Driving to Better Health: Screening for Hypertension and Associated Factors Among Commercial Taxi Drivers in Buffalo City Metropolitan Municipality, South Africa

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RESEARCH ARTICLE

Driving to Better Health: Screening for Hypertension and Associated Factors Among Commercial Taxi Drivers in Buffalo City Metropolitan Municipality, South Africa

Aanuoluwa Odunayo Adedokun1 , * Open Modal Daniel Ter Goon1 Eyitayo Omolara Owolabi1 Oladele Vincent Adeniyi2 Anthony Idowu Ajayi3
Authors Info & Affiliations
The Open Public Health Journal • 29 Dec 2017 • RESEARCH ARTICLE • DOI: 10.2174/1874944501710010303

Abstract

Background:

Hypertension is a critical public health issue in South Africa. Commercial taxi drivers constitute a vulnerable group who are predisposed to hypertension due to the nature of their work. Yet, unlike other population sub-groups, their health status and lifestyle behaviour have rarely been investigated.

Objective:

To screen for hypertension and the associated risks factors among commercial taxi drivers in Buffalo City Metropolitan Municipality (BCMM), South Africa.

Methods:

This was a cross-sectional, descriptive study of a convenience sample of 403 commercial taxi drivers in BCMM. The modified WHO STEPwise questionnaire was used for obtaining demographic and behavioural information from the participants. Blood pressure (BP), blood glucose and anthropometric measurements followed standard procedure. Pre-hypertension was defined as systolic BP of 120-139 mmHg and diastolic BP of 80-89 mmHg and hypertension was defined as a systolic BP ≥140mmHg and/or diastolic BP of ≥90mmHg, self-reported history of hypertension or current medication use. Descriptive and inferential statistics were used to determine the prevalence and associated factors of hypertension. A p-value ≤ 0.05 was considered statistically significant.

Results:

The study participants were 98.8% male, age ranged from 20 to 74 years, with a mean age of 43.3 years (SD±12.5).The prevalence of pre-hypertension was 33.7% and hypertension was 57.0%. After adjusting for confounders, age>35 years (p=0.004), obesity and alcohol use (p<0.001), period of driving>5years (p=0.028) and diabetes (P=0.003) were significant predictors of hypertension.

Conclusion:

The prevalence of hypertension among commercial taxi drivers in BCMM is high and associated with ageing and other cardiovascular risk factors. There is a need for interventions aimed at promoting healthy lifestyle and reduction of hypertension among this group, particularly the older ones.

Keywords: Hypertension, Commercial taxi driver, Screening, South Africa, Blood Pressure, Prevalence.

1. INTRODUCTION

Hypertension, a leading modifiable risk factor for cardiovascular diseases and an independent risk factor for morbidity and mortality, often goes unnoticed as a result of its asymptomatic nature [1-3]. Hypertension (HTN) accounts for 9 million annual deaths worldwide [4]. Globally, there is an increasing prevalence of hypertension, even in economically disadvantaged countries [5].

South Africa is not exempted from the growing burden of hypertension and its complications [6]. More than 6.2 million South Africans are hypertensive with about 53 men and 78 women dying daily from the effect of hypertension; with a high likelihood of a future increase as population ages [7]. Several factors are responsible for this; such as epidemiological transitioning resulting from ageing and urbanization, unhealthy dietary practices, sedentary lifestyle, stressful activities [8, 9] and obesity [8].

The nature of commercial taxi drivers’ work entails several activities ranging from unhealthy dietary pattern, sedentary lifestyle, work pressure, stress to long duration of work [10, 11]; thus rendering them susceptible to the high burden of hypertension [12-14]. Commercial taxi drivers are often relied upon for safe transportation of individuals, goods and services in the country. As such, the economy of several countries somewhat depends on this important group. The health implication of hypertension among commercial drivers should be a concern. Considering the significant role commercial taxi drivers play in a society, the impact of hypertension will not only affect them, but will pose a significant threat to the society at large.

Although several studies have been conducted on the prevalence of hypertension in the general population in South Africa [6, 15-18], by contrast, the profiling of hypertension among commercial taxi drivers has not been undertaken. However, studies exist on hypertension among commercial drivers in other countries, such as Nigeria [19-21], India [10, 14, 22, 23], Iran [24, 25], Brazil [26], Korea [27], Hong Kong [28] and Taiwan [29]. Understanding the magnitude of this problem among commercial taxi drivers is necessary so as to inform health policy makers who have the capacity to implement appropriate intervention strategies in designing a health program tailored to the needs of this special population. Reliable epidemiological data are vital in crafting effective policies and interventions which are most appropriate for a specific group. Also, information on the burden of hypertension among commercial drivers can also assist in assessing their eligibility in the safe transportation of passengers. This study, therefore, examines the prevalence of hypertension and its determining factors among commercial taxi drivers in Buffalo City Metropolitan Municipality (BCMM), South Africa.

2. METHODS

2.1. Study Area and Design

This was a cross-sectional study involving 403 commercial taxi drivers selected across different taxi ranks in Buffalo City Metropolitan Municipality (BCMM), East London, Eastern Cape Province, South Africa. Buffalo City Metropolitan Municipality is one of the 8 districts in the Eastern Cape Province. It is made up of some towns in the Eastern Cape which include East London, Bhisho, King William’s Town and Mdanstane. This municipal area is largely populated by Blacks, 85.2% [30] and transport makes up 12% of its economic sector [31]. The taxi industry is the most available mode of transportation for the public, covering both short and long distance trips, through urban, rural and intercity journeys. It is situated at strategic centers, close to shops, offices and institutions in a city which makes it easily accessible to all.

2.2. Participants and Sample Size

The sample size for this study was based on the estimated number of drivers in the district. According to the statistics at the Department of Transport, the estimated number of commercial taxi drivers was approximately 4000 (Eastern Cape Department of Transport).The appropriate sample size was determined using the Creative Research Systems sample size calculator [32] at a confidence level of 95%. The required sample size was 351participants. However, 403 drivers who were recruited from ten conveniently selected taxi ranks across the district were included in the study. All commercial taxi drivers who were available, willing and met the inclusion criteria were recruited into the study. This study was conducted in March-April, 2017.

2.3. Eligibility Criteria

Participants were included in the study if they were commercial drivers, aged 20 years and above, a member of a recognized taxi association; had worked for at least six months and had fasted eight hours preceding recruitment into the study. Participants were excluded from the study if ill or disabled in such a way that obtaining anthropometric measurements was difficult.

2.4. Study Instrument

The participants were interviewed using the previously validated WHO STEPwise questionnaire [33] which comprises three major items; demographic, behavioural data, and measurements. The instrument was modified to suit the study settings. A pilot study was conducted on 20 commercial taxi drivers to test its suitability in the settings and the effectiveness of the research process. The results of the pilot study were not included in the main study.

2.5. Ethical Approval

Ethical approval for the study was obtained in accordance with Helsinki II Declaration from the University of Fort Hare Research Ethics Committee (Reference number: GOO121SADE01) and the Eastern Cape Department of Health. The Director of the District Department of Health as well as the rank heads gave permission prior to data collection. All participants provided their written informed consent to participate in this study. Their rights to confidentiality and anonymity were ensured throughout the study.

2.6. Data Collection Procedure

Data on demographic and behavioural characteristics were obtained by personal interviews and measurements of blood pressure, blood glucose and anthropometric parameters were obtained using the WHO STEPwise approach. Socio-demographic variables included items on gender, age, race, level of education, marital status, and occupational history. The socioeconomic factors were measured by assessing the level of education and occupational history. Participants’ occupational histories were categorized as periods of driving below two years; within 2-5 years; within 6-10 years and above 10 years. Levels of education were obtained by self-reporting of the highest grade level attained in school and were categorized as, no formal education; primary (grade 1-7); secondary (grade 8-12) and tertiary education. Behavioural variables, such as smoking, alcohol use and consumption of sweet drinks, were obtained through self-reporting.

2.7. Measurements

Blood pressure was measured in accordance with standard protocols [34] with a Medic+ Digital Blood Pressure Monitor. Pre-hypertension was defined as systolic BP of 120-139 mmHg and diastolic blood pressure of 80-89 mmHg and hypertension was defined according to JNC-8 criteria as the average of two systolic blood pressures of > 140mmHg and diastolic of > 90mmHg or history of hypertension and current medication use [35]. Fasting blood glucose of each participant was measured with a validated ACCU-CHEK glucose monitoring apparatus in fasting state. Participants were diagnosed as having diabetes if the fasting plasma glucose (FPG) was ≥ 126mg/dl or 7.0mmol/L [36].

Body weight was measured in light clothes to the nearest 0.01kg in the standing position using a SECA Scale and height was measured to the nearest 0.1cm by a SECA stadiometer in standing position, with closed feet (without shoes) [37]. The waist circumference was taken at the level of the umbilicus by using a non-elastic tape. Body mass index (BMI) was calculated as weight in kg divided by height in square metres (kg/m2). The body mass index (BMI) was categorized in accordance with the World Health Organization’s classification [38], underweight BMI < 18.5 kg/m2, normal (18.5 kg/m2– 24.9 kg/m2), overweight (25.0 kg/m2–29.9 kg/m 2) or obese (≥ 30 kg/ m 2). Abdominal obesity was defined as having a waist circumference of WC ≥ 94 cm for men and WC ≥80 cm for women [39].

3. STATISTICAL ANALYSIS

Data were expressed as mean values ± standard deviations (SD) for continuous variables. Counts (frequencies=n) and proportions (%) were reported for categorical variables. Bivariate and multivariate logistic regressions were used to identify the significant associated factors of hypertension and their 95% confidence interval (95% CI). The logistic regressions were also adjusted for confounding factors. Variables included in the bivariate and multivariate analysis model were considered statistically significant at p-value < 0.05. The Statistical Package for Social Science (SPSS) version 22 was used for data analysis.

4. RESULTS

A total of 403 participants with complete information were used for the study. The age of the participants ranged from 20 to 74 years with a mean age of 43.3 ± 12.5 years. About ninety-nine percent of the participants were male, 30.5% were above the age of 50 years, the majority (73.7%) had a secondary education (grade 8-12); were black (93.3%), were married and had been driving for more than 10 years (47.1%) (Table 1).

Table 1.
Demographic characteristics of the participants.
Variables Frequency (n) Percentage (%)
Sex
Male 398 98.8
Female 5 1.2
Age (years)
20 to 30 72 17.9
31-40 103 25.6
41-50 105 26.0
Above 50 123 30.5
Level of Education
No Formal Education 15 3.7
Grade 1-7 59 14.6
Grade 8-12 297 73.7
Tertiary 32 7.9
Race
Black 376 93.3
Coloured 27 6.7
Marital Status
Married 190 47.1
Separated 8 2.0
Divorced 16 4.0
Widowed 6 1.5
Single 183 45.4
Duration of Driving
<2 years 30 7.4
2-5 years 103 25.6
6-10 years 80 19.9
> 10 years 190 47.1

As shown in Table (2) in the bivariate analysis, age, marital status, level of education, duration of driving, obesity, alcohol use, consumption of sweet drinks, diabetes and abdominal obesity were significantly associated with the prevalence of hypertension.

Table 2.
Bivariate analysis showing determinants of hypertension.
Variables HTN n (%) No HTN n (%) p-value
Age (years)
>35 179 (64.9) 97 (35.1) <0.001
≤ 35 49 (38.6) 78 (61.4)
Marital Status
Ever Married 140(63.6) 80(36.4) 0.002
Never Married 88(48.1) 95(51.9)
Level of Education
No Formal School 12(80.0) 3(20) 0.003
Grade 1-7 44(74.6) 15(25.4)
Grade 8-12 155(52.2) 142(47.8)
Tertiary 17(53.1) 15(46.9)
Income
2000 and below 99(58.9) 69(41.1) 0.420
Above 2000 129(54.9) 106(45.1)
Race
Black 212(56.4) 164(43.6) 0.771
Coloured 16(59.3) 11(40.7)
Period of Driving
5 Years and Below 56(42.1) 77(57.9) <0.001
Above 5years 172(63.7) 98(36.3)
Smoking
Yes 115(57.8) 84(42.2) 0.627
No 113(55.4) 91(44.6)
Obesity
Obese 114(75.5) 37(24.5) <0.001
Not Obese 114(45.2) 138(54.8)
Diabetes
Yes 52 (82.5) 11 (17.5) <0.001
No 176 (51.8) 164 (48.2)
Abdominal Obesity
Yes 176 (71.0) 72(29.0) <0.001
No 52(33.5) 103(66.5)
Have you Ever Consumed any Alcoholic Drink
Yes 153(63.7) 87(36.3) <0.001
No 75(46.0) 88(54.0)
How Often Do You Take Sweet Drinks
Never 16(94.1) 1(5.9) 0.006
Rarely 22(66.7) 11(33.3)
Sometimes 46(55.4) 37(44.6)
Often 144(53.3) 126(46.7)
HTN- Hypertension

In the logistic regression, after adjusting for confounding variables, only age, duration of driving, alcohol use, obesity and diabetes were the significant and independent predictors of hypertension (Table 3).

Table 3.
Binary logistic regression showing predictors of hypertension.
Variables Beta Wald Odd Ratio (CI) p-value
Obesity
Obese 1.212 24.649 3.4(2.1-5.4) <0.001
Non Obese (Reference)
Age
> 35 Years 0.775 8.490 2.2(1.3-3.7) 0.004
≤ 35 Years (Reference)
Diabetes
Diabetes 1.121 8.995 3.1(1.5-6.4) 0.003
Non Diabetic (Reference)
Duration of Driving
> 5 Years 0.561 4.853 1.8(1.1-2.7) 0.028
≤ 5 Years (Reference)
Alcohol Use
Alcohol Users 1.022 18.417 2.8(1.7-4.4) <0.001
Non-alcohol Users(Reference)

5. DISCUSSION

Undiagnosed and uncontrolled hypertension contributes significantly to the burden of cardiovascular diseases and their complications. It is also an independent risk factor for morbidity and mortality [40]. We found an alarmingly high prevalence of hypertension among commercial taxi drivers in this study. To the best knowledge of the authors, no study has been conducted on hypertension among commercial taxi drivers in South Africa. Thus, the findings of this study could only be comparable to studies conducted elsewhere. The prevalence of hypertension found in this study is higher than the reported prevalence of hypertension among commercial taxi drivers across Africa [19-21] and several developing countries [10, 22-25, 27-29] which ranged from 9.0% to 46%. The prevalence recorded in this study is only comparable to the study among commercial drivers in two developed countries, Hong Kong and Taiwan, 57% and 56%, respectively Table (4). Also, the prevalence of hypertension found among the sample in this present study is higher than the reported prevalence (49.2%) among the general population in the same district [18]. The finding in this study affirms the assumed higher risk for hypertension among commercial taxi drivers. A thorough comparison of prevalence across various studies might be difficult as a result of variation in study settings and methodology. However, the findings of this study mirror the notion of an epidemiological transition and the increasing hypertension burden currently sweeping across developing countries. Moreover, commercial drivers are particularly at a higher risk given their unhealthy lifestyle behaviour, in terms of sedentarism, excessive alcohol consumption, smoking and other illicit health behaviours. Also, the high prevalence of pre-hypertension found among this group is a cause for concern. Pre-hypertension indicates a high risk for hypertension [41, 42] thus, there is a possibility of a future increase in hypertension burden if appropriate interventions are not implemented. There is an urgent need to create health awareness, frequent health screening and implementation of effective interventions targeting hypertension among this neglected group, as their health is very crucial to society at large.

Table 4.
Prevalence hypertension among South African commercial taxi drivers compared with the literature.
Country Design/ Sample Size Mean Age (Years) Percentage Author
Abuja, Nigeria Cross- sectional; 389 39.0 ±10.0 9.0% Olusegun et al. [21],
Chittoor, India Cross-sectional; 204 41.38 ±10.45 14.21% Udayar et al. [14],
Bangalore, India Cross- sectional; 500 - 16.0% Satheesh et al. [22],
Iran Cross-sectional;1903 41.55 ±10.43 16.4% Izadi et al. [25],
South-South, Nigeria Cross-sectional; 112 37.49 ±9.3 21.4% Tobin et al. [19],
Sokoto, Nigeria Cross-sectional; 213 47.48 ±10.18 33.5% Erhiano et al. [20],
India Cross-sectional; 587 46.9 ±6.69 34.8% Borle et al. [43],
Brazil Retrospective observational; 659 41.7 ±6.9 38.2% Hirata et al. [13],
South India Cross- sectional;179 36.5 ±8.4 41.3% Lakshman et al. [10],
Iran Cross- sectional; 429 36.6 ±10.7 42.9% Saberi et al. [24],
South Brazil Cross-sectional; 250 41.9 ±10.0 45.2% Sangaleti et al. [26],
India Cross-sectional comparative; 50 - 46.0% Nayak et al. [23],
Korea 433 - 53.3% Shin et al. [27],
Hong Kong 3376 50.9 ±7.6 57.0% Siu et al. [28],
Taiwan Cross-sectional; 1761 - 56.0% Wang et al. [29],
South Africa Cross-sectional; 403 43.3 ±12.5 57.0% Present study.

Age, duration of driving, alcohol use, abdominal obesity and diabetes were significant predictors of hypertension among the study participants. This corroborates several studies [10, 14, 19, 22]. Consistent with other studies [10, 15, 22], a higher prevalence of hypertension was found among participants older than 35 years compared to those below 35 years. Age is an independent risk factor for cardiovascular disorders, especially hypertension [43, 44]. Ageing is often accompanied by changes in the body systems, including the cardiovascular system and degeneration of cells [45] which increases susceptibility to cardiovascular disorders, including hypertension [44]. This might also be the plausible reason for the higher prevalence found among drivers with a longer duration of driving as they constitute those in the higher age group.

Additionally, both generalized and abdominal obesity and diabetes were found to be independently associated with hypertension in the study setting. This is similar to other studies [20, 21]. The association between hypertension and obesity has long been established [46]. Obesity increases the risk of developing hypertension [47] due to the activation of the sympathetic nervous system, renin-angiotensin system, sodium retention among other abnormalities [8, 48]. Obesity, particularly abdominal obesity, exerts a deleterious health effect in the development of insulin resistance and glucose metabolism [49], which predisposes toward diabetes, later, hypertension and ultimately, cardiovascular diseases [50]. Also, hypertension and diabetes share similar metabolic pathways and risk factors such as genetics, physical inactivity, dyslipidemia, insulin resistance and obesity. These factors collectively contribute to the development of arterial stiffness, which promotes the development of hypertension [51, 52]. Thus, the associative link between obesity, diabetes and hypertension among the study participants is expected. This calls for joint intervention programmes targeting all the cardio-metabolic risk factors among commercial taxi drivers in the study setting.

Finally, alcohol usage was significantly associated with hypertension among the study participants. This finding agrees with Udayar et al, study [14], but is in contrast with other studies [19, 22]. Although, controversies exist on the impact of alcohol on health, while moderate alcohol drinking has been shown to improve cardiovascular function, especially among younger age groups, heavy consumption (more than three at a sitting) impacts negatively on cardiovascular health, especially hypertension and atrial fibrillation [53, 54]. Heavy alcohol consumption increases blood pressure [55, 56]. Thus, the high prevalence of hypertension found in this study is not surprising. Anecdotally, most commercial motor drivers in South Africa consume alcohol excessively, smoke and indulge in illicit health behaviours, which tend to compromise their health status. Sadly, South Africa is even reported to be a hard drinking country [57]. Given that the majority of the factors contributing to the high burden of hypertension among commercial taxi drivers are modifiable, and ‘prevention is better than cure’, intervention strategies are needed to safeguard the health of this special population.

5.1. Strengths and Limitations

This study is the first survey conducted to screen for hypertension among commercial taxi drivers in South Africa. Besides, it is a unique study, because it provides important baseline information about the significant correlates of hypertension among commercial taxi drivers. Additionally, multiple BP readings were obtained; and all the measurements were done in the field. Participants with abnormal BP were advised regarding appropriate medical care. Notwithstanding the strengths of this study, the limitations are worth noting. Using a convenience sampling method with 403 drivers is not representative of all of the commercial taxi-driving population. Also, the cross sectional nature of the study does not allow one to determine cause and effect. Lastly, the participants self-report of information may be inaccurately reported due to social desirability (e.g., reporting being physically active or eating fruits and vegetables), or embarrassment (e.g., under-reporting alcohol use) [58].

CONCLUSION

The prevalence of hypertension among commercial taxi drivers in BCMM is alarmingly high. The high prevalence is associated with age, duration of driving and other cardiovascular risk factors such as obesity, diabetes and alcohol use. There is a need for continual awareness creation and screening for cardiovascular risk factors among commercial taxi drivers across the country. Finally, effective interventions targeted at the reduction of modifiable lifestyle behaviours should be implemented among this high risk group.

ETHICS APPROVAL AND CONSENT TO PARTICIPATE

Ethical approval for the study was obtained in accordance with Helsinki II Declaration from the University of Fort Hare Research Ethics Committee (Reference number: GOO121SADE01) and the Eastern Cape Department of Health.

HUMAN AND ANIMAL RIGHTS

No animals were used in this research. All research procedures followed were in accordance with the ethical standards of the committee responsible for human experimentation (institutional and national), and with the Helsinki Declaration of 1975, as revised in 2008 (http://www.wma.net/en/20activities/10ethics/10helsinki/.

CONSENT FOR PUBLICATION

Not applicable

AUTHORS’ CONTRIBUTIONS

Aanuoluwa Odunayo Adedokun, Daniel Ter Goon, Eyitayo Omolara Owolabi and Oladele Vincen Adeniyi contributed to study conception and manuscript preparation. Aanuoluwa Odunayo Adedokun and Eyitayo Omolara Owolabi contributed in the collection of data, Anthony Idowu Ajayi contributed to data analysis and manuscript preparation. All authors read and approved the final manuscript before submission.

CONFLICT OF INTEREST

The authors declare no conflict of interest, financial or otherwise.

ACKNOWLEDGEMENTS

The authors wish to acknowledge the supporting drivers who participated in the study.

REFERENCES

1
Echouffo-Tcheugui JB, Kengne AP, Erqou S, Cooper RS. High Blood Pressure in Sub-Saharan Africa: The Urgent Imperative for Prevention and Control. J Clin Hypertens (Greenwich) 2015; 17(10): 751-5.
2
Roth GA, Huffman MD, Moran AE, et al. Global and regional patterns in cardiovascular mortality from 1990 to 2013. Circulation 2015; 132(17): 1667-78.
3
Tibazarwa KB, Damasceno AA. Hypertension in developing countries. Can J Cardiol 2014; 30(5): 527-33.
4
Lim SS, Vos T, Flaxman AD, et al. A comparative risk assessment of burden of disease and injury attributable to 67 risk factors and risk factor clusters in 21 regions, 1990-2010: A systematic analysis for the Global Burden of Disease Study 2010. Lancet 2012; 380(9859): 2224-60.
5
van de Vijver S, Akinyi H, Oti S, et al. Status report on hypertension in Africa--consultative review for the 6th Session of the African Union Conference of Ministers of Health on NCD’s. Pan Afr Med J 2013; 16(38): 38.
6
Hasumi T, Jacobsen KH. Hypertension in South African adults: Results of a nationwide survey. J Hypertens 2012; 30(11): 2098-104.
8
Jiang S-Z, Lu W, Zong X-F, Ruan H-Y, Liu Y. Obesity and hypertension. Exp Ther Med 2016; 12(4): 2395-9.
9
Hall JE, do Carmo JM, da Silva AA, Wang Z, Hall ME. Obesity-induced hypertension: Interaction of neurohumoral and renal mechanisms. Circ Res 2015; 116(6): 991-1006.
10
Lakshman A, Manikath N, Rahim A, Anilakumari VP. Prevalence and Risk Factors of Hypertension among Male Occupational Bus Drivers in North Kerala, South India: A Cross-Sectional Study. ISRN Preventive Medicine 2014. 2014; 2014: 9.
11
Puhkala J, Kukkonen-Harjula K, Mansikkamäki K, et al. Lifestyle counseling to reduce body weight and cardiometabolic risk factors among truck and bus drivers--a randomized controlled trial. Scand J Work Environ Health 2015; 41(1): 54-64.
12
Rosenthal T, Alter A. Occupational stress and hypertension. J Am Soc Hypertens 2012; 6(1): 2-22.
13
Hirata RP, Sampaio LM, Leitao Filho FS, Braghiroli A, Balbi B, Romano S, et al. General characteristics and risk factors of cardiovascular disease among interstate bus drivers. Sci World J 2012. 2012: 216702.
14
Udayar SE, Sampath S, Arun D, Sravan S. Epidemiological study of cardiovascular risk factors among public transport drivers in rural area of Chittoor district of Andhra Pradesh. Int J Community Med Public Health 2015; 2(4): 415-20.
15
Peltzer K, Phaswana-Mafuya N. Hypertension and associated factors in older adults in South Africa. Cardiovasc J Afr 2013; 24(3): 67-71.
16
Peer N, Steyn K, Lombard C, Gwebushe N, Levitt N. A high burden of hypertension in the urban black population of Cape Town: The cardiovascular risk in Black South Africans (CRIBSA) study. PLoS One 2013; 8(11): e78567.
17
Adeniyi OV, Yogeswaran P, Longo-Mbenza B, Ter Goon D. Uncontrolled Hypertension and Its Determinants in Patients with Concomitant Type 2 Diabetes Mellitus (T2DM) in Rural South Africa. PLoS One 2016; 11(3): e0150033.
18
Owolabi EO, Goon DT, Adeniyi OV, Seekoe E. Social epidemiology of hypertension in Buffalo City Metropolitan Municipality (BCMM): cross-sectional study of determinants of prevalence, awareness, treatment and control among South African adults. BMJ Open 2017; 7(6): e014349.
19
Tobin EA, Ofili AN, Asogun DA, Igbinosun PO, Igba KO, Idahosa AV. Prevalence Of Hypertension And Associated Factors. Int J Res Med 2013; 2(3): 5-12.
20
Erhiano EE, Igbokwe VU, El-Khashab MM, Okolo RU, Awosan KJ. Prevalence of Hypertension among Commercial Bus Drivers in Sokoto, Sokoto State Nigeria. IIJMMS 2015; 2(3): 34-9.
21
Olusegun SO, Ikeoluwapo OA. Prevalence of hypertension and associated risk factor among interstate commercial drivers in Jabi Park Abuja. IJMMS 2016; 8(7): 75-83.
22
Satheesh BC, Veena RM. A Study of Prevalence of Hypertension among Bus drivers in Bangalore city. IJCRR 2013; 05(17): 90-4.
23
Nayak P, Chakravarty PG, Vyas A. Prevalence of hypertension in long route heavy vehicle commercial driver and other employees. Int J Res Med 2014; 3(3): 119-22.
24
Saberi HR, Moravveji AR, Fakharian E, Kashani MM, Dehdashti AR. Prevalence of metabolic syndrome in bus and truck drivers in Kashan, Iran. Diabetol Metab Syndr 2011; 3(1): 8.
25
Izadi N, Malek M, Aminian O, Saraei M. Medical risk factors of diabetes mellitus among professional drivers. J Diabetes Metab Disord 2013; 12(1): 23.
26
Sangaleti CT, Trincaus MR, Baratieri T, et al. Prevalence of cardiovascular risk factors among truck drivers in the South of Brazil. BMC Public Health 2014; 14(1063): 1063.
27
Shin SY, Lee CG, Song HS, et al. Cardiovascular disease risk of bus drivers in a city of Korea. Ann Occup Environ Med 2013; 25(1): 34.
28
Siu SC, Wong KW, Lee KF, et al. Prevalence of undiagnosed diabetes mellitus and cardiovascular risk factors in Hong Kong professional drivers. Diabetes Res Clin Pract 2012; 96(1): 60-7.
29
Wang PD, Lin RS. Coronary heart disease risk factors in urban bus drivers. Public Health 2001; 115(4): 261-4.
30
Wikipedia. Buffalo City Metropolitan Municipality. 2017 June 12, [cited 2017]. Available from: https://en.wikipedia.org/wiki/Buffalo_City _Metropolitan_ Municipality
31
The Local Government Handbook. Overview: Buffalo City Metropolitan Municipality. 2017 June 14, [cited 2017]. Available from: https://www.localgovernment.co.za/metropolitans/view/7/Buffalo-City-Metropolitan-Municipality.
32
Creative Research Systems. Sample size calculator 2015. Available from: https://www.surveysystem.com/sscalc.htm
33
World Health Organization. STEPS: A framework for surveillance: The WHO STEPwise approach to Surveillance of noncommunicable diseases (STEPS). retrieved from, http://wwww.hoint/ncd_surveillance//steps_framework_dec03 2003.
34
Seedat YK, Rayner BL, Veriava Y. South African hypertension practice guideline 2014. Cardiovasc J Afr 2014; 25(6): 288-94.
35
Bell K, Twiggs J, Olin BR. Hypertension: The Silent Killer:Updated JNC-8 Guideline Recommendations 2015.
36
American Diabetes Association. American Diabetes Association. Diagnosing Diabetes and Learning about Prediabetes 2014. Available from: http://www.diabetes.org/diabetes-basics/ diagnosis/?referrer=https://www.google.co.za/ 2014. [cited 2016 July 4]
37
Marfell-Jones M, Olds T, Stew A, Carter L. International standards for anthropometric assessment. Australia: The International Society for the Advancement of Kinanthropometry 2006.
38
World Health Organization. Definition, diagnosis & classification of diabetes mellitus and its complications: Report of a WHO Consultation. Part 1: Diagnosis andclassification of diabetes mellitus. Geneva: WHO, 1999. Available from: http://www.who.int/iris/handle/10665/66040
39
World Health Organization. Waist circumference and waist-hip ratio: Report of a WHO expert consultation, 2011.8-11 December 2008.; Geneva. 2011.
40
Kayima J, Wanyenze RK, Katamba A, Leontsini E, Nuwaha F. Hypertension awareness, treatment and control in Africa: A systematic review. BMC Cardiovasc Disord 2013; 13(54): 54.
41
Wang R, Lu X, Hu Y, You T. Prevalence of prehypertension and associated risk factors among health check-up population in Guangzhou, China. Int J Clin Exp Med 2015; 8(9): 16424-33.
42
Xu T, Liu J, Zhu G, Liu J, Han S. Prevalence of prehypertension and associated risk factors among Chinese adults from a large-scale multi-ethnic population survey. BMC Public Health 2016; 16(1): 775.
43
Borle AL, Jadhao A. Prevalence and Associated Factors of Hypertension among Occupational Bus Drivers in Nagpur City, Central India- A Cross Sectional Study. Natl J Community Med 2015; 6(3): 423-8.
44
McDonald M, Hertz RP, Unger AN, Lustik MB. Prevalence, awareness, and management of hypertension, dyslipidemia, and diabetes among United States adults aged 65 and older. J Gerontol A Biol Sci Med Sci 2009; 64(2): 256-63.
45
Suastika K, Dwipayana P, Semadi SM, Kuswardhani TR. Age is an Important Risk Factor for Type 2 Diabetes Mellitus and Cardiovascular Diseases: InTech Open Science; 2012. Available from: http://www.intechopen.com/books/ glucosetolerance/ age-is-an-important-risk-factor-for-type-2-diabetes-mellitus-and-cardiovascular-diseases 2012.
46
Chiang BN, Perlman LV, Epstein FH. Overweight and hypertension. A review. Circulation 1969; 39(3): 403-21.
47
Borrell LN, Samuel L. Body mass index categories and mortality risk in US adults: The effect of overweight and obesity on advancing death. Am J Public Health 2014; 104(3): 512-9.
48
Re RN. Obesity-related hypertension. Ochsner J 2009; 9(3): 133-6.
49
Pinto G, Beltrán-Sánchez H. Prospective study of the link between overweight/obesity and diabetes incidence among Mexican older adults: 2001-2012. Salud publica de Mexico 2015; 57(0 1): 515-21.
50
World Heart Federation. World Heart Federation. Obesity. Cardiovascular risk factors. 2016 Available from: http://www.world-heart-federation.org/ cardiovascular-health/ cardiovascular-disease-risk-factors/obesity/ 2016. [cited 2016 June 15]
51
Cheung BM, Li C. Diabetes and hypertension: is there a common metabolic pathway? Curr Atheroscler Rep 2012; 14(2): 160-6.
52
DeMarco VG, Aroor AR, Sowers JR. The pathophysiology of hypertension in patients with obesity. Nat Rev Endocrinol 2014; 10(6): 364-76.
53
Pisa P, Kruger A, Vorster H, Margetts B, Loots Du T. Alcohol consumption and cardiovascular disease risk in an African population in transition: The Prospective Urban and Rural Epidemiology (PURE) study. South Afr J Clin Nutr 2010; 23(sup 2): 29-37.
54
Samokhvalov AV, Irving HM, Rehm J. Alcohol consumption as a risk factor for atrial fibrillation: A systematic review and meta-analysis. Eur J Cardiovasc Prev Rehabil 2010; 17(6): 706-12.
55
Husain K, Ansari RA, Ferder L. Alcohol-induced hypertension: Mechanism and prevention. World J Cardiol 2014; 6(5): 245-52.
56
Sheps SG. Does drinking alcohol affect your blood pressure? 2015. Available from: http://www.mayoclinic.org/ diseases-conditions/ high-blood-pressure/ expert-answers/blood-pressure/faq-20058254 2015.
57
Morojele NK, Ramsoomar L. Addressing adolescent alcohol use in South Africa. S Afr Med J 2016; 106: 551-3.
58
Elshatarat RA, Burgel BJ. Cardiovascular Risk Factors of Taxi Drivers. Journal of Urban Health. Bull N Y Acad Med 2016; 93(3): 589-606.