Comorbidity patterns of depression and anxiety among Chinese psychiatric patients: a latent profile analysis

Depression and anxiety are highly prevalent around the world. Previous research mainly adopted variable-centered analyses, which overlooked different latent patterns. Moreover, few studies focused on the comorbidity patterns and risk factors of depression and anxiety within the Chinese context. This study aims to explore the comorbidity patterns of depression and anxiety among psychiatric patients in China and examine the potential predictors of their severity categorization. We recruited 282 patients diagnosed with depression and/or anxiety in China and used questionnaires to collect data. Latent Profile Analysis (LPA) was employed to identify subgroups within the sample. Subsequently, we used multinomial logistic regression to explore the factors predicting those subgroups. The LPA results revealed three subgroups: Mild Symptoms Group, Moderate Symptoms Group, and Severe Symptoms Group. The regression results indicated that poor family function, high neuroticism, and rumination were significant predictors of classification into more severe symptom groups. The findings suggest that clinicians should assess patients more accurately and implement tailored interventions based on the severity levels of the patients.