INTRODUCTION

One of the leading brain disorders in developing countries such as sub-Saharan Africa (SSA) is represented by epilepsy. It is estimated that 80% of people living with epilepsy (PWE) around the world, reside in developing world such as Africa (1). In Ethiopia, the prevalence of epilepsy in rural area was estimated to be 5.1 in 1000 and incidence was 64 /100,000 (2). Contrary to the western countries, very few PWE get adequate treatment in low-and middle-income countries (LMIC), whereby the treatment gap reaches around 95 % (1,3). Antiepileptic drugs (AEDs) are effective in treatment of epilepsy whereby about 70% of patients with epilepsy can be seizure free. Good adherence to AEDs will results in remission and functional restoration among individuals suffering from epilepsy (4). In most cases the stigma of the disorder plays a major role in discouraging people from seeking treatment for symptoms and becoming identified with the disorder; in different communities there is a belief that epilepsy is contagious and hesitate to give help a person who has fallen during seizure (5); further worsening the poor adherence of AEDs among PWE.

Epilepsy is widely associated with increased mortality and morbidity. PWE have estimated mortality of two to three times than general population (3). In most developing countries, factors that attribute for treatment gap of epilepsy in includes: limited access to health care facilities, unavailability of AED, lack of awareness of medical treatment, cultural stigmas and poor adherence (6). Non-adherence to medication treatment regimens is a worldwide health problem. Non-adherence rates among patients with epilepsy range from 30% to 50 % and highly associated with morbidity and mortality of the illness (4–7). Poor adherence to AEDs leads to repeated seizure attack, psychosocial stress; factors contributing to the treatment adherence could be individual factors like demographic and socioeconomic features, perception and beliefs about epilepsy; disease features like seizure frequency and severity; medication use like number of daily doses and side effects, and factors related to patient–provider relationship (4–7). To date, most of the studies conducted to evaluate AEDs adherence among PWE did not account for the influence of variables such as, comorbid depression.

Therefore, the objective of this study was to assess the prevalence of AEDs adherence and associated factors in epileptic individuals in tertiary care centers in Addis Ababa, Ethiopia.

METHODS AND MATERIALS

Study area and design

The study was conducted at the Neurology referral clinic in Tikur Anbesa Specialized Hospital (TASH) and Zewditu Memorial Hospital (ZMH). TASH is the largest specialized referral teaching hospital in the country. Epilepsy is one of the top ten diseases seen at neurology referral clinic. ZMH is one of the tertiary level public hospital affiliated with TASH and located in the vicinity of TASH. Combined, nearly 1,200 PWE /year are seen both at TASH and ZMH. The Study was conducted from April 1st, 2018 to September 30, 2018. This is a facility based observational cross-sectional survey in a sample of an epileptic patients visiting the two neurology referral clinic during study period fulfilling the inclusion criteria; age ≥13 years and on the AEDs treatment for at least six months.

Assessment tools used during the study

Morisky Medication Adherence Scale (MMAS-8) was used for adherence assessment. Sensitivity of this scale was estimated to be 93%, and the specificity was 53%. The medication adherence measure proved to be reliable with good concurrent and predictive validity in primarily low income, minority patients with hypertension. Score of ≤ 2 are to be adherent and >2 are to be non-adherent (8). Depression was assessed using a well validated assessment tool; Patient Health Questionnaire (PHQ)-9 PHQ-9 with a sensitivity of 88% and specificity of 88% for major depression. PHQ-9 score 5, 10, 15, and 20 represents mild, moderate, moderately severe and severe depression (9).

Statistical analysis

Clinical characteristics were first described by their means, frequency, percentile, and standard deviation. Association were done using chi square or Fisher exact test, logistic regression analysis and results were presented using odds ratio (OR), and p value was set at < 0.05 as statistically significant.

Ethical considerations

Ethical clearance was obtained from Addis Ababa University School of Medicine Neurology Department Ethics Committee. All questionnaires were coded to maintain maximum confidentiality. All patients gave a written or verbal consent before the interview.

RESULTS

Baseline and clinical characteristics of study participants

A total of 250 epileptic patients were included in the present study. The mean age was 29.4 ± 11.5 years. The prevalence of AEDs non-adherence was 47.6% (n=119) and 45.2% fulfilled diagnostic criteria of comorbid depression (Table 1). Those participants age below 30 years shows significant association with antiepileptic drugs non-adherence compared with those above age 30 (Figure 1). Males accounted for 54% (n=135). The majority (92%) came from urban areas. More than half (65.6%) were single. Majority (65.2%) of the participants attended primary education and above; and little more than half of the patients were unemployed. Out of the total participants, nearly two-third of the patients reported having seizure in the past two weeks despite taking the AEDs. In majority of the epileptic patients (n=215, 86%), the antiepileptic drug was initiated immediately / or after one year. Those individuals who reported stigma shows higher AEDs non-adherence compared to those with no-stigma (Figure 2). Hundred thirty-nine (55.6%) participants were on monotherapy; and more than half (59.6%) of the patients pay for their AEDs by themselves (Table 1).

Risk factors of antiepileptic drugs (AEDs) non-adherence in the study participants

In the present study, individuals aged below 30 year were significantly associated with AEDs non-adherence compared to those above 30 (p=0.01); and no significant difference was observed between gender and AEDs non-adherence (p=0.85). In the present study, single epileptic patients are associated with AEDs non-adherence. No association was observed between non-adherence and employment status; level of education; AEDs polytherapy; and AEDs insurance coverage (Table 2). Co-morbid depression was significantly associated with AEDs non-adherence (p=0.009). In the present survey, near-significant association was observed between AEDs non-adherence and having seizure in the past two years (p=0.05). Higher proportion of AEDs non-adherence was observed among epileptic patients who started AEDs immediately/ or after 1 year, compared to those patients who started AEDs late after epilepsy diagnosis (p=0.08) (Table 2).

Logistic regression analysis of AEDs non-adherence and covariates

In the present study, in multivariate logistic analysis, age of the study participants (AOR 0.94, 95% CI 0.89-0.98, p=0.006); age at first seizure (AOR 1.07, 95% CI 1.03-1.12, p=0.001); and comorbid depression (AOR 1.80, 95% CI 1.01-0.32, p=0.04) were found to be an independent predictors of AEDs non-adherence when adjusted for the covariates. In univariate logistic regression analysis, being single was associated with AEDs non-adherence (COR 2.05, 95% CI 1.20-3.51, p=0.009); however, when adjusted for age, age at first seizure, and comorbid depression, near-significant association was observed (p=0.07) (Table 3).

DISCUSSION AND CONCLUSION

Patients with epilepsy have increased mortality and morbidity compared to general population (10–12). Non-adherence to AEDs considered one of the reasons for such detrimental effect of epilepsy (13,14). The present study found out that 46.7% of patients were non-adherent to their AEDs. Globally the rate of non-adherence range between 30 and 50 % (15–17). The present study is consistent with cross sectional study conducted in Nigeria were the rate of non-adherence was 44.5 % (16), but higher than other studies (10,11,18). The discrepancy in the rate of non-adherence with other study is due to different methods in assessing adherence and sample size. This result highlighted the need to address the poor antiepileptic drug adherence observed among people living with epilepsy in Ethiopia.

In the present study, higher proportion of non-adherence was observed in younger, single, and those study participants who reported stigma. Many of the studies including local regarding factors associated with poor treatment adherence found longer treatment duration, forgetfulness, complex therapy, cost of the drug and comorbid illness (14–17,19). In this study comorbid depression found to be predictor of poor adherence which is consistent with one study in china (12). In the present study, factors such as; being single and feeling of stigma because of their diagnosis was associated with higher proportion of AEDs non-adherence. These is consistent with previously reported studies; which identified the following factors influencing adherence including: specific beliefs about medications, being depressed or anxious, poor medication self-administration management, being married, uncontrolled recent seizures, frequent medication dosage times, being female, and financial or cost of drugs (5,6,20,21). Therefore, it’s important to tackle these factors in epileptic patients to improve their AEDs adherence.

In the present observation, younger study participants, having seizure in a younger age, and experiencing seizure in the past two years were associated with antiepileptic drugs non-adherence. These results are consistent with previously reported studies (4,6,20–23). This highlighted on the need to focus on the younger epileptic patients to improve their adherence and frequently assessing their antiepileptic medications schedules; this way we may able to detect those having poor adherence and able to intervene earlier.

Through logistic regression, age at first seizure, being single and comorbid depression showed association with poor adherence. Previous studies also showed consistent findings with the present study (22–25).This finding necessitate screening of patient regularly for comorbid depression and giving emphasis regarding treatment adherence among younger age groups.  In the present study, comorbid depression was observed in nearly half of the study participants. This is consistent with previously reported studies which shown that the prevalence of depression is higher in those with epilepsy as compared to matched healthy controls (26–28). Depression is the most common comorbid psychiatric disorder in patients with epilepsy, yet it remains under- recognized and under-treated and reported by nearly 43% (26–28). This result further supports the need to include routine screening of depression among epileptic patients in Ethiopia; in order to identify, diagnose, and treat early. The limitations of this study include: small sample size and lack of healthy control groups. In summary, the present study showed high prevalence of antiepileptic medication non-adherence among epileptic patients in Addis Ababa, Ethiopia. Furthermore, participants age, age at first seizure, and comorbid depression were found to be independent predictors of AEDs non-adherence. We recommend conducting a future prospective control study in order to consolidate the present results.

Acknowledgements: We thank all the patients who participated in this study and all the nurses working at the two neurology clinics

Declarations:

Consent to publish: Participants consent for publication is not applicable.

Availability of data and materials: All data sets on which the conclusions of the manuscript rely are available as spread excel sheets documents and available from the corresponding author on reasonable request from the journal.

Competing interests: The authors declare they have no competing financial interests.

Funding: No funding was received.

Table 1: Baseline characteristics of study participants (n=250)

Table 2: Risk factors of AEDs non-adherence in the study participants (n=250)

Table 3: Logistics regression analysis of AEDs non-adherence and covariates

COR: Crude odds ratio; AOR: Adjusted odds ratio; CI: Confidence interval; Ref.: Reference.

Figure 1: Bar graph showing association between those below age 30 years and antiepileptic drugs (AEDs) non-adherence.

Figure 2: Bar graph showing a near-significant association between stigma and antiepileptic drugs (AEDs) non-adherent study participants