|Year : 2023 | Volume
| Issue : 1 | Page : 46-52
Predictors of blood pressure control amongst primary care patients of a teaching hospital in Bauchi, North-Eastern Nigeria
Muhammad Attahiru1, Pitmang Labo Simon1, Yahkub Babatunde Mutalub2, Mark Divine Akangoziri1, Bukar Alhaji Grema3
1 Department of Family Medicine, Abubakar Tafawa Balewa University Teaching Hospital, Bauchi, Nigeria
2 Department of Clinical Pharmacology and Therapeutics/Department of Family Medicine, Abubakar Tafawa Balewa University/Abubakar Tafawa Balewa University Teaching Hospital, Bauchi, Nigeria
3 Department of Family Medicine, Aminu Kano Teaching Hospital, Kano, Nigeria
|Date of Submission||20-Sep-2022|
|Date of Decision||26-Nov-2022|
|Date of Acceptance||28-Dec-2022|
|Date of Web Publication||09-Feb-2023|
Department of Family Medicine, Abubakar Tafawa Balewa University Teaching Hospital, Bauchi
Source of Support: None, Conflict of Interest: None
Background: Poorly managed hypertension is still a serious global public health issue, despite medication. It is unclear what is causing treated hypertensive patients to have trouble achieving their target blood pressure (BP). Aim: The goal of this study was to determine the predictors of BP control amongst hypertensive patients attending a teaching hospital in North-eastern Nigeria. Materials and Methods: A cross-sectional study was conducted on 277 hypertensive patients from a tertiary healthcare institution. Data were analysed using version 20 of the Statistical Package for the Social Sciences (SPSS). Frequency and percentages were used to summarise data while Chi-square test was used to test for associations. To identify the factors linked to BP control, logistic regression was employed. At P < 0.05, predictors of BP control were found using adjusted odds ratios (AORs) with a 95% confidence interval (CI). Results: The respondents' average age was 53.1 ± 14.6 years, of which 67.5% were female. The level of optimal BP control was 40.8%. Factors associated with reduced BP control include not currently married (AOR = 0.29 [95% CI: 0.16–0.53], P ≤ 0.0001), imperfect adherence (AOR = 0.37 [95% CI: 0.22–0.64], P ≤ 0.0001), taking more than two drugs (AOR = 0.3 [95% CI: 0.14–0.64], P = 0.001) and body mass index (BMI) ≥25 kg/m2 (AOR = 0.40 [95% CI: 0.22–0.72], P = 0.002). Conclusion: The optimal BP control is alarmingly low in this setting. Marital status, medication adherence, increased pill burden and BMI ≥25 kg/m2 negatively affect the attainment of BP control.
Keywords: Blood pressure control, hypertension, North-eastern Nigeria, primary care
|How to cite this article:|
Attahiru M, Simon PL, Mutalub YB, Akangoziri MD, Grema BA. Predictors of blood pressure control amongst primary care patients of a teaching hospital in Bauchi, North-Eastern Nigeria. Niger Postgrad Med J 2023;30:46-52
|How to cite this URL:|
Attahiru M, Simon PL, Mutalub YB, Akangoziri MD, Grema BA. Predictors of blood pressure control amongst primary care patients of a teaching hospital in Bauchi, North-Eastern Nigeria. Niger Postgrad Med J [serial online] 2023 [cited 2023 Mar 31];30:46-52. Available from: https://www.npmj.org/text.asp?2023/30/1/46/369306
| Introduction|| |
In the developed and developing world, hypertension is a common but serious health problem. In 2010, it was estimated to have contributed to 9.4 million deaths and 7% of the world's health burden. It is the main risk factor for cardiovascular diseases, whose aftermaths were linked with high morbidity and mortality. Hypertension if left unchecked, can advance to cause stroke, myocardial infarction, cardiac failure, dementia, renal failure and visual impairment, causing human suffering and imposing severe financial burden.
The target blood pressure (BP) level using medication has been constantly evolving over the past decades with the accumulation of evidence from large-scale, outcome-driven clinical trials. It is unclear what is causing treated hypertensive patients to struggle to reach their desired BP levels; however, this has been a major public health concern globally. Previous research indicated that a number of patient- and physician-related factors, such as patient adherence and physician reluctance regarding increasing both the number and dose of medication, are likely to be a factor. A cross-sectional study in the Greater Accra Region of Ghana revealed that gender, level of education, having one or more comorbidity and abnormal lipid in the blood predicted BP control while an increased pill burden and length of diagnosis of 2–5 years, however, were associated with reduced BP control. Age above 85 years, unemployment, not currently married and being a non-smoker were factors associated with uncontrolled hypertension amongst Singapore elderly residential population. Labeit et al. showed that positive predictors of adequate BP control were coronary heart disease and antihypertensive drug while poor control was associated with increasing age, male gender and obesity. A cross-sectional study in Western Nigeria showed female participants were two and half times more likely to have their BP controlled than male participants, those who adhered to their medications and regular with their clinic follow up have approximately 3 fold and 3.5 odds of having their BP controlled respectively, so also absence of diabetes mellitus was found to be an independent predictor of BP control. A hospital-based descriptive cross-sectional study by Ojo et al. and Iloh et al. showed that having a strong perceived family support, female gender, adherence to medication, taking antihypertensive for more than 3 years and taking more than one antihypertensive drugs were found to be an independent predictors of BP control.
Therefore, the focus of this study is on patient-level factors influencing BP control in hypertensive individuals in Nigeria's North-Eastern Region. The results of this study will support guidelines for the creation of comprehensive policies that will move the nation closer to achieving the global targets of BP control.
| Materials and Methods|| |
This hospital-based descriptive cross-sectional study included hypertensive patients who visited the general outpatient clinic of a teaching hospital in North-eastern Nigeria from December to February 2020. Unpublished medical records showed that 900 hypertensive patients were seen throughout the 3-month study. Using systematic random sampling with a sampling interval of three, a total of 277 patients were recruited for the study. The sample size was determined following the approach for determining the minimum sample size for descriptive studies with populations under 10,000 (finite population).
n = (Zα/2) 2p.q.N/e2(N − 1) + (Zα/2) 2p.q
where n is the minimum sample size, Zα/2 is the value of a standard variate at a specified level of confidence (1.96) and e is the degree of precision, which is often fixed at 5%, P = proportion of hypertensive with controlled hypertension (35.0%) from a previous study in South-eastern Nigeria.
N = population size over the study period which is 900
n = 252.
An additional 10% was added to allow for precision. Therefore, 277 participants were recruited for the study.
Those that were recruited for the study included all hypertensive, aged eighteen years and above, with a primary diagnosis of hypertension, who had granted informed consent, and were receiving outpatient treatment for hypertension at the general out-patient clinic for at least six months with at least three different clinic visits. Critically ill patients, those with secondary hypertension and high-risk populations such as hypertensive patients with endocrine disorder (such as diabetes mellitus), kidney diseases and previous adverse cardiovascular events such as myocardial infarction and cerebrovascular accident were all excluded from the study. The ethical approval was dated June 21, 2019, Ref. Abubakar Tafawa Balewa University Teaching Hospital Bauchi ATBUTH/ADM/42/VOL. 1, ATBUTH (REC) and assigned number – 0019/2019.
Data were pooled from informed and willing patients who attended the hospital's general outpatient clinics. An interviewer-administered questionnaire was used to gather information by the researchers and a trained research assistant, a registrar from the Department of Family Medicine. The questionnaire was translated into Hausa (the local language spoken by majority of the participants) by a trained research interpreter, and the back translation was performed appropriately. The questionnaire consisted of sociodemographic, clinical characteristics and Hill-Bone Compliance Scale Short Form for accessing medication adherence which has nine questions with each item answered on a four-point Likert scale resulting in a score ranging from 9 to 36 points. A score of 9 points indicated perfect adherence and >9 points indicated imperfect adherence. The weight and height measurements were measured with the Hanson weighing scale® and Charder stadiometer®, respectively. The body mass index (BMI) was calculated from the weight (kg) divided by height square (m2). The BMI was further grouped into three categories (<25.0 kg−2 as normal, 25.0–29.9 kg−2 as overweight and 30 kg−2 and above as obesity). BP was measured with Accoson mercury sphygmomanometer twice for each participant at an interval of at least 2 min in sitting position after ensuring that the patient had rested for 5 min. Additional measurements were taking only if the first two readings differed by >10 mmHg or more. The mean of the BP of each patient was categorised into two groups: (A) controlled hypertension (systolic blood pressure [SBP] <140 and DBP <90 mmHg) for adults below 60 years and (SBP <150 mmHg and DBP <90 mmHg) for individual 60 years and above and (B) uncontrolled hypertension (SBP ≥140 mmHg and DBP ≥90 mmHg) for adult below 60 years and (SBP ≥150 mmHg and DBP ≥90 mmHg) for individual above 60 years. The measurement equipment was standardised and calibrated according to the manufacturers' specification. Standard operating procedures were developed for the weighing scale, height measurement and BP monitor.
The IBM Statistical Package for Social Science (SPSS) for Windows, Version 20.0. Armonk, New York was used to pool, store and analyse data. Frequency tables were used to present the results. Values were reported as proportions for qualitative variables, whereas means and standard deviations were employed to describe quantitative data. The Pearson Chi-square test was used to test for associations. Logistic regression was used to determine the factors associated with BP control. Adjusted odds ratios with 95% confidence interval (CI) were used to identify predictors of BP control. The level of significance was considered the probability error of <5% (P < 0.05).
| Results|| |
Sociodemographic characteristics of respondents
The sociodemographic details of the respondents are shown in [Table 1]. The respondents' ages ranged from 20 to 90 years, with a mean age of 53.1 ± 14.6 years. However, most respondents, 44.4%, were within the age bracket of 40–59 years. About two-thirds, 67.5%, of respondents were female and currently married 66.1%. Based on the level of education acquired, 55.6% had no formal education. Only about a fifth (19.1%) of respondents were civil servants, and little over half (59.2%) had monthly incomes of <20,000 Naira.
Clinical characteristics of respondents
According to [Table 2], the majority of participants, 40.4%, had hypertension within the past 1–5 years, and more than half – 59.9% – had at least one comorbid condition, such as osteoarthritis, poor vision, hearing loss, asthma, peptic ulcer disease and erectile dysfunction. The majority of respondents, 48.7%, were using only antihypertensive drug while a smaller percentage, 46.6%, were taking antihypertensive drug along with lifestyle changes. More than three-quarters of participants, 82.7%, were taking one or two antihypertensive drugs with a quarter admitting having one form of medication side effect. A perfect adherence was found in 40.4% of participants while 59.6% had imperfect adherence. The anthropometric variable showed a mean BMI of 27.4 kg/m2 ± 6.6 with more than a third 36.8% being overweight.
Level of blood pressure control amongst respondents
The pattern of respondents' BP control is depicted in [Figure 1]. Half of the participants, 50.9%, had their SBP under control, and 57.8% had their diastolic BP under control. Less than half of the participants (40.8%) had their BP under control.
Relationship between socio-demographic and blood pressure control (N=277)
Using Pearson's Chi-square test [Table 3], only marital status did appear to have an impact on hypertension control (χ2=7.322, P = 0.007). The clinical variables that were shown to be statistically significant for BP control included the number of medications (2 = 5.997, P = 0.014), the level of medication adherence (2 = 10.995, P = 0.001) and BMI (2 = 3.964, P = 0.046).
|Table 3: Relationship between sociodemographic and clinical variables with level of blood pressure control|
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Predictors of blood pressure control
Binary logistic regression analysis was carried out to identify the independent predictors of BP control [Table 4]. Data were fit for the model (P = 0.11 for Hosmer–Lemeshow test and P ≤ 0.0001 for Omnibus test) and 22% variation in outcome could be explained with the model (R2 = 0.221). The odds of controlled BP for participants not currently married are 71% less than those who were currently married (OR: 0.29 [95% CI: 0.16–0.53, P ≤ 0.0001]) and participants with imperfect adherence are 63% less likely to have controlled BP compared to those with perfect adherence (OR: 0.37 [95% CI: 0.22–0.64, P ≤ 0.0001]). Those on more than two antihypertensive medications (OR: 0.3 [95% CI: 0.14–0.64, P = 0.001]) and having a BMI ≥25 kg/m2 (OR: 0.40 [95% CI: 0.22–0.72, P = 0.002]) were more likely to have their BP less controlled than those on one or two antihypertensive medications and having a BMI <25 kg/m2, respectively.
|Table 4: Multivariate analysis of independent predictors of blood pressure control|
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| Discussion|| |
According to reports, there is a wide range in the prevalence of BP control depending on a number of variables, including, amongst others, the study's location, sample size, setting (community or hospital), inpatient or outpatient status and the reference value for BP control.
Hypertension control was achieved in 40.8% of participants, with a slightly higher proportion of 57.8% achieving diastolic control compared to systolic control of 50.9%. The BP control rate is similar to 46.4% in Western Nigeria, 42.2% in Ethiopia and 40% in South Africa. However, Ngango and Omole and Saju et al. reported the BP control rate of 60.7% and 75.1% in a cross-sectional study conducted in a large community health centre, South of Johannesburg, and in a prospective family-based cohort study in India. Most places in the world, particularly in developing nations, appear to have suboptimal BP control as a common finding., Surprisingly, the BP control rate in this study is higher than 35.8% reported by Katibi et al. in Ilorin, North Central Nigeria, 35.0% by Iloh et al. in Umuahia, South-eastern Nigeria, 34.5% by Tamuno and Babashani in Kano, North-western Nigeria and 29.5% by Jhaj et al. in India. Other regions of the world with lower prevalence of hypertension control have also been recorded, including 2.6% in Kenya, 24.1% in Tunisia and 20.3% in Germany.
The possible explanation for the high level of BP control in this study may be due to rather more specific factors. For instance, the prevalence was similar to that reported by Ojo et al. in a primary care clinic in South-western Nigeria but significantly higher than that found amongst speciality clinics in Zaria, Ilorin and Kano. Being the primary care division of the hospital, it is therefore possible that family medicine clinics manage uncomplicated hypertension, which was comparatively easier to control, as opposed to specialty clinics that manage complicated hypertension and hence difficult BP control. Another possible explanation for the relatively high-control rate, in this study, could be attributed to the exclusion of patients with secondary hypertension in whom achieving the target BP goal can be challenging. It may also imply that the comprehensive treatment provided at the family medicine clinics, in addition to sufficient time for patient counselling and health education, helped patients develop better self-management skills, which, in turn, helped them better control their hypertension. Furthermore, the setting of this study could also account for the high level of hypertension control found amongst study participants. This claim could be supported by the result of Ojo et al. who reported a BP control rate of 46.4% in a primary care clinic in Western Nigeria as compared to a BP control rate of 30.6% in a community-based cross-sectional study conducted in Ngaoundere, Cameroon.
Studies investigating the relationship between age, gender, employment status, marital status, duration of hypertension, presence of comorbidities, BMI and BP control found inconsistent results. While some believed that they could predict BP control, others claimed that they had little to no influence in controlling hypertension. In this study, it was observed that BMI, marital status, medication adherence and indeed the number of antihypertensive medications were found to predict hypertension control.
Poorly controlled BP was significantly more amongst participants who were not married at the time of the study compared to those that were married (adjusted odds ratio [AOR] = 0.29; 95% CI: 0.16–0.53). This is similar to a study by Elperin et al. where those who were no longer married were more likely to have uncontrolled hypertension. This may be explained by the finding that people who have regular, intimate contact with a spouse or partner are more likely to adopt health-promoting behaviours through social direct control methods including encouraging, reminding, monitoring and sometimes nagging. The psychological stress related to failed marriages, divorce or widowhood, which has been proven to affect hypertension management, is another explanation for the participants' inability to regulate their BP when they were not currently married.
In addition, participants taking more than two antihypertensive drugs had uncontrolled BP that was statistically higher than that of those on one or two antihypertensive drugs (AOR = 0.3; 95% CI 0.14–0.64). This is comparable to two studies done in Ghana by Okai et al. and Sarfo et al. The observed loss in BP control amongst patients who reported taking more than two antihypertensive drugs per day may be due to the difficulty of high pill burden. Similar findings from more advanced settings demonstrated that patients using three or more drugs were more likely to forget taking their medication or have a treatment gap compared to those taking two drugs. Although, in some settings, patients are educated to appreciate the severity of their condition to mitigate these treatment gaps. Moreso, a fixed-dose combination polypill, can be used to improve antihypertensive drug compliance.,
An independent predictor of BP control in this study was medication adherence (AOR = 0.3; 95% CI: 0.14–0.64), with participants who had poor adherence having considerably higher BP readings than those who had good adherence. This result is supported by numerous studies worldwide.,, Mazzaglia et al. in an observational analysis from a randomised controlled trial showed that a high-compliance to antihypertensive treatment was related to a reduction in cardiovascular events amongst newly diagnosed hypertensive patients. This reduction in cardiovascular risks was likely driving, at least in part, by a significant decrease in BP with the appropriate use of antihypertensive medication. In this study, the controlled systolic and diastolic BP were significantly higher in the percipients with perfect adherence compared to the imperfect group. Measures to increase patient compliance should be a top priority for healthcare professionals managing hypertensive patients because, according to past and present research, patient adherence to an antihypertensive drug regimen is crucial for preventing future cardiovascular events.
BP was also found to be uncontrolled amongst study participants with BMI ≥ 25 kg/m2 compared to those with BMI < 25 kg/m2. This association was found to be statistically significant using multivariate analysis (AOR = 0.40; 95% CI 0.22, 0.72). Labeit et al. and Raji et al. reported similar findings. This could be explained by the cumulative effect and the benefits of lifestyle changes such as weight loss, healthy diet, frequent exercise and other behavioural adjustments such as smoking cessation and reduction in alcohol consumption. They not only lower systolic and diastolic BP but also guard against hypertension-related problems. Therefore, doctors should inform patients about the advantages of living a healthy life and, if necessary, encourage lifestyle changes, including weight loss and avoiding tobacco. Another reason would be that being overweight or obese is known to increase sympathetic nervous system activity, fasting plasma insulin and leptin levels, all of which can result in higher BP.
The current study had some limitations, including the fact that it was a point study; there was no opportunity to observe participants for a long period, which could have yielded better data. Second, the possibility of selection bias due to the recruitment of participants from a tertiary care clinic rather than the general population may have limited our findings. Furthermore, the questionnaires are inherent to recall bias. Finally, the presence of other concurrent medical conditions may have affected patients' adherence and BP control, although attempt was made to address this by studying the impact of comorbidity on outcome measures.
| Conclusion|| |
This study concludes that optimal BP control is alarmingly low in this setting. Marital status, medication adherence, increased pill burden and BMI ≥ 25 kg/m2 negatively affect the attainment of BP control. Data from this study will support calls to develop comprehensive policies that will inch the country closer to achieving the global targets of BP control.
The authors would like to take this medium to thank its participants and the doctors of the Family Medicine department of ATBUTH, Bauchi, for their role in data collection.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Lim SS, Vos T, Flaxman AD, Danaei G, Shibuya K, Adair-Rohani H, et al.
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;380:2224-60.
Agbor VN, Takah NF, Aminde LN. Prevalence and factors associated with medication adherence among patients with hypertension in Sub-Saharan Africa: Protocol for a systematic review and meta-analysis. BMJ Open 2018;8:e020715.
Chowdhury EK, Owen A, Krum H, Wing LM, Ryan P, Nelson MR, et al.
Barriers to achieving blood pressure treatment targets in elderly hypertensive individuals. J Hum Hypertens 2013;27:545-51.
Okai DE, Manu A, Amoah EM, Laar A, Akamah J, Torpey K. Patient-level factors influencing hypertension control in adults in Accra, Ghana. BMC Cardiovasc Disord 2020;20:123.
Seow LS, Subramaniam M, Abdin E, Vaingankar JA, Chong SA. Hypertension and its associated risks among Singapore elderly residential population. J Clin Gerontol Geriatr 2015;6:125-32.
Labeit AM, Klotsche J, Pieper L, Pittrow D, Einsle F, Stalla GK, et al.
Changes in the prevalence, treatment and control of hypertension in Germany? A clinical-epidemiological study of 50.000 primary care patients. PLoS One 2012;7:e52229.
Awobusuyi J, Adebola A, Ajose F. Prevalence and socio-demographic profile of hypertensive patients in a Nigerian general out-patients' department. Internet J Third World Med 2012;10:1-9.
Ojo OS, Malomo SO, Sogunle PT. Blood pressure (BP) control and perceived family support in patients with essential hypertension seen at a primary care clinic in Western Nigeria. J Family Med Prim Care 2016;5:569-75.
] [Full text]
Iloh GU, Ofoedu JN, Njoku PU, Amadi AN, Godswill-Uko EU. Medication adherence and blood pressure control amongst adults with primary hypertension attending a tertiary hospital primary care clinic in Eastern Nigeria. Afr J Prm Health Care Fam Med 2013;5:1-6.
Ibrahim MM, Damasceno A. Hypertension in developing countries. Lancet 2012;380:611-9.
Kothari CR, Garg G. Sampling and statistical inference. In: Reseach Methodology Methods and Techniques. 3rd
ed. New Delhi: New Age International Ltd; 2014. p. 167-8.
Koschack J, Marx G, Schnakenberg J, Kochen MM, Himmel W. Comparison of two self-Rating instruments for medication adherence assessment in hypertension revealed Insufficiient psychometric properties. J Clin Epidemiol 2010;63:299-306.
James PA, Oparil S, Carter BL, Cushman WC, Dennison-Himmelfarb C, Handler J, et al.
2014 evidence-based guideline for the management of high blood pressure in adults: Report from the panel members appointed to the Eighth Joint National Committee (JNC 8). JAMA 2014;311:507-20.
Awoke A, Awoke T, Alemu S, Megabiaw B. Prevalence and associated factors of hypertension among adults in Gondar, Northwest Ethiopia: A community based cross-sectional study. BMC Cardiovasc Disord 2012;12:113.
Van der Merwe E, Carboni A. Strategies to improve blood pressure control and cardiovascular outcomes in hypertensive patients. In Rayner B. Combination therapy in hypertension. S Afr Fam Pract 2011;53:525-32.
Ngango JM, Omole OB. Prevalence and socio-demographic correlates of cardiovascular risk factors among patients with hypertension in South African primary care. Cardiovasc J Afr 2018;29:344-51.
Saju MD, Allagh KP, Scaria L, Joseph S, Thiyagarajan JA. Prevalence, awareness, treatment, and control of hypertension and its associated risk factors: Results from baseline survey of SWADES family cohort study. Int J Hypertension 2020;2020:1-7.
Egan BM, Zhao Y, Axon RN. US trends in prevalence, awareness, treatment, and control of hypertension, 1988-2008. JAMA 2010;303:2043-50.
Bramlage P, Böhm M, Volpe M, Khan BV, Paar WD, Tebbe U, et al.
global perspective on blood pressure treatment and control in a referred cohort of hypertensive patients. J Clin Hypertens (Greenwich) 2010;12:666-77.
Katibi IA, Olarinoye JK, Kuranga SA. Knowledge and practice of hypertensive patients as seen in a tertiary hospital in the middle belt of Nigeria. Niger J Clin Pract 2010;13:159-62.
] [Full text]
Tamuno I, Babashani M. Blood pressure control amongst hypertensive patients in a tertiary health care facility in Northern Nigeria. Res J Med Sci 2012;6:26-32.
Jhaj R, Gour PR, Kumari S, Sharma S. Association between medication adherence and blood pressure control in urban hypertensive patients in central India. Int J Non Commun Dis 2018;3:9-14.
Hendriks ME, Wit FW, Roos MT, Brewster LM, Akande TM, de Beer IH, et al.
Hypertension in sub-Saharan Africa: Cross-sectional surveys in four rural and urban communities. PLoS One 2012;7:e32638.
Ben Romdhane H, Ben Ali S, Skhiri H, Traissac P, Bougatef S, Maire B, et al.
Hypertension among Tunisian adults: Results of the TAHINA project. Hypertens Res 2012;35:341-7.
Oyati AI, Orogade AA, Danbauchi SS, Azuh PC. Awareness, treatment and control of hypertension among hypertensives in Zaria. J Med Trop 2011;13:139-44.
Mbouemboue OP, Ngoufack TJ. High blood pressure prevalence, awareness, control, and associated factors in a low-resource African setting. Front Cardiovasc Med 2019;6:119.
Elperin DT, Pelter MA, Deamer RL, Burchette RJ. A large cohort study evaluating risk factors associated with uncontrolled hypertension. J Clin Hypertens (Greenwich) 2014;16:149-54.
Bozorgmanesh M, Ghoreishian H, Mohebi R, Azizi F, Hadaegh F. Sex-specific predictors of the prehypertension-to-hypertension progression: Community-based cohort of a West-Asian population. Eur J Prev Cardiol 2014;21:956-63.
Sarfo FS, Mobula LM, Burnham G, Ansong D, Plange-Rhule J, Sarfo-Kantanka O, et al.
Factors associated with uncontrolled blood pressure among Ghanaians: Evidence from a multicenter hospital-based study. PLoS One 2018;13:e0193494.
Panjabi S, Lacey M, Bancroft T, Cao F. Treatment adherence, clinical outcomes, and economics of triple-drug therapy in hypertensive patients. J Am Soc Hypertens 2013;7:46-60.
Hashmi SK, Afridi MB, Abbas K, Sajwani RA, Saleheen D, Frossard PM, et al.
Factors associated with adherence to anti-hypertensive treatment in Pakistan. PLoS One 2007;2:e280.
Cimmaruta D, Lombardi N, Borghi C, Rosano G, Rossi F, Mugelli A. Polypill, hypertension and medication adherence: The solution strategy? Int J Cardiol 2018;252:181-6.
Huffman MD, Xavier D, Perel P. Uses of polypills for cardiovascular disease and evidence to date. Lancet 2017;389:1055-65.
Muntner P, Carey RM, Gidding S, Jones DW, Taler SJ, Wright JT Jr., et al.
Potential US population impact of the 2017 ACC/AHA high blood pressure guideline. Circulation 2018;137:109-18.
Mukora-Mutseyekwa FN, Chadambuka EM. Drug adherence behavior among hypertensive out-patients at a tertiary health institution in Manicaland province, Zimbabwe, 2011. Patient Prefer Adherence 2013;7:65-70.
Mazzaglia G, Ambrosioni E, Alacqua M, Filippi A, Sessa E, Immordino V, et al.
Adherence to antihypertensive medications and cardiovascular morbidity among newly diagnosed hypertensive patients. Circulation 2009;120:1598-605.
Matsumura K, Arima H, Tominaga M, Ohtsubo T, Sasaguri T, Fujii K, et al.
Impact of antihypertensive medication adherence on blood pressure control in hypertension: The COMFORT study. QJM 2013;106:909-14.
Raji YR, Abiona T, Gureje O. Awareness of hypertension and its impact on blood pressure control among elderly Nigerians: Report from the Ibadan study of aging. Pan Afr Med J 2017;27:190.
Frisoli TM, Schmieder RE, Grodzicki T, Messerli FH. Beyond salt: Lifestyle modifications and blood pressure. Eur Heart J 2011;32:3081-7.
Masuo K, Mikami H, Ogihara T, Tuck ML. Weight gain-induced blood pressure elevation. Hypertension 2000;35:1135-40.
[Table 1], [Table 2], [Table 3], [Table 4]