Medication Adherence Among Patients with Multimorbidity in the United Arab Emirates

Overtreatment and Undertreatment of Early-Stage Breast Cancer in Older Women: Evaluating the POWER Trial

INTRODUCTION

Radiation therapy (RT) omission is acceptable in older women with early-stage estrogen receptor + breast cancer treated with breast-conserving surgery (BCS) and adjuvant endocrine therapy (AET). However, RT rates in this population remain high, causing concern for overtreatment. Conversely, patients who omit RT and do not complete a course of AET are at risk of undertreatment. In the Pre-Operative Window of Endocrine Therapy to Inform Radiation Therapy Decisions (POWER) trial, participants receive 90 days of preoperative endocrine therapy to assess tolerance before deciding about RT. This study aimed to determine the rates of undertreatment and overtreatment institutionally and among POWER trial participants.

METHODS

Data were retrospectively collected from medical records of women aged ≥ 65 years diagnosed with invasive, estrogen receptor +/human epidermal growth factor receptor 2- breast cancer, ≤ 3 cm, who had BCS between 2012 and 2022. Patients were categorized as undertreated (BCS alone), overtreated (BCS + RT + AET), or appropriately treated (BCS + RT or BCS + AET).

RESULTS

The cohort included 478 patients, of whom 62 (12.97%) were undertreated, 202 (42.26%) were overtreated, and 214 (44.77%) were appropriately treated. Appropriately treated patients were more likely to be aged 70-79 years (P < 0.0001) and have high health literacy (P = 0.0003). Of the 37 patients (7.71%) in the POWER trial, more were appropriately treated than patients not in the POWER trial (81.1% versus 44.8%) (P < 0.0001).

CONCLUSIONS

Despite long-standing guideline changes, RT utilization remains high. This study highlights how a novel patient-centered approach to guide adjuvant therapy decisions may increase the number of appropriately treated patients.

Trends and determinants of choline alfoscerate use in newly diagnosed Alzheimer's disease patients in Korea

BACKGROUND

Choline alfoscerate, a cholinergic precursor, is widely used in Korea for dementia-related symptoms and is covered by national health insurance (NHI). This study investigates the utilization trends and factors influencing choline alfoscerate prescription in newly diagnosed Alzheimer's disease (AD) patients using real-world data.

METHODS

We analyzed data from the Health Insurance Review and Assessment Service (HIRA) for patients aged 60 years and older who were newly diagnosed with AD between 2012 and 2019. Patients with prescriptions for acetylcholinesterase inhibitors (AChEIs) or memantine within 60 days of diagnosis were included. Choline alfoscerate utilization was defined as prescriptions within 60 days of initial diagnosis. Factors influencing its use were identified through multiple logistic regression analyses, and trends over time were assessed using the Cochran-Armitage Trend test.

RESULTS

Among the 330,326 study participants, 99,845 (33.08%) were prescribed choline alfoscerate, with usage increasing from 15.96% in 2012 to 47.65% in 2019. Factors positively associated with its use included male sex, MedAid insurance, and osteoarthritis. Conversely, usage decreased with comorbidities such as hypertension, congestive heart failure, stroke/transient ischemic attack, chronic kidney disease, and depression.

CONCLUSION

Choline alfoscerate usage in Korea has significantly increased, partly due to its national insurance coverage and the absence of disease-modifying therapies for AD. Given the uncertain efficacy and potential risks of choline alfoscerate, continuous monitoring and rigorous evaluation of its long-term benefits and safety are essential. Further research is necessary to establish definitive evidence for its effectiveness and guide its therapeutic use in AD management.

Highlights

Choline alfoscerate usage among newly diagnosed AD patients in Korea increased from 15.96% in 2012 to 47.65% in 2019.Male sex (OR = 1.05) and MedAid insurance coverage (OR = 1.07) were associated with higher odds of choline alfoscerate usage.Usage was more likely in patients with osteoarthritis (OR = 1.05) and less likely among those with hypertension (OR = 0.96), stroke/TIA (OR = 0.80), chronic kidney disease (OR = 0.80), and depression (OR = 0.93).Patients in rural areas had higher odds of using choline alfoscerate (OR = 1.28) compared to those in metropolitan areas (OR = 1.00).Despite limited evidence of efficacy, the extensive use of choline alfoscerate highlights the need for continuous monitoring and rigorous evaluation to ensure its safety and therapeutic value in AD management.

Developing and Validating a Nomogram for Non-Adherence to Inhaler Therapy Among Elderly Chronic Obstructive Pulmonary Disease Patients Based on the Social Ecological Model

Purpose

This study aimed to identify the risk predictors of non-adherence to inhaler therapy and construct a nomogram prediction model for use in Chinese elderly patients with chronic obstructive pulmonary disease (COPD).

Patients and Methods

A cross-sectional study was conducted with 305 participants recruited from a tertiary care hospital in Anhui, China. Adherence was analyzed using the Test of Adherence to Inhalers. Potential predictive factors were incorporated based on the social ecological model, and data were collected through a questionnaire method. R version 4.3.3 was utilized to perform the least absolute shrinkage and selection operator regression model and multivariable logistic regression analysis to identify risk factors and establish a nomogram prediction model.

Results

The results of the multivariable analysis revealed that medication beliefs, illness perception, the COPD Assessment Test score, smoking status, and education level were significant risk factors for non-adherence to inhaler therapy in elderly COPD patients (all P < 0.05). The nomogram prediction model for non-adherence to inhaler therapy in elderly COPD patients demonstrated a good discriminative ability, with an area under the receiver operating characteristic curve of 0.912. The C-index was 0.922 (95% CI: 0.879 to 0.965), and the Brier value was 0.070, indicating good consistency and calibration. Decision curve analysis indicated that the use of the nomogram would be more beneficial in clinical practice when the threshold probability of non-adherence exceeds 17%.

Conclusion

This study identified predictive factors regarding non-adherence among elderly patients with COPD and constructed a predictive nomogram. By utilizing the nomogram model healthcare professionals could swiftly calculate and comprehend the non-compliance level of COPD patients, thus guiding the development of personalized interventions in clinical practice.

Effect of medication adherence on quality of life, activation measures, and health imagine in the elderly people: a cross-sectional study

BACKGROUND

Usually, old age brings a poor quality of life due to illness and frailty. To prolong their lives and ensure their survival, all elderly patients with chronic diseases must adhere to their medications. In our study, we investigate medication adherence for elderly patients and its impact on the general health of the patient.

METHODS

We implemented a cross-sectional survey-based study with four sections in April 2022 in Saudi Arabia. Data about the participants' demographic characteristics, the Morisky Medication Adherence Scale, Patient Activation Measure (PAM) 13, and EQ-5D-5 L.

RESULTS

A total of 421 patients participated in this study, their mean age was 60.4 years, and most of them were males. Most of our population is living independently 87.9%. The vast majority of people have a low adherence record in the Morisky Medication Adherence Scale (8-MMAS) classes (score = < 6). Moreover, the average PAM13 score is 51.93 (Level2) indicating a low level of confidence and sufficient knowledge to take action. Our analysis showed a significant correlation between socioeconomic status and medication adherence. Also, there was an association between housing status and medication adherence. On the other hand, we found no correlation between medication adherence and quality of life (QOL) by EQ-5D-5 L.

CONCLUSION

Medication adherence is directly affected by living arrangements, as patients who live with a caretaker who can remind them to take their medications at the appropriate times have better medication adherence than those who live alone. Medication adherence was also significantly influenced by socioeconomic status, perhaps as a result of psychological effects and the belief of the lower-salaried population that they would be unable to afford the additional money required to cure any comorbidities that arose as a result of the disease. On the other hand, we did not find any correlation between medication adherence and quality of life. Finally, awareness of the necessity of adherence to medication for the elderly is essential.

Medication regimen complexity and its impact on medication adherence in patients with multimorbidity at a comprehensive specialized hospital in Ethiopia

Background

Medication regimen complexity (MRC) is suspected to hinder medication adherence in patients with multiple illnesses. Despite this, the specific impact on Ethiopian patients with multimorbidity is unclear. This study assessed MRC and its impact on medication adherence in patients with multimorbidity.

Methods

A hospital-based cross-sectional study was conducted on patients with multimorbidity who had been followed at the University of Gondar Comprehensive and Specialized Hospital (UoGCSH), Ethiopia, from May to July 2021. Medication complexity was measured using the validated Medication Regimen Complexity Index (MRCI) tool, and the Adherence in Chronic Diseases Scale (ACDS) was used to measure medication adherence. Pearson's chi-square test was used to examine associations between MRCI levels and medication adherence. Ordinal logistic regression analysis was used to determine the impact of MRC and other associated variables on medication adherence. Statistical significance was determined using the adjusted odds ratio (AOR) at p-value <0.05 and its 95% confidence range.

Results

Out of 422 eligible patients, 416 (98.6%) were included in the study. The majority of participants (57.2%) were classified as having a high MRCI score with a mean (±SD) score of 9.7 (±3.4). Nearly half of the patients (49.3%) had low medication adherence. Patients with medium (AOR = 0.43, 95% CI: 0.04, 0.72) and higher (AOR = 0.31, 95% CI: 0.07, 0.79) MRCI levels had lower odds of medication adherence. In addition, monthly income (AOR = 4.59, 95% CI: 2.14, 9.83), follow-up durations (AOR = 2.31, 95% CI: 1.09, 4.86), number of medications (AOR = 0.63, 95% CI: 0.41, 0.97), and Charlson comorbidity index (CCI) (AOR = 0.36, 95% CI: 0.16, 0.83) were significantly associated with medication adherence.

Conclusion

Medication regimen complexity in patients with multimorbidity was found to be high and negatively impacted the levels of medication adherence. Healthcare providers and other stakeholders should seek interventions aimed at simplifying drug regimen complexity and improving adherence.

Medication Adherence of Older Adults with Hypertension: A Systematic Review

Objective

Hypertension (HTN) significantly increases the risk of stroke and heart disease, which are the leading causes of death and disability globally, particularly among older adults. Antihypertensive medication is a proven treatment for blood pressure control and preventing complications. However, medication adherence rates in older adults with HTN are low. In this review, we systematically identified factors influencing medication adherence in older adults with HTN.

Methods

We applied the PRISMA guidelines and conducted systematic searches on PubMed, MEDLINE, and Google Scholar in July 2022 to identify preliminary studies reporting factors influencing medication adherence among older adults with HTN. The convergent integrated analysis framework suggested by the Joanna Briggs Institute for systematic reviews was adopted for data synthesis.

Results

Initially, 448 articles were identified, and after title and abstract screening, 16 articles qualified for full-text review. During this phase, three articles were excluded for reporting on irrelevant populations or focusing on issues beyond the review's aim, leaving thirteen studies in the final review. After data synthesis, fifteen themes were extracted from the key findings of the included studies. The most prevalent themes included the number of medications used (53.9%, n=7 studies), financial status (38.5%, n=5), sex (38.5%, n=5), age (30.1%, n=4), duration of disease (23.1%, n=3), comorbidities (23.1%, n=3), and health compliance (23.1%, n=3). Other themes, such as education, health literacy, health belief, medication belief, perception of illness, patient-physician relationship, self-efficacy, and social support, were also identified.

Conclusion

The findings of this review highlight critical areas for developing innovative, evidence-based programs to improve medication adherence in hypertensive older adults. Insights from this review can contribute to improving medication adherence and preventing future health complications.

Low medication adherence and its associated factors among patients with type 2 diabetes mellitus attending Amana Hospital in Dar es Salaam, Tanzania: a cross-sectional study

BACKGROUND

Low medication adherence among patients with type 2 diabetes mellitus (T2DM) is associated with significant morbidity and mortality globally. We investigated the prevalence of low medication adherence and its associated factors among patients with T2DM.

METHODS

We used the Bengali version of the 8-item Morisky Medication Adherence Scale (MMAS-8) in measuring medication adherence among patients with T2DM who were attending the diabetes clinic at Amana Regional Referral Hospital in Dar es Salaam, Tanzania, from December 2021 to May 2022. Binary logistic regression analysis under multivariate analysis was used to determine the predictors of low medication adherence after controlling for confounders. A two-tailed p-value <0.05 was considered significant.

RESULTS

The prevalence of low medication adherence was 36.7% (91/248) of the subjects included in the study. Lack of formal education (adjusted odds ratio [AOR] 5.3 [95% confidence interval {CI} 1.717 to 16.312], p=0.004), having comorbidities (AOR 2.1 [95% CI 1.134 to 3.949], p=0.019) and drinking alcohol (AOR 3.5 [95% CI 1.603 to 7.650], p=0.031) were the independent predictors of low medication adherence.

CONCLUSION

More than one-third of the patients with T2DM in this study had low medication adherence. Our study also showed that a lack of formal education, having comorbidities and drinking alcohol were significantly associated with low medication adherence.

Uncontrolled Hypertension, Treatment, and Predictors among Hypertensive Out-Patients Attending Primary Health Facilities in Johannesburg, South Africa

Hypertension is a poorly controlled risk factor for cardiovascular disease in South Africa, particularly among patients receiving care in the public sector who are mostly from low socioeconomic backgrounds. This cross-sectional study investigated uncontrolled hypertension, treatment, and predictors among hypertensive out-patients attending primary health care facilities in Johannesburg, South Africa. The WHO STEPwise approach to the surveillance of non-communicable diseases was used to collect data, including sociodemographic and lifestyle factors, health status, and measurements for anthropometry and blood pressure along with self-reported adherence to treatment, estimated through the general medication adherence scale. Uncontrolled hypertension was defined as systolic blood pressure ≥140 mmHg and/or diastolic blood pressure ≥90 mmHg in diagnosed patients receiving anti-hypertensive treatment. Overweight and obesity were defined as a body mass index ≥25 and ≥30 kg/m2, respectively. Logistic regression models were used to assess the predictors of uncontrolled hypertension. Four hundred (n = 400) hypertensive out-patients (mean age: 50 ± 8 years) participated in this study, with most living in poor sociodemographic environments. The prevalence rate of uncontrolled hypertension was 57%. Obesity (62% vs. 42%, p ≤ 0.0001), salt consumption (90% vs. 55%, p ≤ 0.0001), alcohol intake (42% vs. 19%, p ≤ 0.0001), a smoking habit (23% vs. 4%, p ≤ 0.0001), alternative medicine use (51% vs. 40%, p = 0.043), and comorbidities (64% vs. 36%, p ≤ 0.0001) were higher in the uncontrolled group than the controlled group, whereas the prevalence of physical activity (38% vs. 15%, p ≤ 0.0001) was high in the controlled group vs. the uncontrolled. Overall, 85% of the patients moderately adhered to treatment, only 2% exhibited high adherence, and 13% demonstrated low adherence; over half of the patients received tri-therapy treatment. The predictors of uncontrolled hypertension are a number of prescribed antihypertensive therapies [adjusted odds ration = 2.39; 95% confidence interval: 1.48-3.87], treatment adherence [0.46; 0.21-0.97], salt consumption [28.35; 7.87-102.04], physical activity [0.22; 0.13-0.37], current alcohol use [2.10; 1.22-3.61], and current cigarette smoking [4.79; 1.88-12.18]. The high prevalence of uncontrolled hypertension in this study suggests a need to optimize prescriptions, adherence to BP-lowering medications, and lifestyle modifications. The management of comorbidities such as diabetes could offer considerable benefits in controlling blood pressure.

Factors influencing adherence to non-communicable disease medication in India: secondary analysis of cross-sectional data from WHO - SAGE2

Background: Non-communicable diseases (NCDs) are a leading cause of death globally and disproportionately affect those in low- and middle-income countries lower-middle-income countries. Poor medication adherence among patients with NCDs is prevalent in India due to lack of initiation, missed dosing or cessation of treatment, and represents a growing healthcare and financial burden. Objective: This study aimed to identify factors influencing medication adherence in adults with NCDs in India. Methods: We performed a cross-sectional study, conducting secondary data analysis on the second wave of the World Health Organisation's 'Study on global AGEing and adult health (SAGE)', a survey that collected data from predominantly older adults across India. Bivariate analysis and multivariate logistic regression modelling were conducted to specifically interrogate the reasons for lack of initiation and cessation of treatment. Reporting of this study was informed by the STROBE guidelines. Results: The average medication adherence rate was 51% across 2,840 patients with one or more NCDs, reflecting non-initiation and lack of persistence of treatment. The strongest factor significantly predicting non-adherence to medication across these components was multimorbidity (odds ratio 0.47, 95% CI 0.40-0.56). Tobacco use (OR = 0.76, CI 0.59-0.98) and never having attended school (OR = 0.75, CI 0.62-0.92) were significantly associated with poor medication adherence (p < 0.05) while rural living (OR = 0.70, CI 0.48-1.02), feelings of anxiety (OR = 0.84, CI 0.66-1.08) and feelings of depression (OR = 0.90, CI 0.70-1.16) were factors lacking statistically significant association with medication adherence on multivariate analysis. Older age (OR = 2.02, CI 1.51-2.71) was significantly associated with improved medication adherence whilst there was a weak association between increased wealth and improved medication use. Limitations: The SAGE2 survey did not capture whether patients were taking their medication doses according to prescribed instructions-as a result our findings may under-estimate the true prevalence of medication non-adherence. Conclusion: Our analysis provides evidence that poor medication adherence in India is multifactorial, with distinct socioeconomic and health-system factors interacting to influence patient decision making. Future large-scale surveys interrogating adherence should assess all components of adherence specifically, whilst public health interventions to improve medication adherence should focus on barriers that may exist due to multimorbidity, comorbid depression and anxiety, and low educational status.

Multimorbidity, Treatment, and Determinants among Chronic Patients Attending Primary Health Facilities in Tshwane, South Africa

The growing burden of non-communicable diseases amidst the largest burden of HIV in South Africa leads to disease combinations of multimorbidity with the complexity of care. We conducted a cross-sectional study to assess multimorbidity, medication adherence, and associated factors among out-patients with chronic diseases in primary health care (PHC) facilities in Tshwane, South Africa. A structured questionnaire was used to collect data on comorbidities and medication adherence, along with socio-demographic and lifestyle factors. Logistic regression models were used to analyse the determinants of multimorbidity and medication adherence. In all 400 patients with chronic diseases (mean age: 47 ± 12 years) living in poor environments, common chronic conditions were hypertension (62%), diabetes (45%), HIV (44%), TB (33%), hypercholesterolemia (18%), and gout (13%). The proportion of concordant comorbidity (i.e., diseases with similar risk profiles and management) was 72%, more than 28% of discordant comorbidity (i.e., diseases not related in pathogenesis or management). Most patients had two coexisting chronic conditions (75%), while few had more than two chronic conditions (23%) and single-occurring conditions (2%). Prevalence rates for common multimorbidity patterns were 25% (HIV and TB), 17% (hypertension and diabetes), 9% (hypertension, diabetes, and hypercholesterolemia), and 2% (hypertension diabetes and HIV), while medication adherence was estimated at 74%. In multivariate analysis, multimorbidity was associated with an older age and lower socio-economic status, while medication non-adherence was associated with a younger age and socio-economic factors. The study highlights the presence of multimorbidity among primary care patients attributed to hypertension, diabetes, HIV, and TB in South Africa with non-adherence to medication in one-third of patients. Policies are needed for education on multimorbidity with a need to optimize lifestyle modifications, perhaps proactive outreach or nursing contact with high-risk patients with public-health-sensitive conditions, such as HIV and/or TB, as well as patients with a history of non-adherence to medications. Considerations should be given to the development of a medication adherence scale for multiple chronic conditions beyond assessing adherence to a single index medication.

Relationship between Treatment Burden, Health Literacy, and Medication Adherence in Older Adults Coping with Multiple Chronic Conditions

A prospective study was conducted to investigate the impact of treatment burden and health literacy on medication adherence among older adults with multiple chronic conditions (MCC) and to explore the potential moderating effects of demographic and clinical factors. Face-to-face structured interviews were conducted among older adults aged 60 and above using the Burden of Treatment Questionnaire (TBQ-15), Short Form Health Literacy Questionnaire (HLS-SF12), and Malaysia Medication Adherence Assessment Tool (MyMAAT). This study included 346 older adults aged 60 years and above with two or more chronic conditions (n = 346). Hypertension (30.2%), hyperlipidemia (24.0%), and diabetes (18.0%) were the most reported chronic conditions among participants. The mean score of treatment burden was 53.4 (SD = 28.2), indicating an acceptable burden of treatment. The mean score of health literacy was 16.4 (SD = 12.6), indicating a limited health literacy level among participants; meanwhile, the mean score of medication adherence was 32.6 (SD = 12.3), indicating medication non-adherence among participants. Medication adherence was significantly correlated with treatment burden (r = -0.22, p < 0.0001), health literacy (r = 0.36, p < 0.0001), number of chronic conditions (r = -0.23, p < 0.0001), and age (r = -0.11, p < 0.05). The study findings emphasize that multimorbid older adults with high treatment burdens and low health literacy are more likely to have poor medication adherence. This underscores the importance for clinicians to address these factors in order to improve medication adherence among older adults with multiple chronic conditions (MCC).

Medication Adherence among Patients with Diabetes Mellitus and Its Related Factors-A Real-World Pilot Study in Bulgaria

Background and Objectives: The objective is to evaluate medication adherence level (MA) and the relevant determinants of MA among patients with type 2 diabetes mellitus (T2DM) monitored in ambulatory settings by general practitioners. Materials and Methods: A cross-sectional study was conducted among patients with T2DM monitored in a GP practice in Sofia, Bulgaria (September-December 2022). All patients were interviewed according to a predesigned questionnaire after granting informed consent. MA level was evaluated through the Morisky-Green four-item questionnaire, and health-related quality of life was evaluated by EQ-5D-5L and VAS (visual analogue scale). Data were aggregated and statistically evaluated. Results: The total number of observed patients was 93. Around 48.4% of patients were female, and 90.3% of patients were between 50 and 80 years of age. Multimorbidity was identified among 70% (n = 65) of the respondents. High and medium levels of MA were revealed in 64.51% and 33.3% of respondents, respectively. Patients treated with insulin secretagogues were most adherent to the therapy (n = 83.3%) in comparison with the other treatment groups. The onset of the disease, professional status, age, gender, number of therapies, and quality of life did not affect the level of MA (p > 0.05). VAS scores among nonsmokers (VAS = 63.16 ± 20.45 vs. 72.77 ± 14.3) and non-consumers of alcohol (VAS = 63.91 ± 19.34 vs. VAS = 72.54 ± 15.98) were statistically significant lower (p < 0.05). A significant related factor for MA was years lived with diabetes (OR = 3.039, 95% CI 1.1436-8.0759, p = 0.0258). The longer the disease duration, the more the odds for a high MA level increased. Conclusions: The number of nonadherent diabetic patients in Bulgaria is low, which might be evidence of patients' concern about their own health and understanding about the importance of prescribed therapy. Further comprehensive study with additional patients is required to confirm the results and investigate the predicting factors for a high level of MA.

Association between medication literacy and medication adherence and the mediating effect of self-efficacy in older people with multimorbidity

BACKGROUND

Multimorbidity has a significant impact on public health and primary care. Medication adherence is recognized as the most effective measure for managing and preventing multimorbidity. Studies have shown that medication literacy has a positive effect on medication adherence in patients with multimorbidity. However, limited knowledge exists regarding the underlying mechanisms of this relationship in older adults with multimorbidity. Therefore, the aim of this study was to investigate the mediating role of self-efficacy in the association between medication literacy and medication adherence in this population.

METHODS

This study employed a cross-sectional design and convenience sampling method to survey older patients with multimorbidity in six communities in Zhengzhou, China, from July 12, 2021, to December 15, 2021. Participants were assessed using a demographic questionnaire, the Chinese Version of the Medication Literacy Scale (C-MLS), the Self-Efficacy for Appropriate Medication Use Scale (SEAMS), and the Chinese Version of the Morisky Medication Adherence Scale-8 (C-MMAS-8). Data were analyzed using descriptive statistics, t-tests, one-way analysis of variance, Pearson correlation analysis, and mediation analysis.

RESULTS

A total of 350 elderly patients met the inclusion criteria, and 328 valid questionnaires were collected. The mean age of the participants was 74.90 ± 7.37 years, with a slightly higher proportion of males (55.8%) than females (44.2%). The mean score for medication adherence was 4.85 ± 1.57, indicating poor medication adherence among the participants. Medication adherence scores varied significantly among participants of different ages, education levels, employment statuses and kinds of medication (p < 0.01). Scores for medication literacy and self-efficacy showed a significant positive correlation with medication adherence scores (all p < 0.001). The standardized coefficient for the total effect and direct effect of medication literacy on medication adherence was 0.268 (95% CI: 0.201, 0.335) and 0.187 (95% CI: 0.123, 0.252), respectively. After introducing self-efficacy into the model, the standardized coefficient for the indirect effect was 0.081 (95% CI: 0.049, 0.120), indicating that self-efficacy partially mediated the relationship between medication literacy and medication adherence, accounting for 30.22% of the total effect.

CONCLUSION

This study might suggest that medication literacy indirectly affected medication adherence in older people with multimorbidity through self-efficacy. Health care providers should be aware of the importance of improving medication literacy and implement strategies aimed at increasing self-efficacy to achieve the goal of improving medication adherence in older adults with multimorbidity.

Medication adherence and its impact on glycemic control in type 2 diabetes mellitus patients with comorbidity: A multicenter cross-sectional study in Northwest Ethiopia

BACKGROUND

Medication nonadherence in patients with chronic diseases, particularly in type 2 diabetes mellitus (T2DM) with comorbidity, has continued to be the cause of treatment failure. The current study assessed medication adherence and its impact on glycemic control in T2DM patients with comorbidity.

METHODS

An institutional-based multicenter cross-sectional study was conducted among T2DM patients with comorbidity at the selected hospitals in Northwest Ethiopia. Medication adherence was measured using a structured questionnaire of the General Medication Adherence Scale (GMAS). A logistic regression model was used to identify predictors of the level of medication adherence and glycemic control. P < 0.05 at 95% confidence interval (CI) was statistically significant.

RESULTS

A total of 403 samples were included in the final study. This study showed that more than three-fourths (76.9%) of the participants were under a low level of medication adherence. Source of medication cost coverage [AOR = 10.593, 95% CI (2.628-41.835; P = 0.003], monthly income (P < 0.00), self-monitoring of blood glucose (SMBG) practice [AOR = 0.266, 95% CI (0.117-0.604); P = 0.002], number of medications [AOR = 0.068, 95% CI (0.004-0.813); P = 0.014] and medical conditions [AOR = 0.307, 95% CI (0.026-0.437); P = 0.018] were found to be significant predictors of medication adherence. Significantly, majority (74.7%) of participants had poor levels of glycemic control. Patients who had a high level of medication adherence [AOR = 0.003, 95% CI (0.000-0.113); P = 0.002] were found less likely to have poor glycemic control compared with patients who were low adherent to their medications.

CONCLUSION

The current study concluded that medication adherence was low and significantly associated with poor glycemic control. Number of medical conditions and medications were found to be associated with medication adherence. Management interventions of T2DM patients with comorbidity should focus on the improvement of medication adherence.