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23 January 2025: Clinical Research  

Factors Affecting Medication Adherence in Middle-Aged and Elderly Patients in China: A Cross-Sectional Study

Jun-kai Dou1ABCDEFG, Huan Liu2ABCDEFG, Yan Mei1BC, Jin Mei1CD, Xue-zhi Shi1BC, Aoqi Dong3BC, Zhengxia Yang4BC, Xiubin Tao4ADEFG, Ming Zhang56ABCDEFG*

DOI: 10.12659/MSM.945805

Med Sci Monit 2025; 31:e945805

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Abstract

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BACKGROUND: As the population ages, comorbidities among elderly patients are becoming a significant problem, due to associated risks and mortality. Medication adherence is crucial for controlling chronic diseases and improving patient outcomes; therefore, it is important to understand medication adherence among hospitalized patients.

MATERIAL AND METHODS: A cross-sectional study was conducted from June 2023 to April 2024 in 2 tertiary hospitals in Wuhu City, Anhui Province, China. Patients were divided into 2 age groups: 45 to 60 years and over 60 years. Data were collected using a self-designed sociodemographic questionnaire, the 4-item Morisky Medication Adherence Scale (MMAS-4), frailty scale, social frailty scale, and subjective cognitive decline questionnaire 9 (SCD-Q9).

RESULTS: A total of 963 inpatients were recruited, with 18.0% being middle-aged and 82.0%, elderly. The prevalence of medication adherence was 50.2%. Univariate analysis showed that medication adherence was significantly associated with place of residence, having relatives as medical personnel, physical frailty, social frailty, and subjective cognitive symptoms. Correlation analysis revealed that medication adherence was significantly negatively correlated with physical frailty, social frailty, and subjective cognitive symptoms. Binary logistic regression confirmed significant associations between medication adherence and physical frailty, social frailty, and subjective cognitive symptoms.

CONCLUSIONS: This study investigated medication adherence and its influencing factors among hospitalized patients with comorbidities in Anhui Province, China, identifying several influencing factors. Therefore, targeted interventions should be implemented by the government and relevant departments to improve patients’ medication adherence.

Keywords: Cognitive Dysfunction, Comorbidity, frailty, medication adherence

Introduction

With the changes in lifestyle and acceleration of aging, multiple diseases among middle-aged and elderly people have become a common phenomenon. Recent systematic studies have shown that the prevalence of multiple diseases, known as multimorbidity, ranges from 23% to 33% and continues to increase with age [1]. Multimorbidity, defined as the presence of 2 or more chronic conditions, has significant implications for public health and primary care [2]. Multimorbidity is associated with higher medical costs, worse clinical outcomes, and higher disability and mortality [1,3]. Medication adherence is defined as patients taking medications as prescribed to achieve the best control of the disease [4]. Taking medication as the doctor directs is the most effective measure for treating chronic diseases [5].

Timely, regular, and long-term medication adherence can effectively relieve symptoms and further control the progression of the disease. Studies [6–8] have shown that improving medication adherence can effectively improve quality of life and reduce morbidity and mortality in patients with multimorbidity. However, studies have found that 65% of older adults with multimorbidity did not take their medications as prescribed [9], and older adults are particularly susceptible to non-adherence with medical recommendations, due to the polypharmacy associated with multimorbidity [10]. Poor medication adherence has a major impact on a patient’s health, including increased risk of death and disease progression and decreased disease control and quality of life [11]. In addition, poor medication adherence has been associated with increased healthcare utilization and costs [12]. Studies have found that medication adherence is related to patient sex [13], age [14], lack of physical activity [15], cognitive function [16–18], education level [19], alcohol consumption quantity [15], drug quantity [18], drug cost [16], and adverse drug reactions [16–18]. Polypharmacy due to comorbidities and increased dosing frequency due to specific dietary or time constraints can affect medication adherence in middle-aged and elderly people.

Lack of patient knowledge and negative beliefs about medications are essential predictors of non-adherence [20]; fear of drug addiction is one of the main reasons older adults do not adhere to their medications. There are few studies on medication adherence in middle-aged and elderly patients taking multiple medications [21].

Therefore, we investigated and analyzed the medication adherence status of middle-aged and elderly inpatients with chronic diseases for the following 3 purposes: (1) to evaluate the medication adherence status of middle-aged and elderly hospitalized patients with chronic diseases; (2) to explore the influencing factors of medication adherence among middle-aged and elderly inpatients with chronic diseases; and (3) to explore the correlations between medication adherence and frailty, social frailty, and subjective cognitive decline in middle-aged and elderly inpatients with chronic diseases.

Material and Methods

SETTING AND PARTICIPANTS:

A survey study was conducted in the First Affiliated Hospital of Wannan Medical College (Yijishan Hospital of Wannan Medical College), and the Affiliated Hospital of Wangnan Medical College, 2 tertiary hospitals in Wuhu City, Anhui Province, China, from June 2023 to April 2024. This study hired 10 nursing undergraduate and master students who had received questionnaire standardization training as investigators to collect data. The sample size was calculated as follows:

with Zα=1.96, 95% CI, and error range of 5%. The proportion of medication adherence in patients with chronic diseases (P) was 45.7% (7), and the δ value was 0.05. Considering a 20% invalid survey response rate, the expected sample size was at least 458. Finally, 1000 patients responded to the survey, and 963 of the 1000 provided valid responses (response rate 96.3%).

Eligible patients were invited to participate in the study. Patients were provided with detailed information about the content and significance of the study and were informed of survey precautions and the principle of anonymous participation. All patients were informed that the content they filled in was strictly confidential to the on-site investigators, and that the questionnaire would not collect any personal privacy information, which could encourage patients to truthfully complete the questionnaire for this study. Each questionnaire was numbered immediately after completion and checked by the investigator for missing or obvious erroneous information. If there was missing information, patients were asked to fill it out again. For patients with special circumstances who could not fill out the questionnaire independently, the investigator would read the questionnaire content verbatim, the patient will choose the answer, and then the investigator recorded the answers on the questionnaire based on the patient’s answer, to help them complete the questionnaire. Additionally, all questionnaires were returned immediately after completion.

The inclusion criteria were as follows: (1) inpatients aged 45 years old and above; (2) informed consent and cooperate in completing the questionnaire was obtained; (3) diagnosis of at least 2 chronic diseases (hypertension, diabetes, coronary heart disease, stroke, and other chronic diseases); and (4) taking ≥1 drug for more than 3 consecutive months.

The exclusion criteria were as follows: (1) severe intellectual problems or mental illness; (2) severe cardiopulmonary insufficiency; and (3) severe hearing or vision problems (Figure 1).

SOCIODEMOGRAPHIC CHARACTERISTICS:

After we conducted a literature review analysis, we created a self-designed sociodemographic information form, which was used to collect general sociodemographic profile data from the study participants. Sociodemographic information included age, sex, marital status, education level, physical examination status, place of residence, course of chronic diseases, and per capita monthly household income.

MEDICATION ADHERENCE: Medication adherence was assessed using the 4-item Morisky Medication Adherence Scale (MMAS-4), a reliable self-report questionnaire [22]. The MMAS-4 is a general self-report medication-taking behavior scale applicable to a variety of medical conditions. It consists of 4 items with a scoring scheme of “yes”=0 and “no”=1. These items are summed to produce a score range of 0 to 4 points. If a patient has a score above 1 point, they are considered to have bad medication adherence [23].

FRAILTY SCALE: The frailty scale was used to evaluate physical frailty [24]. This frailty scale includes 5 self-reported components: fatigue, resistance, ambulation, illness, and loss of weight. A “yes” answer was scored as 1 point, while a “no” answer was scored as 0. The total score is the sum of the scores of the 5 items, and the score ranges from 0 to 5. The higher the total score, the greater the degree of frailty, and a score of 3 or higher indicates frailty. The frailty scale has the advantages of being short, convenient, and time-saving, it has strong predictive validity, and it is suitable for rapid screening in cross-sectional studies of large-sample inpatients. This scale has relatively excellent internal consistency, and the Cronbach alpha coefficient in this study was 0.881.

SOCIAL FRAILTY SCALE: Social frailty was defined using the HALFE social frailty scale, which includes 5 self-reported components: inability to help others, limited social participation, loneliness, financial difficulty, and living alone [25]. HALFE is an abbreviation for the 5 elements: Help, pArticipation, Loneliness, Financial, and living alonE. If an item was answered “no”, the item was scored 0 points, if it was answered “yes”, then the item scored 1 point. Patients with summed scores of 3 or more points were categorized as having social frailty. Research has found that the HALFE scale has relatively good internal reliability [26], and the Cronbach alpha value in this study was 0.883.

SUBJECTIVE COGNITIVE SYMPTOMS: Symptoms of subjective cognitive decline were assessed with the subjective cognitive decline-questionnaire 9 (SCD-Q9), which is considered a relatively reliable scale for assessing cognitive decline [27]. The SCD-Q9 measures the 9 core items of subjective cognitive decline and contains 2 dimensions and 9 items, including the overall memory function and time comparison (4 items) and daily activity ability (5 items). Each item’s score can be 0, 0.5, or 1, and the total score of the SCD-Q9 ranges from 0 to 9, with higher scores indicating more severe subjective cognitive decline. In our study, the Cronbach alpha value of the SCD-Q9 was 0.80.

STATISTICAL ANALYSIS:

All data were inputted into Microsoft Office Excel 2016 (Microsoft Corporation) software, and SPSS version 21.0 (IBM Corp, Armonk, NY, USA) was used to conduct the statistical analysis. Categorical variables are expressed as numbers or percentages. Univariate analysis was performed in this study using the chi-square test to compare categorical variables. Pearson correlation analysis was used to analyze the interrelationship between the 3 variables. Using medication adherence as the dependent variable (good=0, poor=1), binary logistic regression was performed to examine the effects of sociodemographic characteristics, physical frailty, social frailty, and subjective cognitive decline on medication adherence status. Statistical significance was determined by a P value <0.05.

ETHICS APPROVAL:

This study was approved by the institution’s ethics review board. All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki declaration and its later amendments or comparable ethical standards.

Results

PARTICIPANT CHARACTERISTICS:

Table 1 shows the sociodemographic characteristics of the patients in this study. A total of 963 patients were included. The mean age was 70.75 (SD=10.90) years, ranging from 45 to 98 years. Of the patients, 509 (52.9%) were male, and 454 (47.1%) were female. A total of 125 (13.0%) patients had a chronic disease course <1 year, 110 (11.4%) had a duration of 1 to 3 years, 85 (8.8%), 4 to 5 years, 158 (16.4%), 6 to 10 years, 171 (17.8%), 11 to 15 years, 113(11.7%), 16 to 20 years, and 201 (20.9%), ≥21 years.

FACTORS ASSOCIATED WITH MEDICATION ADHERENCE IN THE UNIVARIATE ANALYSIS:

In this study, the prevalence of poor medication adherence among the patients with multiple chronic diseases was 49.8% (480/963). In univariate analysis, factors that were closely related to poor medication adherence were place of residence, friends and relatives were health care workers, physical frailty, social frailty, and subjective cognitive decline (P<0.05; Table 2).

CORRELATIONS BETWEEN MEDICATION ADHERENCE AND RELEVANT INDICATORS:

As shown in Table 3, subjective cognitive decline was negatively associated with medication adherence (r=−0.313, P<0.001), and the relationship between physical frailty and medication adherence was statistically significant (r=−0.278, P<0.001). Social frailty correlated negatively with medication adherence (r=−0.226, P<0.001).

BINARY ANALYSIS FACTORS ASSOCIATED WITH MEDICATION ADHERENCE:

In the binary logistic regression analysis, the independent variable (P<0.05) and the dependent variable (grouping, 0=good medication adherence, 1=poor medication adherence) were put into the model. The factors that affected medication adherence in patients with comorbid chronic diseases are shown in Table 4. Patients living in town usually had better medication adherence than those living in rural areas (OR=0.986, 95% CI 0.693–1.404), as did patients living in cities (OR=0.682, 95% CI 0.504–0.924). The more severe the physical frailty, the worse the medication adherence status (OR=2.100, 95% CI 1.590–2.773). The more severe the social frailty, the worse the medication adherence status (OR=1.546, 95% CI 1.091–2.189). Subjective cognitive decline was a risk factor for medication adherence (OR=2.055, 95% CI 1.502–2.812).

Discussion

LIMITATIONS:

This study had limitations. First, because this was a cross-sectional study, it was impossible to determine the causal relationship between medication adherence and frailty, social frailty, and subjective cognitive decline in patients with comorbidities. Second, our study sample size included only patients with comorbidities hospitalized in Wuhu City, Anhui Province, limiting the generalizability of our findings.

Conclusions

In conclusion, middle-aged and elderly patients with comorbidities in Anhui, China, showed low medication adherence. Physical frailty, social frailty, and subjective cognitive symptoms were all significantly associated with medication adherence. Because of the critical impact of medication adherence on the quality of life for patients with comorbidity, active and effective interventions are needed for them to improve their medication adherence and mental health.

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