Abstract
Bipolar disorder seasonality has been documented previously, though information on the effect of demographic and clinical variables on seasonal patterns is scant. This study examined effects of age, sex, index admission, and predominant polarity on bipolar disorder seasonality in a nationwide population. An inpatient cohort admitted to hospital exclusively for mental illness was derived from the Taiwan National Health Insurance Research Database for 2002-2007. The authors identified 9619 inpatients with bipolar disorder, who had generated 15 078 acute admission records. An empirical mode decomposition method was used to identify seasonal oscillations in bipolar admission data, and regression and cross-correlation analyses were used to quantify the degree and timing of bipolar admission seasonality. Results for seasonality timing found that manic or mixed episodes peak in spring or summer, and depressive episodes peak in winter. Analysis for degree of seasonality revealed that (1) the polarity of patients' index admission predicted the seasonality of relapse admissions; (2) seasonality was significant in female admissions for depressive episodes and in male admissions for manic episodes; (3) young adults displayed a higher degree of seasonality for acute admissions than middle-aged adults; and (4) patients with predominantly depressive admissions displayed a higher degree of seasonality than patients with predominantly manic admissions. Demographic and clinical variables were found to affect the seasonality of acute admissions for bipolar disorders. These findings highlight the need for research on identification and management of seasonal features in bipolar patients.
Original language | English |
---|---|
Pages (from-to) | 478-485 |
Number of pages | 8 |
Journal | Chronobiology International |
Volume | 30 |
Issue number | 4 |
DOIs | |
Publication status | Published - May 2013 |
Externally published | Yes |
Keywords
- Age
- Bipolar disorder
- Empirical mode decomposition
- Gender
- Hospital admissions
- Hospitalization
- Seasonality
- Sex
- Time-series analysis
ASJC Scopus subject areas
- Physiology
- Physiology (medical)