Globally, the non-communicable disease prevalence, such as Diabetes mellitus (DM) and hypertension, is estimated to be 25-30% in low- and middle-income countries [1] and 3.3% in developing countries [2]. Indonesia as low- and middle-income country, ranks seventh globally in diabetes mellitus (DM) prevalence, with around 10 million adults affected [3]. Complications from type 2 DM are a leading cause of death in the country [4]. Especially in Central Java, Indonesia, DM accounted for 18.33% of all reported non-communicable disease cases and ranked the second highest percentage [5]. Experts project that non-communicable diseases will cause economic losses amounting to 4.47 trillion US$ from 2012 to 2030, equivalent to 1.5 times Indonesia’s 2012 Gross Domestic Product [6]. Furthermore, low public awareness about DM makes it challenging to manage blood glucose effectively, leading to various complications [7].

DM significantly impacts the quality of human resources and substantially increases healthcare costs [8]. Non-communicable diseases have common characteristics that make affected individuals more vulnerable to emergency conditions, such as a two to three times higher risk of heart attacks and strokes [1]. Therefore, all parties, including the community and the government, should actively participate in countering DM [8]. Research indicates that understanding the complexities of patient decision-making helps healthcare professionals engage better with individuals living with diabetes [7]. Good adherence to diabetes treatment can control blood sugar levels and minimize cardiovascular events [9]. For diabetic patients who are unaware of how to adhere to medication properly, unintentional factors such as irregular access to oral hypoglycemic agents and insulin can arise [10]. Patients with lower treatment adherence often exhibit poor glycemic control compared to those with higher adherence [11–13].

Factors influencing medication adherence include gender, education, employment status, duration of illness, health insurance coverage, knowledge about the disease, accessibility to healthcare services, healthcare provider’s role, motivation for treatment, and family support [14–19]. Age, disease duration, treatment adherence, diet, and physical activity can affect blood glucose levels [20][21]. A combined analysis of six studies on anti-diabetic medication practice determinants showed that age and place of residence are significant determinants of adherence to anti-diabetic medication in Ethiopia [22]. Meanwhile, intentional factors like lack of perceived benefits from medication, fear of side effects, and increasing regimen complexity contribute to reduced medication adherence [23][24]. Therefore, the present study aimed to determine the medication adherence profile in patients with type 2 DM and the influencing factors in Kalinyamatan Primary Health Center, Central Java, Indonesia.

Place of the research. The study was conducted at at Kalinyamatan Community Health Center in Jepara in October 2022, involving patients with Diabetes Mellitus who visited the health center.

This research involved 90 respondents in Kalinyamatan Primary Health Center, Central Java, Indonesia. We included individuals diagnosed with type 2 DM, having the disease for more than a year, and visiting the health center, and excluded the patients with DM who did not live with their families.

This research used a total sampling technique, meaning that all members of the population who met the inclusion criteria were included in the study, ensuring that the sample fully represents the studied population. The researcher wants to capture the characteristics of every individual within the population, leading to more comprehensive and generalizable findings.

This study conducted a descriptive correlational design with a cross-sectional approach to determine the medication adherence profile in patients with type 2 DM and the influencing factors in Kalinyamatan Primary Health Center, Central Java, Indonesia. Primary data collection was from Diabetes Mellitus patients who visited Kalinyamatan Community Health Center. Respondents filled out questionnaires to gather information on gender, education, age, occupation, duration of illness, family support, and medication adherence. The Perceived Social Support-Family Questionnaire (PSS-Fa) [25] was used to measure the variable of family support while measuring medication adherence using the Morisky Adherence Scale (MMAS-8) questionnaire [26].

The collected data from the respondents underwent a thorough review for completeness of responses, scoring, and coding. Subsequently, the data were analyzed using statistical software, SPSS version 22. Descriptive analysis was utilized to describe the characteristics of the respondents, including gender, education, age, occupation, duration of illness, family support, and treatment adherence. Simple and multiple logistic regression analyses were employed to determine the factors influencing treatment adherence among diabetes mellitus patients.

This study was approved by the Ethics Committee of Universitas Ngudi Waluyo University on October 25, 2022, with approval number 103/KEP/EC/UNW/2022. Informed consent was provided to all respondents before participating in the study.

This study included 90 individuals with type 2 DM. The data analyzed covered the characteristics of the respondents, including gender, education, age, occupation, duration of illness, family support, and treatment adherence. Table 1 provides a complete breakdown of these characteristics.

Based on Table 1, the majority of the respondents were female (57.8%), below 60 years old (83.3%), had a low level of education (83.3%), were unemployed (52.2%), had a duration of illness of two years or more (64.4%), received good family support (61.1%), and demonstrated high medication adherence (75.6%). However, there was still a 24.4% non-adherence rate among DM patients.

Table 2 shows that the simple logistic regression analysis identified four factors significantly influencing medication adherence among DM patients (p<0.05). Age was a significant predictor (p=0.007, OR=0.232, 95% CI=0.80-0.67), indicating that younger patients were more likely to adhere to medication. Education level also played a significant role (p=0.048, OR=8.143, 95% CI=1.02-64.84), suggesting that patients with higher education levels were more likely to adhere to their treatment. Occupation was another influential factor (p=0.012, OR=3.659, 95% CI=1.30-10.01), with employed individuals showing higher adherence. Lastly, family support had a strong impact (p=0.002, OR=5.143, 95% CI=1.82-14.52), where patients with better family support were significantly more likely to follow their medication regimen. However, gender (p=0.259) and duration of illness (p=0.547) did not show a significant impact on medication adherence in this study (p>0.05), indicating that these factors were not strong predictors of adherence in the sample population.

Factors significantly influencing medication adherence were analyzed using multiple logistic regression to identify the most impactful factor. Table 3 shows that occupation emerged as the most influential factor in medication adherence (p=0.015, 95% CI=1.39-20.56). It indicates that employed individuals were significantly more likely to adhere to their medication regimen compared to unemployed. The wide confidence interval suggests a strong effect, although there may be some variability in the estimate.

The research results indicate that 24.4% of respondents have low adherence, 41.1% of diabetes mellitus patients have forgotten to take their medication at some point, 33.3% did not take their medication in the last two weeks, and 37.8% forgot to bring their medication when traveling. These findings align with other studies [27], which reported that nearly half of the respondents (44.9%) were non-adherent to their prescribed medication. Additionally, 22.5% had poor medication adherence, while the remainder fell into moderate and high adherence categories [28].

Four factors significantly influence medication adherence among diabetes mellitus patients, namely age, education, occupation, and family support, whereas gender and duration of illness do not. Multiple logistic regression analysis identified occupation as a significant factor influencing medication adherence, with a p-value of 0.015 (95% CI 1.39-20.56). Age and education level were found to be associated with adherence, which is consistent with the previous findings [27]. However, this contrasts with another study that found no association between age, education level, and medication adherence in diabetes mellitus patients [28]. Among respondents aged over 60 years, 11 (52%) were classified as having high adherence. Higher adherence rates increase with age [29]. As individuals age, the risk of developing various chronic diseases increases. Comorbidity can influence adherence by increasing awareness of a particular illness [30].

Additionally, 19 (95%) of respondents with higher education levels had high adherence, indicating that higher education correlates with better information absorption and behavior. Behavior is influenced by predisposing factors such as knowledge; better knowledge leads to better behavior [17]. The occupation was associated with adherence, corroborating previous findings that reported a statistically significant relationship between socioeconomic class and adherence [31]. However, this is contrary to the findings [28, 32] that found no association between occupation and adherence levels. Employed individuals tend to have less time to visit healthcare facilities, while unemployed individuals are generally more adherent due to having more time for healthcare visits.

Family support, referring to verbal information, goals, tangible assistance, or actions provided by individuals familiar with the issue, plays a role in the social environment. The interconnectedness between family and the environment is known as family support [33]. Family support can impact the health of individuals with chronic diseases, as indicated by a study conducted in Klaten, Indonesia. Patients are more motivated to maintain their health if they have good communication and family coping mechanisms [34]. Family support is one of the reinforcing factors that contribute to adherence behavior. Individuals can manage their health better at home due to the family’s ability to identify health problems, make decisions, offer care, maintain and improve household health, and locate necessary medical facilities [35]. Those receiving family support are more likely to follow medical advice compared to those without such support. Thus, family and social support are crucial for addressing health issues [36]. A study in Sukabumi found a significant relationship between family support and medication adherence among diabetes mellitus patients at the Internal Medicine Clinic of R. Syamsudin, S.H. Hospital, with a chi-square test p-value of 0.000 [37].

Addressing the issue of non-adherence among DM patients, healthcare providers should develop targeted educational programs, especially for older patients and those with lower education levels, emphasizing the importance of medication adherence. Involving family members in patient care is essential, as family support plays a crucial role. Workplaces should offer flexibility to help patients manage their treatment schedules. Regular monitoring and community-based interventions, such as medication reminders or visits by healthcare workers, can significantly improve adherence.

Researchers have been unable to control other factors that may affect medication adherence in this study, namely participation in health insurance, disease knowledge, access affordability to health services, health worker’s role, and motivation to look for treatment.

Further research is needed to measure the various factors that influence medication adherence.

There is still a 24.4% non-adherence rate among DM patients in Central Java, Indonesia. Four factors may influence medication adherence among diabetes mellitus patients, namely age, education, occupation, and family support, while gender and duration of illness have no significant impact in this study.

The source of financing. The authors’ funding to carry out the research.

Conflicts of interests. No conflicts of interest.

Author’s contribution. Puji Lestari – the concept or study design or to the obtaining, data analysis, or interpreting results, making significant changes to the manuscript; Liyanovitasari – the concept of study, writing an article, Heri Prabowo – the concept of study, writing an article. The authors approved the article’s final version before publication. They consented to be responsible for all aspects of the work, which implies proper resolution and investigation of its accuracy and integrity issues.

Acknowledgments. The author would like to express gratitude to the Head and staff members of Kalinyamatan Jepara Community Health Center; all the respondents who participated in this study; and the Nursing Undergraduate Program, Faculty of Health, Universitas Ngudi Waluyo.