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Association of disrupted circadian rhythmicity with mood disorders, subjective wellbeing, and cognitive function: a cross-sectional study of 91 105 participants from the UK Biobank
Abstract
Background
Disruption of sleep and circadian rhythmicity is a core feature of mood disorders and might be associated with increased susceptibility to such disorders. Previous studies in this area have used subjective reports of activity and sleep patterns, but the availability of accelerometer-based data from UK Biobank participants permits the derivation and analysis of new, objectively ascertained circadian rhythmicity parameters. We examined associations between objectively assessed circadian rhythmicity and mental health and wellbeing phenotypes, including lifetime history of mood disorder.
Interpretation
Circadian disruption is reliably associated with various adverse mental health and wellbeing outcomes, including major depressive disorder and bipolar disorder. Lower relative amplitude might be linked to increased susceptibility to mood disorders.
... In cancer patients, depression is a common symptom that facilitates cancer development and impedes effective therapy (Fishbein et al., 2021). Circadian disruption is not only a prevalent feature of depressed patients but also a significant risk factor for depression (Lyall et al., 2018). These findings suggest that the circadian clock is a potential link between depression and cancer. ...
... The depressed state of patients leads to deleterious effects for both therapeutic treatments and cancer progression (Wang et al., 2020). Depression is accompanied by circadian rhythm disruption (Fishbein et al., 2021), and dysregulation of circadian rhythms serves as a risk factor for depression (Lyall et al., 2018). These interactive relationships suggest an important role for the broken circadian clock acting as a bridge that connects cancer to depression. ...
... Additionally, depression in cancer patients is becoming increasingly prevalent, as shown by a distress rate in cancer patients that is four-times higher than in the healthy population (Yang et al., 2022). Moreover, circadian disruption is a common characteristic of depressed individuals (Lyall et al., 2018). Thus, we propose that cancer and depression converge at the level of the circadian clock to influence one other, indicating linkage of the circadian clock to both cancer and depression. ...
Circadian clocks orchestrate daily rhythms in many organisms and are essential for optimal health. Circadian rhythm disrupting events, such as jet-lag, shift-work, night-light exposure and clock gene alterations, give rise to pathologic conditions that include cancer and clinical depression. This review systemically describes the fundamental mechanisms of circadian clocks and the interacting relationships among a broken circadian clock, cancer and depression. We propose that this broken clock is an emerging link that connects depression and cancer development. Importantly, broken circadian clocks, cancer and depression form a vicious feedback loop that threatens systemic fitness. Arresting this harmful loop by restoring normal circadian rhythms is a potential therapeutic strategy for treating both cancer and depression.
... Wrist actigraphy is a technique that allows long-term recording of activity with minimal discomfort and safety challenges for the subject. The availability of off-the-shelf medical or research grade actigraphy devices has enabled larger scale collection of actigraphy data [1], and there is increasing consensus around feature engineering and biological interpretations of specific parameters derived from analysis of actigraphic recordings [2][3][4]. Analyses of rest and activity patterns have highlighted specific alterations in psychiatric disorders as compared to healthy controls, as well as among different disorders [5][6][7][8]. ...
... Analyses of rest and activity patterns have highlighted specific alterations in psychiatric disorders as compared to healthy controls, as well as among different disorders [5][6][7][8]. Patients suffering from an episode of major depressive disorder (MDD) display globally lower levels of activity [9], with shorter diurnal activity period and shorter bouts of activity [6,10], and flattened circadian fluctuations in activity levels [1,[11][12][13]. In addition, symptom severity has been shown to correlate with the amount of moderate intensity physical activity [14] and with the number of sedentary bouts [15], while increasing the level of activity by structured, supervised physical activity has been proven to be an effective antidepressant intervention [16][17][18]. ...
... Feature extraction was performed on recordings cropped between first and last midnight to yield an integer number of 24 h periods. The following features were extracted: circadian period; scaling exponent [4]; intradaily variability; interdaily stability; circadian peak and trough; relative amplitude [1,2,27]. The features extracted and included as predictors for model development are listed in Table 1, and the correlation matrix for all predictors as well as outcome variable (MADRS) is shown in Fig. 2A. ...
Objective measures, such as activity monitoring, can potentially complement clinical assessment for psychiatric patients. Alterations in rest–activity patterns are commonly encountered in patients with major depressive disorder. The aim of this study was to investigate whether features of activity patterns correlate with severity of depression symptoms (evaluated by Montgomery–Åsberg Rating Scale (MADRS) for depression). We used actigraphy recordings collected during ongoing major depressive episodes from patients not undergoing any antidepressant treatment. The recordings were acquired from two independent studies using different actigraphy systems. Data was quality-controlled and pre-processed for feature extraction following uniform procedures. We trained multiple regression models to predict MADRS score from features of activity patterns using brute-force and semi-supervised machine learning algorithms. The models were filtered based on the precision and the accuracy of fitting on training dataset before undergoing external validation on an independent dataset. The features enriched in the models surviving external validation point to high depressive symptom severity being associated with less complex activity patterns and stronger coupling to external circadian entrainers. Our results bring proof-of-concept evidence that activity patterns correlate with severity of depressive symptoms and suggest that actigraphy recordings may be a useful tool for individual evaluation of patients with major depressive disorder.
... In the field of sleep and biological rhythms research, the use of actimetry arouse as an effective tool to detect patterns of activity in mood disorders and to distinguish psychopathologies [19,20]. For example, several reports describe that depressed individuals are more active during the rest period, and sometimes less active during the day, reflecting a lower amplitude of the rhythms of motor activity throughout the day [21,22]. Most commercial devices are also equipped with a luximeter that allows for the assessment of light exposure. ...
... This study shows the characteristics of self-reported and actimetry-based circadian rhythms and sleep-wake behavior related to adolescents with MDD and with a HR for depression compared with those with LR for future depression. These results are in line with the recent discoveries in adults [21,22,[36][37][38] and provides novel evidence by introducing a HR group and describing detailed analyses of actimetry and light exposure in a controlled sample of adolescents from the community. ...
... This first hypothesis is quite plausible vis-a-vis the results of increased SJL in this group and the report of greater irregularity in both bedtime and wakeup time. The second is that adolescents in the MDD group could be more active in their rest period due to depressive symptoms that might lead to psychomotor reduction during waking periods and more fragmented sleep at night, both signs of mood disorders [21]. ...
Study Objectives
Major Depressive Disorder (MDD) in adolescence is associated with irregularities in circadian rhythms and sleep. The characterization of such impairment may be critical to design effective interventions to prevent development of depression among adolescents. This study aimed to examine self-reported and actimetry-based circadian rhythms and sleep-wake behavior associated with current MDD and high-risk for MDD among adolescents.
Methods
Ninety-six adolescents who took part in the IDEA-RiSCo study were recruited using an empirically-developed depression-risk stratification method: 26 classified as low-risk (LR), 31 as high-risk (HR), and 39 as a current depressive episode (MDD). We collected self-report data on insomnia, chronotype, sleep schedule, sleep hygiene as well as objective data on sleep, rest-activity and light exposure rhythms using actimetry for 10 days.
Results
Adolescents with MDD exhibited more severe insomnia, shorter sleep duration, higher social jetlag (SJL), lower relative amplitude (RA) of activity and higher exposure to artificial light at night (ALAN) compared to the other groups. They also presented poorer sleep hygiene compared to the LR group. The HR group also showed higher insomnia, lower RA, higher exposure to ALAN and higher SJL compared to the LR group.
Conclusions
High-risk adolescents shared sleep and rhythm alterations with the MDD group, which may constitute early signs of depression, suggesting that preventive strategies targeting sleep should be examined in future studies. Furthermore, we highlight that actimetry-based parameters of motor activity (particularly RA) and light exposure are promising constructs to be explored as tools for assessment of depression in adolescence.
... 22 Finally, relationships between inconsistent sleep timing and adverse mental health are increasingly recognized, including with mood disorders, depression, wellbeing, and cognitive function. [23][24][25][26] Indeed, during the initial phase of the COVID-19 pandemic, links between poor sleep and adverse mental health symptoms have been reported based on survey data, 2,4,[27][28][29] with poor sleep associated with anxiety and depression symptoms. 2 However, most surveys have limited resolution of sleep-wake measurement (eg, daily logs or cross-sectional surveys vs 30-second epochs) and lack prepandemic data. ...
... 2 However, most surveys have limited resolution of sleep-wake measurement (eg, daily logs or cross-sectional surveys vs 30-second epochs) and lack prepandemic data. Moreover, sleep health has several dimensions (duration, timing, quality, regularity) linked with mental health, 19 and published studies during the pandemic have not included measures of variability in sleep timing, which has been associated with depressed mood 23,25 and other adverse health outcomes. 30,31 To address these knowledge gaps, we examined objective sleep and mental health among U.S. users of a sleep wearable (WHOOP, Inc., Boston, Massachusetts) before and during the COVID-19 pandemic using comprehensive sets of mental health (symptoms of anxiety or depression, burnout, and substance use to cope with stress or emotions) and sleep variables (duration, sleep onset, sleep offset, consistency of sleep timing, and wakefulness during time in bed). ...
... 43 While a standard based on sleep consistency has not yet been established, more consistent sleep timing is generally associated with better health outcomes. [23][24][25] Given the distribution of sleep consistency scores in the mental health sample (percentiles: 25th = 71.5; 50th = 76.3; ...
Objectives
To characterize objective sleep patterns among U.S. adults before and during the COVID-19 pandemic, and to assess for associations between adverse mental health symptoms and (1) sleep duration and (2) the consistency of sleep timing before and during the pandemic.
Design
Longitudinal objective sleep-wake data during January-June 2020 were linked with mental health and substance use assessments conducted during June 2020 for The COVID-19 Outbreak Public Evaluation (COPE) Initiative.
Setting
Adult users of WHOOP—a commercial, digital sleep wearable.
Participants
Adults residing in the U.S. and actively using WHOOP wearable devices, recruited by WHOOP, Inc.
Intervention
The COVID-19 pandemic and its mitigation.
Measurements
Anxiety or depression symptoms, burnout symptoms, and new or increased substance use to cope with stress or emotions.
Results
Of 4912 participants in the primary analytic sample (response rate, 14.9%), we observed acutely increased sleep duration (0.25 h or 15 m) and sleep consistency (3.51 points out of 100) and delayed sleep timing (onset, 18.7 m; offset, 36.6 m) during mid-March through mid-April 2020. Adjusting for demographic and lifestyle variables, participants with persistently insufficient sleep duration and inconsistent sleep timing had higher odds of adverse mental health symptoms and substance use in June 2020.
Conclusions
U.S. adult wearable users displayed increased sleep duration, more consistent sleep timing, and delayed sleep onset and offset times after the COVID-19 pandemic onset, with subsample heterogeneity. Associations between adverse mental health symptoms and pre- and mid-pandemic short sleep duration and inconsistent sleep timing suggest that these characteristics warrant further investigation as potential modifiable mental health and substance use risk factors.
... As a part of circadian rhythms, the rest-activity pattern indicates circadian rhythmicity, reflecting the timing and regularity of physical activity and sleep [21]. Relative amplitude is a common and convenient non-parametric measure of the amplitude of rest-activity rhythm calculated from the most active continuous 10 h (M10, "day") and the least active continuous 5 h (L5, "night") in an average 24 h [22,23]. The computing formula is as follows: ...
... As it suggests, relative amplitude ranges from 0 to 1. Higher values reflect a clearer distinction between activity levels during the most and least active periods of the day, on the contrary, lower values indicate disrupted circadian rhythms. We derived relative amplitude by processing raw accelerometer data in UK Biobank (field ID 90004) [22]. ...
Circadian rhythm disruption (CRD) is a shared characteristic of various brain disorders, such as Alzheimer’s disease (AD), Parkinson’s disease (PD), and major depression disorder (MDD). Disruption of circadian rhythm might be a risk factor for brain disorder incidents. From 7-day accelerometry data of 72,242 participants in UK Biobank, we derived a circadian relative amplitude variable, which to some extent reflected the degree of circadian rhythm disruption. Records of brain disorder incidents were obtained from a wide range of health outcomes across self-report, primary care, hospital inpatient data, and death data. Using multivariate Cox proportional hazard ratio regression, we created two models adjusting for different covariates. Then, linear correlations between relative amplitude and several brain morphometric measures were examined in participants with brain MRI data. After a median follow-up of around 6.1 years, 72,242 participants were included in the current study (female 54.9%; mean age 62.1 years). Individuals with reduced relative amplitude had increasing risk of all-cause dementia (Hazard ratio 1.23 [95% CI 1.15 to 1.31]), PD (1.33 [1.25 to 1.41]), stroke (1.13 [1.06 to 1.22]), MDD (1.18 [1.13 to 1.23]), and anxiety disorder (1.14 [1.09 to 1.20]) in fully adjusted models. Additionally, significant correlations were found between several cortical regions and white matter tracts and relative amplitude that have been linked to dementia and psychiatric disorders. We confirm CRD to be a risk factor for various brain disorders. Interventions for regulating circadian rhythm may have clinical relevance to reducing the risk of various brain disorders.
... Recently, many lines of evidence in humans or animal models clearly demonstrated a close relationship between MDD and the disturbances of sleep-wake and circadian systems (12)(13)(14)(15)(16)(17). The hypothesis that dysregulations of circadian rhythm may play a critical role in the pathophysiology of MDD, is supported by recent findings in the field of molecular biology and genetics of the complex machinery regulating biological clocks (13,(18)(19)(20)(21). Therefore, disturbed circadian function have been suggested to be a major risk factor in the development of MDD (14,18,(22)(23)(24)(25). Focused on the people who are vulnerable to the disturbances of circadian rhythm will provide pivotal evidence in the prevention of MDD. ...
... Emerging studies have showed that more than 90% of depressed patients reported disruptions in sleep including insomnia and early morning awakening. These patients tend to have more severe forms of MDD and may be at an increased risk for suicidal ideation and suicidal behaviors (20,103,104), which supports a circadian hypothesis of depression that based, in part, on data showing that a subgroup of depressed patients has dysregulated 24 h rhythms including sleep, hormonal secretions, core body temperature and mood (17,24,105,106). Perhaps the strongest and most direct evidence for a circadian defect in depression comes from a study of postmortem 24 h sinusoidal gene expression rhythms across six regions of human brain showing a dramatic dysregulation of circadian genes in MDD compared to controls (19). ...
Background
Circadian rhythm was involved in the pathogenesis of depression. The detection of circadian genes and white matter (WM) integrity achieved increasing focus for early prediction and diagnosis of major depressive disorder (MDD). This study aimed to explore the effects of PER1 gene polymorphisms (rs7221412), one of the key circadian genes, on the association between depressive level and WM microstructural integrity.Materials and methodsDiffusion tensor imaging scanning and depression assessment (Beck Depression Inventory, BDI) were performed in 77 healthy college students. Participants also underwent PER1 polymorphism detection and were divided into the AG group and AA group. The effects of PER1 genotypes on the association between the WM characteristics and BDI were analyzed using tract-based spatial statistics method.ResultsCompared with homozygous form of PER1 gene (AA), more individuals with risk allele G of PER1 gene (AG) were in depression state with BDI cutoff of 14 (χ2 = 7.37, uncorrected p = 0.007). At the level of brain imaging, the WM integrity in corpus callosum, internal capsule, corona radiata and fornix was poorer in AG group compared with AA group. Furthermore, significant interaction effects of genotype × BDI on WM characteristics were observed in several emotion-related WM tracts. To be specific, the significant relationships between BDI and WM characteristics in corpus callosum, internal capsule, corona radiata, fornix, external capsule and sagittal stratum were only found in AG group, but not in AA group.Conclusion
Our findings suggested that the PER1 genotypes and emotion-related WM microstructure may provide more effective measures of depression risk at an early phase.
... The Composite Scale of Morningness (CSM) (Smith et al., 1989), the Diurnal Type Scale (DTS), the Circadian Type Questionnaire (CTQ), and the Preference Scale (PS) can also be considered instruments for evaluating chronotype . Other relatively objective tools can evaluate chronotypes, including core body temperature, dim light melatonin onset (DLMO), a sleep diary (Carney et al., 2012), wrist accelerometry, and actigraphs Lyall et al., 2018). We have reviewed the three most commonly used questionnaires in the Supplementary Material. ...
... Disrupted circadian rhythmicity or SJL may be crucial in the development, outcome, and treatment of human health (Foster et al., 2013;Jagannath et al., 2017;Gold and Kinrys, 2019). A study of more than 90,000 participants indicated that circadian dysfunction is related to a range of mental disorders, such as major depressive disorder (MDD), BD, and seasonal affective disorder (SAD), as well as to poorer mental experiences, such as more loneliness, lower happiness, and reduced satisfaction (Lyall et al., 2018). Research using unpredictable chronic mild stress in a mice model with depression-like behaviors identified decreased amplitude of activity and body temperature rhythm (Logan et al., 2015). ...
The circadian rhythm is crucial for physiological and behavioral functions. Chronotype, which represents individual preferences for activity and performance, is associated with human health issues, particularly psychiatric disorders. This narrative review, which focuses on the relationship between chronotype and mental disorders, provides an insight into the potential mechanism. Recent evidence indicates that (1) the evening chronotype is a risk factor for depressive disorders and substance use disorders, whereas the morning chronotype is a protective factor. (2) Evening chronotype individuals with bipolar disorder tend to have more severe symptoms and comorbidities. (3) The evening chronotype is only related to anxiety symptoms. (4) The relationship between chronotype and schizophrenia remains unclear, despite increasing evidence on their link. (5) The evening chronotype is significantly associated with eating disorders, with the majority of studies have focused on binge eating disorders. Furthermore, the underlying mechanisms or influence factors are described in detail, including clock genes, brain characteristics, neuroendocrinology, the light/dark cycle, social factors, psychological factors, and sleep disorders. These findings provide the latest evidence on chronotypes and psychiatric disorders and serve as a valuable reference for researchers.
... Disruptions and age-related changes of circadian rhythms, which underlie the regulation of physiological processes during the 24-h light-dark cycle (61), may contribute to shortened life span and metabolic dysfunction in animal model organisms (62)(63)(64) and negatively impact overall health and cognitive function in humans (65,66). The relevance of TFs in the regulation of circadian rhythms is immediately apparent, as the core oscillatory circadian clock gene network is formed by the two TFs CLOCK and BMAL1 (67,68). ...
... (61), is thought to be the main timer and regulator of metabolic, physiological, and behavioral processes during the 24-h light-dark cycle that shapes nearly all living processes on Earth. It has long been intuitively appreciated and is by now well supported scientifically that circadian rhythms in humans change with age and that a prolonged disruption of normal circadian rhythms has negative effects on overall health, well-being, mood, and cognitive function (65,66). At the core of the circadian clock gene network, so far best studied in mammals, are several interlocking, self-regulating transcriptional feedback loops, the intricacies of which have been reviewed previously (67,68) and are only briefly described here. ...
Aging is the single largest risk factor for many debilitating conditions, including heart diseases, stroke, cancer, diabetes, and neurodegenerative disorders. While far from understood in its full complexity, it is scientifically well-established that aging is influenced by genetic and environmental factors, and can be modulated by various interventions. One of aging's early hallmarks are aberrations in transcriptional networks, controlling for example metabolic homeostasis or the response to stress. Evidence in different model organisms abounds that a number of evolutionarily conserved transcription factors, which control such networks, can affect lifespan and healthspan across species. These transcription factors thus potentially represent conserved regulators of longevity and are emerging as important targets in the challenging quest to develop treatments to mitigate age-related diseases, and possibly even to slow aging itself. This review provides an overview of evolutionarily conserved transcription factors that impact longevity or age-related diseases in at least one multicellular model organism (nematodes, flies, or mice), and/or are tentatively linked to human aging. Discussed is the general evidence for transcriptional regulation of aging and disease, followed by a more detailed look at selected transcription factor families, the common metabolic pathways involved, and the targeting of transcription factors as a strategy for geroprotective interventions.
... There is a great prevalence of sleep and circadian rhythm dysregulation in BD patients, and these are now recognized as one of the diagnostic criteria for manic and depressive episodes [12][13][14]. The manic and depressive episodes differ not only in mood and behavioral aspects but also in the actual state of the circadian system, as assessed by daily profiles of melatonin production and clock gene expression in BD patients [15,16]. ...
Lithium is an effective mood stabilizer, but the mechanism of its therapeutic action is not well understood. We investigated the effect of lithium on the circadian clock located in the ventricle barrier complex containing the choroid plexus (CP), a part of the glymphatic system that influences gross brain function via the production of cerebrospinal fluid. The mPer2Luc mice were injected with lithium chloride (LiCl) or vehicle, and their effects on the clock gene Nr1d1 in CP were detected by RT qPCR. CP organotypic explants were prepared to monitor bioluminescence rhythms in real time and examine the responses of the CP clock to LiCl and inhibitors of glycogen synthase kinase-3 (CHIR-99021) and protein kinase C (chelerythrine). LiCl affected Nr1d1 expression levels in CP in vivo and dose-dependently delayed the phase and prolonged the period of the CP clock in vitro. LiCl and CHIR-99021 had different effects on 1] CP clock parameters (amplitude, period, phase), 2] dexamethasone-induced phase shifts of the CP clock, and 3] dynamics of PER2 degradation and de novo accumulation. LiCl-induced phase delays were significantly reduced by chelerythrine, suggesting the involvement of PKC activity. The effects on the CP clock may be involved in the therapeutic effects of lithium and hypothetically improve brain function in psychiatric patients by aligning the function of the CP clock-related glymphatic system with the sleep-wake cycle. Importantly, our data argue for personalized timing of lithium treatment in BD patients.
... These now-familiar "lockdowns" prohibited any non-essential activities outside home, which led to significant disruption in individuals' daily lives and a possible reduction in coping strategies for dealing with stress. Previous studies have demonstrated that disruptions in daily routines increase the risk of various mental disorders (Lyall et al., 2018). Disruption of lifestyle routine brought by lengthy home quarantine may lead to heavy psychological stress (Rubin and Wessely, 2020), which can increase the risk of mental disorders, even among individuals without any psychiatric history Liu et al., 2020a). ...
Background:
Studying the role of psychological resilience in self-perceived stress and mental disorders among family members of medical workers can help us understand its importance in mental health care and guide us to develop psychological intervention strategies for family members of medical workers.
Methods:
A total of 671 family members of medical workers were enrolled. Self-perceived stress, resilience, depression symptoms, anxiety symptoms, and post-traumatic stress disorder (PTSD) symptoms were measured in our research.
Results:
The prevalence of anxiety, depression, and PTSD symptoms among relatives of medical workers were 49.0 %, 12.2 %, and 20.3 % respectively during the COVID-19 epidemic. According to the Multivariate regression model, compared with family members of doctor, family members of nurse and medical technologists were more likely to report anxiety symptoms. Female members of medical staff were more likely to have PTSD symptoms than male counterparts; and family members of medical technologist appeared to less likely have PTSD symptoms than family members of either doctor or nurse. The mediation analysis confirmed that mental resilience mediated the relationship between self-perceived stress and anxiety symptoms.
Limitations:
Single cross-sectional study design without the follow-up comparative analysis, only self-reported measurements were adopted, and inadequate pre-set demographic variables.
Conclusions:
To the best of our knowledge, our study firstly demonstrated the risk of psychological distress present in the family members of medical providers during the COVID-19 epidemic. Meanwhile, our findings highlighted the importance of mental resilience in family members of frontline medical workers as it mediated the relationship between self-perceived stress and anxiety symptoms.
... It negatively affects mental health and leads to the development of increased anxiety and symptoms of depression. Lyall et al. found that the use of Facebook around bedtime increased the likelihood of developing major depressive disorder by 6% and decreased subjective happiness by 9% [41]. Aldao notes that such a situation locks us into a vicious circle of negativity: "the more time we spend scrolling, the more we find those dangers, the more we get sucked into them, the more anxious we get" [42]. ...
Objective:
The aim: The paper attempts to investigate the impact of social networks and digital media on mental health and psychological well-being.
Patients and methods:
Materials and methods: The data collection was carried out using PubMed, Scopus, Web of Science, Google Scholar databases. Research papers were identified according to the search terms "cyberspace", "cyberpsychology", "digital media", "virtual reality", "social networks", "mental health", "psychological well-being", "beauty", "beauty standards". The authors used integrative anthropological approach, interpretive research paradigm, and multidisciplinary analysis.
Conclusion:
Conclusion: The digital world is a relatively recent phenomenon, therefore, the potential relationship between its use and mental health and psychological well-being has not yet been adequately explored. Most of the research has been conducted over the last decades; and until now the scientific community has not been able to fully interpret the obtained results and come to final conclusions. As Timpano and Beard rightly pointed out, the future research should be focused on types and motivations for the use of social networks; identify potential mechanisms linking the social media use and mental health symptoms; reveal an impact of social networks on declines in face-to-face social interactions; understand the link of social networks with maladaptive coping strategies and health behaviors. The relationship between social networks, digital media use and psychological functioning is not straightforward and depends on many factors. However, we should not forget that there is nothing new under the sun. The same people act in both digital and physical spaces. And the psychological problems that are revealed in the digital universe are the same that "accompany" the actors of the digital communication process in the real, physical world. Anyway, we cannot avoid cyberspace, so we have to learn how to interact within this challenging world.
... Las prohibiciones de actividades no esenciales fuera del hogar, el cierre de las escuelas y trabajos han obligado a millones de personas a modificar sus rutinas diarias de la noche a la mañana. Estos cambios e interrupciones en la vida cotidiana de las personas aumentan el riesgo de desarrollar una variedad de trastornos mentales (Lyall et al., 2018). Además, si las interrupciones de los ritmos de vida se llegan a prolongar por tiempos muy largos como medida contra el contagio del virus, la angustia psicológica puede aumentar, lo que provocará el riesgo de desarrollar enfermedades mentales incluso en personas sanas sin antecedentes médicos (Liu et al., 2020;Qiu et al., 2020). ...
Introducción. La pandemia ha llevado a la población mundial a enfrentar problemas en el área de la salud mental tales como la angustia, ansiedad y depresión. Aunado a esto, las medidas preventivas para disminuir el número de contagios en los países derivaron en un aislamiento que representó un reto en la forma tradicional de educación. Objetivo. El objetivo de este trabajo es presentar una revisión bibliográfica de las afectaciones en la salud mental durante la pandemia COVID-19. Asimsmo, su relación con el desempeño escolar dentro de la nueva forma de enseñanza a partir de las tecnologías aplicadas. Resultados. Los resultados demuestran que la incorporación de la salud mental en las estrategias de aprendizaje y con ayuda de la tecnología educativa, permitirá al estudiantado el desarrollo de una conducta adecuada ante la sociedad y un incremento en el rendimiento académico.
... Rest-activity rhythms are considered an output of the underlying circadian clock. Previous studies have indicated that lower levels in parameters related to amplitude of activity are associated with an increased risk of major depressive disorder (MDD) (Ávila Moraes et al., 2013) and bipolar disorder (BD) (Rock et al., 2014), and with greater mood instability (Lyall et al., 2018). In fact, when compared to healthy controls, individuals with MDD exhibit reduced daytime motor activity, indicative of a lower relative amplitude (RA) of activity (Burton et al., 2013). ...
Background
Alterations in circadian system organization have been related to major depressive disorder manifestations. This study aimed to evaluate chronobiological parameters, such as sleep, levels of 6-sulfatoxymelatonin, and others derived from actimetry as potential predictors of adequate treatment response in MDD.
Methods
98 adult women with confirmed diagnosis of MDD were included. Participants completed standard questionnaires (Hamilton Depression Rating Scale – HAM-D; Munich Chronotype Questionnaire - MCTQ) at baseline and after 4 weeks of treatment. Urinary samples for assessing 6-sulfatoxymelatonin were collected on the day before and immediately after pharmacological treatment administration, and 28 continuous days of actigraphy data were collected during the protocol. Participants were classified into Responder (R) or Non-responder (NR) to antidepressant treatment in 4 weeks (early responder), which was characterized by a ≥50 % decrease in the HAM-D score.
Results
The following biological rhythms variables significantly predicted a better treatment response in a model controlling for age, sex, and previous treatments: higher levels of activity (M10 - average activity in the 10 most active hours within the 24 h-day) and an earlier center of the 10 most active hours (M10c), as well as lower intradaily variability (IV) of light exposure. Sleep parameters and 6-sulfatoxymelatonin levels did not associate with treatment response prediction.
Limitation
Actimetry data were not assessed before changing in the treatment plan.
Conclusion
Different patterns in activity and light exposure might be linked to early antidepressant response.
... For example, rats with chronic jet lag simulation presented enhanced depressive behaviors and cognitive de cits (21). Disrupted circadian rhythmicity with mood disorders was found associated with cognitive function based on large-scale UK Biobank data (22). Evening chronotype and circadian disruption might bring cognitive and psychiatric vulnerability due to "desynchronization effect" (23). ...
Background
Bipolar disorder (BD) is a common and disabling mental disorder with circadian rhythm and neurocognitive features playing important roles in treatment response and rehabilitation. Limited evidence existed for circadian rhythm interaction with long-term neurocognitive functioning. This protocol is designed to investigate whether circadian rhythm could predict long-term change neurocognitive functioning and treatment response in BD patients.
Methods
This is a prospective observational study protocol. We plan to include 47 BD patients within depressive episodes. Participants will be evaluated from clinical, circadian rhythm and neurocognitive perspectives at baseline, 6-month and 12-month follow-ups using questionnaires, actigraphy, vitamin D concentration and computed cognitive tests. Both cross-sectional and longitudinal associations between participants’ circadian rhythm patterns and cognitive functioning and treatment response will be detected. Spearman correlation, Pearson correlation and multiple linear regression models will be applied for statistical analysis.
Discussion
We suppose that circadian rhythm could predict change of neurocognitive functioning and that circadian rhythm is associated with treatment response and adherence, social functioning and quality of life. Results using this protocol may provide additional information for BD pathophysiology, treatment targets and prediction.
Trial Registration
This study was approved by Chinese Clinical Trial Registry (Registration Code: ChiCTR2200064922) registered on 21st October 2022.
... However, there is insufficient data to understand the mechanism or causeeffect relationship between circadian rhythm and oxidative stress and the resulting disease. There have been reports that show disturbances in circadian rhythm affecting people's cognition, sleep deprivation affecting emotions, and circadian rhythm disturbances increase the risk of depression and bipolar disorder, but there are few studies related to the relevance of various indicators, the method of disturbing the circadian rhythm, or recovery [22][23][24]. ...
Objective:
This study aimed to explore the relationship among several indices of circadian rhythms and lipid peroxidation of brain tissue in mice.
Methods:
After entrainment of 4-week-old mice, one group was disrupted their circadian rhythms for three days and the other group for seven days (n = 10, respectively). After a recovery period, the Y-maze test, the elevated plus maze test, the tail suspension test, and the forced swimming test were conducted. To assess lipid peroxidation in brain tissue, thiobarbituric acid reactive substances were measured in the cortex, hippocampus, and cerebellum.
Results:
When circadian rhythms were disrupted and adapted back to their original rhythm, the recovery time of the 7-day disruption group (median 3.35 days) was significiantly faster than one of the 3-day disruption group (median 4.87 days). In the group with a 7-day disruption, mice that had recovered their rhythms early had higher malondialdehyde levels in their hippocampus compared to those with delayed recovery. The entrainment of circadian rhythms was negatively correlated with the malondialdehyde level of brain tissue. The behavioral test results showed no differences depending on the disruption durations or recovery patterns of circadian rhythms.
Conclusion:
These results suggest that disruption types, recovery patterns, and the entrainment of circadian rhythms are likely to affect oxidative stress in adolescents or young adult mice. Future study is needed to confirm and specify these results on the effects of circadian rhythms on oxidative stress and age-dependent effects.
... (accessed on 01/08/2022). Further details on the quality control applied to the actigraphy data can be found in [31]. This study was covered by the generic ethical approval for UK Biobank studies from the NHS National Research Ethics Service (approval letter dated 17 June 2011, Ref 11/NW/0382) for project #26209. ...
Variability in the timing of daily sleep is increasingly recognized as an important factor in sleep and general physical health. One potential driver of such daily variations in sleep timing is different work and social obligations during the “working week” and weekends. To investigate the nature of weekday/weekend differences in the timing of sleep offset, we examined actigraphy records of 79,161 adult participants in the UK Biobank who wore an actiwatch for 1 week. The time of sleep offset was found to be on average 36 min later on weekends than on weekdays, and when this difference was expressed as an absolute value (i.e., irrespective of sleep offset being either later or earlier on weekends), it was 63 min. Younger age, more socioeconomic disadvantage, currently being in employment, being a smoker, being male, being of non-white ethnicity and later chronotype were associated with greater differences in sleep offset between weekdays and weekend days. Greater differences in sleep offset timing were associated with age-independent small differences in cardiometabolic health indicators of BMI and diastolic blood pressure, but not HbA1c or systolic blood pressure. In a subset of participants with Type 2 Diabetes Mellitus, weekday/weekend sleep offset differences were associated weakly with BMI, systolic blood pressure and physical activity. Overall, this study demonstrates potentially substantive differences in sleep offset timings between weekdays and weekends in a large sample of UK adults, and that such differences may have public health implications.
... In addition to the daily impact and distress of poor sleep, long-term sleep disturbance has also been widely associated with physical and mental wellbeing (Grandner, 2019). For example, there are established associations with cardiovascular health (Makarem et al., 2019), obesity (Hargens et al., 2013), smoking and substance abuse (Hasler et al., 2012), cognitive, emotional and behavioural dysregulation (Palagini et al., 2019), poorer academic performance, work success and learning capacity (Barnes & Watson, 2019;Hershner, 2020), deficits to affective functioning including mood disorders, suicidal behaviour and self-harm (Lyall et al., 2018). Given the prevalence and widespread impact of insufficient sleep amongst young people and adults globally, sleep disturbances presents not only as a significant public health problem, but also an economic burden on society. ...
Insufficient quantity and quality of sleep is a public health concern that can be addressed by interventions for improving sleep outcomes. Environmental factors such as poor air quality are a potential target for intervention, particularly in light of associations between air pollution and worse sleep. The aim of this pilot study was to investigate the effects of using an air purifier on sleep outcomes and mood in 30 healthy adults. There were two conditions: (i) air purifier with a high-efficiency particulate air filter; (ii) air purifier with a placebo filter. Participants undertook both conditions, each over 2 weeks with a 2-week washout, following a counterbalanced, double-blind design. Daily sleep outcomes were measured with actigraphy watches and sleep diaries, whilst daily mood was assessed with the Positive and Negative Affect Schedule. The Insomnia Severity Index, the Pittsburgh Sleep Quality Index, and symptoms of anxiety and depression were measured pre- and post-. The purifier filter was associated with increased total sleep time for an average of 12 min per night, and increased total time in bed for an average of 19 min per night relative to the placebo. There were several sleep and mood outcomes for which no changes were observed, and time awake after sleep onset was higher for the purifier filter. Air quality was better during the high-efficiency particulate air filter condition. These findings offer positive indications that environmental interventions that improve air quality can have benefits for sleep outcomes in healthy populations who are not exhibiting clinical sleep disturbances.
... An advantage of passive data collection is that they only require minimal contributions from the participant, which greatly improves study compliance enabling efficient longitudinal data collection. 13 Mental health has been linked to various types of passively collected data, including geolocation, 71,72 sleep disturbance data, 58,73 and smartphone usage patterns. 15,74 Although the passive data collected using smartphones might not be as informative as in-depth clinical measurements, the minimally invasive nature over longer time periods might lead these data to be considered to be as valuable as more costly data acquisition methods, especially when combined across multiple data sources. ...
Computational models have great potential to revolutionise psychiatry research and clinical practice. These models are now used across multiple subfields, including computational psychiatry and precision psychiatry. Their goals vary from understanding mechanisms underlying disorders to deriving reliable classification and personalised predictions. Rapid growth of new tools and data sources (eg, digital data, gamification, and social media) requires an understanding of the constraints and advantages of different modelling approaches in psychiatry. In this Series paper, we take a critical look at the range of computational models that are used in psychiatry and evaluate their advantages and disadvantages for different purposes and data sources. We describe mechanism-driven and mechanism-agnostic computational models and discuss how interpretability of models is crucial for clinical translation. Based on these evaluations, we provide recommendations on how to build computational models that are clinically useful.
... Interestingly, our investigation of relative amplitude found negative genetic correlations with both depression and BIP-II, but not with BIP-I, which is a reflection of findings at the phenotypic level [13][14][15][16] . We note that the strongest and most statistically significant correlation in the present analysis was between depression and relative www.nature.com/scientificreports/ ...
Major Depression and Bipolar Disorder Type I (BIP-I) and Type II (BIP-II), are characterized by depressed, manic, and hypomanic episodes in which specific changes of physical activity, circadian rhythm, and sleep are observed. It is known that genetic factors contribute to variation in mood disorders and biological rhythms, but unclear to what extent there is an overlap between their underlying genetics. In the present study, data from genome-wide association studies were used to examine the genetic relationship between mood disorders and biological rhythms. We tested the genetic correlation of depression, BIP-I, and BIP-II with physical activity (overall physical activity, moderate activity, sedentary behaviour), circadian rhythm (relative amplitude), and sleep features (sleep duration, daytime sleepiness). Genetic correlations of depression, BIP-I, and BIP-II with biological rhythms were compared to discover commonalities and differences. A gene-based analysis tested for associations of single genes and common circadian genes with mood disorders. Depression was negatively correlated with overall physical activity and positively with sedentary behaviour, while BIP-I showed associations in the opposite direction. Depression and BIP-II had negative correlations with relative amplitude. All mood disorders were positively correlated with daytime sleepiness. Overall, we observed both genetic commonalities and differences across mood disorders in their relationships with biological rhythms: depression and BIP-I differed the most, while BIP-II was in an intermediate position. Gene-based analysis suggested potential targets for further investigation. The present results suggest shared genetic underpinnings for the clinically observed associations between mood disorders and biological rhythms. Research considering possible joint mechanisms may offer avenues for improving disease detection and treatment.
... For example, a greater RA indicates that individuals are more active during the day and less active at night, implying better sleep. Previous studies have observed that lower RA showed a strong link with health span-related risk factors (37) or diseases such as inflammation (17), obesity (38,39), glucose tolerance (19), and diabetes (40,41). It was also the only predictor that outperformed traditional predictors of all-cause mortality in the UK Biobank except age (42). ...
Impaired rest–activity circadian rhythm has been associated with increased risk for morbidity and mortality. Animals with mutations in clock genes display accelerated aging and shortened life span. Whether impaired rest–activity circadian rhythm is also associated with processes of aging in humans has not been explored. We analyzed accelerometry and physiological data from 7 539 adults participating in the 2011–2014 waves of the U.S. National Health and Nutrition Examination Surveys. We used accelerometry data to compute rest–activity rhythm measurements. We used physiological data to compute measurements of biological aging according to 3 published algorithms: Klemera–Doubal method (KDM) Biological Age, PhenoAge, and homeostatic dysregulation (HD). In the models adjusting multiple covariates, participants with higher relative amplitude (RA) and interdaily stability (IS) and lower intradaily variability (IV) exhibited less advanced biological aging indexed by KDM and PhenoAge (effect sizes for 1-quantile increase in these rest–activity measurements ranged from 0.54 to 0.57 “years” for RA, 0.24 to 0.28 “years” for IS, and 0.24 to 0.35 “years” for IV, ps < .001). Similar finding was observed for biological aging indexed by HD, but the significance was limited to RA with 1-quantile increase in RA associated with 0.09 log units decrease in HD (p < .001). The results indicate that blunted rest–activity circadian rhythm is associated with accelerated aging in the general population, suggesting that interventions aiming at enhancing circadian rhythm may be a novel approach for the extension of a healthy life span.
... Studies have shown that low daytime light is an important environmental risk factor for mood, sleep, and circadian rhythm-related outcomes (Burns et al. 2021). Long-term circadian disruptions are associated with many pathological conditions such as anxiety (Coles et al. 2015;Lyall et al. 2018;Serin and Acar Tek 2019). ...
Anxiety disorders are a major public health concern in China. Previous studies have provided evidence for associations between ambient temperature and anxiety outpatient visits, but no studies have examined short-term effects of other meteorological factors such as sunshine duration, wind speed, and precipitation on increased anxiety outpatient visits. We aimed to assess the association between climatic factors and outpatient visits for anxiety in Suzhou, a city with a temperate climate in Anhui Province, China. Daily anxiety outpatient visits, meteorological factors, and air pollutants from 2017 to 2019 were collected. A quasi-Poisson generalized linear regression model combined with distributed lag non-linear model (DLNM) was used to quantify the effects of extreme meteorological factors (sunshine duration, wind speed, and precipitation) on anxiety outpatient visits. All effects were presented as relative risk (RR), with the 90th and 10th percentiles of meteorological factors compared to the median. Subgroup analyses by age and gender were performed to identify susceptible subgroups. A total of 11,323 anxiety outpatient visits were reported. Extremely low sunshine duration and low and high wind speed increased the risk of anxiety outpatient visits. The strongest cumulative effects occurred at lag 0–14 days, and the corresponding RRs of extremely low sunshine duration and low and high wind speed were 1.417 (95% CI: 1.056–1.901), 1.529 (95% CI: 1.028–2.275), and 1.396 (95% CI: 1.007–1.935), respectively. Subgroup analyses showed that males and people aged ≥45 years appeared to be more susceptible to the cumulative effects of extremely low sunshine duration. In addition, the adverse effects of extreme wind speed were more pronounced in the cold season. This study provides evidence that extreme climatic factors have a lagged effect on anxiety outpatient visits. In the context of climate change, these findings may help develop weather-based early warning systems to minimize the effects of extreme meteorological factors on anxiety.
... Thus, there were differences between the diurnal fluctuations of monoamine oxi-dase activity in the brain [34], enzymatic activity in blood lymphocytes, and diurnal variations of cell count in lymphoid organs in GC and Wistar rat strains [35]. Experimental and epidemiological researches provided strong evidences of the connection between disturbed circadian rhythm and psychoemotional disorders [16,17,36]. Discovered differences in diurnal activity of GC females actualize further exploration of circadian rhythms in catatonic animals. ...
Maternal behavior is an important factor for the offspring’s development in mammals. Particular
traits of maternal behavior in early ontogenesis may have a lasting effect on a number of behavioral and physiological parameters of offspring in their adulthood. In this study, the maternal behavior of GC rats
(GC stands for “genetic catatonics”) and control Wistar rats from the first to the 20th day after delivery was
examined. Observations were carried out in a home cage during the day using an automated video recording
system without the experimenter’s presence. GC female rats were found in the nest and nursed pups more
often as compared to the female Wistar rats. Wistar female rats “rested” outside the nest more often during
the day, along with less frequent manipulations with nest material and less frequent self-grooming.
The change in the frequency of maternal behavior patterns as the offspring matured had similar dynamics in
both rat strains. When comparing activity in the light and dark phases of the light/dark cycle, it was found that
GC females had a greater activity outside the nest at night. It was assumed that distinguished maternal behavior of catatonic rats might be due to greater anxiety in GC rats as compared to control rats.
Keywords: maternal behavior, catalepsy, catatonia, GC rat strain, circadian rhythm, animal model
DOI: 10.3103/S0096392522020080
... Both wake and sleep electroencephalograms (EEGs) can be biomarkers of depression and antidepressant treatments. Disturbed sleep and the sleep-wake cycle are essentially associated with various psychological disorders, including depression [223][224][225]. The major typical sleep EEG biomarkers of MDD are reduced rapid eye movement (REM) sleep onset latency, increased REM sleep time and increased density of REMs during REM sleep, reduced sleep efficiency, and reduced total sleep time of slow wave sleep (SWS, the deepest stage of nonrapid eye movement (NREM) sleep) [226]. ...
Here we present a complex hypothesis about the psychosomatic mechanism of serotonergic psychedelics. Serotonergic psychedelics affect gut microbes that produce a temporary increase of 5-HT by their host enterochromaffin cells (ECs). This increased 5-HT production-which is taken up and distributed by platelets-may work as a hormone-like regulatory signal that could influence membrane permeability in the host organs and tissues and in the brain. Increased plasma 5-HT levels could enhance permeability of the blood-brain barrier (BBB). Transiently increased permeability of the BBB allows for plasma 5-HT to enter the central nervous system (CNS) and be distributed by the volume transmission. Next, this gut-derived 5-HT could modulate excitatory and inhibitory neurotransmission and produce special network disintegration in the CNS. This transient perturbation of the normal neural hierarchy allows patients access to suppressed fear information and perform an emotional reset, in which the amygdale may have a key role.
Keywords: classic psychedelics; serotonin; gut-brain axis; platelets; membrane permeability; volume transmission; amygdala
... Students following regular work-rest schedule had significant lower risk of mental health problems. This finding was partly supported by a study based on the UK Bio-bank, where circadian disruption was reliably associated with various adverse mental health outcomes [45]. However, the age range of its study sample is 37-73 years old, the result might be not applicable for college students, and further studies are needed to confirm such relationship. ...
Background
Mental health problems are important public health issues among college students and are associated with various social factors. However, these influencing factors were scarcely summarized in Chinese college students comprehensively. This study aims to assess the associations between socio-demographic characteristics, lifestyles, social support quality (SSQ) and mental health among Chinese college students .
Methods
A cross-sectional study was conducted in Wuhan, China, from October 2017 to February 2018. College students from 18 colleges or universities were randomly recruited using multi-stage cluster sampling method. The Multidimensional Scale of Perceived Social Support scale and 12-items General Health Questionnaire were used to estimate students’ SSQ and mental health statuses, respectively. Logistic regression analysis was used to evaluate the associations between socio-demographic characteristics, lifestyles, SSQ and mental health problems.
Results
A total of 10,676 college students were included. Among them, 21.4% were identified as having possible mental health problems. Students being a female, aged 18–22 years old, whose mother held college degrees and above, and drinking alcohol were more likely to have mental health problems ( P < 0.05). Contrarily, having general or higher household economic levels, work-rest regularly, and sleeping ≥ 7 h were preventive factors ( P < 0.05). Especially, a decreasing trend in the risk of having mental health problems with the improvement of SSQ was identified.
Conclusion
Besides socio-demographic and lifestyle factors, social support is a critical factor for mental health among college students. Improving SSQ, especially which from the family, could be an effective method to prevent mental health problems among college students.
... A study of 91,000 individuals indicates a potential association between biological rhythm disorders and MDD or bipolar disorder (BD) (Lyall et al., 2018). In fact, sleep disorder, a type of biological rhythm disorder, is a key feature of depressive disorders. ...
Background
Non-suicidal self-injury (NSSI) is an important risk factor for suicide in adolescents with depressive disorders; therefore, it is important to predict NSSI occurrence as early as possible. Disturbances in biological rhythms are characteristic manifestations of depressive disorders and can lead to immune dysfunction, leading to changes in tumor markers. This study aimed to produce an index that utilizes tumor markers to predict NSSI behaviors among adolescents with depressive disorders.
Methods
A total of 120 hospitalized adolescent patients with depressive disorders aged 14–24 years were included in this study. Participants were divided into NSSI and non-NSSI groups based on self-reports using the Ottawa Self-Injury Inventory. Demographics, tumor marker concentrations, other peripheral blood indices, Hamilton Depression Rating Scale (HDRS) scores, and Hamilton Anxiety Rating Scale (HAMA) scores were compared between the two groups. Logistic regression analysis was conducted to develop a joint index, and a receiver operating characteristic (ROC) curve was created to predict NSSI behaviors among adolescents with depressive disorders.
Results
Compared with the non-NSSI group, the NSSI group had significantly higher insight, retardation, insomnia, hopelessness, psychiatric anxiety, total HDRS and HAMA scores, and significantly higher levels of cancer antigen 125 (CA-125), cancer antigen 19-9 (CA19-9), and carcinoembryonic antigen (CEA). In addition, a joint index was developed by combining CA-125, CA19-9, CEA, HDRS total score, HAMA total score and age using multiple logistic regression to predict NSSI behaviors. The area under the curve was 0.831, with a sensitivity and specificity of 0.734 and 0.891, respectively.
Conclusion
A combination of depression score, tumor marker levels, and age can identify NSSI behaviors among adolescents with depressive disorders.
... Certain immunological processes and drug efficacy are sensitive to specific points in the circadian cycle, highlighting the need to understand the role of circadian rhythms from a pharmacodynamics perspective [16,17]. In addition, disruptions in rest-activity cycles have been associated with adverse outcomes in posttraumatic stress and affective disorder studies [18,19]. This underscores the need to meaningfully quantify circadian rhythms in ecological contexts, such as the assessment of diurnal rhythms, as reflected in smartphone use data. ...
Background
Irregularities in circadian rhythms have been associated with adverse health outcomes. The regularity of rhythms can be quantified using passively collected smartphone data to provide clinically relevant biomarkers of routine.
Objective
This study aims to develop a metric to quantify the regularity of activity rhythms and explore the relationship between routine and mood, as well as demographic covariates, in an outpatient psychiatric cohort.
Methods
Passively sensed smartphone data from a cohort of 38 young adults from the Penn or Children’s Hospital of Philadelphia Lifespan Brain Institute and Outpatient Psychiatry Clinic at the University of Pennsylvania were fitted with 2-state continuous-time hidden Markov models representing active and resting states. The regularity of routine was modeled as the hour-of-the-day random effects on the probability of state transition (ie, the association between the hour-of-the-day and state membership). A regularity score, Activity Rhythm Metric, was calculated from the continuous-time hidden Markov models and regressed on clinical and demographic covariates.
Results
Regular activity rhythms were associated with longer sleep durations (P=.009), older age (P=.001), and mood (P=.049).
Conclusions
Passively sensed Activity Rhythm Metrics are an alternative to existing metrics but do not require burdensome survey-based assessments. Low-burden, passively sensed metrics based on smartphone data are promising and scalable alternatives to traditional measurements.
... The bidirectional relationship between sleep and mental health (i.e. adequate, good quality sleep contributes to good mental health, and good mental health contributes to better, adequate sleep) is well-established [27][28][29], with symptoms of depression and anxiety being clearly associated with sleep duration, quality and timing [30][31][32]. Younger women appear to be particularly vulnerable [33,34], and there is a positive relationship between meeting sleep duration recommendations and mental health for children and adolescents [22]. More recent research has documented associations between sleep duration and sleep quality, and mental health conditions among pregnant women [35], and harmful alcohol use (a risk for poor mental health) in women more generally [36]. ...
Abstract Background Relationships between mental health and multiple health behaviours have not been explored in young South African women experiencing social constraints. The aim of this study was to identify associations between mental health indicators and risk factors with physical activity, sedentary behaviour, and sleep, amongst young women living in Soweto, a predominantly low-income, urban South African setting. Methods For this cross-sectional study, baseline measurements for participants (n = 1719, 18.0–25.9 years old) recruited for the Healthy Life Trajectories Initiative were used including: physical activity, sedentary behaviour (sitting, screen and television time), sleep (duration and quality), depression and anxiety indicators, emotional health, adverse childhood experiences, alcohol-use risk; social vulnerability, self-efficacy, and social support. Results Multiple regression analyses showed that depression (β = 0.161, p
... [22] There is evidence to believe that shortened sleep duration within a 24-hour period may be an important factor for circadian misalignment, causing increased sleepiness and increased susceptibility to mental health disorders such as depressive mood and bipolar disorders. [11,24] Hankinson noted that patient care is most often considered to be more important than the health and well-being of the nurse. [25] James, Butterfield, Tuell's study concluded sleep deprivation may likely impair the nursing student's overall confidence to practice safely when in a clinical environment. ...
Background: Nursing students are prone to inadequate sleep but not fully aware of personal health risks, potential safety and quailty of care issues. Poor sleep hygiene can impact cognition, aleartness, cognitive speed, and accuracy of tasks completion, lower grades, fatigue and depression.Methods: This descriptive study addressed quantitative data from a 4-point Likert scale and open-ended questions. Nursing students from the National Student Nurse Association enrolled in an associate or baccalaureate program and having had at least one clinical experience were invited to particiate in the study.Results: Results indicate the amount of sleep needed is not being achieved. Participants reported ingesting substances to stay awake and to induce sleep. Nineteen percent of students reported making an error during a clinical experience.Conclusions: Students may be naive in thinking short- and long-term use of sleep-inducing aides and stimulants for wakefulness pose no risks to personal safety and safety of patients. By identifying and addressing systemic causes of nursing students lack of sleep using a comprehensive approach to educate, impose consequences, and promote sleep hygiene at the local and national levels, students will have fewer reasons and justifications for not achieving adequate sleep.
... Due to work schedules, night shift work forcefully disrupts the normal circadian rhythm, leading to a lack of sleep and excessive fatigue, with adverse consequences for mental health (Lyall et al. 2018). A cross-sectional study reported a higher prevalence of depression among nurses who worked night shifts in South Korea (Lee et al. 2016). ...
Background
Depression is considered as a global problem. Recently, the prevalence of depression among night shift workers has been attracting people's attention. This study aims to explore the associations among night shift work, shift frequency and depression among Chinese workers and to explore whether sleep disturbances are a critical factor.
Methods
The cross-sectional survey consists of 787 autoworkers from a manufacturing plant in Fuzhou, China. Information about night shift work, shift frequency, depression, and sleep disturbances were collected from work records and responses to the Patient Health Questionnaire (PHQ-9) and the Pittsburgh Sleep Quality Index (PSQI). A mediation model was generated to examine relationship between night shift work, sleep disturbances, and depression.
Results
Our results found that night shift work, shift frequency, sleep disturbances, and depression had positive and significant relationships in a sample of Chinese workers. Night shift work, shift frequency and sleep disturbances were associated with an increased risk of depression among workers (OR: 4.23, 95% CI 2.55–7.00; 3.91, 2.31–6.63; 6.91, 4.40–10.86, respectively). Subsequent mediation analysis found that the association between night shift work and depression appeared to be partially mediated by sleep disturbances.
Conclusion
These findings suggest that appropriate intervention and management strategies should be considered to alleviate the mental health burden of night shift workers.
... Sleep timing and duration across days "in-real-life," as well as its regularity, cannot be fully assessed in lab studies [3]. Actimetry has also proven to be useful for studying physical activity, mobility, light exposure, and behavior in field and epidemiological studies [4,5]. The most outstanding advantage of actimetry is that it enables continuous recordings, besides being a noninvasive and convenient method that does not interfere with the individuals' normal routine. ...
Study objectives
In field studies using wrist-actimetry, not identifying/handling off-wrist intervals may result in their misclassification as immobility/sleep and biased estimations of rhythmic patterns. By comparing different solutions for detecting off-wrist, our goal was to ascertain how accurately they detect nonwear in different contexts, and identify variables that are useful in the process.
Methods
We developed algorithms using heuristic (HA), and machine learning (ML) approaches. Both were tested using data from a protocol followed by 10 subjects, which was devised to mimic contexts of actimeter wear/nonwear in real-life. Self-reported data on usage according to the protocol was considered the gold standard. Additionally, the performance of our algorithms was compared to that of visual inspection (by 2 experienced investigators) and Choi algorithm. Data previously collected in field studies were used for proof-of-concept analyses.
Results
All methods showed similarly good performances. Accuracy was marginally higher for one of the raters (visual inspection) than for heuristically developed algorithms (HA, Choi). Short intervals (especially <2h) were either not or only poorly identified. Consecutive stretches of zeros in activity were considered important indicators of off-wrist (for both HA and ML). It took hours for raters to complete the task as opposed to the seconds or few minutes taken by the automated methods.
Conclusions
Automated strategies of off-wrist detection are similarly effective to visual inspection, but have the important advantage of being faster, less costly, and independent of raters’ attention/experience. In our study, detecting short intervals was a limitation across methods.
... This unexpected change led to an abrupt awareness of the danger and the consequent need to adapt to heavy restrictions imposed by each government, inevitably upsetting people's daily routines. Social isolation and development of mental disorders represent two of the main consequences derived from interruptions in the daily routine [5,6]. In this context, a viable solution to reduce isolation and facilitate daily interactional exchanges could be the use of technological devices acting as assistants. ...
The present study aims to explore user acceptance and perceptions toward different quality levels of synthetical voices. To achieve this, four voices have been exploited considering two main factors: the quality of the voices (low vs high) and their gender (male and female). 186 volunteers were recruited and subsequently allocated into four groups of different ages respec-tively, adolescents, young adults, middle-aged and seniors. After having randomly listened to each voice, participants were asked to fill the Virtual Agent Voice Acceptance Questionnaire (VAVAQ). Outcomes show that the two higher quality voices of Antonio and Giulia were more appreciated than the low-quality voices of Edoardo and Clara by the whole sample in terms of pragmatic, hedonic and attractiveness qualities attributed to the voices. Concerning preferences towards differently aged voices, it clearly appeared that they varied according to participants age' ranges examined. Furthermore, in terms of suitability to perform different tasks, participants considered Antonio and Giulia equally adapt for healthcare and front office jobs. Antonio was also judged to be significantly more qualified to accomplish protection and security tasks, while Edoardo was classified as the absolute least skilled in conducting household chores.
... Mood disorders are a group of mental disorders characterized by emotional imbalance, including major depressive disorder (MDD) and bipolar disorder (BD). In addition to emotional abnormalities, sleep abnormalities are also strongly associated with symptoms associated with mood disorders (Jackson et al., 2003;Lyall et al., 2018). Sleep disorder is a common complaint of patients with mood disorders, while paradoxical sleep deprivation (PSD) causes manic-like behavior in mice (Arent et al., 2015), induces mania in healthy subjects, and exacerbates manic episodes or lead to the transition from depression to mania in patients with bipolar disorder (Kaplan and Harvey, 2013). ...
The glymphatic system, a recently discovered macroscopic waste removal system in the brain, has many unknown aspects, especially its driving forces and relationship with sleep, and thus further explorations of the relationship between the glymphatic system and a variety of possible related diseases are urgently needed. Here, we focus on the progress in current research on the role of the glymphatic system in several common central nervous system diseases and mood disorders, discuss the structural and functional abnormalities of the glymphatic system which may occur before or during the pathophysiological progress and the possible underlying mechanisms. We emphasize the relationship between sleep and the glymphatic system under pathological conditions and summarize the common imaging techniques for the glymphatic system currently available. The perfection of the glymphatic system hypothesis and the exploration of the effects of aging and endocrine factors on the central and peripheral regulatory pathways through the glymphatic system still require exploration in the future.
... For example, genetic studies have characterized circadian activity rhythm and sleep pattern phenotypes in individuals with BD and suggested that these phenotypes show familial loading [33] and may be trait characteristics of BD. Other large-scale community cohort studies demonstrated associations between the amplitude and stability of circadian rhythms in BD [34]. Furthermore, systematic reviews and metaanalyses of cross-sectional studies of individuals with BD compared with healthy controls repeatedly suggest that circadian dysrhythmias are more common in patients, even in euthymia [16,35]. ...
Bipolar disorder (BD) is characterized by recurrent mood episodes. It is increasingly suggested that disturbances in sleep–wake cycles and/or circadian rhythms could represent valuable predictors of recurrence, but few studies have addressed this question. Euthymic individuals with BD (n = 69) undertook 3 weeks of actigraphy recording and were then followed up for a median duration of 3.5 years. Principal component analyses were used to identify core dimensions of sleep quantity/variability and circadian rhythmicity. Associations between clinical variables and actigraphy dimensions and time to first recurrence were explored using survival analyses, and then using area under the curve (AUC) analyses (early vs. late recurrence). Most participants (64%) experienced a recurrence during follow-up (median survival time: 18 months). After adjusting for potential confounding factors, an actigraphy dimension comprising amplitude and variability/stability of circadian rhythms was a significant predictor of time to recurrence (p = 0.009). The AUC for correct classification of early vs. late recurrence subgroups was only 0.64 for clinical predictors, but combining these variables with objectively measured intra-day variability improved the AUC to 0.82 (p = 0.04). Actigraphy estimates of circadian rhythms, particularly variability/stability and amplitude, may represent valid predictive markers of future BD recurrences and could be putative targets for future psychosocial interventions.
... Wrist actimetry. The rest-activity cycle is a core behavioral measure of the circadian system and often disturbed in depressed patients 34 . An actimeter is a body-worn device, which comprises an accelerometer and allows the measurement of physical activity over periods of days or weeks. ...
Bright light therapy is an effective treatment option for seasonal and non-seasonal affective disorders. However up to now, no study has investigated effects of dynamic bedroom lighting in hospitalized patients with major depression. A bedroom lighting system, which automatically delivered artificial dawn and dusk and blue-depleted nighttime lighting (DD-N lighting) was installed in a psychiatric ward. Patients with moderate to severe depression were randomly assigned to stay in bedrooms with the new lighting or standard lighting system. Patients wore wrist actimeters during the first two treatment weeks. Additionally, hospitalization duration and daily psychotropic medication were retrieved from patients’ medical charts. Data from thirty patients, recorded over a period of two weeks, were analyzed. Patients under DD-N lighting generally woke up earlier (+ 20 min), slept longer (week 1: + 11 min; week 2: + 27 min) and showed higher sleep efficiency (+ 2.4%) and shorter periods of nighttime awakenings (− 15 min). In the second treatment week, patients started sleep and the most active 10-h period earlier (− 33 min and − 64 min, respectively). This pilot study gives first evidence that depressed patients’ sleep and circadian rest/activity system may benefit from bedroom lighting when starting inpatient treatment.
... Our work follows this assumption as well, but it pushes these analyses one step further by studying the rhythms of activity on the phone throughout the whole day instead of only detecting the sleep hours. Previous studies have shown the importance of studying behavioral and activity rhythms 30 and how deviations from these rhythms could be an early sign of mental disorders 31 . It is therefore crucial to better understand the rhythms of sleep and activity. ...
Human activities follow daily, weekly, and seasonal rhythms. The emergence of these rhythms is related to physiology and natural cycles as well as social constructs. The human body and its biological functions undergo near 24-h rhythms (circadian rhythms). While their frequencies are similar across people, their phases differ. In the chronobiology literature, people are categorized into morning-type, evening-type, and intermediate-type groups called chronotypes based on their tendency to sleep at different times of day. Typically, this typology builds on carefully designed questionnaires or manually crafted features of time series data on people’s activity. Here, we introduce a method where time-stamped data from smartphones are decomposed into components using non-negative matrix factorization. The method does not require any predetermined assumptions about the typical times of sleep or activity: the results are fully context-dependent and determined by the most prominent features of the activity data. We demonstrate our method by applying it to a dataset of mobile phone screen usage logs of 400 university students, collected over a year. We find four emergent temporal components: morning activity, night activity, evening activity and activity at noon. Individual behavior can be reduced to weights on these four components. We do not observe any clear categories of people based on the weights, but individuals are rather placed on a continuous spectrum according to the timings of their phone activities. High weights for the morning and night components strongly correlate with sleep and wake-up times. Our work points towards a data-driven way of characterizing people based on their full daily and weekly rhythms of activity and behavior, instead of only focusing on the timing of their sleeping periods.
... Chronic disruption of the circadian rhythms is often found in people with shift working and traveling to a different time zone. Epidemiologic studies have revealed a robust relationship between shift workers and many types of diseases, all of which are highly associated with systemic inflammation (Knutsson, 2003;Lyall et al., 2018;Torquati et al., 2018). The mechanisms behind the development of systemic inflammatory diseases elicited by chronic circadian misalignment are associated with the dysregulation of the innate immune system such as the heightened release of proinflammatory cytokines in response to endotoxic shock by lipopolysaccharide (LPS) (Castanon-Cervantes et al., 2010). ...
The circadian rhythm is a biological system that creates daily variations of physiology and behavior with a 24-h cycle, which is precisely controlled by the molecular circadian clock. The circadian clock dominates temporal activity of physiological homeostasis at the molecular level, including endocrine secretion, metabolic, immune response, coupled with extrinsic environmental cues (e.g., light/dark cycles) and behavioral cues (e.g., sleep/wake cycles and feeding/fasting cycles). The other side of the clock is that the misaligned circadian rhythm contributes to the onset of a variety of diseases, such as cancer, metabolic diseases, and cardiovascular diseases, the acceleration of aging, and the development of systemic inflammation. The role played by macrophages is a key mediator between circadian disruption and systemic inflammation. At the molecular level, macrophage functions are under the direct control of the circadian clock, and thus the circadian misalignment remodels the phenotype of macrophages toward a 'killer' mode. Remarkably, the inflammatory macrophages induce systemic and chronic inflammation, leading to the development of inflammatory diseases and the dampened immune defensive machinery against infectious diseases such as COVID-19. Here, we discuss how the circadian clock regulates macrophage immune functions and provide the potential risk of misaligned circadian rhythms against inflammatory and infectious diseases.
Many chronic disease symptomatologies involve desynchronized sleep-wake cycles, indicative of disrupted biorhythms. This can be interrogated using body temperature rhythms, which are well-established biomarkers for circadian clock function. Here, we investigated the association of wrist temperature amplitudes with a future onset of disease in the UK Biobank one year after actigraphy. Among 425 disease conditions (range n = 200-6,728) compared to controls (range n = 62,107 − 91,134), a total of 73 (36.5%) disease phenotypes were significantly associated with decreased amplitudes of wrist temperature (Benjamini-Hochberg FDR q < 0.05) and 26 (13%) PheCODEs passed a more stringent significance level (Bonferroni-correction α < 0.05). Here, for example, a two-standard deviation (1.8° Celsius) lower wrist temperature amplitude corresponded to hazard ratios of 1.91 (1.58–2.31 95% CI) for NAFLD, 1.69 (1.53–1.88) for type 2 diabetes, 1.25 (1.14–1.37) for renal failure, 1.23 (1.17–1.3) for hypertension, and 1.22 (1.11–1.33) for pneumonia. A comprehensive phenome-wide atlas of the identified mappings has been made available at http://bioinf.itmat.upenn.edu/biorhythm_atlas/. These findings strongly suggest peripheral thermoregulation as a digital biomarker.
The present study aims to explore user’ acceptance and perceptions toward different quality levels of synthetical voices. To achieve this, four voices have been exploited considering two main factors: the quality of the voices (low vs high) and their gender (male and female). 186 volunteers were recruited and subsequently allocated into four groups of different ages respectively, adolescents, young adults, middle-aged and seniors. After having randomly listened to each voice, participants were asked to fill the Virtual Agent Voice Acceptance Questionnaire (VAVAQ). Outcomes show that the two higher quality voices of Antonio and Giulia were more appreciated than the low-quality voices of Edoardo and Clara by the whole sample in terms of pragmatic, hedonic and attractiveness qualities attributed to the voices. Concerning preferences towards differently aged voices, it clearly appeared that they varied according to participants age’ ranges examined. Furthermore, in terms of suitability to perform different tasks, participants considered Antonio and Giulia equally adapt for healthcare and front office jobs. Antonio was also judged to be significantly more qualified to accomplish protection and security tasks, while Edoardo was classified as the absolute least skilled in conducting household chores.
Non-standard working hours and their effects on health of workers in the electricity and gas industries attached to the occupational medicine centers located in Algiers
The need to study effects of non-standard working hours (HAT) on the health of workers in the electricity and gas industries is justified by the continuity of service required. The study focused on a random sample of 600 workers, the data was collected by a self-administered questionnaire, from the medical file and by analysis of work situations. Logistic and linear regressions included several individual factors of which pre-recruitment medical examination data.
The prevalence of HAT work is 69.17%, that of night work is 39.67%: night shift work (TPN) (27.5%) and night work on-call is (12.16%); that of weekend work (WE) is 42.16%, it is associated the most with night work. The prevalence of excessive daytime sleepiness (somnolence) is 8%, “often” sleep disorders (TSS) is 34.33%.
The rhythm including night shifts increased the risk of TSS (adjusted Odds ratio (ORa) = 2.31 [95% CI 1.24- 4.33], p=0.008) and Epworth score values (adjusted Coefficient ß (Coef. ßa)=2.18 3.42 ],p=0.0006). It also doubled the risk of work accidents and multiplied by 4.5 (ORa) the risk of incompatibility with family life, among other perceived effects. The prevalence of definite psychic symptomatology is 20.33% for the anxious and 13.5% for the depressed. HADS scores are increased by night work on-call.
The rhythm including adjusted daytime work and WE associated with frequent travel was the most anxiety-provoking.
The calculated prevalences: 11.66% for diabetes, 14.83% for hypertension, 23.17% for metabolic syndrome, and 9.83% for the high cardiovascular risk
The risk of hypertension was increased by the number of weekend days worked per year ≥ 25 (ORa= 2.06 [95% CI: 1.18 ; 3.57], p = 0.01).
Night shift work increased the risk of type 2 diabetes (ORA= 2.61[95%CI: 1.14; 5.95],p= 0.02),metabolic syndrome (ORa= 3.19 [1.67 ; 6.08],p= 0.0004) and the values of the age differences (Coef.ßa =3.13[95%CI: 1.21 ; 5.05],P= 0.001). It promoted weight gain and dyslipidemia.
Non standard-hours without night work also had demonstrated effects (overtime working hours).
Our results agree with data from the literature, but exposure to other constraints and occupational risks are important and effects can entangle.
In total, workers in HAT who have the highest occupational exposure to risks and the most morbidity compared to those in standard hours; as well as the night workers compared to day workers.
Keywords: non-standard hours, night shift work, night work on-call, weekend work, irregular hours. Overtime work.
The objective of this study was to evaluate the relationship between self-perceived rhythms measured using the Mood Rhythm Instrument for adolescents (MRhI-Y) and depressive and psychiatric symptoms measured with the Children’s Depressive Instrument (CDI) and the Strengths and Difficulties Questionnaire (SDQ). In this study, 186 adolescents were recruited in Rio Grande do Sul, Brazil. We performed a Spearman correlation analysis to evaluate the relationships between quantitative variables. All variables that had a statistically significant correlation were included in ANOVA multiple regression models. The dependent variables in the multiple regression analyses were CDI score and total and emotional scores on the SDQ. We found that only Cognitive self-perceived rhythmicity contributed significantly to the first multiple regression with CDI as the outcome variable. The second regression with SDQ Emotional score as the outcome variable showed that female sex, age, and self-perceived affective rhythmicity contributed significantly to the model. The third regression with SDQ total score as the outcome variable showed that chronotype, self-perceived cognitive symptoms, and affective rhythmicity contributed significantly to the model. In conclusion, we found that lower self-perceived rhythmicity in cognitive factors and higher self-perceived rhythmicity in affective factors were related to presence and intensity of psychiatric and depressive symptoms.
Hypertension (HTN) has been associated with a greater risk of affective disorders. Paradoxically, several studies have shown the opposite effect in which high blood pressure relates to less depressive symptoms and greater well-being. Here we dissolve this paradox and clarify the relationship between mental health, blood pressure and the development of HTN using the UK Biobank. In adjusted multiple linear regression models, we found that the presence of a HTN diagnosis was associated with impaired mental health (i.e. more depressive symptoms (N = 303,771; β = 0.043; 95% CI [0.039, 0.047]; p<0.001) and lower well-being scores (N = 129,876; β = -0.057; 95% CI [-0.064, -0.050]; p<0.001)) at baseline, whereas higher systolic blood pressure (SBP) was associated with fewer depressive symptoms (N = 303,771; β = -0.063; 95% CI [-0.067, -0.060]; p<0.001) and higher well-being scores (N = 129,876; β = 0.057; 95% CI [0.051, 0.063]; p<0.001). These effects persisted until follow-up (~10 years later). To explore a potential link between the mental health-blood pressure association and the development of HTN, we compared participants who were normotensive at baseline and developed HTN until follow-up with those who stayed normotensive. Notably, the adjusted model showed impaired mental health already at baseline in HTN developers (i.e., before HTN diagnosis; depressive symptoms: β = 0.060; 95% CI [0.045, 0.076]; p<0.001; well-being: β = -0.043; 95% CI [-0.068, -0.017]; p<0.001), indicating that people who develop HTN might require higher blood pressure levels for the same mental health outcomes as normotensives. In addition, the negative association between SBP and depressive symptoms at baseline was moderated by HTN development (β = -0.014; 95% CI [-0.026, -0.003]; p=0.015), suggesting that the negative relationship between mental health and blood pressure was accentuated in people developing HTN several years before receiving their HTN diagnosis. We further observed that higher SBP was associated with lower emotion-related brain activity from functional magnetic resonance imaging (fMRI; β = -0.032 95% CI [-0.045, -0.019]; p<0.001). This effect was also moderated by HTN diagnosis, suggesting an impact of SBP and HTN on the central nervous processing of emotions. Possible mechanisms are discussed, including regulatory baroreceptor circuits linking arterial blood pressure to neural processing of emotions. Overall, our results show an interrelation between mental health and blood pressure that may be involved in the development of HTN. In people who develop HTN, this relationship seems to be altered, such that higher blood pressure is required to sustain mental health, potentially offering a novel perspective for developing preventive and therapeutic measures.
Objectives
Sleep problems are a transdiagnostic feature of nearly all psychiatric conditions, and a strong risk factor for initial and recurrent episodes. However, people with severe mental ill health (SMI) are often excluded from general population surveys, and as such the extent and associates of poor sleep in this population are less well understood. This study explores sleep health in an SMI sample during the COVID-19 pandemic, using multiple regression to identify risk factors, including daily routine, wellbeing and demographics.
Methods
An existing cohort of people with an SMI diagnosis were sampled. Participants were invited to complete a self-report survey about their health and the impacts of COVID-19 and associated public health measures. Sleep duration, efficiency, and quality were measured using items from the Pittsburgh Sleep Quality Index (PSQI).
Results
Two hundred forty-nine adults (aged 21–84 years) completed the survey. Mean sleep duration and efficiency were similar to general population estimates, at 7 h 19 min and 78%, respectively. However, 43% reported “bad” sleep quality that was associated with being younger in age as well as disturbed routine and declined wellbeing. Indeed, 37% reported a disturbed routine during the pandemic.
Conclusions
High estimates of perceived poor sleep quality in the SMI population align with previous findings. Supporting people with SMI to maintain routine regularity may work to protect sleep quality and wellbeing. Future research should more closely examine sleep health in people with SMI, using accessible and scalable measures of objective and subjective sleep, examining longitudinal trends.
The daily alternation between sleep and wakefulness is one of the most dominant features of our lives and is a manifestation of the intrinsic 24 h rhythmicity underlying almost every aspect of our physiology. Circadian rhythms are generated by networks of molecular oscillators in the brain and peripheral tissues that interact with environmental and behavioural cycles to promote the occurrence of sleep during the environmental night. This alignment is often disturbed, however, by contemporary changes to our living environments, work or social schedules, patterns of light exposure, and biological factors, with consequences not only for sleep timing but also for our physical and mental health. Characterised by undesirable or irregular timing of sleep and wakefulness, in this Series paper we critically examine the existing categories of circadian rhythm sleep–wake disorders and the role of the circadian system in their development. We emphasise how not all disruption to daily rhythms is driven solely by an underlying circadian disturbance, and take a broader, dimensional approach to explore how circadian rhythms and sleep homoeostasis interact with behavioural and environmental factors. Very few high-quality epidemiological and intervention studies exist, and wider recognition and treatment of sleep timing disorders are currently hindered by a scarcity of accessible and objective tools for quantifying sleep and circadian physiology and environmental variables. We therefore assess emerging wearable technology, transcriptomics, and mathematical modelling approaches that promise to accelerate the integration of our knowledge in sleep and circadian science into improved human health.
In the supply chain, companies are increasingly relying on the combination of internal knowledge creation and external knowledge resources to form a new “open innovation” approach. How to govern inter-organizational relationships (IOR) is a key determinant of knowledge creation, which involves both formal contracts and relationship behaviors. Formal contracts determine the roles and obligations of partners in the exchange, and relationship behavior is generated by mutual benefit from the exchange of various resources. Moreover, when the knowledge creation process requires partners to exchange knowledge, supply chain technologies such as the Internet of Things (IoT) and cloud-computing based advanced communication services are key in promoting the partners’ willingness to communicate. Therefore, this study uses the governance mechanism of the supply chain as a theoretical framework, and proposes an innovative and complete research model to explore the factors that influence open innovation capability in supply chains. PLS is used to analyze 140 samples collected from 600 organizations, the response rate is 23.3%. This study finds that supply chain technology has a stronger effect than both of the IOR issues, contractual governance and relational governance, for the exchange of tacit knowledge and explicit knowledge. The findings improve our understanding on how governance mechanism and technology drive the knowledge creation process towards open innovation success in the context of supply chains.
Dendrobium officinale polysaccharide (DOP) has received an increasing amount of attention as it could alleviate AD-related cognitive impairment via the regulation of microglial activation. However, the modulatory mechanism of DOP on circadian rhythm disruption (CRD) and related cognitive impairment needs further investigation. In our study, the circadian rhythm disruption mice showed a deficit in recognition and spatial memory. DOP treatment reshaped the perturbation of gut microbiota caused by CRD, including up-regulated the abundance of Akkermansia and Alistipes, down-regulated the abundance of Clostridia. In addition, DOP restored histopathological changes, reduced inflammatory cells infiltration and strengthened mucosal integrity. Mechanistically, DOP ameliorated intestinal barrier dysfunction by up-regulating tight junction protein expression, which in turn improved the invasion of lipopolysaccharide to blood and brain. The change of these contributes to inhibiting the NF-κB activation and neuroinflammation, and thus attenuating hippocampus neuronal damage and the deposition of Aβ. Meanwhile, our results revealed that DOP could reverse the levels of metabolites derived related to cognitive function improvement, and these metabolites were closely associated with the key microbiota. Therefore, we speculated that DOP has the potential to provide neuroprotection against cognitive impairment by modulating the gut microbiota.
The interplay of environmental, social, and behavioral factors influencing human circadian phase in ecological conditions remains elusive. The Uruguayan national dance school END-SODRE operating in two shifts (morning: 8:30-12:30 and night: 20:00-24:00) allowed us to evaluate how social demands, chronotype, environmental light, physical activity, and sleep patterns affected individual circadian phase measured by the onset of the nocturnal increase of melatonin (DLMO) in a single study. The DLMO was 1.5h earlier in morning-shift dancers (n=7) compared to night-shift dancers (n=11). Sleep time and chronotype (only in night-shift dancers) were associated with the circadian phase. In training days, during each participant’s phase-advance and phase-delay time windows, light exposure was similar between morning and night-shift dancers and did not correlate with DLMO. In contrast, the time spent in moderate-vigorous physical activity during each participant’s phase-lag time window was higher in night-shift dancers than in morning-shift dancers and positively correlated with DLMO.
The circadian system is responsible for internal functions and regulation of the organism according to environmental cues (zeitgebers). Circadian rhythm dysregulation or chronodisruption has been associated with several diseases, from mental to autoimmune diseases, and with life quality change. Following this, some therapies have been developed to correct circadian misalignments, such as light therapy and chronobiotics. In this manuscript, we describe the circadian‐related diseases so far investigated, and studies reporting relevant data on this topic, evidencing this relationship, are included. Despite the actual limitations in published work, there is clear evidence of the correlation between circadian rhythm dysregulation and disease origin/development, and, in this way, clock‐related therapies emerge as great progress in the clinical field. Future improvements in such interventions can lead to the development of successful chronotherapy strategies, deeply contributing to enhanced therapeutic outcomes. Circadian rhythm dysregulation or chronodisruption has been associated with several diseases. Some therapies have been developed to correct circadian misalignments, such as light therapy and chronobiotics. Clock‐related therapies emerge as great progress in the clinical field and can lead to the development of successful chronotherapy strategies, contributing to enhanced therapeutic outcomes.
Background:
Cardiometabolic diseases (CMDs) including hypertension, coronary heart disease, diabetes and stroke, are always combined with each other, leading to cardiometabolic multimorbidity (CMM). Mood disorder was associated with onset of CMD. However, the impact of mood disorder on the transition from single CMD to CMM was poorly understood.
Methods:
A total of 95,351 participants with single CMD, with median age of 59 (range 40 to 71) years from UK Biobank were enrolled at baseline. Competing risk regression models were used to estimated hazard ratios (HRs) and 95 % confidence intervals (CIs) of association between mood disorder categories and progress from single CMD to CMM. Association of mood disorder with mortality, and life expectancy differences were also calculated by flexible parametric proportion-hazard models.
Results:
Relative associations were observed between mood disorder and the progress from first onset of CMD to CMM. Adjusted HRs for progress to CMM from those with comorbid CMD plus depression or bipolar were increased (depression: 1.23 [1.19 1.27]; bipolar: 1.47 [1.31 1.66]), compared with those with the sole CMD. Mood disorder also had impact on all-cause mortality (depression: 1.17 [1.10 1.24]; bipolar: 2.03 [1.74 2.32]) and reduced life expectancy estimates for those with single CMD.
Limitations:
This cohort primarily comprises White individuals. Covariates only measured at baseline and assumed unchanged during follow-up.
Conclusions:
Mood disorder conferred greater hazard on the CMM and mortality outcome. This study highlighted the importance of depression and bipolar in disease progression, from single CMD, to multimorbidity or mortality.
Although some research highlights the benefits of behavioral routines for individual functioning, other research indicates that routines can reflect an individual's inflexibility and lower well-being. Given conflicting accounts on the benefits of routine, research is needed to examine how routineness versus flexibility in health-related behaviors correspond to personality traits, health, and occupational outcomes. We adopt a nonlinear dynamical systems approach to understanding routine using automatically sensed health-related behaviors collected from 483 information workers over a roughly two-month period. We utilized multidimensional recurrence quantification analysis to derive a measure of health regularity (routineness) from measures of daily step count, sleep duration, and heart rate variability (which relates to stress). Participants also completed measures of personality, health, and job performance at the start of the study and for two months via Ecological Momentary Assessments. Greater regularity was associated with higher neuroticism, lower agreeableness, and greater interpersonal and organizational deviance. Importantly, these results were independent of overall levels of each health indicator in addition to demographics. It is often believed that routine is desirable, but the results suggest that associations with routineness are more nuanced, and wearable sensors can provide insights into beneficial health behaviors.
Mental health in UK Biobank: development, implementation and results from an online questionnaire completed by 157 366 participants – CORRIGENDUM - Volume 4 Issue 5 - Katrina A. S. Davis, Jonathan R. I. Coleman, Mark Adams, Naomi Allen, Gerome Breen, Breda Cullen, Chris Dickens, Elaine Fox, Nick Graham, Jo Holliday, Louise M. Howard, Ann John, William Lee, Rose McCabe, Andrew McIntosh, Robert Pearsall, Daniel J. Smith, Cathie Sudlow, Joey Ward, Stan Zammit, Matthew Hotopf
Background
Previous physical activity (PA) research in schizophrenia has relied largely upon self-report measures. However, the accuracy of this method is questionable. Obtaining accurate measurements, and determining what may influence PA levels in schizophrenia, is essential to understand physical inactivity in this population. This study examined differences in self-reported and objectively measured PA in people with schizophrenia and the general population using a large, population-based dataset from the UK Biobank.
Methods
Baseline data from the UK Biobank (2007–2010) were analyzed; including 1078 people with schizophrenia (54.19 ± 8.39 years; 55% male) and 450549 without (56.44 ± 8.11; 46% male). We compared self-reported PA with objectively measured accelerometry data in schizophrenia and comparison samples. We also examined correlations between self-report and objective measures.
Results
People with schizophrenia reported the same PA levels as those without, with no differences in low, moderate, or vigorous intensity activity. However, accelerometry data showed a large and statistically significant reduction of PA in schizophrenia; as people with schizophrenia, on average, engaged in less PA than 80% of the general population. Nonetheless, within the schizophrenia sample, total self-reported PA still held significant correlations with objective measures.
Conclusions
People with schizophrenia are significantly less active than the general population. However, self-report measures in epidemiological studies fail to capture the reduced activity levels in schizophrenia. This also has implications for self-report measures of other lifestyle factors which may contribute toward the poor health outcomes observed in schizophrenia. Nonetheless, self-report measures may still be useful for identifying how active individuals with schizophrenia relative to other patients.
BACKGROUND:
Physical activity has not been objectively measured in prospective cohorts with sufficiently large numbers to reliably detect associations with multiple health outcomes. Technological advances now make this possible. We describe the methods used to collect and analyse accelerometer measured physical activity in over 100,000 participants of the UK Biobank study, and report variation by age, sex, day, time of day, and season.
METHODS:
Participants were approached by email to wear a wrist-worn accelerometer for seven days that was posted to them. Physical activity information was extracted from 100Hz raw triaxial acceleration data after calibration, removal of gravity and sensor noise, and identification of wear / non-wear episodes. We report age- and sex-specific wear-time compliance and accelerometer measured physical activity, overall and by hour-of-day, week-weekend day and season.
RESULTS:
103,712 datasets were received (44.8% response), with a median wear-time of 6.9 days (IQR:6.5-7.0). 96,600 participants (93.3%) provided valid data for physical activity analyses. Vector magnitude, a proxy for overall physical activity, was 7.5% (2.35mg) lower per decade of age (Cohen's d = 0.9). Women had a higher vector magnitude than men, apart from those aged 45-54yrs. There were major differences in vector magnitude by time of day (d = 0.66). Vector magnitude differences between week and weekend days (d = 0.12 for men, d = 0.09 for women) and between seasons (d = 0.27 for men, d = 0.15 for women) were small.
CONCLUSIONS:
It is feasible to collect and analyse objective physical activity data in large studies. The summary measure of overall physical activity is lower in older participants and age-related differences in activity are most prominent in the afternoon and evening. This work lays the foundation for studies of physical activity and its health consequences. Our summary variables are part of the UK Biobank dataset and can be used by researchers as exposures, confounding factors or outcome variables in future analyses.
Obesity is a risk factor for a plethora of severe morbidities and premature death. Most supporting evidence comes from observational studies that are prone to chance, bias and confounding. Even data on the protective effects of weight loss from randomized controlled trials will be susceptible to confounding and bias if treatment assignment cannot be masked, which is usually the case with lifestyle and surgical interventions. Thus, whilst obesity is widely considered the major modifiable risk factor for many chronic diseases, its causes and consequences are often difficult to determine. Addressing this is important, as the prevention and treatment of any disease requires that interventions focus on causal risk factors. Disease prediction, although not dependent on knowing the causes, is nevertheless enhanced by such knowledge. Here, we provide an overview of some of the barriers to causal inference in obesity research and discuss analytical approaches, such as Mendelian randomization, that can help to overcome these obstacles. In a systematic review of the literature in this field, we found: (i) probable causal relationships between adiposity and bone health/disease, cancers (colorectal, lung and kidney cancers), cardiometabolic traits (blood pressure, fasting insulin, inflammatory markers and lipids), uric acid concentrations, coronary heart disease and venous thrombosis (in the presence of pulmonary embolism), (ii) possible causal relationships between adiposity and gray matter volume, depression and common mental disorders, oesophageal cancer, macroalbuminuria, end-stage renal disease, diabetic kidney disease, nuclear cataract and gall stone disease, and (iii) no evidence for causal relationships between adiposity and Alzheimer's disease, pancreatic cancer, venous thrombosis (in the absence of pulmonary embolism), liver function and periodontitis.
Sleep is important for optimal cognitive functioning across the lifespan. Among older adults (≥55 years), self-reported short and long sleep durations have been repeatedly, albeit inconsistently, reported to elevate the risk for poor cognitive function. This meta-analytic review quantitatively summarizes the risk for poorer cognitive function among short and long sleepers in older adults. Eligible publications were searched online and manually. A total of 35 independent samples (N = 97,264) from 11 cross-sectional and seven prospective cohort studies were included. Pooled odds ratios (OR) with 95% confidence intervals (CI) were derived using random-effects models. Self-reported short and long sleep increased the odds for poor cognitive function by 1.40 (CI = 1.27-1.56) and 1.58 times (CI = 1.43-1.74), respectively. Effect sizes varied across studies and may have been moderated by both study type (cross-sectional and prospective) and cognitive domain assessed. For cross-sectional studies, extreme sleep durations were significantly associated with poorer multiple-domain performance, executive functions, verbal memory, and working memory capacity. Prospective cohort studies revealed the significant long-term impact of short and long sleep on multiple-domain performance only. These findings establish self-reported extreme sleep duration as a risk factor for cognitive aging.
Cathie Sudlow and colleagues describe the UK Biobank, a large population-based prospective study, established to allow investigation of the genetic and non-genetic determinants of the diseases of middle and old age.
In this study, we sought to advance understanding of trait vulnerability to bipolar disorder (BD) by testing whether instability of the 24-hr activity rhythm was a biomarker of the trait. Locomotor activity was measured over 7 days using actigraphy in participants allocated to groups of high (n = 36) and low (n = 36) trait vulnerability for BD. As predicted, the high-vulnerability group recorded a significantly lower 24-hr activity rhythm amplitude than the low-vulnerability group, indicating a less stable activity pattern. Consistent with the notion of accumulating risk, results showed the lowest activity rhythm amplitudes in participants in the high-vulnerability group with a history of depression. Secondary investigations showed that mania proneness explained more variance than depression proneness, pointing to specificity of the findings for BD. The data reinforce claims that instability of daily rhythms is a biomarker of trait vulnerability to BD.
Considering the marked changes in sleep and circadian rhythms across the lifespan, age may contribute to the heterogeneity in sleep-wake profiles linked to mood disorders. This study aimed to investigate the contributions of age and depression severity to sleep-wake disturbances. The Hamilton Depression Rating Scale (HDRS) was administered to assess current symptoms severity in 238 persons with a history of a mood disorder between 12 and 90 years of age (y.o.). Actigraphy was recorded over five to 22 days. Regression analyses and analyses of variance [age (12-19 y.o., 20-39 y.o., 40-59 y.o., and ≥60 y.o.) by depression severity (HDRS< and ≥8)] were conducted. The 12-19 y.o. and 20-39 y.o. groups had a delayed sleep schedule and acrophase compared to all other groups. The ≥60 y.o. group had a lower rhythmicity and amplitude (p≤.006) than the 12-19 y.o. group (p≤.046). Participants with a HDRS≥8 spent longer time in bed, had later sleep offset times and had lower circadian rhythmicity than those with a HDRS<8 (p≤.036). Younger age and higher HDRS score correlated with later sleep onset and offset times, longer time in bed, higher WASO, lower sleep efficiency and later acrophase (p≤.023). Age was a significant predictor of delayed sleep and activity schedules (p≤.001). The profile of sleep-wake cycle disturbances associated with mood disorders changes with age, with prominent sleep phase delay during youth and reduced circadian strength in older persons. Conversely, disruptions in sleep consolidation seem more stable across age.
White matter (WM) change plays an important role in age-related cognitive decline. In this review, we consider methodological advances with particular relevance to the role of WM in age-related changes in processing speed. In this context, intra-individual variability in processing speed performance has emerged as a sensitive proxy of cognitive and neurological decline while neuroimaging techniques used to assess WM change have become increasingly more sensitive. Together with a carefully designed task protocol, we emphasize that the combined implementation of intra-individual variability and neuroimaging techniques hold promise for specifying the WM-processing speed relationship with implications for normative and clinical samples. (JINS, 2014, 20, 1-6).
This study assessed daily rest-activity patterns in euthymic, medication-naïve bipolar phenotype individuals. The Mood Disorder Questionnaire was used to identify 19 bipolar phenotype individuals and 21 controls. Participants wore an Actiwatch-L for 2 weeks to assess their sleep behaviour and circadian rest-activity rhythmicity. Bipolar phenotype individuals had increased movement during sleep, as assessed by the fragmentation index, greater activity levels during their least active 5 h (2 am-7 am), and lower circadian relative amplitude compared to controls. Higher activity levels during sleep affecting circadian amplitude in young adults with the bipolar phenotype may be associated with vulnerability for developing mood disorder.
UK Biobank is a landmark cohort of over 500,000 participants which will be used to investigate genetic and non-genetic risk factors for a wide range of adverse health outcomes. This is the first study to systematically assess the prevalence and validity of proposed criteria for probable mood disorders within the cohort (major depression and bipolar disorder).
This was a descriptive epidemiological study of 172,751 individuals assessed for a lifetime history of mood disorder in relation to a range of demographic, social, lifestyle, personality and health-related factors. The main outcomes were prevalence of a probable lifetime (single) episode of major depression, probable recurrent major depressive disorder (moderate), probable recurrent major depressive disorder (severe), probable bipolar disorder and no history of mood disorder (comparison group). Outcomes were compared on age, gender, ethnicity, socioeconomic status, educational attainment, functioning, self-reported health status, current depressive symptoms, neuroticism score, smoking status and alcohol use.
Prevalence rates for probable single lifetime episode of major depression (6.4%), probable recurrent major depression (moderate) (12.2%), probable recurrent major depression (severe) (7.2%) and probable bipolar disorder (1.3%) were comparable to those found in other population studies. The proposed diagnostic criteria have promising validity, with a gradient in evidence from no mood disorder through major depression and probable bipolar disorder in terms of gender distribution, socioeconomic status, self-reported health rating, current depressive symptoms and smoking.
The validity of our proposed criteria for probable major depression and probable bipolar disorder within this cohort are supported by these cross-sectional analyses. Our findings are likely to prove useful as a framework for a wide range of future genetic and non-genetic studies.
Circadian clocks are endogenous oscillators driving daily rhythms in physiology and behavior. Synchronization of these timers to environmental light-dark cycles ('entrainment') is crucial for an organism's fitness. Little is known about which oscillator qualities determine entrainment, i.e., entrainment range, phase and amplitude. In a systematic theoretical and experimental study, we uncovered these qualities for circadian oscillators in the suprachiasmatic nucleus (SCN-the master clock in mammals) and the lung (a peripheral clock): (i) the ratio between stimulus (zeitgeber) strength and oscillator amplitude and (ii) the rigidity of the oscillatory system (relaxation rate upon perturbation) determine entrainment properties. Coupling among oscillators affects both qualities resulting in increased amplitude and rigidity. These principles explain our experimental findings that lung clocks entrain to extreme zeitgeber cycles, whereas SCN clocks do not. We confirmed our theoretical predictions by showing that pharmacological inhibition of coupling in the SCN leads to larger ranges of entrainment. These differences between master and the peripheral clocks suggest that coupling-induced rigidity in the SCN filters environmental noise to create a robust circadian system. Molecular Systems Biology 6: 438; published online 30 November 2010; doi:10.1038/msb.2010.92
A substantial amount of research has been conducted in an effort to understand the impact of short-term (<48 hr) total sleep deprivation (SD) on outcomes in various cognitive domains. Despite this wealth of information, there has been disagreement on how these data should be interpreted, arising in part because the relative magnitude of effect sizes in these domains is not known. To address this question, we conducted a meta-analysis to discover the effects of short-term SD on both speed and accuracy measures in 6 cognitive categories: simple attention, complex attention, working memory, processing speed, short-term memory, and reasoning. Seventy articles containing 147 cognitive tests were found that met inclusion criteria for this study. Effect sizes ranged from small and nonsignificant (reasoning accuracy: g = -0.125, 95% CI [-0.27, 0.02]) to large (lapses in simple attention: g = -0.776, 95% CI [-0.96, -0.60], p < .001). Across cognitive domains, significant differences were observed for both speed and accuracy; however, there were no differences between speed and accuracy measures within each cognitive domain. Of several moderators tested, only time awake was a significant predictor of between-studies variability, and only for accuracy measures, suggesting that heterogeneity in test characteristics may account for a significant amount of the remaining between-studies variance. The theoretical implications of these findings for the study of SD and cognition are discussed.
The UK Biobank project is a large prospective cohort study of ~500,000 individuals from across the United Kingdom, aged between 40-69 at recruitment. A rich variety of phenotypic and health-related information is available on each participant, making the resource unprecedented in its size and scope. Here we describe the genome-wide genotype data (~805,000 markers) collected on all individuals in the cohort and its quality control procedures. Genotype data on this scale offers novel opportunities for assessing quality issues, although the wide range of ancestries of the individuals in the cohort also creates particular challenges. We also conducted a set of analyses that reveal properties of the genetic data – such as population structure and relatedness – that can be important for downstream analyses. In addition, we phased and imputed genotypes into the dataset, using computationally efficient methods combined with the Haplotype Reference Consortium (HRC) and UK10K haplotype resource. This increases the number of testable variants by over 100-fold to ~96 million variants. We also imputed classical allelic variation at 11 human leukocyte antigen (HLA) genes, and as a quality control check of this imputation, we replicate signals of known associations between HLA alleles and many common diseases. We describe tools that allow efficient genome-wide association studies (GWAS) of multiple traits and fast phenome-wide association studies (PheWAS), which work together with a new compressed file format that has been used to distribute the dataset. As a further check of the genotyped and imputed datasets, we performed a test-case genome-wide association scan on a well-studied human trait, standing height.
Prediction models are developed to aid health care providers in estimating the probability or risk that a specific disease or condition is present (diagnostic models) or that a specific event will occur in the future (prognostic models), to inform their decision making. However, the overwhelming evidence shows that the quality of reporting of prediction model studies is poor. Only with full and clear reporting of information on all aspects of a prediction model can risk of bias and potential usefulness of prediction models be adequately assessed. The Transparent Reporting of a multivariable prediction model for Individual Prognosis or Diagnosis (TRIPOD) Initiative developed a set of recommendations for the reporting of studies developing, validating, or updating a prediction model, whether for diagnostic or prognostic purposes. This article describes how the TRIPOD Statement was developed. An extensive list of items based on a review of the literature was created, which was reduced after a Web-based survey and revised during a 3-day meeting in June 2011 with methodologists, health care professionals, and journal editors. The list was refined during several meetings of the steering group and in e-mail discussions with the wider group of TRIPOD contributors. The resulting TRIPOD Statement is a checklist of 22 items, deemed essential for transparent reporting of a prediction model study. The TRIPOD Statement aims to improve the transparency of the reporting of a prediction model study regardless of the study methods used. The TRIPOD Statement is best used in conjunction with the TRIPOD explanation and elaboration document. To aid the editorial process and readers of prediction model studies, it is recommended that authors include a completed checklist in their submission (also available at www.tripod-statement.org).
© 2015 Royal College of Obstetricians and Gynaecologists.
Widening inequality in the distribution of resources, higher rates of unemployment and deteriorating conditions in the inner cities have concentrated attention in Britain, and elsewhere in Europe, upon the idea and exact meaning of ‘deprivation’. This scientific concept is used extensively not only in the analysis of social conditions but also, in an applied form, as an instrument of policy in allocating resources to particular regions, areas and services. This paper argues that the indicators which are chosen to represent the phenomenon are often unduly restricted and even involve double counting. As a result the distribution and severity of deprivation seems to be seriously misperceived and resources misallocated. A review of the available studies shows how the concept might be treated more coherently in relation to that of poverty.
Objectives:
Aging is associated with changes in circadian rhythms. Current evidence supports a role for circadian rhythms in the pathophysiology of depression. However, little is known about the relationship between depressive symptoms and circadian activity rhythms in older adults. We examined this association in community-dwelling older women.
Methods:
We performed a cross-sectional analysis of 3,020 women (mean age: 83.55 ± 3.79 years) enrolled in the Study of Osteoporotic Fractures. Depressive symptoms were assessed with the Geriatric Depression Scale categorizing participants as "normal" (0-2; referent group, N = 1,961), "some depressive symptoms" (3-5, N = 704), or "depressed" (≥6, N = 355). Circadian activity rhythm variables were measured using wrist actigraphy.
Results:
In age-adjusted and Study of Osteoporotic Fractures site-adjusted models, greater levels of depressive symptoms were associated with decreased amplitude (height; df = 3,014, t = -11.31, p for linear trend <0.001), pseudo F-statistic (robustness; df = 3,014, t = -8.07, p for linear trend <0.001), and mesor (mean modeled activity; df = 3014, t = -10.36, p for linear trend <0.001) of circadian activity rhythms. Greater levels of depressive symptoms were also associated with increased odds of being in the lowest quartile for amplitude (df = 1, χ(2) = 9240, p for linear trend <0.001), pseudo F-statistic (df = 1, χ(2) = 49.73, p for linear trend <0.001), and mesor (df = 1, χ(2) = 81.12, p for linear trend <0.001). These associations remained significant in multivariate models. Post-hoc analyses comparing mean amplitude, mesor, and pseudo F-statistic values pair-wise between depression-level groups revealed significant differences between women with "some depressive symptoms" and the "normal" group.
Conclusion:
These data suggest a graded association between greater levels of depressive symptoms and more desynchronization of circadian activity rhythms in community-dwelling older women. This association was observed even for women endorsing subthreshold levels of depressive symptoms.
Data are reported on a series of short-form (SF) screening scales of DSM-III-R psychiatric disorders developed from the World Health Organization's Composite International Diagnostic Interview (CIDI). A multi-step procedure was used to generate CIDI-SF screening scales for each of eight DSM disorders from the US National Comorbidity Survey (NCS). This procedure began with the subsample of respondents who endorsed the CIDI diagnostic stem question for a given disorder and then used a series of stepwise regression analyses to select a subset of screening questions to maximize reproduction of the full CIDI diagnosis. A small number of screening questions, between three and eight for each disorder, was found to account for the significant associations between symptom ratings and CIDI diagnoses. Summary scales made up of these symptom questions correctly classify between 77% and 100% of CIDI cases and between 94% and 99% of CIDI non-cases in the NCS depending on the diagnosis. Overall classification accuracy ranged from a low of 93% for major depressive episode to a high of over 99% for generalized anxiety disorder. Pilot testing in a nationally representative telephone survey found that the full set of CIDI-SF scales can be administered in an average of seven minutes compared to over an hour for the full CIDI. The results are quite encouraging in suggesting that diagnostic classifications made in the full CIDI can be reproduced with excellent accuracy with the CIDI-SF scales. Independent verification of this reproduction accuracy, however, is needed in a data set other than the one in which the CIDI-SF was developed. Copyright © 1998 Whurr Publishers Ltd.
Previous studies showed circadian rhythm disturbances in patients with Alzheimer's disease. Rest-activity rhythm disturbances manifest themselves through a fragmentation of the rhythm, a weak coupling with Zeitgebers, and high levels of activity during the night. The aim of the present study was to investigate which factors contribute to the presence of these disturbances. Therefore, several rest-activity rhythm, constitutional, and environmental variables were assessed in a heterogeneous group of 34 patients with Alzheimer's disease, including presenile and senile patients living at home or in a nursing home, as well as in 11 healthy controls. Circadian rest-activity rhythm disturbances were most prominent in institutionalized patients. Regression analyses showed the involvement of the following variables. First stability of the rest-activity rhythm is associated with high levels of daytime activity and high levels of environmental light resulting from seasonal effects as well as from indoor illumination. Presenile onset contributed to instability of the rhythm. Second, fragmentation of periods of activity and rest is associated with low levels of daytime activity, and is most prominent in moderately severe dementia. Third, night-time activity level is higher during the times of the year when the days are getting shorter and lower when the days are growing longer. These findings indicate that rest-activity rhythm disturbances may improve by increasing environmental light and daytime activity, an assumption for which empirical evidence has recently been published.
Several recent studies have found associations between childhood maltreatment and adverse adult health outcomes. However, methodologic problems with accurate case determination, appropriate sample selection, and predominant focus on sexual abuse have limited the generalizability of these findings.
We administered a survey to 1,225 women who were randomly selected from the membership of a large, staff model health maintenance organization in Seattle, Washington. We compared women with and without histories of childhood maltreatment experiences with respect to differences in physical health status, functional disability, numbers and types of self-reported health risk behaviors, common physical symptoms, and physician-coded ICD-9 diagnoses.
A history of childhood maltreatment was significantly associated with several adverse physical health outcomes. Maltreatment status was associated with perceived poorer overall health (ES = 0.31), greater physical (ES = 0.23) and emotional (ES = 0.37) functional disability, increased numbers of distressing physical symptoms (ES = 0.52), and a greater number of health risk behaviors (ES = 0.34). Women with multiple types of maltreatment showed the greatest health decrements for both self-reported symptoms (r = 0.31) and physician coded diagnoses (r = 0.12).
Women with childhood maltreatment have a wide range of adverse physical health outcomes.
The goal of this study was to develop and validate a short form of the Childhood Trauma Questionnaire (the CTQ-SF) as a screening measure for maltreatment histories in both clinical and nonreferred groups.
Exploratory and confirmatory factor analyses of the 70 original CTQ items were used to create a 28-item version of the scale (25 clinical items and three validity items) and test the measurement invariance of the 25 clinical items across four samples: 378 adult substance abusing patients from New York City, 396 adolescent psychiatric inpatients, 625 substance abusing individuals from southwest Texas, and 579 individuals from a normative community sample (combined N=1978).
Results showed that the CTQ-SF's items held essentially the same meaning across all four samples (i.e., measurement invariance). Moreover, the scale demonstrated good criterion-related validity in a subsample of adolescents on whom corroborative data were available.
These findings support the viability of the CTQ-SF across diverse clinical and nonreferred populations.
Little is known about lifetime prevalence or age of onset of DSM-IV disorders.
To estimate lifetime prevalence and age-of-onset distributions of DSM-IV disorders in the recently completed National Comorbidity Survey Replication.
Nationally representative face-to-face household survey conducted between February 2001 and April 2003 using the fully structured World Health Organization World Mental Health Survey version of the Composite International Diagnostic Interview.
Nine thousand two hundred eighty-two English-speaking respondents aged 18 years and older.
Lifetime DSM-IV anxiety, mood, impulse-control, and substance use disorders.
Lifetime prevalence estimates are as follows: anxiety disorders, 28.8%; mood disorders, 20.8%; impulse-control disorders, 24.8%; substance use disorders, 14.6%; any disorder, 46.4%. Median age of onset is much earlier for anxiety (11 years) and impulse-control (11 years) disorders than for substance use (20 years) and mood (30 years) disorders. Half of all lifetime cases start by age 14 years and three fourths by age 24 years. Later onsets are mostly of comorbid conditions, with estimated lifetime risk of any disorder at age 75 years (50.8%) only slightly higher than observed lifetime prevalence (46.4%). Lifetime prevalence estimates are higher in recent cohorts than in earlier cohorts and have fairly stable intercohort differences across the life course that vary in substantively plausible ways among sociodemographic subgroups.
About half of Americans will meet the criteria for a DSM-IV disorder sometime in their life, with first onset usually in childhood or adolescence. Interventions aimed at prevention or early treatment need to focus on youth.
Sleep/wake timing shifts later in young humans during the second decade of life. In this review we describe sleep/wake patterns, changes in these patterns across adolescence, and evidence for the role of environmental, psychosocial, and biological factors underlying these changes. A two-process model incorporating circadian (Process C) and sleep/wake homeostatic (Process S) components is outlined. This model may help us to understand how developmental changes translate to shifted sleep/wake patterns. Delayed sleep phase syndrome (DSPS), which has a typical onset during the second decade of life, may be an extreme manifestation of homeostatic and circadian changes in adolescence. We describe symptoms, prevalence, and possible etiology of DSPS, as well as treatment approaches in adolescents.
A quarter of the world's population is subjected to a 1 hr time change twice a year (daylight saving time, DST). This reflects a change in social clocks, not environmental ones (e.g., dawn). The impact of DST is poorly understood. Circadian clocks use daylight to synchronize (entrain) to the organism's environment. Entrainment is so exact that humans adjust to the east-west progression of dawn within a given time zone. In a large survey (n = 55,000), we show that the timing of sleep on free days follows the seasonal progression of dawn under standard time, but not under DST. In a second study, we analyzed the timing of sleep and activity for 8 weeks around each DST transition in 50 subjects who were chronotyped (analyzed for their individual phase of entrainment). Both parameters readily adjust to the release from DST in autumn but the timing of activity does not adjust to the DST imposition in spring, especially in late chronotypes. Our data indicate that the human circadian system does not adjust to DST and that its seasonal adaptation to the changing photoperiods is disrupted by the introduction of summer time. This disruption may extend to other aspects of seasonal biology in humans.
Circadian genes, rhythms and the biology of mood disorders
- C A Mcclung
Mcclung CA. Circadian genes, rhythms and the biology of mood
disorders. Pharmacol Ther 2007; 114: 222-32.
Sleep-wake disturbance in interepisode bipolar disorder and high-risk individuals: a systematic review and meta-analysis
- T H Ng
- K F Chung
- Fyy Ho
- W F Yeung
- K P Yung
- T H Lam
Ng TH, Chung KF, Ho FYY, Yeung WF, Yung KP, Lam TH.
Sleep-wake disturbance in interepisode bipolar disorder and
high-risk individuals: a systematic review and meta-analysis.
Sleep Med Rev 2015; 20: 46-58.
Cognitive processing speed and the structure of white matter pathways: convergent evidence from normal variation and lesion studies
- A U Turken
- S Whitfield-Gabrieli
- R Bammer
- J V Baldo
- N F Dronkers
- Jde Gabrieli
Turken AU, Whitfield-Gabrieli S, Bammer R, Baldo JV,
Dronkers NF, Gabrieli JDE. Cognitive processing speed and the
structure of white matter pathways: convergent evidence from
normal variation and lesion studies. Neuroimage 2008; 42: 1032-44.
Association of disrupted circadian rhythmicity with mood disorders, subjective wellbeing, and cognitive function: a cross-sectional study of 91 105 participants from the UK Biobank
- L M Lyall
- C A Wyse
- N Graham
Lyall LM, Wyse CA, Graham N, et al. Association of disrupted circadian
rhythmicity with mood disorders, subjective wellbeing, and cognitive
function: a cross-sectional study of 91 105 participants from the UK Biobank.
Lancet Psychiatry 2018; published online May 15. http://dx.doi.org/10.1016/
S2215-0366(18)30139-1.
GWAS identifies 10 loci for objectively-measured physical activity and sleep with causal roles in cardiometabolic disease
- A Doherty
- K Smith-Bryne
- T Ferreira
Doherty A, Smith-Bryne K, Ferreira T, et al. GWAS identifies 10 loci for
objectively-measured physical activity and sleep with causal roles in
cardiometabolic disease. bioRxiv 2018; published online Feb 8. DOI:10.1101/
261719 (preprint).
Genome sequencing of first 50,000 UK Biobank participants