Baseline patient characteristics.

Background and aims
Medication adherence is a determinant of managing chronic disease. Failure to adhere to treatment can result in disease progression, increased hospitalizations, and a higher risk of complications and mortality. This study aimed to determine the level of medication adherence in older adults with type 2 diabetes based on the Health Action Process Approach (HAPA).
Methods
This study is a descriptive-analytical cross-sectional study that was conducted on 179 older adults with type 2 diabetes. Data were collected using the Morisky Medication Adherence Scale (MMAS-8-Item) and the HAPA questionnaire. We used the chi-square test to compare adherence to medication by demographic characteristics and multiple binary logistic regression analysis to predict factors related to medication adherence based on the HAPA dimensions.
Results
A total of 179 participants (87 men and 92 women) with a mean age of 64.65 ± 4.99 years were enrolled. Low medication adherence was reported by 62% of participants. No significant associations were found between socio-demographic factors (gender, marital status, education, employment, and income) and adherence levels. Logistic regression analysis revealed that smoking (OR = 4.309, 95% CI [1.18, 15.67], p = 0.027) and perceived barriers to adherence (OR = 1.036, 95% CI [1.01, 1.06], p = 0.001) were significantly associated with increased odds of medication non-adherence. Conversely, higher recovery self-efficacy (OR = 0.924, 95% CI: 0.86–0.99, p = 0.027) and coping planning (OR = 0.963, 95% CI: 0.93–0.99, p = 0.022) were associated with reduced odds of non-adherence. The most common self-reported reasons for suboptimal adherence were lack of affordability (17.5%), lack of family support (10%), and poor understanding of the disease (9.4%).
Conclusion
This study highlights that older people had suboptimal adherence to medication. Smoking and perceived barriers were significant risk factors, increasing the likelihood of poor adherence. Conversely, higher levels of recovery self-efficacy and coping planning served as protective factors, reducing the risk of non-adherence. Policymakers and planners should consider the mentioned factors in designing interventions to change behavior for chronic diseases like diabetes.