Network analysis of anxiety and depressive symptoms among patients with cardiovascular disease

Abstract

Abstract Background Patients with cardiovascular disease (CVD) often experience anxiety and depression. However, the central and bridge symptoms of anxiety and depression among patients with CVD remain unclear. Network analysis is a statistical method that can reveal and visualise complex relationships between multiple variables. This study aimed to identify the central and bridge symptoms in the anxiety-depression network, which may provide potential targets for preventing and intervening in anxiety and depression. Methods A total of 1180 patients with CVD were selected from the Psychology and Behavior Investigation of Chinese Residents. The survey was conducted from July 10 to September 15, 2021. Face-to-face electronic questionnaires were distributed to respondents by the investigators. The Generalized Anxiety Disorder 7 (GAD-7) and Patient Health Questionnaire-9 were used to assess anxiety and depressive symptoms among patients with CVD. Network analysis was conducted using R4.02 to identify central and bridge symptoms in the anxiety-depression network. Results Among the 1180 patients with CVD included in this study, 673 (57%) were male and 507 (43%) were female. More than half (53.5%) of patients were under 60 years old. The mean GAD-7 score was 4.66 ± 4.38, and 169 (14.3%) patients had anxiety symptoms. The mean PHQ-9 score was 6.29 ± 5.29, and 235 (19.9%) had depressive symptoms. Furthermore, 144 (12.2%) patients people had both anxiety and depressive symptoms. In the network of anxiety and depressive symptoms, “unable to sit still because of anxiety”, “feeling afraid that something terrible is about to happen”, and “feeling bad or like a failure, or disappointing oneself or family” were the most influential and central symptoms. We also found that “feeling afraid that something terrible is about to happen” and “thoughts of dying or hurting oneself in some way” were pivotal bridge symptoms between anxiety and depression. Conclusions This study provides new insights into the network structure of anxiety and depression in patients with CVD. These identified central and bridge symptoms may be potentially effective targets for preventing anxiety and depression in patients with CVD, and may provide treatment strategies for patients with anxiety and depression.

Keywords

• Cardiovascular disease
• Anxiety
• Depression
• Network analysis
• Central and Bridge symptoms