Yu Jin Lee1, Hyeon Chang Kim2, Eun Lee3, Sun Jae Jung4. 1. Department of Public Health, Graduate School, Yonsei University, Seoul, Republic of Korea. 2. Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea; Cardiovascular and Metabolic Disease Etiology Research Center, Yonsei University College of Medicine, Seoul, Republic of Korea. 3. Department of Psychiatry and Institute of Behavioral Science in Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea. 4. Department of Preventive Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea; Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. Electronic address: SUNJAEJUNG@yuhs.ac.
Abstract
BACKGROUND: The heterogeneity of depressive symptoms in suicidality is poorly understood. This study examines the heterogeneous association between subfactors of depressive symptoms in suicidality. METHODS: The data of 5742 participants aged 19 and older were taken from the 2014 and 2016 Korean National Health and Nutrition Examination Surveys and analyzed. Subfactors of depressive symptoms were identified utilizing factor analyses that yielded two groups (typical- and other-depressive factors). Multivariable logistic regression models were used to estimate the association between each factor and suicidality after adjusting for covariates. RESULTS: Typical depressive factors included cardinal and somatic symptoms, whereas other depressive factors contained cognitive and other symptoms. The typical factors were associated with each suicidality in succession, however, others depressive factors were not. The heterogeneity of subfactors made the greatest impact on suicide attempts, controlling for all covariates, followed by suicide plans, with a robust coefficient of typical depressive factors. These differential patterns of subfactors existed especially in females and younger people, suggesting the importance of concerning typical depressive factors for those groups. LIMITATIONS: Although a confirmatory factor analysis was performed, depressive subfactors need validation and reliability tests. CONCLUSIONS: Our study findings may help to explain why an improved understanding of the typical depressive factors including cardinal and somatic symptoms is important to prevent suicidality, especially in females and younger people.
BACKGROUND: The heterogeneity of depressive symptoms in suicidality is poorly understood. This study examines the heterogeneous association between subfactors of depressive symptoms in suicidality. METHODS: The data of 5742 participants aged 19 and older were taken from the 2014 and 2016 Korean National Health and Nutrition Examination Surveys and analyzed. Subfactors of depressive symptoms were identified utilizing factor analyses that yielded two groups (typical- and other-depressive factors). Multivariable logistic regression models were used to estimate the association between each factor and suicidality after adjusting for covariates. RESULTS: Typical depressive factors included cardinal and somatic symptoms, whereas other depressive factors contained cognitive and other symptoms. The typical factors were associated with each suicidality in succession, however, others depressive factors were not. The heterogeneity of subfactors made the greatest impact on suicide attempts, controlling for all covariates, followed by suicide plans, with a robust coefficient of typical depressive factors. These differential patterns of subfactors existed especially in females and younger people, suggesting the importance of concerning typical depressive factors for those groups. LIMITATIONS: Although a confirmatory factor analysis was performed, depressive subfactors need validation and reliability tests. CONCLUSIONS: Our study findings may help to explain why an improved understanding of the typical depressive factors including cardinal and somatic symptoms is important to prevent suicidality, especially in females and younger people.
Authors: Sun Jae Jung; Ye Jin Jeon; Karmel W Choi; Ji Su Yang; Jeong-Ho Chae; Karestan C Koenen; Hyeon Chang Kim Journal: Brain Behav Date: 2021-02-27 Impact factor: 2.708