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The association of suicide risk with negative life events and social support according to gender in Asian patients with major depressive disorder

Park S, Hatim Sulaiman A, Srisurapanont M, Chang SM, Liu CY, Bautista D, et al.

Psychiatry Res, 2015 Aug 30;228(3):277-82.
PMID: 26160206 DOI: 10.1016/j.psychres.2015.06.032

We investigated the associations between negative life events, social support, depressive and hostile symptoms, and suicide risk according to gender in multinational Asian patients with major depressive disorder (MDD). A total of 547 outpatients with MDD (352 women and 195 men, mean age of 39.58±13.21 years) were recruited in China, South Korea, Malaysia, Singapore, Thailand, and Taiwan. All patients were assessed with the Mini-International Neuropsychiatric Interview, the Montgomery-Asberg Depression Rating Scale, the Symptoms Checklist 90-Revised, the Multidimensional Scale of Perceived Social Support, and the List of Threatening Experiences. Negative life events, social support, depressive symptoms, and hostility were all significantly associated with suicidality in female MDD patients. However, only depressive symptoms and hostility were significantly associated with suicidality in male patients. Depression severity and hostility only partially mediated the association of negative life events and poor social support with suicidality in female patients. In contrast, hostility fully mediated the association of negative life events and poor social support with suicidality in male patients. Our results highlight the need of in-depth assessment of suicide risk for depressed female patients who report a number of negative life events and poor social supports, even if they do not show severe psychopathology.
Influence of birth cohort on age of onset cluster analysis in bipolar I disorder

Bauer M, Glenn T, Alda M, Andreassen OA, Angelopoulos E, Ardau R, et al.

Eur. Psychiatry, 2015 Jan;30(1):99-105.
PMID: 25498240 DOI: 10.1016/j.eurpsy.2014.10.005

PURPOSE: Two common approaches to identify subgroups of patients with bipolar disorder are clustering methodology (mixture analysis) based on the age of onset, and a birth cohort analysis. This study investigates if a birth cohort effect will influence the results of clustering on the age of onset, using a large, international database.
METHODS: The database includes 4037 patients with a diagnosis of bipolar I disorder, previously collected at 36 collection sites in 23 countries. Generalized estimating equations (GEE) were used to adjust the data for country median age, and in some models, birth cohort. Model-based clustering (mixture analysis) was then performed on the age of onset data using the residuals. Clinical variables in subgroups were compared.
RESULTS: There was a strong birth cohort effect. Without adjusting for the birth cohort, three subgroups were found by clustering. After adjusting for the birth cohort or when considering only those born after 1959, two subgroups were found. With results of either two or three subgroups, the youngest subgroup was more likely to have a family history of mood disorders and a first episode with depressed polarity. However, without adjusting for birth cohort (three subgroups), family history and polarity of the first episode could not be distinguished between the middle and oldest subgroups.
CONCLUSION: These results using international data confirm prior findings using single country data, that there are subgroups of bipolar I disorder based on the age of onset, and that there is a birth cohort effect. Including the birth cohort adjustment altered the number and characteristics of subgroups detected when clustering by age of onset. Further investigation is needed to determine if combining both approaches will identify subgroups that are more useful for research.

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