The social zeitgeber theory, circadian rhythms, and mood disorders: Review and evaluation

2006 ◽  
Vol 26 (6) ◽  
pp. 679-694 ◽  
Author(s):  
Louisa D. Grandin ◽  
Lauren B. Alloy ◽  
Lyn Y. Abramson
Keyword(s):  
Circadian Rhythms ◽  
Mood Disorders ◽  
The Social ◽  
Social Zeitgeber

Genetic aetiology of mood disorders

2012 ◽  
pp. 650-658
Author(s):  
Pierre Oswald ◽  
Daniel Souery ◽  
Julien Mendlewicz
Keyword(s):  
Affective Disorder ◽  
Mood Disorders ◽  
Molecular Genetics ◽  
Psychosocial Factors ◽  
Affective Disorders ◽  
Social Life ◽  
Bipolar Affective Disorder ◽  
Molecular Genetic ◽  
The Social ◽  
Life Context

Advances towards the understanding of the etiological mechanisms involved in mood disorders provide interesting yet diverse hypotheses and promising models. In this context, molecular genetics has now been widely incorporated into genetic epidemiological research in psychiatry. Affective disorders and, in particular, bipolar affective disorder (BPAD) have been examined in many molecular genetic studies which have covered a large part of the genome, specific hypotheses such as mutations have also been studied. Most recent studies indicate that several chromosomal regions may be involved in the aetiology of BPAD. Other studies have reported the presence of anticipation in BPAD and in unipolar affective disorder (UPAD). In parallel to these new developments in molecular genetics, the classical genetic epidemiology, represented by twin, adoption and family studies, provided additional evidence in favour of the genetic hypothesis in mood disorders. Moreover, these methods have been improved through models to test the gene-environment interactions. In addition to genetic approaches, psychiatric research has focused on the role of psychosocial factors in the emergence of mood disorders. In this approach, psychosocial factors refer to the patient's social life context as well as to personality dimensions. Abnormalities in the social behavior such as impairment in social relationships have been observed during episode of affective disorders, and implicated in the etiology of affective disorders. Further, gender and socio-economic status also emerged as having a possible impact on the development of affective disorders. Finally, the onset and outcome of affective disorders could also be explained by interactions between the social life context and the individual's temperament and personality. The importance of temperament and personality characteristics in the etiology of depression has been emphasized in various theories, although disagreement exists with regard to terminology and the etiology. While significant advances have been done in these two major fields of research, it appears that integrative models, taking into account the interactions between biological (genetic) factors and social (psychosocial environment) variables offer the most reliable way to approach the complex mechanisms involved in the etiology and outcome of mood disorders. This chapter will review some of the most promising genetic and psychosocial hypotheses in mood disorders that can be integrated in interactive models.

Social adjustment and self-esteem in remitted patients with mood disorders

1999 ◽  
Vol 14 (3) ◽  
pp. 137-142 ◽  
Author(s):  
A Serretti ◽  
MC Cavallini ◽  
F Macciardi ◽  
C Namia ◽  
L Franchini ◽  
...  
Keyword(s):  
Mood Disorder ◽  
Mood Disorders ◽  
Social Adjustment ◽  
Social Function ◽  
Self Esteem ◽  
The Self ◽  
Major Depressive ◽  
The Social ◽  
Depressive Episodes ◽  
Social Adjustment Scale

SummaryMood disorders are characterized by manic and depressive episodes alternating with normal mood. While social function is heavily impaired during episodes of illness, there are conflicting opinions about inter-episode function. The present paper focuses on self-esteem and social adjustment in remitted mood disorders patients.Patients with mood disorders (99 bipolar and 86 major depressive subjects, in remission) were compared with a group of 100 control subjects. The self-esteem scale (SES) and the social adjustment scale (SAS) were used to measure self-esteem and social adjustment, respectively, in both groups of subjects.Patients with mood disorder exhibited worse social adjustment and lower self-esteem than control subjects.These results strongly confirm previous observations of poor inter-episode function in patients with mood disorder.

scholarly journals Distinct Circadian Assessments From Wearable Data Reveal Social Distancing Promoted Internal Desynchrony Between Circadian Markers

2021 ◽  
Vol 3 ◽  
Author(s):  
Yitong Huang ◽  
Caleb Mayer ◽  
Olivia J. Walch ◽  
Clark Bowman ◽  
Srijan Sen ◽  
...  
Keyword(s):  
Heart Rate ◽  
Circadian Rhythms ◽  
Phase Error ◽  
Laboratory Data ◽  
The Body ◽  
Social Distancing ◽  
Circadian Phase ◽  
The Social ◽  
Before And After ◽  
Using Data

Mobile measures of human circadian rhythms (CR) are needed in the age of chronotherapy. Two wearable measures of CR have recently been validated: one that uses heart rate to extract circadian rhythms that originate in the sinoatrial node of the heart, and another that uses activity to predict the laboratory gold standard and central circadian pacemaker marker, dim light melatonin onset (DLMO). We first find that the heart rate markers of normal real-world individuals align with laboratory DLMO measurements when we account for heart rate phase error. Next, we expand upon previous work that has examined sleep patterns or chronotypes during the COVID-19 lockdown by studying the effects of social distancing on circadian rhythms. In particular, using data collected from the Social Rhythms app, a mobile application where individuals upload their wearable data and receive reports on their circadian rhythms, we compared the two circadian phase estimates before and after social distancing. Interestingly, we found that the lockdown had different effects on the two ambulatory measurements. Before the lockdown, the two measures aligned, as predicted by laboratory data. After the lockdown, when circadian timekeeping signals were blunted, these measures diverged in 70% of subjects (with circadian rhythms in heart rate, or CRHR, becoming delayed). Thus, while either approach can measure circadian rhythms, both are needed to understand internal desynchrony. We also argue that interventions may be needed in future lockdowns to better align separate circadian rhythms in the body.

scholarly journals A High Cattle-Grazing Density Alters Circadian Rhythmicity of Temperature, Heart Rate, and Activity as Measured by Implantable Bio-Loggers

2021 ◽  
Vol 12 ◽  
Author(s):  
Carlos Palacios ◽  
Javier Plaza ◽  
José-Alfonso Abecia
Keyword(s):  
Heart Rate ◽  
Circadian Rhythms ◽  
Sine Wave ◽  
Mean Value ◽  
Circadian Rhythmicity ◽  
Average Value ◽  
The Social ◽  
Grazing Area ◽  
The Mean ◽  
Animal Grazing

Six cows managed under extensive grazing conditions were used to study the effect of moving the animals to a higher grazing density on the circadian rhythms of temperature (T), heart rate (HR), and activity (ACT), which were recorded by implantable bio-loggers. Cows were maintained at a density of 1.5 livestock units per hectare (LSUs/ha; low density, LD) until they were moved to a grazing area at 128 LSUs/ha (high density, HD). Animals were implanted subcutaneously with a T, HR, and ACT bio-logger, which was programmed to record data at 5-min intervals. For each animal, cosinor rhythmometry (the study of circadian rhythms by fitting a sine wave to a time series) was applied to the data recorded over 5 days in LD and HD. Mean Midline Estimating Statistic of Rhythm (MESOR; the average value around which the variable oscillates), amplitude (difference between the peak and the mean value of a wave), and acrophase (timing of peak activity) were calculated and evaluated statistically. Differences between mean day and nighttime values, and mean LD and HD values were calculated. Cows presented cosinor curves that fit a 24-h rhythm (p < 0.001) in T, HR, and ACT at both densities. MESOR (T: 37.98 vs. 38.02°C; HR: 69.12 vs. 65.91 bpm; ACT: 49.39 vs. 40.41 mg, for LD and HD, respectively) and amplitude (T: 0.28 vs. 0.28°C; HR: 4.12 vs. 3.14 bpm; ACT: 18.14 vs. 11.28 mg, respectively) did not differ significantly between the two densities; however, significant (p < 0.05) differences between densities occurred in the acrophase of the three variables; specifically, the T acrophase was 2 h later at HD (22:45 h) than LD (20:45 h), and HR (LD: 19:51; HD: 16:49 h) and ACT acrophases 3 and 2 h earlier at HD than LD (LD: 14:47; HD: 12:49 h), respectively. T and ACT differed significantly (p < 0.01) between daytime (mean ± SE; 37.92 ± 0.19°C, 40.39 ± 4.74 mg) and nighttime (38.14 ± 0.17°C, 29.93 ± 5.66 mg). In conclusion, our study suggests that a high animal grazing density might exacerbate the social competence for valuable resources for animals, resulting in shifting the circadian rhythmicity of temperature, heart rate, and activity of the cows, advancing or delaying their acrophases.

Sleep and mood disorders: Relationship to circadian rhythms

1996 ◽  
Vol 6 ◽  
pp. 34
Author(s):  
T.A. Wehr ◽  
E. Leibenluft ◽  
P.J. Schwartz ◽  
E.H. Turner ◽  
N.E. Rosenthal
Keyword(s):  
Circadian Rhythms ◽  
Mood Disorders

scholarly journals Gaining Insights Into the Estimation of the Circadian Rhythms of Social Activity in Older Adults From Their Telephone Call Activity With Statistical Learning: Observational Study (Preprint)

2020 ◽  
Author(s):  
Timothée Aubourg ◽  
Jacques Demongeot ◽  
Nicolas Vuillerme
Keyword(s):  
Older Adults ◽  
Circadian Rhythms ◽  
Statistical Learning ◽  
Elderly Population ◽  
Social Activity ◽  
The Elderly ◽  
Telephone Call ◽  
Data Set ◽  
Age Related ◽  
The Social

BACKGROUND Understanding the social mechanisms of the circadian rhythms of activity represents a major issue in better managing the mechanisms of age-related diseases occurring over time in the elderly population. The automated analysis of call detail records (CDRs) provided by modern phone technologies can help meet such an objective. At this stage, however, whether and how the circadian rhythms of telephone call activity can be automatically and properly modeled in the elderly population remains to be established. OBJECTIVE Our goal for this study is to address whether and how the circadian rhythms of social activity observed through telephone calls could be automatically modeled in older adults. METHODS We analyzed a 12-month data set of outgoing telephone CDRs of 26 adults older than 65 years of age. We designed a statistical learning modeling approach adapted for exploratory analysis. First, Gaussian mixture models (GMMs) were calculated to automatically model each participant’s circadian rhythm of telephone call activity. Second, k-means clustering was used for grouping participants into distinct groups depending on the characteristics of their personal GMMs. RESULTS The results showed the existence of specific structures of telephone call activity in the daily social activity of older adults. At the individual level, GMMs allowed the identification of personal habits, such as morningness-eveningness for making calls. At the population level, k-means clustering allowed the structuring of these individual habits into specific morningness or eveningness clusters. CONCLUSIONS These findings support the potential of phone technologies and statistical learning approaches to automatically provide personalized and precise information on the social rhythms of telephone call activity of older individuals. Futures studies could integrate such digital insights with other sources of data to complete assessments of the circadian rhythms of activity in elderly populations.

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