Factors related to quality of life for patients with type 2 diabetes with or without depressive symptoms - results from a community-based study in China

Aims and objectives To explore the factors related to quality of life for patients with type 2 diabetes with or without depressive symptoms in China. Background In patients with type 2 diabetes with or without depressive symptoms, different factors such as gender, social context or regional setting may affect their quality of life. Design This was a cross-sectional study. Methods Of 791 registered patients with type 2 diabetes from four communities in Beijing, cluster sampling was used to recruit patients for participation. Self-rating depression scale was used to screen for depressive symptoms; demographic and clinical data were collected, and quality of life and social support were assessed using appropriate tools. The factors associated with quality of life were tested using multivariate linear regression. Results The prevalence of depressive symptoms in 667 patients with diabetes was 44.2%. Quality of life of patients with depressive symptoms was worse than that of patients without depressive symptoms, and this was associated negatively with history of diabetic complications, usage of hypoglycaemic agents or insulin and self-rating depression scale scores and positively with salary and subjective social support. Conclusions The factors related to quality of life for patients with or without depressive symptoms are different. For patients with depressive symptoms, better salary and subjective social support are associated positively with their quality of life, while the presence of diabetic complications, a higher score for depressive symptoms and need for hypoglycaemic agents or insulin are negatively associated with quality of life. Relevance to clinical practice It is suggested that the nurse should screen depression for patients with diabetes, especially for those with diabetic complications or low social support. This should be done in the community regularly in order to find diabetic patients with depression in time. In addition, the results can provide a reference to clinical nursing care for patients with diabetes in hospitals.