Methods: A cross-sectional study was conducted at the Universiti Kebangsaan Malaysia Medical Centre (UKMMC) using outpatient population diabetic patients. Demographic data on social and clinical characteristics were collected from participants. Several questionnaires were administered, including the Beck Depression Inventory-II (BDI-II) to measure depressive symptoms, the Generalized Anxiety Disorder-7 (GAD-7) to assess anxiety symptoms, the Big Five Inventory (BFI) to evaluate personality traits, and the WHO Quality of Life-BREF (WHOQOL-BREF) to assess QOL. Multivariate binary logistic regression was performed to determine the predictors of poor glycaemic control.
Results: 300 patients with diabetes mellitus were recruited, with the majority (90%) having type 2 diabetes. In this population, the prevalence of poor glycaemic control (HbA1C ≥ 7.0%) was 69%, with a median HbA1C of 7.6% (IQR = 2.7). Longer duration of diabetes mellitus and a greater number of days of missed medications predicted poor glycaemic control, while older age and overall self-perception of QOL protected against poor glycaemic control. No psychological factors were associated with poor glycaemic control.
Conclusion: This study emphasizes the importance of considering the various factors that contribute to poor glycaemic control, such as duration of diabetes, medication adherence, age, and QOL. These findings should be used by clinicians, particularly when planning a multidisciplinary approach to the management of diabetes.
METHODS: This cross-sectional study recruited 300 diabetic patients via convenience sampling from the Endocrine outpatient clinic of Universiti Kebangsaan Malaysia Medical Centre, a tertiary referral healthcare facility in Kuala Lumpur. Socio-demographic characteristics and clinical history were obtained from each participant. The Generalised Anxiety Disorder-7 (GAD-7) was administered to assess anxiety symptoms, the Beck Depression Inventory (BDI) to assess depressive symptoms, the Big Five Inventory (BFI) to evaluate personality traits, and the World Health Organization Quality of Life-BREF (WHOQOL-BREF) to measure quality of life (QOL). Stepwise multiple logistic regression analyses were performed to determine the association between various factors, and depression and anxiety.
RESULTS: The prevalence of depression was 20% (n = 60) while anxiety was 9% (n = 27). Co-morbid depression (adjusted odds ratio [OR] = 9.89, 95% confidence interval [CI] = 2.63-37.14, p = 0.001) and neuroticism (adjusted OR = 11.66, 95% CI = 2.69-50.47, p = 0.001) increased the odds of developing anxiety, while conscientiousness (adjusted OR = 0.45, 95% CI = 0.23-0.80, p = 0.004) and greater psychological-related QOL (adjusted OR = 0.47, 95% CI = 0.29-0.75, p = 0.002) were protective. Co-morbid anxiety (adjusted OR = 19.83, 95% CI = 5.63-69.92, p p = 0.002), social relationship-related QOL (adjusted OR = 0.84, 95% CI = 0.71-.0.99, p = 0.047), and physical health-related QOL (adjusted OR = 0.69, 95% CI = 0.58-0.83, p