shows the age of the respondent
Adv is a dummy showing the influence of advertising
Sb shows the social background of the respondent
G is the gender of the respondent
ε is the error term
β0…7 are the parameters of the model
3.2 Justification for the Choice of Variables
3.2.1 Smoker/nonsmoker
It is the dependant variable. This variable shows whether one is a smoker or a non smoker and it
is a dummy variable which takes the value of zero if the respondent is a non smoker and one if
the respondent is a smoker.
3.2.2 Level of education
It is the level of education of the respondent and an explanatory variable. It is generally believed
that those who attained a higher level of education have much knowledge about the dangers of
smoking than with lower educational levels. It is a dummy variable and the levels of education
will be subdivided into the following categories. No education at all will take a dummy of zero,
attained primary level will take a dummy of 1, attained up to high school will take a dummy of 2,
attained up to diploma level will take a dummy of 3 and those with a degree and above will take
a dummy of 4. Thus it is assumed as the level of education increases the number of smokers in
the groups must decrease as well as the average number of cigarettes smoked.
16
3.2.3 Occupation
Occupation of the respondent and it is a dummy explanatory variable which takes a value of zero
if respondent is unemployed, 1 if self employed, 2 if employed doing a blue collar job and 3 if
employed for a white collar job. It is hypothesized that those who do white collar jobs tend to
smoke less than those who do blue collar jobs and those who do not work at all.
3.2.4 Income level
An explanatory variable which will show us the range of the Income the respondent falls in. the
variable is also a dummy variable and will take the following values those with income ranging
from zero to $100 will take a value of zero, 1 for those ranging from $101-$300, 2 for those
ranging from $301-$500, 3 for those ranging from $501-$1000 and 4 for those earning from
$1001 and above. It is believed that one of the reasons for smoking is to reduce stress and also
believed that income level also influences levels of stress. Those with higher levels of income
have lower stress levels than those with lower income levels. Thus those with higher income tend
to smoke less than those with lower income levels. Also those with higher income have greater
chances to access information on the hazards of smoking as well as detailed health advice from
private clinics and doctors.
3.2.5 Social background
Social background is a dummy explanatory variable which shows the background of the
respondent. It takes a value of 0 if no friend or relative smokes, 1 if there is a family member or
friend only who smokes and two if both friends and family smoke. It is generally believed that
those who have family members or friends who smoke have high chances of ending up smoking
as well. Thus ones‟ social background has a high influence on ones‟ behavior.
17
3.2.6 Age
It is an explanatory variable which shows the age of the respondent whether a smoker or a nonsmoker. Generally it is believed that the youths are very experimentive about certain things and
therefore are highly likely to smoke more than the elders.
3.2.7 Gender
Refers to the gender of the respondent and it is a dummy explanatory variable that takes a value
of 0 if the respondent is female and 1 if respondent is male . It is generally believed that the male
members of a society are the ones who are likely to smoke more than the females and thus the
young males grow with the belief that to prove their manhood have to do things such as smoking.
3.2.8 Advertising
It is believed that advertisement of cigarettes tend to influence others to start smoking especially
the youth. This is an independent dummy variable thus if a respondent feels that advertisements
played a bigger part in influencing one to smoke the value will be 1 and zero if one was not
influenced to smoke by advertisements
3.3 Diagnostic Tests
The multiple linear regression method is used through an econometric software package called
STATA. The primary data obtained from questionnaires is entered into the Microsoft –Excel
worksheet and then imported into STATA 11 program work file to test various statistics
necessary for the research.
18
3.3.1 Multicollinearity
It arises when two or more variables (or combinations of variables) are highly (but not perfectly)
correlated with each other. The term Multicollinearity is due to Ragnar Frisch (1933). Originally
it meant the existence of a perfect or exact, linear relationship among some or all explanatory
variables of a regression model.
R2 is the measure of goodness of fit to the multiple regression models and it is used to detect
Multicollinearity. A high R2 but few significant t ratios are the classic symptom of
Multicollinearity. High Pair Wise correlations among regressors are another suggested rule of
thumb. If the pair wise or zero order correlation coefficient between two regressors is high in
excess of 0.8, then Multicollinearity is a serious problem.
If Multicollinearity is not serious we adopt the do nothing school of thought as expressed by
Blanchard. When it is serious we may follow some rules of thumb which include a priori
information, dropping a variable(s) and specification bias, transformation of variables and
additional or new data.
3.3.2 Heteroskedasticity
When Heteroskedasticity is present, multiple linear regression estimation places more weights on
the observations which have large error variances than those with small error variances.
Heteroskedasticity can be tested using Breusch-Pagan or Cook-Weisberg test
for
Heteroskedasticity.
3.4 DATA SOURCES
The researcher used primary data obtained from Kadoma urban residents who are of the age
groups 15 years and above. The author used 15 as the minimum age because it is generally
believed that those who indulge into smoking early usually start at this age. The researcher used
Kadoma urban so as to reduce the cost of travelling since he also resides in Kadoma urban. The
author drafted a questionnaire which targeted both smokers and non-smokers to collect data.
The study used 16 wards which fall under Kadoma urban. According to 2002 population census
Kadoma urban has a population of about 76 351(zimstats 2002). The census of the same period
also showed that the total population for people of the age 15 and above is 49 307 Within the 16
19
wards we have high density suburbs, medium density suburbs and low density suburbs. The
samples drawn from each ward will be in proportion to the number of households in the ward.
The author used two sampling techniques which are stratified sampling and simple random
sampling. First the wards were divided into 3 strata namely high density suburbs, medium
density suburbs and low density suburbs. In stratified sampling the population is partitioned into
groups, called strata, and sampling is performed separately within each stratum. Each stratum
will have households of the same characteristics that is high density, low density or medium
density. Having divided the wards into strata with homogenous characteristics systematic
random sampling will now be used drawing proportionate samples from each stratum.
Systematic random sampling was used to select the household from where to interview an
individual in the desired age group in each of the stratum of the 16 wards. Systematic sampling is
a statistical method involving the selection of elements from an ordered sampling frame. The
researcher used the house numbers which were available in every street of the suburbs and this
was used as a sampling frame. Systematic random sampling is applicable only if the given
population is logically homogeneous because systematic sample units are uniformly distributed
over the population. From the sampling frame, a starting point is chosen at random and choices
thereafter are at regular intervals (K).
K =N/n: where n is the sample size and N is the population size.
Each household in the population has known and equal probability of selection. According to
Krejcie and Morgan model of determining a sample size for a given population, the best sample
size giving a 95% confidence interval for a population of 49 307 will be 381. Thus for the best
results to be obtained a sample size of 381 will be used. This sample will be drawn from the
households of the 16 wards and will be proportionate to the number of households within each
ward.
20
Ward number
No of households Population size
Sample size
1
1888
7966
40
2
1783
6591
33
3
1086
4796
24
4
1200
4688
23
5
1403
5501
27
6
1553
6765
34
7
1006
3926
20
8
1896
7637
38
9
1332
5361
27
10
1017
4324
22
11
1281
5105
25
12
521
2236
11
13
566
2445
12
14
196
1482
7
15
1156
5170
26
16
584
2358
12
Above is a table showing the wards, number of households in each ward, the population size in
each ward (the source of the data is the central statistics office publications of the 2002
population census) and the sample size of respondents to be drawn from each ward as calculated
by the author. The sample size for each ward was calculated to be in proportion to the total
population of each ward using the formula below:
Sample size for ward i = Ni / N
for all i=1;2;…;16
Were Ni is the total population for the ith ward
N is the total population for Kadoma urban
For the selected households, questionnaires were administered to them to fill in the requested
information. The researcher used both closed ended and open ended questions. With the use
21
closed ended questions, quantification of data was carried out easily and effectively. Also open
ended questions were used because they allow the respondent to give a detailed and adequate
answer given the leeway to answer in their own expression or own words. The use of
questionnaires has the general advantages of versatility, speed and lower costs. Versatility refers
to a technique`s ability to collect information on the many types of primary data of interest for
example demographic or socioeconomic characteristics and lifestyle.
3.5 Conclusion
The multiple linear regression model adopted in this research has been constructed in accordance
with the law of parsimony. The model used is believed to be consistent with theory and also its
coefficients will also take signs that are consistent with economic theories. The model is believed
will sufficiently satisfy the objectives of the research.
22
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