Highs and lows, ups and downs: Meteorology and mood in bipolar disorder

Abstract

Seasonal variation of manic and depressive symptoms is a controversial topic in bipolar disorder research. Several studies report seasonal patterns of hospital admissions for depression and mania and variation in symptoms that appear to follow a seasonal pattern, whereas others fail to report such patterns. Differences in research methodologies, data analysis strategies, and temporal resolution of data may partly explain the variation in findings between studies. The current study adds a novel perspective to the literature by investigating specific meteorological factors such as atmospheric pressure, hours of sunshine, relative humidity, and daily maximum and minimum temperatures as more proximal predictors of self-reported daily mood change in people diagnosed with bipolar disorder. The results showed that daily maximum temperature was the only meteorological variable to predict clinically-relevant mood change, with increases in temperature associated with greater odds of a transition into manic mood states. The mediating effects of sleep and activity were also investigated and suggest at least partial influence on the prospective relationship between maximum temperature and mood. Limitations include the small sample size and the fact that the number and valence of social interactions and exposure to natural light were not investigated as potentially important mediators of relationships between meteorological factors and mood. The current data make an important contribution to the literature, serving to clarify the specific meteorological factors that influence mood change in bipolar disorder. From a clinical perspective, greater understanding of seasonal patterns of symptoms in bipolar disorder will help mood episode prophylaxis in vulnerable individuals.

Maximum Temperature and Solar Radiation as Predictors of Bipolar Patient Admission in an Emergency Psychiatric Ward

“…Recently, another important study, conducted on eleven BD type I patients by Bullock and colleagues, stressed the importance of maximum temperature to predict the transition from depressed to manic mood on consecutive days, particularly in the absence of a direct sunshine hours effect on mood. The authors showed that, in a small sample of bipolar patients, daily maximum temperature predicted a clinically relevant mood change, in particular a transition into manic mood states [23]. Despite the fact that almost all cerebral processes are sensitive to temperature fluctuations, which were reported to intrinsically modulate behavioral changes and reflexively generate autonomic responses [49], the authors suggested an active involvement of maximum temperature in a model in which its effect was likely mediated by sleep disruption [23].…”

“…Recently, some authors investigated the role of these factors in bipolar patients with significant impact on both the onset and course of BD and consequently on sleep-wake cycle, mood and energy [10,12,13,14,15,16]. Furthermore, certain authors indicated that environmental factors, such as humidity, day length, ultraviolet radiation, temperature, rainfall/atmospheric pressure or airborne allergens exert a significant role on the admission of BD patients, particularly in (hypo)manic phase, or when they exhibit specific symptoms such as psychosis, impulsiveness, and suicidal behavior/aggression [14,17,18,19,20,21,22,23,24,25].…”

Comparison of sociodemographic and clinical characteristics of bipolar patients with and without seasonal patterns

“…6 In another study, daily maximum temperature was the only meteorological variable to predict clinically relevant mood change; this suggests that increases in temperature are associated with higher odds of a transition into manic mood states. 7 However, there are no significant results showing that environmental factors such as exposure to daylight are associated with seasonal patterns. 8 It has also been reported that patients with bipolar depression can heal more quickly in rooms receiving more sunlight.…”

Cycles of self-reported seizure likelihood correspond to yield of diagnostic epilepsy monitoring

“…Psychogenic non-epileptic seizures (PNES) are linked to psychiatric comorbidities including post-traumatic stress, anxiety and depressive disorders 38 , which may show similar modulating factors as multi-day epileptic rhythms. By the same token, other episodic psychiatric conditions may adhere to slow modulation, including bipolar disorder 39,40 , depression 41,42 and other psychopathologies 43 . Studying multi-day cycles within non-epileptic populations is likely to prove crucial to fully understand the mechanisms of epileptic rhythms.…”