Modifiable lifestyle risk factors for stroke among a high risk hypertensive population in Greater Kampala, Uganda; a cross-sectional study
© The Author(s) 2017
Received: 9 August 2017
Accepted: 28 November 2017
Published: 4 December 2017
To describe the modifiable lifestyle risk factors for stroke among a high risk population for stroke. Africa suffers from rapid population growth, adoption of harmful western diets, and increased prevalence of hypertension and obesity.
A total of 440 study participants were screened and 87 individuals with hypertension plus at least one other known stroke risk factor were enrolled. The prevalence of hypertension and diabetes mellitus in the screened population was 19.7 and 1.8%, respectively. Among those with hypertension only 2.3% (2/87) had ever had serum lipid assessment. Seventy-two percent (68/87) had very high serum LDL-cholesterol, while 33.3% (29/87) had low levels of HDL-cholesterol, and 67.8% had mean blood pressures greater than 160/100 mmHg and 40% (35/87) were obese, with a BMI ≥30. Targeting individuals with modifiable stroke risk factors and implementing self-management programs may be a way to reduce stroke burden in Uganda.
Stroke is the second most common cause of mortality worldwide, and remains a leading cause of adult disability. Developing countries account for nearly 85% of global deaths from stroke [1–4]. In Africa, stroke accounts for 15% of hospital admissions and is a major contributor to mortality in both rural and urban areas . Modifiable factors include hypertension, dyslipidemia, diabetes, cardiac disorders, sickle cell disease, high fat diet, sleep apnea, obesity, tobacco smoking, migraines, alcohol and drug abuse, oral contraceptive use, and lack of exercise [6–9]. The increasing prevalence of hypertension in low income countries represent a substantial public health problem with associated economic and social impacts . Few studies have described the modifiable risk factors in Uganda [8, 11]. Information is lacking regarding modifiable risk factors among the stroke high risk populations in our settings. We describe the modifiable risk factors among a stroke high risk urban population in Mukono district, central Uganda.
This was part of a cross sectional study of 440 participants, assessing barriers and facilitators to stroke risk reduction and a cross-sectional population survey on stroke knowledge and attitudes in Greater Kampala, Uganda, [12, 13].
A total of 87 study participants were deemed to be high risk for stroke from the cross-sectional survey. For this study, a high risk for stroke was defined as being hypertensive with at least one other known modifiable stroke risk factor.
A modified expanded questionnaire based on the World Health Organization (WHO) STEPs questionnaire  was used in this study. Trained study nurses collected information including demographic data, family history of hypertension and diabetes mellitus, past and present medical history of stroke risk factors was collected and a blood sample for analysis. They assessed the lifestyle, physical activity, dietary history including salt intake, drug history and self-reported drug adherence. They also measured the height and weight using standardized protocols to determine the body mass index (BMI) . Blood pressure was measured using standardized protocols between 8 am and 11 am, with an Omron automated sphygmomanometer model HEM-907 (Omron Healthcare Corp., Bannockburn, Illinois, USA), whose accuracy has been validated . Hypertension was defined as a systolic blood pressure ≥ 140 mmHg and/or a diastolic blood pressure of ≥ 90 mmHg, or treatment with anti-hypertensive medication . A point of care, capillary blood sample was obtained for measurement of the random blood sugar (RBS) level using a One Touch Ultra® glucometer from Johnson and Johnson Company, United Kingdom.
Total cholesterol (TC), low-density lipoprotein cholesterol (LDL), and triglycerides (TG) were considered high if they were ≥ 200 mg/dL, ≥ 3.37 mmol/L, ≥ 110 mg/dL, respectively; while high-density lipoprotein cholesterol (HDL) was considered low ≤ 40 mg/dL. Obesity was defined as BMI ≥ 30 kg/m2, while BMI ≥ 25 kg/m2 was deemed overweight. Descriptive statistics of mean, frequency, and percentages were used to summarize data on socio-demographic variables and associated clinical factors. All statistical analysis was performed using STATA software version 12 (Stata Corporation, College Station, TX, USA).
Demographic and clinical characteristics in a community-recruited sample of 87 Ugandans with hypertension and at least 1 other stroke risk factor (N = 87)
Age in years, Median (IQR)
Previous medical history
Ever been diagnosed with diabetes
Ever been diagnosed with hypertension
Ever had blood test for lipid levels
Ever had heart attack
Ever diagnosed with heart disease or had heart surgery
Currently using tobacco
Current alcohol consumption
Suspected alcohol problem
Only 2.3% (2/87) had ever had laboratory assessment of serum lipids and 7 (8.1%) had concurrent HIV/AIDS co-infection.
Only 17.2% (N = 15) of individuals with hypertension had engaged in any sport in the previous 3 months before the study. Of these, only 13% (N = 11) engaged in vigorous physical exercise. The majority of individuals endorsed walking as their main form of physical activity.
Only 24.1% (21/87) of participants included fruits in their diets for 3 or more days in a typical week, while 29% did not include fruits in a typical week. Approximately one-third ate green leafy vegetables 3 or more days in a typical week, and 55.2% ate vegetables between 1 and 3 days in a typical week. The majority reported that vegetable oil was their most common type of oil/fat used in cooking. Ninety-three percent of the study participants (N = 81) reported that they usually added salt to their prepared food. Of these, half used the palm of their hand to measure added cooking salt, while 36% measured salt using their fingers (pinch of salt), and 6.9% used a tea spoon.
Physical and laboratory parameters among the 87 clinically evaluated patients with hypertension
n (N = 87)
Blood pressure levels classifications (SBP/DBP) mmHg
Normal: < 120/< 80
Hypertensive: ≥ 140/≥ 90
Hypertension, stage 1: 140–159/90–99
Hypertension, stage 2: > 160/> 100
Body mass index (BMI)
Normal weight; 20–24.9 kg/m2
Over weight; ≥ 25 kg/m2
Obese; ≥ 30 kg/m2
Optimal: less than 2.59 mmol/L
Near/above optimal: (2.59–3.34 mmol/L)
Borderline high: (3.37–4.12 mmol/L)
High: (4.15–4.90 mmol/L)
Very high: greater than (4.90 mmol/L)
High LDL: ≥ 130 mg/dL (≥ 3.37 mmol/L)
Desirable: less than 200 mg/dL (5.18 mmol/L)
Borderline high: 200–239 mg/dL (5.18 to 6.18 mmol/L)
High: 240 mg/dL (6.22 mmol/L) or higher
High TC: ≥ 200 mg/dL
Low HDL: ≤ 40 mg/dL
Low level, increased risk: Less than 40 mg/dL (1.0 mmol/L) for men and less than 50 mg/dL (1.3 mmol/L) for women
Average level, average risk: 40–50 mg/dL (1.0–1.3 mmol/L) for men and between 50 and 59 mg/dl (1.3–1.5 mmol/L) for women
High level, less than average risk: 60 mg/dL (1.55 mmol/L) or higher for both men and women
Desirable: less than 150 mg/dL (1.70 mmol/L)
Borderline high: 150–199 mg/dL (1.7–2.2 mmol/L)
High: 200–499 mg/dL (2.3–5.6 mmol/L)
Very high: greater than 500 mg/dL (5.6 mmol/L)
High TG: ≥ 110 mg/dL
Laboratory tests and results of the 87 clinically evaluated patients with hypertension with one or more risk factor for stroke
Blood urea nitrogen (BUN)
109.7 (72, 133.4)
50.2 (42.4, 59.9)
104.9 (66.1, 134.1)
Total cholesterol (mg/L)
111.4 (84.2, 207.8)
Blood glucose (mg/dL)
95 (83, 106)
Serum creatinine estimation (mmol/L)
91 (77, 102.3)
Of the enrolled sample, only 55% (48/87) were on anti-hypertensive medications at the time of the survey. Nearly 22% (19/87) were taking the antihypertensive drug; Nifedipine, followed by Bendroflumethiazide, Atenolol and Captopril at 9.2, 6.9 and 3.5%, respectively. Only two study participants were receiving aspirin as an anti-platelet agent and only one study participant (1.2%) was receiving lipid lowering drugs. Twenty-six percent of the female study participants (15/57) were currently using hormonal contraception methods. Twelve percent (7/57) were using oral contraceptives while 14% (8/57) were using injectable contraceptives.
Among enrolled participants, only 12.6% self-reported that they never forget taking their medications while 10.3% (9/87) reported they always forget their medications. 11.5% reported they had missed their medication doses the day preceding the interview. Nearly 28% (24/87) had missed their doses in the last 2 weeks preceding the interview. Only 20.7% reported that they sometimes stop taking their medications because they feel their blood pressure is controlled.
Reducing stroke burden and helping people to make the behavioral changes needed to diminish their likelihood of stroke is urgently. Key findings of this study are that about 70% of the study participants, were aware that they had hypertension, but their blood pressure was elevated and were not involved in actively managing their hypertension. Poorly recognized and managed hypertension appears to be a key modifiable stroke risk factor while life-style issues such as improving diet can be an additional focus of effort. This cross-sectional study found that the majority (94.3%) of people with hypertension had blood pressures greater than 140/90 mmHg, among these 67.8% had JNC-VII, hypertension stage 2 levels despite being prescribed antihypertensive medications. Most individuals with hypertension had abnormal fasting blood cholesterol levels while only 3.5% had high serum triglycerides.
HTN remains one of the important modifiable risk factors for stroke [18–21]. Whereas antihypertensive agents are the most effective agent to reduce blood pressure, behavioral interventions such as improving knowledge and self-management approaches should be used synergistically with antihypertensive agents [22, 23]. The National Non-Communicable Diseases Risk Factor Survey reported a high prevalence of hypertension (28.5%) within central Uganda among adults and that only 7% were aware that they were hypertensive . This study found a prevalence of 19.7% and of these 67.8% were aware that they were hypertensive. It is possible that the relatively high proportion of individuals who were aware of their hypertension reflects urbanization and education trends. Our study included only urban villages with no rural populations. A study in a similar area reported an age standardized prevalence of hypertension of 27.2% (95% CI 25.9–28.5), though two-thirds of the study population resided in rural settings. Earlier studies have shown that awareness and knowledge related to blood pressure are very poor in this area [24, 25]. Among the study participants, 67.8% had JNC-VII, hypertension stage 2 levels of > 160/100 mmHg despite the medications. This would mean either these study participants were not regularly taking their medications or the treatment being prescribed was ineffective in blood pressure control. Further studies are needed to explore this among this population.
The Adult Treatment Panel III (ATP III) guidelines recommend the initiation of non-pharmacological management of hypercholesterolemia with lifestyle modifications, such as balanced diet, physical activity, and smoking cessation, for patients with total cholesterol of above 200 mg/dL . Only one study participant was taking lipid lowering medications yet over half had abnormal serum lipids. No studies have described the prevalence of dyslipidemia among hypertensives in Uganda, however some studies looking at stroke patients and diabetics have reported prevalence of 17.8 and 20.5% [27, 28]. Studies in similar settings have reported higher levels of dyslipidemia among hypertensives up to 60% in Nigeria, . There is an urgent need for attending physicians to routinely test the serum lipid levels among their patients with hypertension.
Current guidelines recommend increasing physical activity as a means to prevent hypertension, [30–32] and regular exercise is associated with up to a 70% reduced risk of ischemic stroke later in life . In contrast to individuals at risk for stroke in other settings, many Ugandans walk long distances as their primary mode of transport. This may be sufficient exercise for some individuals, although urbanization and greater reliance on automobile or motorcycle transport may heighten activity-related stroke risk in the future among Ugandans.
Diet that includes frequent consumption of high quality fats (polyunsaturated and monounsaturated fats primarily from plant sources and fish), fruits, vegetables, and whole grains are associated with large reductions in CVD risk [34–36]. Only 24.1% of the study participants included fruits in their diets for 3 or more days in a typical week, while 28% did not include any fruits in their diets. Only 30% ate green leafy vegetables 3 or more days in a typical week. It is not entirely clear if the relatively high consumption of starchy foods and low consumption of fruits and vegetables is due to lack of knowledge vs. lack of access to healthier foods that may be beyond the financial reach of many Ugandans.
In conclusion, addressing modifiable lifestyle risk factors should be routinely integrated into primary hypertension care especially in primary health care facilities to reduce the risk of stroke among high risk populations.
Our study is limited by the fact that it was cross-sectional, used close-ended questions, and was confined to a fairly limited geographic area. The sample size of 87 is a major limitation for this study and might not provide sufficient inferences to make robust conclusions. Because participants of this study were residents of urban areas, the findings of this paper are not likely to applicable to the whole nation or rural settings within Uganda. The data collected from survey respondents was not adjusted to represent the population from which the sample was drawn.
All authors critically read through the manuscript and revised the manuscript for important intellectual content. All authors discussed the results and commented on the manuscript. All authors read and approved the final manuscript.
We also thank our study subjects for participating in this study.
The authors declare that they have no competing interests.
Availability of data and materials
All data generated or analyzed during this study are included in this published article.
Consent for publication
Ethics approval and consent to participate in this study
Written informed consent was obtained from the next of kin/legal representatives for all study participants. Ethical approval for the study was obtained from Makerere University College of Health Sciences’ School of Medicine review board and ethics committee Ref number 2015-073, UNCST Ref Number. HS 1858 and University Hospitals Institutional Review Board, UHCMC IRB Number: 04-15-18.
The study was supported by a grant from the National Institutes Health (R21NS094022-01) to Martha Sajatovic and Elly Katabira. The funders had no role in the study design, collection, analysis, and interpretation of data and in writing the manuscript.
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
- Feigin VL, Forouzanfar MH, Krishnamurthi R, Mensah GA, Connor M, Bennett DA, Moran AE, Sacco RL, Anderson L, Truelsen T, et al. Global and regional burden of stroke during 1990–2010: findings from the Global Burden of Disease Study. Lancet. 2010;383(9913):245–54.View ArticleGoogle Scholar
- Mathers CD, Lopez AD, Murray CJL. The burden of disease and mortality by condition: data, methods, and results for 2001. Glob Burd Dis Risk Factors. 2006;45:88.Google Scholar
- Strong K, Mathers C, Bonita R. Preventing stroke: saving lives around the world. Lancet Neurol. 2007;6(2):182–7.View ArticlePubMedGoogle Scholar
- Krishnamurthi RV, Feigin VL, Forouzanfar MH, Mensah GA, Connor M, Bennett DA, Moran AE, Sacco RL, Anderson LM, Truelsen T, et al. Global and regional burden of first-ever ischaemic and haemorrhagic stroke during 1990–2010: findings from the Global Burden of Disease Study 2010. Lancet Glob Health. 2013;1(5):e259–81.View ArticlePubMedPubMed CentralGoogle Scholar
- Etyang AO, Scott JA. Medical causes of admissions to hospital among adults in Africa: a systematic review. Glob Health Action. 2013;6:1–14.PubMedGoogle Scholar
- Fagan SCDC, editor. Stroke. New York: McGraw-Hill Companies; 2008.Google Scholar
- Olamoyegun MAAA, Fawale MB, Ogbera AO. Dyslipidaemia as a risk factor in the occurrence of stroke in Nigeria: prevalence and patterns. Pan Afr Med J. 2016;25:72.View ArticlePubMedPubMed CentralGoogle Scholar
- O’Donnell MJ, Chin SL, Rangarajan S, Xavier D, Liu L, Zhang H, Rao-Melacini P, Zhang X, Pais P, Agapay S, et al. Global and regional effects of potentially modifiable risk factors associated with acute stroke in 32 countries (INTERSTROKE): a case–control study. Lancet. 2016;388(10046):761–75.View ArticlePubMedGoogle Scholar
- Maredza M, Bertram MY, Gomez-Olive XF, Tollman SM. Burden of stroke attributable to selected lifestyle risk factors in rural South Africa. BMC Public Health. 2016;16:143.View ArticlePubMedPubMed CentralGoogle Scholar
- World Health Organization. A global brief on hypertension: silent killer, global public health crisis: World Health Day 2013. Geneva: World Health Organization; 2013.Google Scholar
- Nakibuuka J, Sajatovic M, Nankabirwa J, Furlan AJ, Kayima J, Ddumba E, Katabira E, Byakika-Tusiime J. Stroke-risk factors differ between rural and urban communities: population survey in Central Uganda. Neuroepidemiology. 2015;44(3):156–65.View ArticlePubMedPubMed CentralGoogle Scholar
- Kaddumukasa MKJ, Nakibuuka J, Mugenyi L, Ddumba E, Blixen C, Welter E, Katabira E, Sajatovic E. A cross-sectional population survey on stroke knowledge and attitudes in Greater Kampala, Uganda. Cogent Med. 2017;4:1327129.View ArticleGoogle Scholar
- Blixen CNJ, Kaddumukasa M, Nalubwama H, Amollo M, Katabira E, Sajatovic M. Community perceptions of barriers to stroke recovery and prevention in greater Kampala, Uganda: implications for policy and practice. Int J Healthc. 2017;3(2):8–19.View ArticleGoogle Scholar
- World Health Organization. WHO STEPS stroke manual: the WHO STEPwise approach to stroke surveillance/noncommunicable diseases and mental health. Geneva: WHO; 2005.Google Scholar
- WHO. Physical status: the use and interpretation of anthropometry: report of a World Health Organization (WHO) Expert Committee. Geneva: World Health Organization; 1995.Google Scholar
- Gurpreet K, Tee GH, Karuthan C. Evaluation of the accuracy of the Omron HEM-907 blood pressure device. Med J Malays. 2008;63(3):239–43.Google Scholar
- Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, Jones DW, Materson BJ, Oparil S, Wright JT Jr, et al. The seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure: the JNC 7 report. JAMA. 2003;289(19):2560–72.View ArticlePubMedGoogle Scholar
- Law MR, Morris JK, Wald NJ. Use of blood pressure lowering drugs in the prevention of cardiovascular disease: meta-analysis of 147 randomised trials in the context of expectations from prospective epidemiological studies. BMJ. 2009;338:b1665.View ArticlePubMedPubMed CentralGoogle Scholar
- Siragy HM. Major outcomes in high-risk hypertensive patients randomized to angiotensin-converting enzyme inhibitors or calcium channel blocker vs diuretic. The antihypertensive and lipid-lowering treatment to prevent heart attack trial (ALLHAT). Curr Hypertens Rep. 2003;5(4):293–4.View ArticlePubMedGoogle Scholar
- Sundstrom J, Arima H, Jackson R, Turnbull F, Rahimi K, Chalmers J, Woodward M, Neal B. Blood pressure lowering treatment trialists C: effects of blood pressure reduction in mild hypertension: a systematic review and meta-analysis. Ann Int Med. 2015;162(3):184–91.View ArticlePubMedGoogle Scholar
- Ettehad D, Emdin CA, Kiran A, Anderson SG, Callender T, Emberson J, Chalmers J, Rodgers A, Rahimi K. Blood pressure lowering for prevention of cardiovascular disease and death: a systematic review and meta-analysis. Lancet. 2016;387(10022):957–67.View ArticlePubMedGoogle Scholar
- Low WH, Seet W, Ramli AS, Ng KK, Jamaiyah H, Dan SP, Teng CL, Lee VK, Chua SS, Faridah Aryani MY, et al. Community-based cardiovascular risk factors intervention strategies (CORFIS) in managing hypertension: a pragmatic non-randomised controlled trial. Med J Malays. 2013;68(2):129–35.Google Scholar
- Boulware LE, Daumit GL, Frick KD, Minkovitz CS, Lawrence RS, Powe NR. An evidence-based review of patient-centered behavioral interventions for hypertension. Am J Prev Med. 2001;21(3):221–32.View ArticlePubMedGoogle Scholar
- Musinguzi G, Nuwaha F. Prevalence, awareness and control of hypertension in Uganda. PLoS ONE. 2013;8(4):e62236.View ArticlePubMedPubMed CentralGoogle Scholar
- Kaddumukasa M, Kayima J, Kaddumukasa MN, Ddumba E, Mugenyi L, Pundik S, Furlan AJ, Sajatovic M, Katabira E. Knowledge, attitudes and perceptions of stroke: a cross-sectional survey in rural and urban Uganda. BMC Res Notes. 2015;8:819.View ArticlePubMedPubMed CentralGoogle Scholar
- National Cholesterol EducationProgram. Detection, evaluation, and treatment of high blood cholesterol in adults (adult treatment panel iii) final report. Circulation. 2002;106(25):3143–421.Google Scholar
- Mugwano I, Kaddumukasa M, Mugenyi L, Kayima J, Ddumba E, Sajatovic M, Sila C, DeGeorgia M, Katabira E. Poor drug adherence and lack of awareness of hypertension among hypertensive stroke patients in Kampala, Uganda: a cross sectional study. BMC Res Notes. 2016;9:3.View ArticlePubMedPubMed CentralGoogle Scholar
- Mwebaze RM, Kibirige D. Peripheral arterial disease among adult diabetic patients attending a large outpatient diabetic clinic at a national referral hospital in Uganda: a descriptive cross sectional study. PLoS ONE. 2014;9(8):e105211.View ArticlePubMedPubMed CentralGoogle Scholar
- Adamu UG, Okuku GA, Oladele CO, Abdullahi A, Oduh JI, Fasae AJ. Serum lipid profile and correlates in newly presenting Nigerians with arterial hypertension. Vasc Health Risk Manag. 2013;9:763–8.View ArticlePubMedPubMed CentralGoogle Scholar
- Brook RD, Appel LJ, Rubenfire M, Ogedegbe G, Bisognano JD, Elliott WJ, Fuchs FD, Hughes JW, Lackland DT, Staffileno BA, et al. Beyond medications and diet: alternative approaches to lowering blood pressure: a scientific statement from the american heart association. Hypertension. 2013;61(6):1360–83.View ArticlePubMedGoogle Scholar
- Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, Jones DW, Materson BJ, Oparil S, Wright JT Jr, et al. Seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure. Hypertension. 2003;42(6):1206–52.View ArticlePubMedGoogle Scholar
- Pescatello LS, Franklin BA, Fagard R, Farquhar WB, Kelley GA, Ray CA. American college of sports medicine position stand. Exercise and hypertension. Med Sci Sports Exerc. 2004;36(3):533–53.View ArticlePubMedGoogle Scholar
- Shinton R, Sagar G. Lifelong exercise and stroke. BMJ. 1993;307(6898):231–4.View ArticlePubMedPubMed CentralGoogle Scholar
- Mozaffarian D, Appel LJ, Van Horn L. Components of a cardioprotective diet: new insights. Circulation. 2011;123(24):2870–91.View ArticlePubMedGoogle Scholar
- Park Y, Subar AF, Hollenbeck A, Schatzkin A. Dietary fiber intake and mortality in the NIH-AARP diet and health study. Arch Int Med. 2011;171(12):1061–8.View ArticleGoogle Scholar
- Wang X, Ouyang Y, Liu J, Zhu M, Zhao G, Bao W, Hu FB. Fruit and vegetable consumption and mortality from all causes, cardiovascular disease, and cancer: systematic review and dose-response meta-analysis of prospective cohort studies. BMJ. 2014;349:g4490.View ArticlePubMedPubMed CentralGoogle Scholar