Evaluation of the health-related quality of life of patients with type 2 diabetes in relation to macrovascular and microvascular complications.

purposeThe complications of type 2 diabetes (T2DM) have a negative impact on health-related quality of life (HRQoL) and could lead to increased healthcare costs. However, there is a lack of evidence regarding how and to what extent T2DM complications, particularly macrovascular and microvascular complications, affect the patients' HRQoL. This study aimed to evaluate the HRQoL in relation to diabetes complications and identify associated factors among patients with T2DM.

methodsA cross-sectional study was conducted over six months on T2DM patients at a National University Hospital, Malaysia. Since Malaysia is a multiethnic country with majority Malay-speaking and English widely used, the Malay and English versions of the revised version Diabetes Quality of life (DQoL) questionnaire was used to measure HRQoL. Multiple Linear Regression was applied to estimate association of individual DQoL domains with T2DM-related complications, sociodemographic and clinical characteristics.

resultsA total of 513 patients were recruited in the study. Sociodemographic (age, gender, ethnicity, employment, education) and body mass index affected satisfaction, impact and worry domains while complications affected the impact domain. Poorer HRQoL were demonstrated for severe stages heart failure (p = 0.001), nephropathy (p = 0.029), retinopathy (p < 0.001). The presence of neuropathy (p = 0.004) and foot ulcer (p = 0.039) showed poor HRQoL regardless of severity stage. Increase frequencies of hypoglycaemia (p < 0.001) showed poorer HRQoL compared to those with lesser frequencies.

conclusionThe complications, sociodemographic and clinical characteristics of patients with T2DM affect the HRQoL domains differently. Understanding the point of which complication types and stages impact HRQoL the most can provide insights to clinicians to prioritise on effective interventions. The study findings may assist researchers and policymakers in selecting appropriate health state values when conducting cost-effectiveness studies to aid decision making.