Seasonal variations in mood and behavior associate with common chronic diseases and symptoms in a population-based study

Abstract

The purpose of this study was to assess how seasonality is associated with some of the most common non-communicable diseases (NCDs) in the general Finnish population. The global seasonality score (GSS) was used to measure the magnitude of seasonality in 4689 participants, in addition to which they reported the extent to which the seasonal variations in mood and behavior were experienced as a problem. Regression models and the odds ratios were adopted to analyze the associations adjusted for a range of covariates. Seventy percent of the participants had seasonal variations in sleep duration, social activity, mood, or energy level, and forty percent those in weight and appetite. Angina pectoris and depression were significantly associated with seasonality throughout the analysis. Hypertension, high cholesterol levels, diabetes, other (than rheumatoid) joint diseases and other (than depressive) psychological illnesses were significantly associated with experiencing a problem due to the seasonal variations, with an increase in the GSS, and with seasonal affective disorder and its subsyndromal form. The co-occurrence of the seasonal variations in mood and behavior with certain common NCDs warrants future research to have insights into the etiology and potentially shared pathways and mechanisms of action.

Seasonality of depressive symptoms in women but not in men: A cross-sectional study in the UK Biobank cohort

“…These findings of seasonality of depressive symptoms are consistent with a large body of literature reporting lower mood and increased occurrence of depression in winter months (Basnet et al, 2016;Cobb et al, 2014;Patten et al, 2017). However, our study extends previous findings by reporting evidence of periodicity in the seasonal pattern of depressive symptom changes using the cosinor method (Cornelissen, 2014), and by directly examining associations of depressive symptoms with day length and environmental temperature.…”

“…Seasonal differences in mood and depressive symptoms have often been reported in both the general population and in individuals with mood disorders. At the subclinical level, evidence of greater depressive symptoms, including depressed mood and fatigue, has been reported in winter compared to summer months at temperate latitudes such as Northern Europe, North America and East Asia (Baek et al, 2016;Basnet et al, 2016;Friborg et al, 2012;Kerr et al, 2013;Mersch et al, 2004).…”

Is There a Relationship between Vegetarianism and Seasonal Affective Disorder? A Pilot Study

“…Since vegetarians are more prone to develop mental health issues and SAD patients are more likely to have dysfunctional eating attitudes, it would be interesting to investigate whether a relationship between SAD and vegetarianism exists. In the Finnish general population, 1.4% is vegetarian [17] and 3.6% suffer from SAD [18], and in the Dutch general population, 4.5% are either vegetarians or vegans [19] and 3% suffer from SAD [20]. So far, no research has been done on the relationship between SAD and vegetarianism.…”

The aspect of time in online health information behaviour

“…These studies include analysing social media data for pandemics (Chew and Eysenbach, 2010; Ortiz-Martínez and Jiménez-Arcia, 2017; Seo and Shin, 2017) as well as mood swings and depression (Chen et al, 2018). Search engine data has been utilised to investigate a multitude of illnesses and health issues, like mental health issues (Arendt and Scherr, 2017;Ayers et al, 2013;Tana et al, 2018;Tana, 2018), chronic diseases and symptoms (Basnet et al, 2016), diabetes (Tkachenko et al, 2017), different virus and influenza outbreaks (Bragazzi et al, 2017;Carneiro and Mylonakis, 2009;Kraut et al, 2017;Osuka et al, 2018), transient ischemic attack (Abedi et al, 2015), status epilepticus (Brigo and Trinka, 2015), exercise and weight loss (Madden, 2017), as well as Lyme disease (Pesälä et al, 2017;Seifter et al, 2010). Web traffic again has been utilized for studying accessing health information on the internet related to different topics, such as suicide-related information and pharmacovigilance (Wong et al, 2013;Matsuda et al, 2017).…”