Seasonal variations in hospital admissions for mania: Examining for associations with weather variables over time
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Published on: December 9, 2015
Clara Reece Medici1, Claus Høstrup Vestergaard2, Dusan Hadzi-Pavlovic3
1Department of Clinical Epidemiology, Aarhus University Hospital, Skejby, Denmark; Clinic for OCD and Anxiety Disorders, Aarhus University Hospital, Risskov, Denmark; Psychiatric Research Academy, Department of Affective Disorders (Q2), Aarhus University Hospital, Risskov, Denmark.
Background:
Bipolar disorder is characterized by a seasonal pattern with emerging evidence that weather conditions may trigger symptoms. Thus, our aims were to investigate if year-to-year variations in admissions with mania correlated with year-to-year variations in key meteorological variables, if there was a secular trend in light of climate change and if gender or admission status influenced the seasonal pattern.
Methods:
We undertook a Danish register-based nationwide historical cohort study. We included all adults hospitalized to psychiatric care from 1995 to 2012 with mania using the Danish Psychiatric Central Research Register. The Danish Meteorological Institute provided the meteorological variables. The association between weather and admissions was tested using linear regression.
Results:
Our database comprised 24,313 admissions with mania. There was a seasonal pattern with admission rates peaking in summer. Higher admission rates were associated with more sunshine, more ultraviolet radiation, higher temperature and less snow but were unassociated with rainfall. We did not find a secular trend in the seasonal pattern. Finally, neither gender nor admission status impacted on the overall seasonal pattern of admissions with mania.
Limitations:
Only patients in psychiatric care were included. We could not subdivide by type of bipolar disorder.
Conclusion:
This cohort study based on more than 24,000 admissions identified a distinct seasonal pattern in hospital admissions for those with mania. We found no secular trend. This could indicate that the climate change is not impacting on seasonal patterns, that there is no link between the proposed variables or that change is currently not sufficiently distinctive.
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