This study explored physical and psychiatric comorbidities of mood disorders using association rule mining. There were 7709 subjects who were patients (≥19 years old) diagnosed with mood disorders and included in the data collected by the Korean National Hospital Discharge In-depth Injury Survey (KNHDS) between 2006 and 2018. Physical comorbidities (46.17%) were higher than that of psychiatric comorbidities (27.28%). The frequent comorbidities of mood disorders (F30-F39) were hypertensive diseases (I10-I15), neurotic, stress-related and somatoform disorders (F40-F48), diabetes mellitus (E10-E14), and diseases of esophagus, stomach, and duodenum (K20-K31). The bidirectional association path of mood disorders (F30-F39) with hypertensive diseases (I10-I15) and diabetes mellitus (E10-E14) were the strongest. Depressive episodes (F32) and recurrent depressive disorders (F33) revealed strong bidirectional association paths with other degenerative diseases of the nervous system (G30-G32) and organic, including symptomatic and mental disorders (F00-F09). Bipolar affective disorders (F31) revealed strong bidirectional association paths with diabetes mellitus (E10-E14) and hypertensive diseases (I10-I15). It was found that different physical and psychiatric disorders are comorbid according to the sub-classification of mood disorders. Understanding the comorbidity patterns of major comorbidities for each mood disorder can assist mental health providers in treating and managing patients with mood disorders.
Keywords: ARM (association rule mining); Korean national hospital discharge in-depth injury survey (KNHDS); comorbidity; mood disorder.