Medication adherence in type 2 diabetes mellitus patients during Covid-19 pandemic: a cross-sectional study from the United Arab Emirates.
Ameena AsheqAkram AshamesMoawia Mohd A M AltabakhaNageeb HassanAmmar Abdulrahman JairounPublished in: F1000Research (2021)
Background: Patients with chronic diseases often experience difficulty adhering to recommended treatments as instructed by their healthcare professionals. Recently, diabetes has been associated with the severity of the novel coronavirus disease (Covid-19), which raises the importance of improving medication adherence for diabetic patients to enhance the right use of antidiabetics amid the Covid-19 pandemic. Methods: This work assesses medication adherence among type 2 diabetes mellitus patients in the United Arab Emirates (UAE) and identifies the set of key demographic and health factors significantly associated with medication adherence. A descriptive cross-sectional study was conducted on an appropriate sample of type 2 diabetic patients in the UAE, with 180 patients of both genders and various social levels. A validated version of the eight-item Morisky Medication Adherence Scale (MMAS) was used for data collection. Results: The average MMAS score was 4.88, with 95% confidence intervals (CI) 4.6 and 5.2. 61.67% (n=111), 28.89% (n=52), and 9.44% (n=17) of patients were categorized into low, medium, and high adherent groups, respectively. These findings indicate that a high level of non-compliance to antidiabetic regimens among the population in the UAE. Conclusions : Patients demonstrated low level of compliance to antidiabetic regimens. Therefore, they must receive up-to-date knowledge about the disease and the treatment and enable easy access to their health care providers to enhance medication adherence.
Keyphrases
- end stage renal disease
- healthcare
- coronavirus disease
- newly diagnosed
- chronic kidney disease
- ejection fraction
- peritoneal dialysis
- prognostic factors
- type diabetes
- public health
- gene expression
- sars cov
- adipose tissue
- patient reported outcomes
- risk factors
- metabolic syndrome
- artificial intelligence
- big data
- weight loss
- glycemic control
- skeletal muscle
- health insurance
- respiratory syndrome coronavirus