Predictors of poor adherence to antidiabetic therapy in patients with type 2 diabetes: a cross-sectional study insight from Ethiopia

Abstract

Background: Poor adherence to the medical regimen is a major clinical problem in the management of patients with diabetes. This study sought to investigate the level of medication adherence to antidiabetic therapy and to identify possible predictors of poor adherence. Methods: A hospital based cross-sectional study was conducted from July 2018 to June 2019 among randomly selected follow-up T2D patients at a hospital diabetes clinic. Data were collected through patient interviews, followed by medical chart review. Adherence to antidiabetic therapy that we assessed patients' responses using validated Brief Medication Questionnaire (BMQ). To identify predictors of poor medication adherence, binary logistic regression analyses were performed using SPSS version 25. Statistical significance was set at p value ≤ 0.05. Results: Of the total 357 study participants, 25% were non-adherent to their antidiabetic therapy. Predictors statistically associated with poor adherence were; being female gender (AOR = 1.71, 95% CI 1.01-2.76), and presence of at least one diabetic complication (AOR = 2.02, 95% CI 1.02-3.22). Participants with having at least primary level of education were more likely to adhere to anti-diabetes medication (AOR = 0.42, 95% CI 0.18-0.96). The most common self-reported reasons for non-adherence were forgetfulness, unavailability of medication plus the unaffordability of anti-diabetes medications. Conclusions: The proportion of participants' adherent to anti-diabetes therapies was suboptimal. Being female, the presence of chronic diabetic complications and having no formal education were the main predictors of poor adherence. Strategies that aimed at improving adherence to antidiabetic medications deemed to be compulsory.

Machine Learning Approaches to Predict Risks of Diabetic Complications and Poor Glycemic Control in Nonadherent Type 2 Diabetes

“…Instead of the senior group, the subjects of our study were T2D patients, and the prognosis of T2D we predicted was HbA1c and diabetic complications. In a cross-sectional study, the author explored the main predictors of poor adherence among T2D patients ( Demoz et al, 2020 ). Another study, a previous article by Dr. Wu, assessed multiple ML algorithms and predicted the medication nonadherence risks of patients with T2D ( Wu et al, 2020 ).…”

Predictors of Adherence Toward Specific Domains of Diabetic Self-Care Among Type-2 Diabetes Patients

“…Moreover, in this study, all patients were adherent to antidiabetic medication, because they received at least 80% of medication as per the prescribed dose and frequency. However, inconsistent rates were reported from different studies: 69.4% in Sudan, 31 83.7% in North Ethiopia, 24 85% in Gondar, Northwest Ethiopia, 40 90% in Eastern Ethiopia, 26 67% in Gauteng, SA 27 76.2% in the Philippines, 29 95.7% in Addis Ababa, 33 76% in Aksum, North Ethiopia, 41 and 45% in Davangere, India. 32 The classification approach of adherence toward antidiabetic medication and the nature of self-reported adherence evaluation condition between the studies might expose the adherence rate evaluation to over or underestimation.…”

Magnitude and associated factors of poor medication adherence among diabetic and hypertensive patients visiting public health facilities in Ethiopia during the COVID-19 pandemic

“…Most patients have also implied in their report of perceived negative influence the outbreak had posed in terms of meeting with follow-up appointments, accessing medicines, and affording for prices. These factors are mentioned to account for a remarkable role in patients’ poor adherence to therapy [ 37 , 38 ].…”