Solar insolation in springtime influences age of onset of bipolar I disorder.

OBJECTIVE: To confirm prior findings that the larger the maximum monthly increase in solar insolation in springtime, the younger the age of onset of bipolar disorder. METHOD: Data were collected from 5536 patients at 50 sites in 32 countries on six continents. Onset occurred at 456 locations in 57 countries. Variables included solar insolation, birth-cohort, family history, polarity of first episode and country physician density. RESULTS: There was a significant, inverse association between the maximum monthly increase in solar insolation at the onset location, and the age of onset. This effect was reduced in those without a family history of mood disorders and with a first episode of mania rather than depression. The maximum monthly increase occurred in springtime. The youngest birth-cohort had the youngest age of onset. All prior relationships were confirmed using both the entire sample, and only the youngest birth-cohort (all estimated coefficients P < 0.001). CONCLUSION: A large increase in springtime solar insolation may impact the onset of bipolar disorder, especially with a family history of mood disorders. Recent societal changes that affect light exposure (LED lighting, mobile devices backlit with LEDs) may influence adaptability to a springtime circadian challenge.

Influence of birth cohort on age of onset cluster analysis in bipolar I disorder.

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.

Psychiatric morbidity in Chinese women after cervical cancer treatment in a regional gynaecology clinic.

OBJECTIVES: To identify the prevalence and factors associated with psychiatric disorders in Chinese cervical cancer survivors. METHODS: A cross-sectional study was conducted from May 2011 to April 2012 at the specialist gynaecology outpatient clinic at Pamela Youde Nethersole Eastern Hospital, Hong Kong. All cervical cancer patients who had completed treatment were consecutively recruited. They were interviewed using the Chinese-Bilingual Structured Clinical Interview for DSM-IV Axis I Disorders, Patient Research version. Socio-demographic data and clinical information were collected from the patients and their hospital records were reviewed. RESULTS: A total of 113 patients were recruited into the study. The point prevalence of psychiatric disorders as a group in cervical cancer survivors was 37%. The point prevalence of depressive disorders, anxiety disorders, and schizophrenia were 31%, 16%, and 2%, respectively. Major depressive disorder was the most common mood disorder and generalised anxiety disorder the most common anxiety disorder. Younger age, a history of psychiatric illness, fatigue, menopausal symptoms, and pain were independent predictors of current psychiatric disorders. CONCLUSION: Psychiatric disorders, predominantly depressive and anxiety disorders, are common in Chinese cervical cancer survivors. Identification of independent predictors can help gynaecologists detect these disorders earlier and arrange appropriate interventions.