Hypertension and risk factors in Kenya An analysis of Kenya National Health Survey.
Silvia Nanjala Walekhwa
Master Thesis
Department of Health Management and Health economics Faculty of Medicine
UNIVERSITETET I OSLO
May 15, 2018I
© Silvia Nanjala Walekhwa 2018
Hypertension and risk factors in Kenya: An analysis of Kenya National Health Survey
Silvia Nanjala Walekhwa http://www.duo.uio.no/
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Abstract
Hypertension is a prevalent risk factor of Cardiovascular and it has been escalating in developing countries including Kenya twice as much as developed countries.
Nations rely on evidence to formulate informed policies. Therefore this study’s aim was to provide a link of risk factors to hypertension, systolic blood pressure and diastolic blood pressure using Kenya National Survey data collected in 2015.
The study used quantitative methods to examine the link between tobacco use and
other risk factors and development of hypertension. The results of the study
indicate high prevalence of hypertension and among risk factors: body mass index
(BMI), alcohol, waist hip ratio and tobacco use was high in males than female
among those who were hypertensive as well as very low awareness status in the
population with hypertension. Tobacco use was found as a protective factor to
systolic blood pressure but its protective link to diastolic or hypertension lower
odds was not statistically significant. BMI, age, waist-hip ratio and alcohol use
were prevalent risks to all the three outcome: hypertension, systolic blood pressure
and diastolic blood pressure. Healthcare authorities and policy makers could use
this results in making health promotion and intervention policies.
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Acknowledgement
First and foremost I would like to thank Almighty God for the grace of my life and all the people He put on my path for this achievement.
Secondly I would like to express my gratitude to my supervisor Professor Adnan Kisa, who ensured that I remained on track and gave valuable remarks that improved my work. I also thank my assistant supervisor Eliva Atieno Ambugo who gave me valuable information on my analytical design and study method. I appreciate for all the time and patience that they gave me.
I would also like to thank the University of Oslo for giving me the opportunity to do my masters in Health Economics Policy and Management. I thank the faculty of medicine and my department at large.
I want to thank my family for standing by me in days that seemed stressful. My parents Alfred and Seraphine Walekhwa and all my siblings especially my twin sister Caroline. Sister Margret thanks for all the phone calls of encouragement, thanks sister Angel for love and prayers and all my nieces and nephews.
My friends here in Norway and in far off places are highly appreciated not forgetting my doctor who sustained my health when it was deteriorating.
Last but not least I want to thank my Fiancé’ Carl-Birger for perseverance care and
love he gave me while I was busy with the thesis. Together with his parents, I just
want to say thank you.
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Table of Contents
Abstract ... ii
Acknowledgement ... iii
List of Tables ... vi
List of Figures ... vii
List of Graphs ... viii
CHAPTER ONE ... 1
1. Introduction ... 1
1.1. Background ... 2
1.2. Hypertension and Tobacco prevalence ... 2
1.3. Rational of the study ... 5
1.4. Objective ... 6
1.5. Kenya in a snapshot ... 7
1.5.1. Health profile ... 7
1.5.2. Socio-economic status ... 8
1.5.3. Policies development and implementation ... 9
CHAPTER TWO ... 13
2. Literature Review ... 13
2.1. Tobacco and blood vessels ... 13
2.2. Review of studies ... 14
CHAPTER THREE ... 17
3. Methodology ... 17
3.1. Description of STEPwise 2015 survey design ... 17
3.2. Data Collection Procedures ... 18
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3.3. Study measures ... 19
3.4. Limitation ... 22
3.5. Analytical design ... 22
3.6. Analyses ... 23
CHAPTER FOUR ... 24
4. Results ... 24
4.1. Characteristics of the study population ... 24
4.2. Risk factors prevalence among participants ... 29
4.3. Risk factors prevalence among hypertensive participants ... 29
4.4. Linear regression of systolic blood pressure and diastolic blood pressure on tobacco use ... 35
4.5. Multiple Logistic regression ... 38
4.5.1. Sensitivity Analysis ... 38
CHAPTER FIVE ... 40
5. Discussion ... 40
5.1. Main findings ... 40
5.2. Strengths and limitation ... 43
5.3. Further research ... 43
CHAPTER SIX ... 45
6. Conclusion ... 45
Reference ... 46
Appendix ... 55
VI
List of Tables
Table 1.1 FCTC demand and supply measure to combat Tobacco use ... 10 Table 1.2 Kenyan Tobacco policy in relation to MPOWER strategies ... 12 Table 4.1 Demographics characteristics of participants’ hypertension status and tobacco use status ... 26 Table 4.2 Descriptive statistics of physical measures and continuous variables ... 28 Table 4.3 Risk factors in full sample and in people with hypertension by gender ... 31 Table 4.4 Awareness and Health utilization among people in the selected Hypertension risk factors ... 33
VII
List of Figures
Figure 1.1 Current tobacco smoking in 15 years plus,2012 estimates by WHO regional grouping and World bank groups ... 4 Figure 1.2: Systolic and Diastolic distribution in both and by genders Box plot ... 28
VIII
List of Graphs
Graph 1.1 Gender distribution within residence area and wealth levels ... 25 Graph 1.2 Prevalence of Hypertension ... 30
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CHAPTER ONE 1. Introduction
This study seeks to establish the relationship between tobacco and three blood pressure parameter outcomes; systolic blood pressure, diastolic blood pressure and hypertension. The study further considered common risk factors in development increased levels of the three outcome. The purpose of the study was based on escalating burden of hypertension while the field to the knowledge of risk factors is filled with mixed effects especially about tobacco use. In addition Kenyan studies had been done on regional settings that did not provide clear representation of the country. Hence the anticipation of the study was to provide a clear effect that presents the country population. The research employed quantitative analysis using IBM SPSS version 25 and Stata 15 to explore data from the national survey that included adults aged 18-69 and non-institutionalised.
The study starts with an overview of the burden of the situation and gives a contextual framework for the study, then follows rational of the study and research question. Included in the chapter is a synopsis to understand Kenyan general demographics, social-economic status, health profile and adherence to policy set for risk factor control as well as the country initiatives.
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1.1. Background
Cardiovascular diseases (CVD) are the major source of worldwide high burden attributed by non-communicable diseases, as CVD account for about 45% mortality of the 40 million NCD, (Global Health Observatory, 2016; WHO, 2015). Nevertheless, most of the deaths occur prematurely at an age below 70years and more alarming is that majority are in low and middle income countries (LMIC). For instance in 2015 there were 17 million NCD premature deaths and more than 80% of them occurred in LMIC and over one third was attributed by CVDs, (Global Health Observatory, 2016). CVDs could be referred to as unique conditions of the heart and blood vessel that are essentially and generally caused by common exposure to or trait of a person’s character, (Pathways & Pathways, 2010). Among these sets of risk factors that include habitual individual behaviour such as smoking and metabolic factor such as hypertension, they also interplay with each other particularly smoking as a risk factor to Hypertension, (World Health Organization, 2004).
1.2. Hypertension and Tobacco prevalence
Hypertension stands as one of the dominant risk factor to CVDs and about 1.13 billion people are exposed to this ill-health globally. The studies show that hypertension remains undiagnosed in many individuals especially in Sub-Saharan Africa due to the disease non-evident symptoms, (Addo, Smeeth, & Leon, 2007; WHO, 2009), which later leads to direct or indirect premature deaths as a result of complexities in untreated patients or late diagnosis, (Addo et al., 2007;
Lancet, 2017; Mills et al., 2016). The most common health impacts resulting from high blood pressure include acute myocardial infarction, strokes, cardiac failures and renal failure among others, (WHO, 2014).
Studies suggest that there is an escalating rate of high blood pressure mortalities in LMICs which is about twice of that in high income countries. For instance, 7% and 25% of individuals in high income countries and Africa respectively are likely to die below their 60th birthday due to blood pressure, (Hall, Thomsen, Henriksen, & Lohse, 2011; Mills et al., 2016; van de Vijver et al., 2013; World Health Organization, 2017). A systematic review on Sub-Saharan Africa also indicated similar findings with varying evidence on the prevalence of high blood pressure in the
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region generating a median of 29%, (Ataklte et al., 2015). Nevertheless, continuous evidence in various regions indicate that with rural-urban migration, there seems to be higher hypertension prevalence of between 9%-50% among urban settlers, which has also been reflected in some of the Kenyan studies, (Abajobir et al., 2017; Aliyu, Chiroma, Jajere, & Gujba, 2015; M.D. et al., 2014; Mathenge, Foster, & Kuper, 2010).
A study on CVD causes of death in Kenya found 13.2% prevalence of CVD and hypertensive heart disease prevalence of about 9%, (Ogeng’o, Gatonga, & Olabu, 2011). In a reported survey of 2015 the prevalence of raised blood pressure was 23.8 (SBP≥140 and /or DBP ≥90) while severe hypertension was 8.4% (SBP≥160 and /or DBP ≥100) with high prevalence in women than men of 9.4% and 7.5% respectively. Nevertheless, awareness and control of the condition still remains a challenge as studies have indicated in some settings where the subjects were aware of their condition but were not on medication or instances where high percentage of the subjects were not aware of their condition or risk factors involved, (Awino, Ogonda, Barno, &
Magak, 2016; Ministry of Health, Kenyan National Bureau of Statistics, 2015; Temu et al., 2017).
Dangers of tobacco use are well established even though there could be some probability of lack of awareness of association to specific health conditions, but there are various studies that have widely indicated the behaviour’s risk to CVDs. Smoking has been a global major risk factor on various CVD condition including; stroke, peripheral vascular disease, coronary heart disease, hypertension and cancers among others, (Buttar,Hapar.S., Li, & Rav, 2005; U.S. Department of Health and Human Services, 2010) On a global level it is reported that 63% to 68% NCDs attributed death of all mortality majority are highly associated with tobacco, (Mendis et al., 2011, 2014; WHO, 2008). Yet a number of the deaths occur at the age below 60 years with higher percentages in developing countries than the higher income countries of about 29% and 13%
respectively, (Mendis et al., 2011). Furthermore, an estimate of 12.7% of the 7 million tobacco death mortality is due to secondary smoke exposure (Initiative, 2011).
Health hazards persist even with reported reducing estimates across demographics and socio economic status worldwide, as smoking prevalence is continually on the rise among the people in the developing countries and it is estimated that by 2030 more than 80% of eight million
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premature deaths worldwide will occur in LMIC as a result, (Convention, Control, & Fctc, 2011;
Mendis et al., 2011; WHO, 2008; Ng et al., 2014). The prevalence and preferential differences is also portrayed between gender in the region, with high tobacco smoking among men while females prefer smokeless tobacco, (Abajobir et al., 2017; Brathwaite, Addo, Smeeth, & Lock, 2015; Who, 2013).
Figure 1.1 Current tobacco smoking in 15 years plus,2012 estimates by WHO regional grouping and World bank groups
AFR=African Region AMR=Region of the Americas
SEAR =South-East Asia Region
EUR=European Region EMR=Eastern Mediterranean Region
WPR=Western Pacific Region
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Source: Global status report on NCDs 2014
Abajobir et al. (2017) insinuation that, smoking tobacco causes extreme burden than smokeless worldwide, was earlier disputed by W.H.O and other studies indicate that any form of tobacco is highly addictive and have grave consequences: disease, disability and death occur even though the onset could be in the future of the behaviour. Hence smokeless may not be used as a cessation to quit smoking or as an alternative for a prospective smokers, (Boffetta, Hecht, Gray, Gupta, & Straif, 2008; Gupta & Sreevidya, 2004; Underner, Perriot, & Peiffer, 2012; World Health Organization, 2015).
Accordingly Kenyan tobacco prevalence indicated in Global Adult Tobacco survey (GATs), shows that there are 2.5 million adults of 15 years and above that are currently using tobacco both smoking and smokeless while more than 3.1 million and 2.1 million exposed to secondary smoke in bar or clubs and restaurants respectively (GATS 2014). While among the youths of 13- 15 years, tobacco use prevalence was approximately 10% with the male using more tobacco (12.8%) than the females (6.7%) which is alarming as a risk of ill-health, (Maina et al., 2013).
1.3. Rational of the study
Thus smoking and hypertension pose alarming consequences individually as well as increases concern when exhibited in the same individual, (Nadar & Lip, 2015). This particular modifiable risk need to be better understood to be able to generate suitable control measures, which may result to improved health and reduced mortality and morbidity due to the elimination of the double shared risk it poses. Information on ill-health within sub-Saharan Africa is scarce and is not any different with Kenya. However new developments by W.H.O to monitor NCDs has improved the surveillance of common disease in Kenya on different levels.
Therefore there are studies in Kenya that have been done in several different settings to establish the relationship of these two risk factors, but there appears to be mixed findings indicating lack of association while others show that there is a risk on smokers in developing hypertension, (Joshi et al., 2014; Olack et al., 2015; Onyango, Kombe, Nyamongo, & Mwangi, 2017;
Salehmohamed, 2010; Temu et al., 2017). There is still limited evidence however on smokeless
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tobacco which has been shown with a high uptake in females and the high prevalence of hypertension among women. Hence, understanding that health hazards present differently in populations and with the diversity of the Kenyan population in ethnicity, regional and socio economic status; thus a better understanding on the link between tobacco use and hypertension will assist health authorities and policy makers in making health promotion and intervention policies.
1.4. Objective
To investigate the association between tobacco use and hypertension in the Kenyan population and assess link in other risk factors.
Research questions
How is tobacco use (smoking and smokeless) associated to hypertension?
What are the risk factors in hypertensive individuals in Kenya?
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1.5. Kenya in a snapshot
Kenya lies along the equator on the Africa’s East Coast and gained its independence from the British colony in 1963. The republic has 224,960 sq. miles of land area occupied with a population of about 48 million (The World Bank, 2017) and another 5,200 sq. miles area covered with water. The country shares borders with Uganda, Tanzania, Ethiopia, Somalia and Southern Sudan as well as Indian Ocean that lies on the South East. The country’s 2010 constitution introduced the present 47 counties in which people involvement governance as well as improved policy implementation is the perceived counties’ ultimate objective, (Kabogo & Kabogo, 2016; Kenya National Bureau of Statistics (KNBS), 2016). The countries urban population is increasing as most industrial and manufacturing plants are centralized in urban areas and as rural farming land become scarce, (KNBS, 2016).
1.5.1. Health profile
Kenyan population comprises 49% males and 51% females and their life expectancy at birth is estimated at 64.7 and 69 for men and women respectively based on the country demographic survey (DHS) that analysed all 47 counties, (KNBS, 2014). Women fertility rate is 4 per woman but with variation among counties ranging from 2.3 to 7.8 in Kirinyaga and Wajir respectively. In every 1000 live births there is an estimated infant mortality of 39, child mortality of 14 and 43.4, under-5 mortality. Kenya is also transitioning from the various communicable diseases such as malaria, HIV-AIDs, tuberculosis among others to increasing levels of non-communicable diseases including cancers, diabetes and cardiovascular diseases due to behavioural changes and probably rural-urban migration, (KNBS, 2014; Ministry of Health, KNBS, 2015)
Kenya is a country determined to give the population the highest possible health standards as outlined in 2010 Kenyan constitution which is in line with the global needs. Thus, the driving health policy 2014-2030 is a manifestation to general status of Kenyan health improvement, focusing on: equity assurance, efficiency, participant approaches, patient-centeredness and health service delivery societal liability. The policy further focuses on essential rights to health and freedom of vulnerable members of the society including; youths, children, the minorities, persons with disability among others stressing on the need to engaging all actors to harness and synergize health services delivery in every part and levels, (Ministry of
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Health, 2014). Nevertheless, as CVDs cost continue to rise and especially the burden of hypertension as shown in a recent study by Subramanian et al. (2018) in which stroke admissions and chronic kidney dialysis posed the highest treatment cost with varying rates in regards to public service ($1874 and $5,338) or private ($16,711 and $11,024) respectively.
And this could be a challenge in health financing as well as a hindrance in achieving the policy objectives. As a matter of fact Kenya is financed through a mixed system (government-3.3 billion and private/donor-5.5billion) yet the most dominant is the private which includes out of pocket payments 2.1 billion in 2014, thus equity and accessibility could not be achieved, (IHME, 2016).
To combat NCDs however, Kenya has developed a specific national policy in line with global health needs for prevention and control of NCDs. The document lays priorities on how to tackle the epidemic by integrating existing global initiatives as well as the existing national action plans, legislations, policies and strategies to better facilitate implementation. Main objective of the strategy is to generate and provide evidence based interventions for prevention and control of NCDs that will lead to a reversed increasing trend of morbidity and mortality as well as the cost burden, with a vision to a nation that is free from the burden of preventable NCDs by 2020, (Ministry of of Health, 2015). However, this document focused only on four major NCD conditions that included CVDs and as shown previously the escalation of raised blood pressure in the past 20 years remains to be a key modifiable risk factor for CVDs and especially for stroke, (Ministry of of Health, 2015; WHO, 2014).
1.5.2. Socio-economic status
The Kenyan population of age 15-49 literacy level is high in men (97%) than women (88%) but with realized variance in the counties with male having above 70% in all 47 counties while in females 4 counties are below 50% literacy level with more than half the counties (27) at above 90% literacy level. Wealth reflects a big gap but on a reducing level within the population, (KDHS, 2015).
Kenya relies on agriculture as its economic backbone and is the highest contributor to the nation’s Gross Domestic Product (GDP), accounting for almost 30% while crop production sector plays as rural population key occupation, (Report, 2011). The counties in rural Kenya
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are rife for tobacco production with Nyanza county accounting for about 80% of the total tobacco leaves, (Otieno & Ofulla, 2009; World Health Organization, 2011a). Major tobacco manufacturing production in the region is also done in Kenya with British American tobacco as one of the key leading tobacco industries employing about 450 individuals as active labourers, (British American Tobacco (BAT), 2016). It also contracts 5100 farmers for tobacco production, providing them with seeds, fertilizer and cash, (BAT, 2016). Ministry of health and ministry of agriculture are entitled to assist the farmers out of the trade but they are challenged due to the bond and lack of an appealing replacement for the farmers.
Kenya has a steady economy with $2,925 per capita GDP with less than 10% growth and mostly shaken with political instability in some periods, (IHME, 2016). Unmanufactured tobacco contributes approximately 7% to the GDP in Kenya and has a gross value of about
$17million, (FAOSTAT, 2014; Kenyan Ministry of Health & Kenya National Bureau of Statistics (KNBS), 2014a) with total production and importation of about 35000 tonnes, (FAOSTAT 2013). However, a recent economic survey indicate 4.4% decline in tobacco production which was mostly contributed by the 4.7% decline in cigarette production as other tobacco products had 19% approximate increase in 2015, (KNBS 2016). At this point it is important to note that if individuals change to consume more of the other tobacco products, the burden of disease will still exist as this products affects human in the same manner only with differentiated diseases. Such effects include mouth and oropharynx cancers
1.5.3. Policies development and implementation
Policies play as an elaborate procedure in the quest to change societal behaviour, which may remain quite constant over time but, ultimately with probable steadily increasing change due to the efforts from relevant agency, legislators and any interested parties, (Handbook &
Policy, 1971). Thus, policies to alter behavioural risk factor such as tobacco use which remains to be a major cause of avoidable deaths can go a long way in reducing the epidemic.
Accordingly, W.H.O consented in plea to fight the epidemic through the institution of FCTC treaty which becomes a legal obligation to member countries on ratification and the treaty requires involvement of various stake players within the country to be able to implement and enforce it, (WHO, 2016).
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The FCTC is dedicated to the supply and demand of tobacco as well as environment protection and clarifies the need of; formulating national strategies, packaging and imagery of health warning labels on tobacco products, tobacco taxation increase, protection from second-hand smoke, advertising, promotion and sponsorship bans, support for sustainable economic substitutes and tobacco product content disclosure among others, (Saúde WHO FCTC, 2005).
Table 1.1 FCTC demand and supply measure to combat Tobacco use Reduction of tobacco demand measures
Article 6: Price and tax measures to reduce the demand for tobacco
Article 7: Non-price measures to reduce the demand for tobacco
Article 8: Protection from exposure to tobacco smoke Article 9: Regulation of the contents of tobacco products Article 10: Regulation of tobacco product disclosures Article 11: Packaging and labeling of tobacco products
Article 12: Education, communication, training and public awareness
Article 13: Tobacco advertising, promotion and sponsorship Article 14: Demand reduction measures concerning tobacco dependence and cessation
Reduction of tobacco supply measures
Article 15: Illicit trade in tobacco products
Article 16: Sales to and by minors
Article 17: Provision of support for economically viable alternative activities
Source: (WHO FCTC, 2005)
The treaty also covers issues with information sharing and technical cooperation as well as liability matters within and internationally. The convection main objective being to protect all current and upcoming generation from tobacco ill health and social economic impact, (Saúde WHO FCTC, 2005). In addition as endorsed in the global action plan the set projections are to achieve a relative target of 30% prevalence reduction by 2025 in
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individuals of 15years and above as well as ultimately reducing premature deaths from NCDs by 25% by the same year, (WHO, 2009; WHO, 2016).
Since the initiation of this multilateral treaty, there are 180 signatory and several parties have ratified and implemented most of the FCTC components ranging from approximately above 10% and below 88%, (WHO, 2016). In a research on the Sub-Saharan Africa region FCTC compliance, there was varying implementation status and yet some of the countries such as Malawi had not ratified the treaty at all, (Brathwaite et al., 2015). Even so, a 10 year FCTC implementation progress report indicate improvement in the African region, (Tumwine, 2011).
The implementation of the treaty was further enabled by WHO initiation of supportive policies for member countries utilization. These strategies (MPOWER as illustrated in the table in the next section) are key factor to expedite FCTC implementation in simple and probably effective way.
1.5.3.1. Current Kenyan Tobacco policy
Kenya was among the first WHO members to ratify the FCTC within the five initial years, which lead to introduction of tobacco control policy of 2007 (TCA, 2007). The policy change came with challenges especially from the manufacturing company with different legal cases but with continued amendments the policy meets the FCTC Components in many aspects and with a triumph in the legal battle against the tobacco companies, (KETCA, 2017). In an overview of policy status in Africa it emerged that Kenya had the highest rate of implementation (78%) compared to 9% in Sierra Leon which indicate a good level of adherence to WHO FCTC and MPower package, (Husain, English, & Ramanandraibe, 2016).
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Table 2.2 Kenyan Tobacco policy in relation to MPOWER strategies
MPOWER FCTC KENYA
Monitor tobacco use
Article 20: surveillance to monitor the impact of tobacco use and tobacco prevention
Sect.7 Fund to facilitate research on tobacco and dissemination of information as well as to promote the country cessation and rehabilitation programs
Protect people from second- hand smoke exposure
Article 8: complete smoke-free environment laws
Sect.32 & 33 Right to smoke-free environment and forbidden smoking areas: no smoking in public place except in the secluded smoking areas.
Offer help to quit tobacco use
Article 14: promotes tobacco cessation and treatment for tobacco dependence through appropriate programs and services
Sect.9 & 11: Government to initiate
knowledge sharing and
communication to promote public awareness focusing on the basic social units of the society.
Warn about the dangers of tobacco
Article 11: use of large pictorial warning labels on tobacco packaging
Sect.21 Required package information Warning in Swahili and English above 30% and 50% of the front and back respectively of the total surface
Raise taxes on tobacco
products
Article 6: promotes the adoption of tax and price policies on tobacco products.
Sect.12 implement tobacco tax and price policies as well as prohibit importation and sale of tax free tobacco products
Source: (The Republic of Kenya, 2012; WHO, 2008)
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CHAPTER TWO 2. Literature Review
Tobacco use in all form either as smoke or smokeless has detrimental impact on health while on the other hand hypertension has also been on the rise in populations causing high mortality and morbidity through other complications yet this two risk factors have another interaction and various studies have been done to understand this relationship and identifying those at risk. This chapter will focus on discussing available previous studies that identified specific association of tobacco use to hypertension or raised blood pressure. First, an insight of probable mechanism on how any form of tobacco use could facilitate the raise in blood pressure will be discussed thereafter a review of studies.
2.1. Tobacco and blood vessels
Regardless of many other chemical components in tobacco, the main constitute that is susceptible of increasing systolic blood pressure is nicotine as it has the capability to trigger sympathetic nervous system, (Benowitz & Gourlay, 1997). The blood pressure upsurge is shown to be facilitated through direct stimulus of postganglionic sympathetic nerve endings, which also increases concentration of norepinephrine and epinephrine plasma, (Grassi et al., 1994).
Smoking in particular may accelerate the plague building on the artery walls thus, narrowing the artery and this could be due to the high levels of oxidized low density lipoprotein that is taken by macrophages, and secondly smokers are associated with impaired arterial vasodilation which is also associated with the impaired release of nitric oxide which is believed to be contributing factor of acute CVDs and hastening of atherogenesis, (Benowitz & Gourlay, 1997; Harats et al., 1989; Higman, Greenhalgh, & Powell, 1993) In addition, nicotine and other smoking elements are directly responsible on the effect of the heart rate and vessel constriction which is presumed to be due to the impairment of the baroreflex sensitivity, (Giannattasio et al., 1994; Mancia, Groppelli, Di Rienzo, Castiglioni, & Parati, 1997). Thus unmatched heart blood-flow needs and limited artery function as well as inactive neuro response could lead to various heart diseases, (Benowitz & Gourlay, 1997).
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2.2. Review of studies
In a cross sectional study, Primatesta, Falaschetti, Gupta, Marmot, & Poulter (2001), assessed association of smoking and blood Pressure . Using three year annual national representative health survey sample for England, authors investigated the difference in blood pressure among smokers and never-smokers of ages equal or above 16 years. The results of a linear and logistic regression having adjusted for age, gender, alcohol, body mass index and social class; indicated that on a stratified age or gender, higher blood pressure levels were among those who smoked 10-20 cigarettes a day. However the results also showed that an increasing systolic blood pressure was present in alcoholic men drinkers at an increasing rate of smoking while there was no high systolic blood pressure in non-alcoholic men drinkers. The female finding irrespective of the alcohol intake behaviour was distinct in that light smokers reported a lower systolic blood pressure than non-smokers. In summary the authors concluded that the existing interaction with age, gender and BMI as well as alcohol intake renders a small association of smoking on blood pressure.
Another cross –sectional study in India which included 319 female subjects within age range of 20-70 was conducted to determine hypertension predictors among un-pregnant women, (Bhatt, Sharma, Gupta, Sinha, & Mehrotra, 2017). In analysing the predictors the study used Pearson‘s correlation coefficient linear regression and multiple regression to assess relation between variables and the identification of associated risk factors to hypertension. Results from a univariate linear regression significantly identified that systolic blood pressure was associated to age, smokeless tobacco use and BMI while high body mass index was the major predictor of diastolic blood pressure. Systolic and diastolic were mutually associated with high BMI as well as lower level of education but only systolic blood pressure was explained by higher age and smokeless tobacco consumption.
A prospective cohort study conducted in USA among 28,236 females of age 45 or above to determine the association of cigarette smoking on incidences of developing hypertension, concluded that regardless of the strong association of cigarette use on hypertension, women who smoked over 15 cigarettes daily were the strongly affected with the increased incidences of
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hypertension, (Bowman, Gaziano, Buring, & Sesso, 2007). This study calculated the hazard levels using Cox proportional hazards models with a 95% confidence interval of risks of hypertension. Using never smokers as a baseline, women who smoked daily 1-14 cigarettes had adjusted hazard ratio of 1, 02 (95% CI, 0.92-1.13) and the subjects who smoked over 15 cigarettes daily had age adjusted hazard ratio of 1,10 (95% CI, 1.01-1.19). These hazard ratios further increased when subjects were stratified in BMI categories (normal, overweight and obese) to 1.11 and 1.21, for 1-14 cigarettes and over 15 cigarettes respectively.
A similar study above but ascribed to 13529 men in USA, was also a prospective cohort study of male with ages 40-84 used Cox proportional hazards models to determine the incidental risk of hypertension and smoking. With a 14.5 years median of follow-up 4904 males were realised to have hypertension while in an adjusted model ex-smokers had 1.08 and current smokers had 1.15 relative risk of developing hypertension in comparison to never smokers. The authors neither did they find the number of daily cigarette consumption to vary among smokers risk, thus they concluded that current smoking is associated to hypertension development while an intermediate risk may still exist in ex-smokers, (Papathanasiou et al., 2015).
A study done in Brazil to estimate the prevalence and the risk factors associated with hypertension concluded that obese, overweight or former smokers were the risks to hypertension, (Wenzel, Souza, & Souza, 2009). This cross-sectional study was done among 380 male military personnel with ages ranging from 19-35years and used multiple regressions to analyse association with 90% confidence interval. This model resulted to a higher (52%) prevalence among past smokers in comparison to never smokers (90% CI: 1.13; 2.50). The authors considered the association of weight gain to ex-smokers would have been the probable factors that affected the results as prevalence set of overweight and obesity was 36%.
A South African study on risk of smokeless tobacco use on hypertension, used cross sectional data on 4092 of age 25-70 years black women, the data was analysed using ANOVA and multiple logistic regression, (Ayo & Omole, 2008). The daily eight times smokeless tobacco users, resulted in high systolic and diastolic mean (131mmHg and 84mmHg) as compared to never users (121mmHg and 77mmHg). Even though the authors found hypertension prevalence to be high (23.9%) among snuff users than non-users (17%), the association lacked to indicate
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significance as a risk factor having adjusted for other confounders. In conclusion the authors pointed out that the amounts of snuff consumed have a detrimental risk to hypertension thus highlighted need of cession.
One of the Kenyan study evaluating hypertension risk factors in urban slum dwellers, did a cross-sectional survey that included 1528 adults of 35 and above within Kibera and found prevalence of 8.5 smoking 13.1 alcohol drinking and 29.4 hypertension, (Olack et al., 2015).
Using a multiple logistic regression, the significance of smoking as risk factor to hypertension was reduced in comparison to its independent association to hypertension with an adjusted odds ratio of 1.1 (95%CI 0.74-1.79), however age, BMI, wealth index, physical activity and marital status were associated to hypertension.
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CHAPTER THREE 3. Methodology
The aim of this research is to determine the effect of tobacco use to hypertension as well as identify risk factors characters among the hypertensives. To achieve the objective, the study utilized secondary data provided by the Kenya National Bureau of Statistics and Kenya Ministry of Health in conjunction with WHO global approach which is a stepwise surveillance strategy to NCDs risk factors, (Ministry of Health, KNBS, 2015). This data represents all-inclusive details of a national survey first ever done on NCDs risk factors and injuries. While the systematic design of surveillance employed was set to provide a platform of comparison within and across countries, (World Health Organization, 2011b).
3.1. Description of STEPwise 2015 survey design
In the population selection the survey adopted STEPwise recommendation as well as adjusting for the status in Kenyan. Thus only men and women aged 18-69 and non-institutionalized were included if willing to provide informed participation consent. Considering the 47 counties in the country a two stage stratified cluster sample yielded 6000 subjects in the rural-urban strata having considered complex survey design effect, the age-sex groups number (set at 12 year interval) and probable 80% responsiveness level as well as adjusting for ease of allocation, (Ministry of Health, KNBS, 2015)
To answer the question of this study and understand the tobacco use impact associated with hypertension, the pregnant women were excluded. Reason for this was that pregnancy induces hypertension termed as gestational among the normotensive or chronic hypertension among hypertensive females pre pregnancy or within the first 20 gestational weeks, thus there were no variables measures in the data that could control for these observation in the model, (Roberts et al., 2012) The study population from household sample of 6000, only 92% of occupied household consented for survey to a final 4500 completely interviewed subjects and for this thesis, 3% of the subjects were pregnant 0.3% constituted outlier values and analysis included only those who had less than 5% of missing values which resulted to exclusion of 0.02%
observation and retaining 4272 subjects of analysis.
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3.2. Data Collection Procedures
The survey data was gathered in three steps with a structured tool developed by WHO STEPwise, firstly by administering questionnaire interviews on sociodemographic (gender, age, marital status as well as characteristics of social economic status) and behavioural (tobacco use, diet, Physical activity and alcohol consumption as well as history of raised blood pressure, raised blood sugar, CVD among others) data. Secondly, physical measurement of height, weight, waists, hip circumference and blood pressure while in the third step, tests included blood glucose and blood lipids physical biochemical measurement done on the following day having consented to fasting requirement. Measuring tools included portable electronic weighting scale, constant tension tape for waist and hip circumference and (OMRON®) an automated blood pressure measuring instrument, (Ministry of Health, KNBS, 2015).
April 9th 2015 set off 60 days data collection field work survey, which ended 10th June 2015. The survey was administered with 20 trained teams of research assistants and health workers that worked in group of not less than five by use of eSTEPs software loaded on personal digital assistant (PDA). Prior to the commencement of data collection the groups were enhanced with;
interviewing skills, PDA usage, drawing blood technique, testing and referral procedures as well as importance of informed consent. In addition supervisors were given comprehensive data handling techniques as well as trial or mock interviews were done, (IBID).
Some of the questions included were whether the participant had recently been measured blood pressure and whether the participant was informed of the presence of high blood pressure or whether the individual was taking any medication of blood pressure or seeing a herbalist due to blood pressure. Apart from whether an individual smoked or used any smokeless tobacco, participants also reported on when they initiated the behaviour, frequency and for those who were not currently using tobacco had to report whether they ever used before, (IBID).
The second step followed immediately by taking the height, weight, then blood pressure which was measure thrice on an interval of 5 minutes apart with the help of the clinical personnel. The third step involved interviewers getting consent from the subjects and informing them to fast before the test as the test was undertaken the following day. The supervisors then backed up this information on their laptops with random spot checks and transmitted folders to a central address
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where consistency was determined by the central control team otherwise a feedback was given for rectification. In general the survey maintained numerous steps for quality assurance as well as ethical consideration for all the subjects, staff and data. The procedure was successful with exception of one mishap of the PDA that resulted to repetition of procedure on the affected subjects. Coding and data editing maintained WHO STEPS recommendation by qualified data analysists through different software including Epi Info software and statistical package for social sciences, (Ministry of Health, KNBS, 2015).
3.3. Study measures
To understand the influence of tobacco use (smoking and smokeless) on hypertension, the clarity of other predictors is necessary. As mentioned in previous chapters, different studies have identified various factors that influence hypertension in individuals which include: tobacco use, age, alcohol intake, BMI, waist-hip ratio, physical activity levels and salt intake levels among others. These variables will be tested in this study to estimate the effect on hypertension in this population.
Outcome variables
This study had three outcome variables that were tested and included hypertension, systolic blood pressure and diastolic blood pressure.
Hypertension
The core dependent variable of the study is hypertension which entails elevated arterial blood pressure. Hypertension was defined as systolic and/or diastolic blood pressure of 140 or more and 90 or above respectively, as well as those that were on antihypertensive treatment, (Pickering et al., 2005; Verdecchia et al., 2016). The hypertension variable is classified in this study as a binary outcome on the averages of the three readings of blood pressure.
Systolic and diastolic
Systolic is the pressure that indicates the force against the arterial of the left ventricle contraction and on a blood pressure measurement machine it is indicated with the upper digits of the measuring equipment. On the other hand, diastolic indicates the arterial pressure when filled
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ventricles are relaxing and dilating whereas the readings appear second from above on the measuring instrument, (AMA, 2016).
Nadar & Lip, (2015) suggest that the focus of risk assessment should be on systolic blood pressure to necessitate therapy yet tobacco use may influence these two variables differently and the elevation and reduction of systolic or diastolic pressure explains the level of hypertension.
Thus, these two variable were considered as continuous and were estimated on their arithmetic mean of the three measurement readings during the survey which were done on the same day in 2-5 minutes variance.
The primary Independent variable
Tobacco use (smoking and smokeless) is the main predictor in this study thus, the status was provided in the questionnaire by asking whether participant smoked or used smokeless tobacco and whether they ever used tobacco before. This variable considered the two questions which had binary answer yes/no and categorized it to accommodate all smokers, all smokeless user and those who have never used either cigarette or smokeless tobacco. Hence tobacco use was classified as current, former and compared to never users.
Secondary Predictors (Independent variables)
Body Mass Index (BMI)
Weight in kilogram (kg) and height in meter square (m2) were used to determine BMI. values. As indicated in previous section on how weight and height were achieved, here weight was divided by height (kg/m2). Height was expressed in cm so was converted to meter by dividing with 100.
The values were then categorized underweight was decoded as BMI<18.5 kg/m2, normal as BMI 18.5-24.9 kg/m2, overweight as BMI 25-29.9 kg/m2 and obese as BMI over 30 kg/m2, (Park et al., 2003).
Waist to hip ratio.
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Waist-hip ratio was determined by dividing waist circumference by hip circumference, and decoded as obese if men ratio >=1 and females >=0.85 while overweight if the ratio =0.8-0.84 women or ratio = 0.9-0.99 males, (WHO., 2011)
Physical Activity
Physical activity has been defined by WHO as any skeletal body movement that entails expenditure of energy, (WHO, 2004). Thus, time spend each day on various activities, for instance at work, walking, cycling, and at sports were added up and converted to minutes. For those who had less than 30 minutes a day were classified as low while those who at least had between 30-60 minutes were classified as recommended and those above 60 minutes a day as high.
Alcohol consumption
Current alcohol intake was considered as those who had been drinking for the past 12 months while all those who ever drank were classified as past alcohol consumers and then compared to those who had never drank.
Socio demographic characteristics were only categorized for those that did not have enough power for instance education level high school and above, occupational status government and non-government, retired and those unable to work.
Reliability and validity
The survey provided risk factors comprehensive information on subject and robustness in sample selection as well as the high response rate of the survey provides generalisation of this study to the population of Kenya relevant.
Secondly, the statistical methods used in the study have been tested by various studies in determining risk factors association to hypertension in different settings. Moreover, the variables
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and the measures that were employed in the study are recommended by international bodies and have also been tested in other studies.
Thirdly the procedure employed for physical blood pressure measurement is more robust to ascertain the true blood pressure of the subjects however as Pickering et al. (2005) suggest, not all subjects were measured in the mornings or evenings as it was a continuous process through the day as individuals were measured immediately after the interviews.
3.4. Limitation
The study used cross sectional survey that might be affected by non-response biasness in the sense that those at risk could have refused to consent for participation in the survey thus leading to sample non representative to the population.
Another major limitation with this survey data could also be with the self-reported behaviour which was collected on one occasion, while there is also possibility of miscomprehension of the required information for instance time linked to physical exercise for individuals could have been ballooned, (Sedgwick, 2014).
3.5. Analytical design
Newbold, Carlson, & Thorne (2012) suggest that, the preeminent investigations as well as analysis of effects and correlation of predictive variables on an outcome are probably done through multivariate regression analysis. The model provides an explanation of the dependent variable Y as a result of inclusion of various predictors X1……Xj and estimation of their effect on the outcome. A dependent variable Y thus can be categorical or continuous which also determines the appropriate multivariate model for the best fit. However, continuous dependent variable generally is characterized by an empirical model as:
Y= β0 + β1X1 + β2X2 + β3X3 +…... + βjXj + εi
The model represents a linear multivariate regression where β0 is a constant equal to Y when X is 0 (zero) and represents regression intercept while β1…βj represent predictor variable coefficients and explains the effect change on Y of each corresponding variable when others are held constant. The stochastic component is represented by εi indicating the value variance of the
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predicted continuous variable Y and the observed, (Alexopoulos, 2010; Lemeshow &
Moeschberger, 2005).
On the other hand categorical outcome is generally estimated by logistic regression and the method is most commonly in yes or no (0/1) binary outcome, (Greenland et al., 2016)
The logit model adjusted for other predictors follows that:
Y = ln (𝜋/1−𝜋) = β0 + β1X1 + β2X2 + β3X3 + β4X4…... + βjXj + εi
As in the above linear regression β0 =Y intercept while X1….Xj are independent variables with effects represented as odd ratio (β1….βj) whereas 𝜋 indicate probability of Y to be equal to 1, (Lemeshow & Moeschberger, 2005). This model procedure gives exponentiation β values as odds ratio thus considered a powerful analytical tool in assessing association factor as it offers magnitude effect of the study variable independent of other risk factors, (Chattopadhyay, 2011)
3.6. Analyses
Descriptive statistics, correlation, frequencies, as well as regression analysis were used to execute the statistical analysis in IBM SPSS 25 and Stata 15. The variables significance were evaluated by Chi square for categorical variables and t-test for the continuous variables. SPSS was used for descriptive and mean tests for comparison. Stata 15 was used to estimate the best fitting model and running the linear as well as the logistic regression. Tobacco use and all the other predictors estimated with a bivariate model to establish their individual power.
Significance set at 0.2, those that met the cut point were included in multiple regression. Using backwards stepwise regression, variables for inclusion in the final model were identified through significance and rating of Akaike's information criterion and Bayesian information criterion (AIC&BIC) by selecting the model that had the lowest AIC&BIC. Nonetheless more weight was given to rating from BIC for selection as its rating awards and/or penalises for variable contribution to the model while AIC only penalises, (Jack Lee & Chu, 2012; StataCorp, 2017).
Model 5 which provided the best fit with a high R2 that represented explanatory power of the independent and the control variables. The model was then tested on the three outcomes with the use of weighted data. Nevertheless, assumptions for the models were also tested by Kruskal–
Wallis tests and verified even though the sample in the study was quite big to average normality,
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(Lemeshow & Moeschberger, 2005). The residuals however were not constant due to two outliers that resulted to exclusion in modelling final analysis: Appendix 1b
The models are elaborated below:
Ysystolic = β0 + β1tobaccouse + β2age + β3gender + β4alc + β5BMI + β6marital-st + β7waist-hipratio + β8P-A + β9Edu + β10wealth+ β11region + β12work
Ydiastolic = β0 + β1tobaccouse + β2age + β3gender + β4alc + β5BMI + β6marital-st++ β7waist-hipratio β8P-A + β9Edu + β10wealth+ β11region + β12work
Yhypertension = ln (𝜋/1−𝜋) = β0 + β1tobaccouse + β2age + β3gender + β4alc + β5BMI + β6marital-st + β7waist- hipratio+ β8P-A + β9Edu + β10wealth+ β11region + β12work
CHAPTER FOUR 4. Results
4.1. Characteristics of the study population
The study participants included in this study ranged between 18 and 69 year old with 58.8%
females (2559) after excluding all pregnant women. Moreover the number of women in all the rural-urban setting was high within each of the wealth quantile as shown in the Graph 1.1 and each quantile presented about 20% of the participants (Table 4.1). The participants mean age was 37.82 ±13.46 with almost 70% below the age of 44 years, and about 67% being married, 40%
and 9,9% self-employed or unemployed respectively while homemaker at 24.5% and at least 47% with primary education or 7.7 ±5 years of school. In general 51% of all participants lived in rural setting across the country.
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Graph 1.1 Gender distribution within residence area and wealth levels
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Table 4.1 Demographics characteristics of participants’ hypertension status and tobacco use status
Hypertension Tobacco Use
No yes Never Current Former
Overal l
N %
N (%) N (%) prevalence N (%) N (%) N (%)
Gender females 2559 58.8% 1959
(57.5)
600 (63.4)
23.4 2379 (68.6)
115 (21)
65 (19)
males 1793 41.2% 1447
(42.5)
346 (36.6)
19.3 1090 (31.4)
433 (79)
270 (81)
Age groups 18-29 1406 32.3% 1245
(36.6)
162 (17.1)
11.5 1259 (36.3)
93 (17)
54 (16.1)
30-44 1660 38.1% 1359
(39.9)
301 (31.8)
18.1 1313 (37.8)
226 (41.2)
121 (36.1)
45-59 873 20.1% 565
(16.6)
308 (32.6)
35.3 627 (18.1)
153 (27.9
93 (27.8)
60-69 413 9.5% 237
(7.0)
175 (18.5)
42.4 270 (7.8)
76 (13.9)
67 (20)
Marital status single 774 17.8% 668
(19.6)
106 (11.2)
13.7 648 (18.7)
78 (14.2)
48 (14.3)
married 2926 67.2% 2289
(67.2)
637 (67)
21.8 2347 (67.7)
352 (64.2)
227 (67.8) Divorced
/separated
306 7.0% 223
(6.6)
83 (8.7)
27.1 474 (13.7)
118 (21.5)
60 (17.9)
Widower 346 8.0% 226
(6.6)
120 (12.7)
34.7 265 (7.6)
52 (9.4)
30 (9.0
Main work Employed 822 18.9% 631
(18.5)
191 (20.2)
23.2 618 (17.8)
117 (21.4)
87 (26) Self-employed 1744 40.1% 1364
(40)
380 (40.2)
21.8 1342 (38.7)
236 (43.1)
166 (49.6)
Unemployed 433 9.9% 345
(10.1)
88 (9.3)
20.3 307 (8.8)
85 (15.4)
41 (12.2)
Homemaker 1066 24.5% 838
(24.6)
228 (24.1)
21.4 955 (27.5)
86 (15.5)
25 (7.5)
Student 184 4.2% 164
(4.8)
20 (2.1)
10.9 174 (5.0)
4 (0.7)
6 (1.8) Others(retired
or unable to work)
103 2.4% 64
(1.9)
39 (4.1)
37.9 73
(2.1)
20 (3.6)
10 (3)
Residence Rural 2233 51.3% 1778
(52.2)
455 (48.1)
20.4 1759 (50.7)
309 (56.4
165 (49.3)
Urban 2119 48.7% 1628
(47.8)
491 (51.9)
23.2 1710 (49.3)
239 (43.6)
170 (50.7) Wealth
quantile
1 Poorest 867 19.9% 738
(21.7)
129 (13.6)
14.9 659 (19)
165 (30.1)
43 (12.8)
2 Second 871 20.0% 687
(20.2)
183 (19.3)
21.0 675 (19.5)
120 (21.9)
76 (22.7)
3 Middle 870 20.0% 657
(19.3)
213 (22.5)
24.5 683 (19.7)
110 (20)
77 (23)
4 Fourth 875 20.1% 662
(19.4)
213 (22.5)
24.3 710 (20.5)
80 (14.6)
85 (25.4)
5 Richest 869 20.0% 662
(19.4)
208 (22)
23.9 742 (21.4)
73 (13.3)
54 (16)
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Table 4.1 shows distribution of the demographic characteristics of the participants, their hypertension status and tobacco use. Among hypertensives, there were 36.6% males and 51.9%
urban dwellers, the difference within the groups were not significant at 0.05 level. Within the marital status and age groups, about two thirds of the hypertensives were married orwithin 30 to 59 years of age, while self-employed and homemakers were also more hypertensive within the occupation status (40% and 24%) respectively. In the wealth quantile groups the poorest had the lower percentage (13.5%) among those who were hypertensive while middle, fourth and fifth (richest) quantile were higher at approximately at 22% each.
Higher proportions of the demographic categories among current tobacco users were in males (79%), age groups 30 to 44 (41%) 45 to 59 (27%), the married (64%), self-employed (43%) and employed (21%), rural dwellers (56%) while in the wealth quantile category, about one fifth for second and middle quantiles whereas most of the current tobacco users were the poorest (30.6%).
Among the former tobacco users, similar groups as those in current tobacco users had higher numbers presented as quitters with exception of the wealth quantile groups, the poorest being the lowest as quitters at 12.8%.
Table 4.2 shows the descriptive statistics of physical measures and continuous variables. The results indicate that the two parameters systolic and diastolic had very low as well very high markers (diastolic 48-152mm Hg and systolic 71-264mm Hg) with a mean of 83±12 and 127±20 mm Hg for diastolic and systolic respectively. These two parameters were also different among men and female as well as more skewed to the right among two age groups of 30 to 59 as shown in box plot Figure 1.1. Nevertheless the histogram indicates normal distribution in both full sample and between genders as shown in the Appendix 1. The mean of waist hip ratio of participants is above the recommended normal ratio for women at 0.8±0.08 while BMI mean is just below the overweight threshold at 23.5±5.08kg/m2. Fasting blood glucose mean is at 4.7±1.4 and physical activity of 6±4.2 hours per day with at least no hours of physical exercise for others.