|ORIGINAL RESEARCH REPORT
|Year : 2021 | Volume
| Issue : 3 | Page : 155-160
Medication nonadherence in Nigerian heart failure patients: A cross sectional study
Olagoke Korede Ale1, Abdulwasiu Adeniyi Busari2, Emmanuel S Irokosu2, Akinwumi Akinyinka Akinyede2, Sikiru O Usman1, Sunday O Olayem2
1 Department of Medicine, Therapeutics and Toxicology, College of Medicine, University of Lagos, Nigeria
2 Department of Pharmacology, Therapeutics and Toxicology, College of Medicine, University of Lagos, Nigeria
|Date of Submission||04-Jan-2021|
|Date of Acceptance||09-Jul-2021|
|Date of Web Publication||23-Aug-2021|
Dr. Abdulwasiu Adeniyi Busari
Department of Pharmacology, Therapeutics and Toxicology, College of Medicine, University of Lagos, PMB12003 Idi-Araba, Lagos
Source of Support: None, Conflict of Interest: None
Background: Anti-failure therapy is vital to the reduction of morbidity and mortality associated with heart failure (HF). Medication nonadherence (MNA) has been identified as a major limiting factor for the attainment of therapeutic goals. This study aimed to determine the prevalence and characteristics of MNA in HF patients attending Lagos University Teaching Hospital (LUTH), Lagos. Methods: This was a descriptive cross-sectional study involving 202 previously diagnosed HF patients attending an outpatient clinic in LUTH. Data were obtained from patient's medical records and the use of an interviewer-administered questionnaire. Medication Adherence Report Scale 5-items was used to determine MNA. Results: Of the 202 HF subjects, 68% (n = 128) were aged 31–60 years, 65% (n = 132) were females, 58%, (n = 116) were taking ≤4 pills/day, 54.5% were taking pills twice daily, and 72.3% (n = 146) had comorbid conditions. The overall prevalence of MNA was 69.3% with ACE inhibitors having the highest MNA of 73.2% and angiotensin receptor blocker/neprilysin inhibitor having the least MNA of 0%. MNA was independent of age, gender, educational status, pill burden, duration of HF, history of HF admission, functional status, and specific comorbidities (P < 0.05). However, the presence of three comorbidities was associated with lower MNA (P < 0.05). Conclusion: There is a high prevalence of MNA in Nigerian HF patients. Measures aimed at improving adherence are imperative to improve outcomes in these patients.
Keywords: Heart failure, medication nonadherence, Nigerian
|How to cite this article:|
Ale OK, Busari AA, Irokosu ES, Akinyede AA, Usman SO, Olayem SO. Medication nonadherence in Nigerian heart failure patients: A cross sectional study. J Clin Sci 2021;18:155-60
|How to cite this URL:|
Ale OK, Busari AA, Irokosu ES, Akinyede AA, Usman SO, Olayem SO. Medication nonadherence in Nigerian heart failure patients: A cross sectional study. J Clin Sci [serial online] 2021 [cited 2023 May 28];18:155-60. Available from: https://www.jcsjournal.org/text.asp?2021/18/3/155/324400
| Introduction|| |
Heart failure (HF) is a clinical syndrome characterized by typical symptoms (e.g., breathlessness, ankle swelling, and fatigue) that may be accompanied by signs caused by a structural and/or functional cardiac abnormality, resulting in reduced cardiac output and/or elevated intracardiac pressures at rest or during stress.
In nearly all the regions of the world, HF is common with the prevalence on the rise., Over 20 million people worldwide have HF., The prevalence of HF in the general population is 1%–2%, rising to >10% in people >70 years of age.,, In Nigeria, hospital-based prevalence studies show that HF is responsible for 9.4%–42.5% of medical admissions.,,, HF is the most common complication of hypertension and cardiomyopathy in Africa., It accounts for 3%–7% of all medical admissions in Africa.,,,, Adherence is defined by the World Health Organization (WHO) as the extent to which a person's behavior taking medication, following a diet, and/or executing lifestyle changes, corresponds with agreed recommendations from a health care provider. Medication nonadherence (MNA) is the failure of a patient to conform to prescribed intervals and doses of a treatment regimen. A high prevalence of MNA has been documented in HF patients and is also a major hindrance to the achievement of optimum outcomes.,, The effects of MNA include impaired quality of life, high health-care costs driven by high rates of hospital re-admissions and outpatient hospital care, and high mortality among HF patients.,,
Factors such as age, sex, marital status, educational level, income, pill burden, cost of medications, family support, side effects of medications, and comorbidities are associated with MNA.,,, There is a paucity of data on the prevalence and correlates of MNA in HF patients in Nigeria. This study aimed to determine the prevalence and characteristics of MNA in HF patients in a tertiary health institution in Lagos, Nigeria.
| Methods|| |
Study design and location
This was a hospital-based cross-sectional study of subjects with a diagnosis of HF, placed on oral HF medications, and was being followed up at the cardiology outpatient clinic of the Lagos University Teaching Hospital (LUTH), Idi-Araba, Lagos. LUTH is a tertiary care hospital serving as a referral center for hospitals in Lagos, the commercial capital of Nigeria and its environs.
We studied 202 consecutive subjects aged ≥18 years, with a diagnosis of HF using the Framingham criteria who had been on oral HF medications for at least 6 months. Subjects must have had at least three outpatient clinic visits. Exclusion criteria were age <18 years, <3 outpatient clinic visits, critical illness, and refusal to give consent.
Using a structured questionnaire after obtaining consent, data were collected from each subject. These included age, gender, marital status, ethnicity, education, occupation, income, number of medications taken per time, frequency of dosage, and total pill burden.
Clinical information such as duration of HF, presence, and types of comorbidities and the names and dosage of anti-failure medications prescribed was extracted from the patients' medical records. Height and weight were measured and body mass index was calculated. The New York Heart Association (NYHA) functional classification of all subjects was obtained.
The primary outcome, i.e. MNA of subjects to anti-failure drugs, was assessed using the 5-item medication adherence report scale (MARS-5). The MARS-5 consists of five statements of nonadherent behavior, i.e., forgetting, changing dosages, stopping, skipping, and using a particular medication scored on a 5-point Likert scale with 1 = always, 2 = often, 3 = sometimes, 4 = rarely, and 5 = never. For each drug, the least score obtainable, i.e., 5 represented the worst adherence, while a maximum score obtainable, i.e., 25 represented the best adherence. A score of 5–22 was considered nonadherent, while a score of 23–25 was considered adherent for a particular drug. The maximum score was 25. The overall adherence for each subject was a sum of the MARS-5 scores of all the anti-failure drugs divided by the number of anti-failure medications the subject was on. These included diuretics, angiotensin-converting enzyme inhibitors (ACEIs), angiotensin receptor blockers (ARBs), beta-adrenergic blockers, aldosterone antagonists, ARB/neprilysin inhibitor (ARNI), and cardiac glycosides.
Data were analyzed using Statistical Package for Social Sciences (SPSS®) software for Windows, Version 20.0. Chicago, Illinois, United States. Categorical variables, i.e., gender, age group, marital status, educational status, adherence status, pill burden, number/types of comorbidities, and clinical characteristics, were presented as percentages and/or proportions. Differences in these variables were compared using the Chi-square test or Fisher's exact test as appropriate. P < 0.05 was taken as being statistically significant.
Ethical approval was granted by the Health Research Ethics Committee (HREC) of LUTH (reference no: ADM/DCST/HREC/2648). Participants were adequately informed in a language that they understood the nature, potential benefits, and risks of the study. Written informed consent was obtained from each subject. All data collected from the participants were kept confidential using a passworded retrieval system.
| Results|| |
Most (68%, n = 128) of the subjects were in the 31–60 years age group and majority (65.5%, n = 132) were females [Figure 1] shows the magnitude of medication adherence/non-adherence among the heart failure subjects. Medication adherence among the subjects was independent of their sociodemographic characteristics. [Table 1] shows the sociodemographic characteristics of the HF subjects according to their medication adherence status. The monthly incomes of the subjects were as follows: 66.3% (n = 132) earned < N50,000, 15.6% (n = 31) earned N50,000 – N99,999, 11.6% (n = 23) earned N100,000–N199,999, and 6.5% (n = 13) earned over N200,000.
|Figure 1: Distribution of medication adherence and non-adherence among the patients with chronic heart failure. The proportion of medication non-adherence (MNA) was 69.3% among the patients evaluated.|
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|Table 1: Sociodemographic characteristics of subjects according to their medication adherence status|
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The majority (58%, n = 116) of the subjects were on ≤4 different medications. Twice-daily drug intake was the most frequent dosage (54.5%, n = 109). The medication adherence status of the subjects was independent of their pill burden. [Table 2] summarizes the pill burden of the HF subjects according to their medication adherence status.
|Table 2: Pill burden of subjects according to their medication adherence |
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MNA was highest (73.1%, n = 49) among subjects on ACEI and least (0%, n=0) among patients on ARNI. [Table 3] summarizes the individual medication adherence profiles of the anti-failure medications.
The etiology of HF in this cohort is as follows: Hypertensive heart disease (55%, n = 110), dilated cardiomyopathy (35.5%, n = 71), peripartal cardiomyopathy (2%, n = 4), ischemic heart disease (3.5%, n = 7), and rheumatic heart disease (1%, n = 2). Most (88.5%, n = 177) of the subjects' diagnosis of HF is ≤5 years old, while most (72%, n = 144) were in NYHA functional Class I. None of the subjects was in NYHA Class IV. [Table 4] shows the relationship between medication adherence and selected clinical characteristics of the subjects.
|Table 4: Relationship between adherence and certain clinical characteristic of subjects|
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The majority (72.3%, n = 146) of the HF subjects in this cohort had one or more comorbidities. The presence of three comorbidities in the HF subjects was associated with nonadherence in this study. [Table 5] five shows the relationship between the number of comorbidities in the HF subjects and medication adherence in this cohort. The most common comorbidity of HF in this cohort was hypertension, followed by dyslipidemia. [Table 6] shows the frequency of the various comorbidities and their relationships with medication adherence.
|Table 5: Relationship between subjects' number of comorbidities and medication adherence|
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|Table 6: Relationship between specific comorbidities and medication adherence|
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| Discussion|| |
Adherence of patients to anti-failure medications is crucial to the attainment of optimal outcomes in HF. Our study showed a high prevalence (70%) of MNA among patients with HF. A similar finding, i.e. high prevalence of MNA, has been documented for Nigerian patients with chronic illnesses such as hypertension and diabetes., Raimi et al. in a study of 50 hypertensive and 50 diabetic subjects documented 68% MNA in a Lagos clinic. Abdulazeez et al. in a study of 220 subjects with diabetes mellitus in Ilorin reported an MNA of 73.6%.
These values are higher than the 50% MNA documented by the WHO as the average MNA to long-term therapy in individuals with chronic illnesses. It is also higher than 35.6% nonadherence to antihypertensive and antidiabetic medications by patients under managed health-care in the United States reported by Jing et al. Hood et al. using the proportion of days covered to measure adherence in American HF patients documented MNA of 37%.
Raimi et al. had previously documented the cost of medications/financial constraints as the major reason for MNA in Nigerians. Abdulazeez et al. reported an association of medication adherence with higher patients' financial status. A financially constrained patient may be reluctant to spend on medications, especially if there is no immediate attainment of treatment goals as seen in patients with multiple comorbidities. Cost-related nonadherence is particularly more common in low-income earners. Most of the subjects in this study are low-income earners with two-third of them earning less than N50,000/month. Out-of-pocket payment is the dominant mode of settling medical bills in Nigeria. This may result in inability to refill medications and a consequent low adherence. Conversely, the possession of good health insurance by the subjects in the American studies above may be a driver of high medication adherence. The poor patient reminder system in Nigeria may also contribute to the disparities observed in the MNA prevalence in these studies. Adherence was measured using the self-reporting method in our study and other Nigerian studies, while other indirect methods such as the proportion of days covered were used in the American study. These differences in the methods of MNA assessment may also underlie these differences in MNA.
MNA in our study was independent of the subjects' gender. This is at variance with the negative association between female gender and medication adherence documented by Raimi et al. Differences in the type of tools used for the measurement of medication adherence in these studies may be responsible for this.
Elderly patients on treatment for chronic diseases have been reported to be more likely to be nonadherent to medications than younger patients. However, data from our study showed MNA to be independent of the age of the subjects. The social support system in Nigeria which usually entrusts the responsibility for the administration of medications to the elderly to family members may have blunted in our study the expected higher MNA in the elderly.
Over 70% of the HF subjects in this study had one or more comorbidities. Multiple comorbidities may have a direct impact on the cost of patients' management such as the cost of medications, investigations, and hospital visits. Conversely, low income may be a sequela of reduced productivity arising from HF and comorbidities, However, the presence of comorbidities generally did not influence medication adherence in this study. The only exception was the presence of three comorbidities which were marginally (P = 0.049) associated with MNA.
Pill burden, the number of tablets/capsules that a patient takes regularly and the dosing frequencies of the pills, may influence medication adherence for MNA in patients with chronic illnesses, especially those with many comorbidities. However, there was no significant association between pill burden and MNA in our study.
The class of drug with the least adherence in our study was ACEI. This may be attributed to the side effect profile of ACEI especially dry cough associated with its usage. ARB/neprilysin inhibitor (ARNI) had the best adherence. ARNI is expensive; hence, only highly motivated and financially comfortable patients are likely to be on it in low-middle income countries such as Nigeria. This may underlie the 100% adherence of patients on ARNI.
There is inconsistent evidence for the relationship between MNA and the number of comorbidities. Cholowski and Cantwell documented a positive relationship between the number of comorbidities and adherence in HF patients. Granger et al. reported a negative relationship between adherence and the number of comorbidities, while Wu et al. documented a nonsignificant relationship between the number of comorbidities and medication adherence in HF patients., The presence of three comorbidities was associated with lower MNA in our study. All these inconsistencies may be due to differences in methods of assessing medication adherence.
Adherence was independent of specific comorbidities such as ischemic heart disease, hypertension, diabetes mellitus, dyslipidemia, chronic kidney disease, obesity, and stroke in our study. This is at variance with the documented higher medication adherence in HF patients with coronary heart disease, diabetes mellitus, and dyslipidemia., The above may be attributable to differences in study methodologies and sociocultural responses of the study populations to chronic illness.
This study was conducted in a single center and MNA was measured using a self-reporting method. Self-reporting tends to overestimate patients' actual adherence. A single-center study may limit the generalization of the results of this study considering the diversity of the Nigerian population.
| Conclusion|| |
There is a high prevalence of MNA in Nigerian HF patients and this may negatively impact the desired outcomes in these patients. Institution of measures to improve medication adherence will improve outcomes in Nigerian HF patients.
We thank Dr A. Chukwuemeka of the Cardiology Unit, Department of Medicine, LUTH, Idi-Araba, Lagos, Nigeria, for his contribution. The authors wish to thank Prof. I.A. Oreagba, Head of the Department of Pharmacology, Therapeutics, and Toxicology, of the College of Medicine, University of Lagos, for his unwavering support.
Financial support and sponsorship
Conflicts of interest
There are no conflicts of interest.
| References|| |
Ponikowski P, Voors AA, Anker SD, Bueno H, Cleland JG, Coats AJ, et al.
2016 ESC Guidelines for the diagnosis and treatment of acute and chronic heart failure: The Task Force for the diagnosis and treatment of acute and chronic heart failure of the European Society of Cardiology (ESC) Developed with the special contribution of the Heart Failure Association (HFA) of the ESC. Eur Heart J 2016;37:2129-200.
Mendez GF, Cowie MR. The epidemiological features of heart failure in developing countries: A review of the literature. Int J Cardiol 2001;80:213-9.
Ziaeian B, Fonarow GC. Epidemiology and etiology of heart failure. Nat Rev Cardiol 2016;13:368-78.
Roger VL. Epidemiology of heart failure. Circ Res 2013;113:646-59.
Ojji D, Stewart S, Ajayi S, Manmace M, Sliwa K. A predominance of hypertensive heart failure in Abuja heart study cohort of urban Nigeria: A prospective clinical registry of 1515 de novo cases. Eur J Heart Fail 2013;15:835-42.
Ogah OS, Stewart S, Falase AO, Akinyemi JO, Adegbite GD, Alabi AA, et al.
Contemporary profile of acute heart failure in Southern Nigeria: Data from the abeokuta heart failure clinical registry. JACC Heart Fail 2014;2:250-9.
Osuji CU, Onwubuya EI, Ahaneku GI, Omejua EG. Pattern of cardiovascular admissions at Nnamdi Azikiwe University Teaching Hospital Nnewi, South East Nigeria. Pan Afr Med J 2014;17:116.
Adeoti AO, Ajayi EA, Ajayi AO, Dada SA, Fadare JO, et al.
Pattern and outcomes of medical admissions in Ekiti State University Teaching Hospital, Ado-Ekiti – A 5 year review. Am J Med Sci 2015;5:92-8.
Adedoyin RA, Adesoye A. Incidence and pattern of cardiovascular disease in a Nigerian teaching hospital. Trop Doct 2005;35:104-6.
Khatibzadeh S, Farzadfar F, Oliver J, Ezzati M, Moran A. Worldwide risk factors for heart failure; a systematic review and pooled analysis. Int J Cardiol 2013;168:1186-94.
Kingue S, Dzudie A, Menanga A, Akono M, Ouankou M, Muna W. A new look at adult chronic heart failure in Africa in the age of the Doppler echocardiography: Experience of the medicine department at Yaounde General Hospital. Ann Cardiol Angeiol (Paris) 2005;54:276-83.
Sabate E. Adherence to Long-Term Therapies, Evidence for Action. Geneva: World health Organization; 2003.
Ambardekar AV, Gregg CF, Hernandez WP, Yancy CW, Krantz MJ. Characteristics and in-hospital outcomes for non-adherent patients with heart failure from GET with the guidelines -heart failure. Am Heart J 2009;158:644-52.
Annema C, Luttik M, Jaarsma T. Reasons for re-admission in heart failure: Perspective of patients, caregivers, cardiologist. Heart Lung 2009;38:427-34.
Awad A, Osman N, Altayib S. Medication adherence among cardiac patients in Khartoum State, Sudan: A cross-sectional study. Cardiovasc J Afr 2017;28:350-5.
Abdulazeez FI, Omole M, Ojulari SL. Medication compliance amongst diabetic patients in Ilorin, Nigeria. IOSR – JDMS 2014;13:96-9.
Boima V, Ademola AD, Odusola AO, Agyekum F, Nwanfor CE, Cole H, et al.
Factors associated with medication non-adherence among hypertensive patients in Ghana and Nigeria. Int J Hypertens 2015;2015:205716.
Buanbeng KO, Matowe L, Plange-Rhole J. Unaffordable drug prices: The major cause of non-adherence with hypertensive medications in Ghana. Pharm Sci 2004;7:340-2.
Clime CM, Björck-Linne AK, Isrealsson BY, Willenheimer RB, Erhardt LR. Non-compliance and knowledge of prescribed medications in elderly patients with heart failure. Eur J Heart Fail 1999;1:145-9.
New York Heart Association Criteria Committee. Disease of the Heart and Blood Vessels: Nomenclature and Criteria for Diagnosis. 6th
ed. Boston, Mass: Little, Brown; 1964.
Chan AH, Horne R, Hankins M, Chisari C. The medication adherence report scale: A measurement tool for eliciting patients' reports of nonadherence. Br J Clin Pharmacol 2020;86:1281-8.
Lee D, Mansi I, Bhushan S, Parish R. Non-adherence in at-risk heart failure patients: Characteristics and outcomes. JNSCI 2015;1:5.
Raimi TH. Factors influencing medication adherence among patients with diabetes mellitus and hypertension in Nigeria. Eur J Bio Med Sci Res 2017;518-26.
Lam WY, Fresco P. Medication Adherence Measures: An Overview. Biomed Res Int. 2015;2015:217047.
Jing S, Naliboff A, Kaufman MB, Choy M. Descriptive analysis of mail interventions with physicians and patients to improve adherence with antihypertensive and antidiabetic medications in a mixed-model managed care organization of commercial and Medicare members. J Manag Care Pharm 2011;17:355-66.
Hood SR, Giazzon AJ, Seamon G, Lane KA, Wang J, Eckert GJ, et al.
Association between medication adherence and the outcomes of heart failure. Pharmacotherapy 2018;38:539-45.
Cortaredona S, Ventelou B. The extra cost of comorbidity: Multiple illnesses and the economic burden of non-communicable diseases. BMC Med 2017;15:216.
Ogbemudia EJ, Asekhame J. Rehospitalization for heart failure in the elderly. Saudi Med J 2016;37:1144-7.
Aljadhey H, Tu W, Hansen RA, Blalock SJ, Brater DC, Murray MD. Comparative effects of non-steroidal anti-inflammatory drugs (NSAIDs) on blood pressure in patients with hypertension. BMC Cardiovasc Disord 2012;12:93.
Ezeala-Adikaibe BA, Aneke E, Mbadiwe N, Okudo G, Orjioke C, et al.
Medical comorbidities and physical disability among hypertensive patients from a tertiary hospital clinic in Enugu, south-east Nigeria. Ann Med Health Sci Res 2017;7:22-7.
Farrell B, Merkley VF, Ingar N. Reducing pill burden and helping with medication awareness to improve adherence. Can Pharm J 2013;146:262.
Cholowski K, Cantwell R. Predictors of medication compliance among older heart failure patients. Int J Older People Nurs 2007;2:250-62.
Granger BB, Ekman I, Granger CB, Ostergren J, Olofsson B, Michelson E, et al.
Adherence to medication according to sex and age in the CHARM programme. Eur J Heart Fail 2009;11:1092-8.
Wu JR, Moser DK, Chung ML, Lennie TA. Predictors of medication adherence using a multidimensional adherence model in patients with heart failure. J Card Fail 2008;14:603-14.
Roe CM, Motheral BR, Teitelbaum F, Rich MW. Angiotensin-converting enzyme inhibitor compliance and dosing among patients with heart failure. Am Heart J 1999;138:818-25.
Bagchi AD, Esposito D, Kim M, Verdier J, Bencio D. Utilization of, and adherence to, drug therapy among medicaid beneficiaries with congestive heart failure. Clin Ther 2007;29:1771-83.
Nieuwenhuis MM, Jaarsma T, van Veldhuisen DJ, van der Wal MH. Self-reported versus 'true' adherence in heart failure patients: A study using the Medication Event Monitoring System. Neth Heart J 2012;20:313-9.
[Table 1], [Table 2], [Table 3], [Table 4], [Table 5], [Table 6]
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