Logistic Regression Analysis of Factors Affecting Medication Adherence in Hypertensive Patients at a Private Hospital in Jakarta - Farida Tuahuns; Alifa Sabrina; Fitri Savitri; Benjamin Atta Owusu; Nitinun Pongsiri; Mira Nurhalizah (Jurnal Ilmiah STIKES Yarsi Mataram, 2026)
Hypertension is one of the Non-Communicable Diseases (NCD) that can lead to serious conditions such as heart disease, stroke, or death. It can’t be cured; patients need lifelong medication. That is why adherence to treatment is a must for hypertensive patients. This study aims to investigate the relationship between sociodemographic, clinical factors and medication adherence among hypertension patients at a private hospital in Jakarta. This study is a pilot study using a cross-sectional method with 97 hypertensive patients. Patient medication adherence was assessed using the validated ProMAS questionnaire. The patients’ scores were then divided into two categories: good and poor adherence, based on 80% of the total score. Binary logistic regression was used to identify factors associated with adherence, with model selection based on the Akaike Information Criterion (AIC). The Pseudo-R² by Nagelkerke was used in this study for the model's goodness-of-fit, with a value of 0.232 (23.2%). The results showed that 74 (76.3%) patients had poor adherence, while 23 (23.7%) patients had good adherence. Among all the socioeconomic and clinical variables, only the education variables showed a significant correlation with medication adherence. Patients with college and junior high school education levels were more likely to be compliant compared to those with senior high school education (OR = 10.42 and OR = 8.75, respectively). The results of this study show that medication adherence among hypertensive patients in private hospitals varies based on patients’ backgrounds. The findings highlight the need for hospital policies, such as health education programs based on the patients’ education levels, in order to improve the effectiveness of long-term hypertension management.