The effects of self-selected light-dark cycles and social constraints on human sleep and circadian timing: a modeling approach

The adolescent circadian clock entrains to social time rather than sun time

The circadian timing of sleep is an important determinant of performance and health. There are opposing viewpoints, however, on whether light entrainment of the human circadian clock is mediated primarily by social time or solar time. Here, we provide evidence that adolescents' circadian clock entrains to their behavioral light-dark cycle determined by social demands. The circadian timing of sleep was compared between school and holiday periods in adolescents (n = 112) whose sleep was either constrained or unconstrained by early school start times. The circadian rhythm of melatonin (dim-light melatonin onset [DLMO]) closely tracked adolescents' earlier and shorter actigraphy-determined sleep pattern during the school week. The phase of entrainment from DLMO to sleep (darkness) midpoint was the same between holiday and school periods. As a consequence of obtaining short sleep on school nights, however, adolescents went to sleep later and woke up earlier relative to their melatonin onset. Hence, adolescents were "biologically ready" to go to bed earlier, and they likely woke up closer to the circadian minimum of alertness compared with their holiday sleep. Our results suggest that, in modern society, social constraints on sleep and associated light exposure (natural sunlight and electrical light) play an important role in entraining the circadian clock. Key strategies that may improve the duration and circadian timing of sleep in adolescents include advancing bedtimes, stabilizing sleep across weekdays and weekends, and delaying wake-up times by starting school later.

Validation of the Caen Chronotype Questionnaire: Exploring the added value of amplitude and correlations with actigraphy

Chronotype self-report instruments are time and cost-efficient measures to profile diurnal or time-of-day preferences. The Caen Chronotype Questionnaire (CCQ) captures morningness and eveningness (CCQ-ME) and a circadian amplitude dimension for diurnal variation (distinctiveness; CCQ-DI). This study extends prior multilanguage validations for the English version of the CCQ. In total, 628 participants enrolled from a UK working population (mean age 30.34 ± 8.36 years, 61.3% female) including a subset of shift workers (n = 179; mean age 27.62 ± 5.95 years, 49.2% female). A subsample of participants also wore a consumer-grade actigraph device (Fitbit Charge 4) for seven days to compare chronotype estimates with objective sleep-wake parameters (n = 22; mean age 27.05 ± 3.99 years, 81.8% female, 90.9% worked standard daytime schedules, and 9.1% worked rotating shifts). All participants completed online chronotype measures, including the CCQ and Morningness-Eveningness Questionnaire (MEQ), depressive symptoms (Patient Health Questionnaire; PHQ-9), sleep quality (Pittsburgh Sleep Quality Index; PSQI), and other outcome measures. Results from the Confirmatory Factor Analysis (CFA) offer support for a two-factor structure of the CCQ in an English-speaking sample, highlighting how individual preferences for the timing of activities is associated with chronotype (morningness-eveningness; ME) and a second subjective amplitude dimension (DI). However, in contrast with the original CCQ structure, a more parsimonious solution and best overall fit involved the reduction of the original 16-item questionnaire (8 items per factor) to 4 ME items and 5 DI items. Convergent validity with the reduced CCQ scale (rME) and the MEQ was also established. The CCQ was sensitive in discriminating differences in actigraphic sleep-wake timings between morning-and evening-oriented individuals. Regression models demonstrated that amplitude (CCQ-DI) was a significant predictor explaining most of the variance in depressive symptoms (PHQ-9) compared to other variables. Overall, the English version of the CCQ was shown to be a robust tool in estimating chronotype in a sample of adults based in the UK.

Assessing the best hour to start the day: an appraisal of seasonal daylight saving time

We provide an evidence-based position on the seasonal regulation of clocks daylight saving time (DST) that challenges position papers by sleep associations against the practice. We review the acute, short-term impact and the chronic, long-term impact of DST in the context of the changing ambient light conditions that characterize seasons at Extratropical latitudes. We highlight the association between DST, human physiology (photoreceptive mechanisms) and human daily life. We offer a perspective on the possible scenarios should clock regulations be abandoned.

Examining sex differences in morningness-eveningness and inter-individual variability across years of age: A cross-sectional study

This study investigated the impact of age on morningness-eveningness (ME) and its inter-individual variability, with a focus on sex-specific patterns. A sample of 2890 participants aged 12-94 years (55.85% female) completed the Composite Scale of Morningness. Multiple linear regression analyses revealed a significant Age × Sex interaction, indicating distinct age-dependent patterns for males and females in both ME and its inter-individual variability. We conducted segmented regression analyses to explore these dynamics further and identify breakpoints. Eveningness increased across adolescence, with both males and females reaching peak lateness at 20 years. Morningness increased thereafter until 64.94 years for females and until 59 years for males. Following these sex-specific breakpoints, morningness remained constant for females and increased at a reduced rate for males. After the age of 48, males exhibited greater morningness than females. Inter-individual variability in ME (VME) changed with age, increasing until 33 years for men and 36.80 years for women, followed by a decrease for both sexes. From 50.30 years onward, females showed greater VME compared to men. This study suggests that ME and VME shift across age, and differences between sexes were observed from middle age onwards. Diurnal preferences are likely influenced by internal and environmental variables.

A systematic and meta-analytic review of the impact of sleep restriction on memory formation

Modern life causes a quarter of adults and half of teenagers to sleep for less than is recommended (Kocevska et al., 2021). Given well-documented benefits of sleep on memory, we must understand the cognitive costs of short sleep. We analysed 125 sleep restriction effect sizes from 39 reports involving 1234 participants. Restricting sleep (3-6.5 hours) compared to normal sleep (7-11 hours) negatively affects memory formation with a small effect size (Hedges' g = 0.29, 95 % CI = [0.13, 0.44]). We detected no evidence for publication bias. When sleep restriction effect sizes were compared with 185 sleep deprivation effect sizes (Newbury et al., 2021) no statistically significant difference was found, suggesting that missing some sleep has similar consequences for memory as not sleeping at all. When the analysis was restricted to post-encoding, rather than pre-encoding, sleep loss, sleep deprivation was associated with larger memory impairment than restriction. Our findings are best accounted for by the sequential hypothesis which emphasises complementary roles of slow-wave sleep and REM sleep for memory.

Mapping the physiological changes in sleep regulation across infancy and young childhood

Sleep patterns in infancy and early childhood vary greatly and change rapidly during development. In adults, sleep patterns are regulated by interactions between neuronal populations in the brainstem and hypothalamus, driven by the circadian and sleep homeostatic processes. However, the neurophysiological mechanisms underlying the sleep patterns and their variations across infancy and early childhood are poorly understood. We investigated whether a well-established mathematical model for sleep regulation in adults can model infant sleep characteristics and explain the physiological basis for developmental changes. By fitting longitudinal sleep data spanning 2 to 540 days after birth, we inferred parameter trajectories across age. We found that the developmental changes in sleep patterns are consistent with a faster accumulation and faster clearance of sleep homeostatic pressure in infancy and a weaker circadian rhythm in early infancy. We also find greater sensitivity to phase-delaying effects of light in infancy and early childhood. These findings reveal fundamental mechanisms that regulate sleep in infancy and early childhood. Given the critical role of sleep in healthy neurodevelopment, this framework could be used to pinpoint pathophysiological mechanisms and identify ways to improve sleep quality in early life.

The organization of sleep-wake patterns around daily schedules in college students

The amount of time available in a day is fixed, and consequently, sleep is often sacrificed for waking activities. For college students, daily activities, comprised of scheduled classes, work, study, social, and other extracurricular events, are major contributors to insufficient and poor-quality sleep. We investigated the impact of daily schedules on sleep-wake timing in 223 undergraduate students (age: 18-27 years, 37% females) from a United States university, who were monitored for ~30 days. Sleep-wake timing and daily recorded activities (attendance at academic, studying, exercise-based, and/or extracurricular activities) were captured by a twice-daily internet-based diary. Wrist-worn actigraphy was conducted to confirm sleep-wake timing. Linear mixed models were used to quantify associations between daily schedule and sleep-wake timing at between-person and within-person levels. Later scheduled start time predicted later sleep onset (between and within: p < .001), longer sleep duration on the previous night (within: p < .001), and later wake time (between and within: p < .001). Later schedule end time predicted later sleep onset (within: p < .001) and shorter sleep duration that night (within: p < .001). For every 1 hour that activities extended beyond 10 pm, sleep onset was delayed by 15 minutes at the within-person level and 40 minutes at the between-person level, and sleep duration was shortened by 6 and 23 minutes, respectively. Increased daily documented total activity time predicted earlier wake (between and within: p < .001), later sleep onset that night (within: p < .05), and shorter sleep duration (within: p < .001). These results indicate that daily schedules are an important factor in sleep timing and duration in college students. Clinical Trial: Multi-scale Modeling of Sleep Behaviors in Social Networks; URL: https://clinicaltrials.gov/study/NCT02846077; Registration:NCT02846077.

Improving adjustment to daylight saving time transitions with light

Daylight saving time (DST) is currently utilized in many countries with the rationale that it enhances the alignment between daylight hours and activity peaks in the population. The act of transitioning into and out of DST introduces disruptions to the circadian rhythm, thereby impacting sleep and overall health. Despite the substantial number of individuals affected, the consequences of this circadian disruption have often been overlooked. Here, we employ a mathematical model of the human circadian pacemaker to elucidate how the biological clock interacts with daytime and evening exposures to both natural and electrical light. This interaction plays a crucial role in determining the adaptation to the 1 hour time zone shift imposed by the transition to or from DST. In global discussions about DST, there is a prevailing assumption that individuals easily adjust to DST transitions despite a few studies indicating that the human circadian system requires several days to fully adjust to a DST transition. Our study highlights that evening light exposure changes can be the main driving force for re-entrainment, with chronobiological models predicting that people with longer intrinsic period (i.e. later chronotype) entrain more slowly to transitions to or from DST as compared to people with a shorter intrinsic period (earlier chronotype). Moreover, the model forecasts large inter-individual differences in the adaptation speed, in particular during the spring transition. The predictions derived from our model offer circadian biology-based recommendations for light exposure strategies that facilitate a more rapid adaptation to DST-related transitions or travel across a single time zone. As such, our study contributes valuable insights to the ongoing discourse on DST and its implications for human circadian rhythms.

Causal dynamics of sleep, circadian rhythm, and mood symptoms in patients with major depression and bipolar disorder: insights from longitudinal wearable device data

BACKGROUND

Sleep and circadian rhythm disruptions are common in patients with mood disorders. The intricate relationship between these disruptions and mood has been investigated, but their causal dynamics remain unknown.

METHODS

We analysed data from 139 patients (76 female, mean age = 23.5 ± 3.64 years) with mood disorders who participated in a prospective observational study in South Korea. The patients wore wearable devices to monitor sleep and engaged in smartphone-delivered ecological momentary assessment of mood symptoms. Using a mathematical model, we estimated their daily circadian phase based on sleep data. Subsequently, we obtained daily time series for sleep/circadian phase estimates and mood symptoms spanning >40,000 days. We analysed the causal relationship between the time series using transfer entropy, a non-linear causal inference method.

FINDINGS

The transfer entropy analysis suggested causality from circadian phase disturbance to mood symptoms in both patients with MDD (n = 45) and BD type I (n = 35), as 66.7% and 85.7% of the patients with a large dataset (>600 days) showed causality, but not in patients with BD type II (n = 59). Surprisingly, no causal relationship was suggested between sleep phase disturbances and mood symptoms.

INTERPRETATION

Our findings suggest that in patients with mood disorders, circadian phase disturbances directly precede mood symptoms. This underscores the potential of targeting circadian rhythms in digital medicine, such as sleep or light exposure interventions, to restore circadian phase and thereby manage mood disorders effectively.

FUNDING

Institute for Basic Science, the Human Frontiers Science Program Organization, the National Research Foundation of Korea, and the Ministry of Health & Welfare of South Korea.

Solar clock and school start time effects on adolescents' chronotype and sleep: A review of a gap in the literature

Circadian rhythms are entrained by external factors such as sunlight and social cues, but also depend on internal factors such as age. Adolescents exhibit late chronotypes, but worldwide school starts early in the morning leading to unhealthy sleep habits. Several studies reported that adolescents benefit from later school start times. However, the effect of later school start time on different outcomes varies between studies, and most previous literature only takes into consideration the social clock (i.e. local time of school starting time) but not the solar clock (e.g. the distance between school start time and sunrise). Thus, there is an important gap in the literature: when assessing the effect of a school start time on chronotype and sleep of adolescents at different locations and/or seasons, the solar clock might differ and, consistently, the obtained results. For example, the earliest school start time for adolescents has been suggested to be 08:30 hours, but this school start time might correspond to different solar times at different times of the year, longitudes and latitudes. Here, we describe the available literature comparing different school start times, considering important factors such as geographic position, nationality, and the local school start time and its distance to sunrise. Then, we described and contrasted the relative role of both social and solar clocks on the chronotype and sleep of adolescents. As a whole, we point and discuss a gap in literature, suggesting that both clocks are relevant when addressing the effect of school start time on adolescents' chronotype and sleep.

Mathematical Analysis of Light-sensitivity Related Challenges in Assessment of the Intrinsic Period of the Human Circadian Pacemaker

Accurate assessment of the intrinsic period of the human circadian pacemaker is essential for a quantitative understanding of how our circadian rhythms are synchronized to exposure to natural and man-made light-dark (LD) cycles. The gold standard method for assessing intrinsic period in humans is forced desynchrony (FD) which assumes that the confounding effect of lights-on assessment of intrinsic period is removed by scheduling sleep-wake and associated dim LD cycles to periods outside the range of entrainment of the circadian pacemaker. However, the observation that the mean period of free-running blind people is longer than the mean period of sighted people assessed by FD (24.50 ± 0.17 h vs 24.15 ± 0.20 h, p < 0.001) appears inconsistent with this assertion. Here, we present a mathematical analysis using a simple parametric model of the circadian pacemaker with a sinusoidal velocity response curve (VRC) describing the effect of light on the speed of the oscillator. The analysis shows that the shorter period in FD may be explained by exquisite sensitivity of the human circadian pacemaker to low light intensities and a VRC with a larger advance region than delay region. The main implication of this analysis, which generates new and testable predictions, is that current quantitative models for predicting how light exposure affects entrainment of the human circadian system may not accurately capture the effect of dim light. The mathematical analysis generates new predictions which can be tested in laboratory experiments. These findings have implications for managing healthy entrainment of human circadian clocks in societies with abundant access to light sources with powerful biological effects.

Chronotherapeutic Approaches

The chapter provides a comprehensive review of current approaches to personalized chronodiagnosis and chronotherapy. We discuss circadian clock drug targets that aim to affect cellular clock machinery, circadian mechanisms of pharmacokinetics/pharmacodynamics, and chronotherapeutic approaches aimed at increasing treatment efficacy and minimizing its side effects. We explore how chronotherapy can combat acquired and compensatory drug resistance. Non-pharmacological interventions for clock preservation and enhancement are also overviewed, including light treatment, melatonin, sleep scheduling, time-restricted feeding, physical activity, and exercise.

Predicting neurobehavioral performance of resident physicians in a Randomized Order Safety Trial Evaluating Resident-Physician Schedules (ROSTERS)

OBJECTIVES

Mathematical models of human neurobehavioral performance that include the effects of acute and chronic sleep restriction can be key tools in assessment and comparison of work schedules, allowing quantitative predictions of performance when empirical assessment is impractical.

METHODS

Using such a model, we tested the hypothesis that resident physicians working an extended duration work roster, including 24-28 hours of continuous duty and up to 88 hours per week averaged over 4weeks, would have worse predicted performance than resident physicians working a rapidly cycling work roster intervention designed to reduce the duration of extended shifts. The performance metric used was attentional failures (ie, Psychomotor Vigilance Task lapses). Model input was 169 actual work and sleep schedules. Outcomes were predicted hours per week during work hours spent at moderate (equivalent to 16-20 hours of continuous wakefulness) or high (equivalent to ≥20 hours of continuous wakefulness) performance impairment.

RESULTS

The model predicted that resident physicians working an extended duration work roster would spend significantly more time at moderate impairment (p = .02, effect size=0.2) than those working a rapidly cycling work roster; this difference was most pronounced during the circadian night (p < .001). On both schedules, performance was predicted to decline from weeks 1 + 2 to weeks 3 + 4 (p < .001), but the rate of decline was significantly greater on extended duration work roster (p < .01). Predicted performance impairment was inversely related to prior sleep duration (p < .001).

CONCLUSIONS

These findings demonstrate the utility of a mathematical model to evaluate the predicted performance profile of schedules for resident physicians and others who experience chronic sleep restriction and circadian misalignment.

Uncovering personal circadian responses to light through particle swarm optimization

BACKGROUND AND OBJECTIVES

Kronauer's oscillator model of the human central pacemaker is one of the most commonly used approaches to study the human circadian response to light. Two sources of error when applying it to a personal light exposure have been identified: (1) as a populational model, it does not consider inter-individual variability, and (2) the initial conditions needed to integrate the model are usually unknown, and thus subjectively estimated. In this work, we evaluate the ability of particle swarm optimization (PSO) algorithms to simultaneously uncover the optimal initial conditions and individual parameters of a pre-defined Kronauer's oscillator model.

METHODS

A Canonical PSO, a Dynamic Multi-Swarm PSO and a novel modification of the latter, namely Hierarchical Dynamic Multi-Swarm PSO, are evaluated. Two different target models (under a regular and an irregular schedule) are defined, and the same realistic light profile is fed to them. Based on their output, a fitness function is proposed, which is minimized by the algorithms to find the optimum set of parameters and initial conditions of the model.

RESULTS

We demonstrate that Dynamic Multi-Swarm and Hierarchical Dynamic Multi-Swarm algorithms can accurately uncover personal circadian parameters under both regular and irregular schedules, but as expected, optimization is easier under a regular schedule. Circadian parameters play the most important role in the optimization process and should be prioritized over initial conditions, although assessment of the impact of misestimating the latter is recommended. The log-log linear relationship between mean absolute error and computational cost shows that the number of particles to use is at the discretion of the user.

CONCLUSIONS

The robustness and low errors achieved by the algorithms support their further testing, validation and systematic application to empirical data under a regular or irregular schedule. Uncovering personal circadian parameters can improve the assessment of the circadian status of a person and the applicability of personalized light therapies, as well as help to discover other factors that may lie behind the interindividual variability in the circadian response to light.

Impact of Preoperative Sleep Disturbances on Postoperative Delirium in Patients with Intracranial Tumors: A Prospective, Observational, Cohort Study

Background

Postoperative delirium (POD) is prevalent in craniotomy patients and is associated with high mortality. Sleep disturbances are receiving increasing attention from clinicians as associated risk factors for postoperative complications. This study aimed to determine the impact of preoperative sleep disturbances on POD in craniotomy patients.

Methods

We recruited 130 patients undergoing elective craniotomy for intracranial tumors between May 1st and December 30th, 2022. Preoperative subjective sleep disturbances were assessed using the Pittsburgh Sleep Quality Index on the day of admission. We also measured objective perioperative sleep patterns using a dedicated sleep monitoring device 3 days before and 3 days after the surgery. POD was assessed twice daily using the Confusion Assessment Model for the Intensive Care Unit within the first week after craniotomy.

Results

Preoperative sleep disturbances were diagnosed in 49% of the study patients, and POD was diagnosed in 22% of all the study patients. Sleep disturbances were an independent risk factor for POD (OR: 2.709, 95% CI: 1.020-7.192, P = 0.045). Other risk factors for POD were age (OR: 3.038, 95% CI: 1.195-7.719, P = 0.020) and the duration of urinary catheterization (OR: 1.246, 95% CI: 1.025-1.513, P = 0.027). Perioperative sleep patterns (including sleep latency, deep sleep duration, frequency of awakenings, apnea-hypopnea index, and sleep efficiency) were significantly associated with POD.

Conclusion

This study demonstrated that preoperative sleep disturbances predispose patients undergoing craniotomy to POD, also inferred a correlation between perioperative sleep patterns and POD. The targeted screening and intervention specifically for sleep disturbances during the perioperative period are immensely required.

Method to determine whether sleep phenotypes are driven by endogenous circadian rhythms or environmental light by combining longitudinal data and personalised mathematical models

Sleep timing varies between individuals and can be altered in mental and physical health conditions. Sleep and circadian sleep phenotypes, including circadian rhythm sleep-wake disorders, may be driven by endogenous physiological processes, exogeneous environmental light exposure along with social constraints and behavioural factors. Identifying the relative contributions of these driving factors to different phenotypes is essential for the design of personalised interventions. The timing of the human sleep-wake cycle has been modelled as an interaction of a relaxation oscillator (the sleep homeostat), a stable limit cycle oscillator with a near 24-hour period (the circadian process), man-made light exposure and the natural light-dark cycle generated by the Earth's rotation. However, these models have rarely been used to quantitatively describe sleep at the individual level. Here, we present a new Homeostatic-Circadian-Light model (HCL) which is simpler, more transparent and more computationally efficient than other available models and is designed to run using longitudinal sleep and light exposure data from wearable sensors. We carry out a systematic sensitivity analysis for all model parameters and discuss parameter identifiability. We demonstrate that individual sleep phenotypes in each of 34 older participants (65-83y) can be described by feeding individual participant light exposure patterns into the model and fitting two parameters that capture individual average sleep duration and timing. The fitted parameters describe endogenous drivers of sleep phenotypes. We then quantify exogenous drivers using a novel metric which encodes the circadian phase dependence of the response to light. Combining endogenous and exogeneous drivers better explains individual mean mid-sleep (adjusted R-squared 0.64) than either driver on its own (adjusted R-squared 0.08 and 0.17 respectively). Critically, our model and analysis highlights that different people exhibiting the same sleep phenotype may have different driving factors and opens the door to personalised interventions to regularize sleep-wake timing that are readily implementable with current digital health technology.

Longitude-based time zone partitions and rates of suicide

BACKGROUND

Increasing evidence suggests that conditions with decreased morning and increased evening light exposure, including shift work, daylight-saving time, and eveningness, are associated with elevated mortality and suicide risk. Given that the alignment between the astronomical, biological, and social time varies across a time zone, with later-shifted daylight exposure in the western partition, we hypothesized that western time zone partitions would have higher suicide rates than eastern partitions.

METHODS

United States (U.S.) county-level suicide and demographic data, from 2010 to 2018, were obtained from a Centers for Disease Control database. Using longitude and latitude, counties were sorted into the western, middle, or eastern partition of their respective time zones, as well as the northern and southern halves of the U.S. Linear regressions were used to estimate the associations between suicide rates and time zone partitions, adjusting for gender, race, ethnicity, age group, and unemployment rates.

RESULTS

Data were available for 2872 counties. Across the U.S., western partitions had statistically significantly higher rates of suicide compared to eastern partitions and averaged up to two additional yearly deaths per 100,000 people (p < .001).

LIMITATIONS

Ecological design and limited adjustment for socioeconomic factors.

CONCLUSIONS

To our knowledge, this is the first study of the relationship between longitude-based time zone partitions and suicide. The results were consistent with the hypothesized elevated suicide rates in the western partitions, and concordant with previous reports on cancer mortality and transportation fatalities. The next step is to retest the hypothesis with individual-level data, accounting for latitude, photoperiodic changes, daylight-saving time, geoclimatic variables, physical and mental health indicators, as well as socioeconomic adversity and protection.

Better alignment between circadian preference and sleep and work timings during COVID-19 did not benefit work engagement at home

Modern society is structured around early routines which cause evening types to suffer from health and performance detriments associated with sleep times being misaligned with biological needs (circadian preference). Given that COVID-19 lockdowns were less constrained by social schedules, the current study explores whether temporal behaviours became better aligned with biological needs, and whether these changes benefited work engagement. 406 UK participants reported circadian preference and pre-lockdown and lockdown sleep times, work times, and work engagement. Results found that sleep health improved under lockdown measures in terms of increased sleep duration and reduced social jetlag, and sleep and work times became better aligned with circadian preferences. The most circadian-misaligned participants - students and young adults - exhibited the largest changes to sleep and work habits. However, work engagement decreased more in participants with improved social jetlag and delayed work habits, which is surprising given that these temporal changes reflect improved circadian alignment. We discuss potential moderators including poor sleep quality, non-engaging work-from-home environments, and mental health. These findings have implications for encouraging flexible educational and employment schedules post-COVID-19 to satisfy the common drive to improve circadian alignment, but future work must determine the moderating factors that impair work engagement during remote work.

Pharmacokinetic Model-Based Control across the Blood-Brain Barrier for Circadian Entrainment

The ability to shift circadian phase in vivo has the potential to offer substantial health benefits. However, the blood-brain barrier prevents the absorption of the majority of large and many small molecules, posing a challenge to neurological pharmaceutical development. Motivated by the presence of the circadian molecule KL001, which is capable of causing phase shifts in a circadian oscillator, we investigated the pharmacokinetics of different neurological pharmaceuticals on the dynamics of circadian phase. Specifically, we developed and validated five different transport models that describe drug concentration profiles of a circadian pharmaceutical at the brain level under oral administration and designed a nonlinear model predictive control (MPC)-based framework for phase resetting. Performance of the novel control algorithm based on the identified pharmacokinetic models was demonstrated through simulations of real-world misalignment scenarios due to jet lag. The time to achieve a complete phase reset for 11-h phase delay ranged between 48 and 72 h, while a 5-h phase advance was compensated in 30 to 60 h. This approach provides mechanistic insight into the underlying structure of the circadian oscillatory system and thus leads to a better understanding of the feasibility of therapeutic manipulations of the system.

Effects of Chronotype and Social Jet-Lag on Neurocognitive Functioning

The chronotype, which reflects the circadian rhythm preferences of individuals in their daily activities and sleep-wake cycles, can be considered on a dimension of extreme morningism and extreme eveningism. Individuals with extreme morning and extreme evening chronotypes face many physical and psychological dangers due to accumulated sleep debt, short total sleep time and insufficient sleep efficiency. In extreme chronotypes, especially in extreme evening people, the social jet-lag effect due to the mismatch between social and circadian clocks is thought to exacerbate these dangers. More recent studies have suggested that social jet-lag and chronotype have many negative effects on cognitive functioning. The aim of this article is to review the impact of social jet-lag and chronotype on cognitive functioning.

A real-time, personalized sleep intervention using mathematical modeling and wearable devices

The prevalence of artificial light exposure has enabled us to be active any time of the day or night, leading to the need for high alertness outside of traditional daytime hours. To address this need, we developed a personalized sleep intervention framework that analyzes real-world sleep-wake patterns obtained from wearable devices to maximize alertness during specific target periods. Our framework utilizes a mathematical model that tracks the dynamic sleep pressure and circadian rhythm based on the user's sleep history. In this way, the model accurately predicts real-time alertness, even for shift workers with complex sleep and work schedules (N = 71, t = 13~21 days). This allowed us to discover a new sleep-wake pattern called the adaptive circadian split sleep, which incorporates a main sleep period and a late nap to enable high alertness during both work and non-work periods of shift workers. We further developed a mobile application that integrates this framework to recommend practical, personalized sleep schedules for individual users to maximize their alertness during a targeted activity time based on their desired sleep onset and available sleep duration. This can reduce the risk of errors for those who require high alertness during nontraditional activity times and improve the health and quality of life for those leading shift work-like lifestyles.

Measuring light regularity: sleep regularity is associated with regularity of light exposure in adolescents

STUDY OBJECTIVES

Light is the main time cue for the human circadian system. Sleep and light are intrinsically linked; light exposure patterns can influence sleep patterns and sleep can influence light exposure patterns. However, metrics for quantifying light regularity are lacking, and the relationship between sleep and light regularity is underexplored. We developed new metrics for light regularity and demonstrated their utility in adolescents, across school term and vacation.

METHODS

Daily sleep/wake and light patterns were measured using wrist actigraphy in 75 adolescents (54% male, 17.17 ± 0.83 years) over 2 weeks of school term and a subsequent 2-week vacation. The Sleep Regularity Index (SRI) and social jetlag were computed for each 2-week block. Light regularity was assessed using (1) variation in mean daily light timing (MLiT); (2) variation in daily photoperiod; and (3) the Light Regularity Index (LRI). Associations between SRI and each light regularity metric were examined, and within-individual changes in metrics were examined between school and vacation.

RESULTS

Higher SRI was significantly associated with more regular LRI scores during both school and vacation. There were no significant associations of SRI with variation in MLiT or daily photoperiod. Compared to school term, all three light regularity metrics were less variable during the vacation.

CONCLUSIONS

Light regularity is a multidimensional construct, which until now has not been formally defined. Irregular sleep patterns are associated with lower LRI, indicating that irregular sleepers also have irregular light inputs to the circadian system, which likely contributes to circadian disruption.

Changes in menstrual cycle length and in sleep-wake behaviors during COVID-19 related lockdown in Israel

COVID-19 related lockdowns changed our life. Studies report that young women are more susceptible to lockdown-induced adverse effects and stress. As stress and menstrual cycle are associated, we hypothesized that menstrual cycle length might change during lockdown. We examined menstrual cycle length, and sleep-wake behaviors during lockdown in Israel. Participants were 97 women in their fertile years who used Tempdrop fertility sensor™ to track cycles. Data were collected before, during and after lockdown in Israel. Our main finding is that lockdown was associated with changes in menstrual cycle length of most participants, with either increased of decreased length. Changes were reversed when lockdown was terminated. Sleep duration increased during lockdown but we found no relationship between sleep and menstrual cycle. We suggest these findings contribute to the understanding of the relationship between stress, sleep, and menstrual cycle. Further studies should explore the sources for differential effects in sub-groups of women.

Time Spent Outdoors and Associations with Sleep, Optimism, Happiness and Health before and during the COVID-19 Pandemic in Austria

Social restriction measures (SRM) implemented during the COVID-19 pandemic led to a reduction in time spent outdoors (TSO). The aim of this study was to describe TSO and evaluate its association with sleep outcomes, optimism, happiness and health-status before and during SRM. Two online surveys were conducted in 2017 (N = 1004) and 2020, during SRM (N = 1010), in samples representative of the age, sex and region of the Austrian population. Information on the duration of TSO, sleep, optimism, happiness and health-status was collected. Multivariable-adjusted logistic regression models were used to study the association of TSO with chronic insomnia, short sleep, late chronotype, optimism, happiness and self-rated health-status. The mean TSO was 3.6 h (SD: 2.18) in 2017 and 2.6 h (SD: 1.87) during times of SRM. Men and participants who were older, married or in a partnership and lived in a rural area reported longer TSO. Participants who spent less time outdoors were more likely to report short sleep or a late chronotype in both surveys and, in 2020, also chronic insomnia. Less TSO was associated with lower happiness and optimism levels and poor health-status. Our findings suggest that TSO may be a protective factor for sleep, mood and health, particularly during stressful and uncertain times.

A better alignment between chronotype and school timing is associated with lower grade retention in adolescents

Schools start early in the morning all over the world, contrasting with adolescents' late chronotype. Interestingly, lower academic performance (i.e. grades or qualifications) was associated with later chronotypes. However, it is unclear whether it is a direct effect of chronotype or because students attend school too early to perform at their best. Moreover, little is known about how this affects students' academic success beyond their grades. To address this gap in knowledge, we studied how school timing and chronotype affect grade retention (i.e. repeat a year) in a unique sample of students randomly assigned to one of three different school timings (starting at 07:45, 12:40, or 17:20). Even when controlling for academic performance, we found that later chronotypes exhibit higher odds of grade retention only in the morning, but not in later school timings. Altogether, ensuring a better alignment between school timing and students' biological rhythms might enhance future opportunities of adolescents.

Cognitive control, bedtime patterns, and testing time in female adolescent students: behavioral and neuro-electrophysiological correlates

Introduction

Shorter and/or disrupted sleep during adolescence is associated with cognitive and mental health risks, particularly in females. We explored the relationship between bedtime behavior patterns co-varying with Social Jet Lag (SJL) and School Start Times (SST) and neurocognitive performance in adolescent female students.

Methods

To investigate whether time of day (morning vs. afternoon), early SSTs and days of the school week can be correlated with neurocognitive correlates of sleep insufficiency, we recruited 24 female students aged 16-18 to report sleep logs, and undergo event-related electroencephalographic recordings on Monday, Wednesday, mornings, and afternoons. Using a Stroop task paradigm, we analyzed correlations between reaction times (RTs), accuracy, time of day, day of week, electroencephalographic data, and sleep log data to understand what relationships may exist.

Results

Participants reported a 2-h sleep phase delay and SJL. Stroop interference influenced accuracy on Monday and Wednesday similarly, with better performance in the afternoon. For RTs, the afternoon advantage was much larger on Monday than Wednesday. Midline Event-Related Potentials (ERPs) yielded higher amplitudes and shorter latencies on Wednesday morning and Monday afternoon, in time windows related to attention or response execution. A notable exception were delayed ERP latencies on Wednesday afternoon. The latter could be explained by the fact that delta EEG waves tended to be the most prominent, suggesting heightened error monitoring due to accumulating mental fatigue.

Discussion

These findings provide insights into the interaction between SJL and SST and suggest evidence-based criteria for planning when female adolescents should engage in cognitive-heavy school activities such as tests or exams.

Physiological Rhythms and Biological Variation of Biomolecules: The Road to Personalized Laboratory Medicine

The concentration of biomolecules in living systems shows numerous systematic and random variations. Systematic variations can be classified based on the frequency of variations as ultradian (<24 h), circadian (approximately 24 h), and infradian (>24 h), which are partly predictable. Random biological variations are known as between-subject biological variations that are the variations among the set points of an analyte from different individuals and within-subject biological variation, which is the variation of the analyte around individuals’ set points. The random biological variation cannot be predicted but can be estimated using appropriate measurement and statistical procedures. Physiological rhythms and random biological variation of the analytes could be considered the essential elements of predictive, preventive, and particularly personalized laboratory medicine. This systematic review aims to summarize research that have been done about the types of physiological rhythms, biological variations, and their effects on laboratory tests. We have searched the PubMed and Web of Science databases for biological variation and physiological rhythm articles in English without time restrictions with the terms “Biological variation, Within-subject biological variation, Between-subject biological variation, Physiological rhythms, Ultradian rhythms, Circadian rhythm, Infradian rhythms”. It was concluded that, for effective management of predicting, preventing, and personalizing medicine, which is based on the safe and valid interpretation of patients’ laboratory test results, both physiological rhythms and biological variation of the measurands should be considered simultaneously.

Weight status of working adults: The effects of eating misalignment, chronotype, and eating jetlag during mandatory confinement

This study aimed to examine the association between chronotype, eating jetlag, and eating misalignment with weight status among Malaysian adults during the COVID-19 restriction. This online cross-sectional study included 175 working adults recruited from March to July 2020. The chronotype was assessed using Morningness Eveningness Questionnaire (MEQ) while eating jetlag and mealtime variability were measured using Chrononutrition Profile Questionnaire (CPQ). Multiple linear regression demonstrated that lower breakfast frequency (β=-0.258, p = .002) and longer eating duration (β = 0.393, p < .001) were associated with later first eating events on workfree days. Both intermediate (β = 0.543, p < .001) and evening chronotypes (β = 0.523, p = .001) tend to eat their first meals later compared to morning person. Similar patterns were observed for overall eating jetlaggers in which lower breakfast frequency (β=-0.022, p = .011), longer eating duration (β = 0.293, p < .001), intermediate chronotype (β = 0.512, p < .001), and evening chronotype (β = 0.495, p = .003) were associated with eating later meals on workfree days. Additionally, higher BMI was also associated with eating later meals on workfree days (β = 0.181, p = .025). During movement restriction, discrepancies of mealtimes during work and workfree days offer new insight into modern eating habits that can influence weight status and general eating habits such as breakfast skipping and total daily eating duration. Population meal timing variability was affected during movement restrictions, and it was closely related to weight status.

Nurse rostering with fatigue modelling : Incorporating a validated sleep model with biological variations in nurse rostering

We use a real Nurse Rostering Problem and a validated model of human sleep to formulate the Nurse Rostering Problem with Fatigue. The fatigue modelling includes individual biologies, thus enabling personalised schedules for every nurse. We create an approximation of the sleep model in the form of a look-up table, enabling its incorporation into nurse rostering. The problem is solved using an algorithm that combines Mixed-Integer Programming and Constraint Programming with a Large Neighbourhood Search. A post-processing algorithm deals with errors, to produce feasible rosters minimising global fatigue. The results demonstrate the realism of protecting nurses from highly fatiguing schedules and ensuring the alertness of staff. We further demonstrate how minimally increased staffing levels enable lower fatigue, and find evidence to suggest biological complementarity among staff can be used to reduce fatigue. We also demonstrate how tailoring shifts to nurses' biology reduces the overall fatigue of the team, which means managers must grapple with the issue of fairness in rostering.

Associations Between Multidimensional Sleep Health Parameters and Adolescents' Self-reported Light Exposure in the Free-living Environment

The objective of this study was to characterize the associations between light exposure in the free-living environment and multiple dimensions of sleep health of typically developing adolescents. Fifty-six (29 girls, 27 boys) typically developing adolescents (mean age = 13.59, SD = 0.89, range = 12-17 years) participated. For six consecutive nights, sleep was assessed in the home environment using actigraphy. During the same period, participants were asked to fill out a daily sleep log and a daily light exposure log, and to complete questionnaires regarding their alertness and subjective sleep satisfaction. Longer self-reported exposure to daylight in the morning was associated with longer objectively measured sleep duration. Longer self-reported exposures to electronic devices in the evening were associated with later objectively measured sleep onset and offset times, shorter sleep duration, and greater day-to-day sleep variability. Longer morning exposure to outdoor light was associated with a longer sleep duration. Self-reported light exposure was not associated with sleep satisfaction, alertness/sleepiness, or sleep efficiency. Among the covariates, circadian preference accounted for the highest percentage of variance. Adolescents' sleep health is associated with the self-reported duration of exposure to daylight in the morning and to electronic devices in the evening.

Social jetlag and risk of depression: Results from the Korea National Health and Nutrition Examination Survey

BACKGROUND

Social jetlag, which is the mismatch between endogenous rhythm and social timing, is prevalent among the working population. Social jetlag may result in mood changes; however, evidence of relationship between social jetlag and depressive disorders has not been fully verified. Hence, this study aimed to investigate the association between social jetlag and depressive symptoms in a representative working population of South Korea.

METHODS

This study included 5447 Korean employees in the Korea National Health and Nutrition Examination Survey. Social jetlag was calculated as the difference between the midpoint of sleep time on weekdays and free days. Depressive symptoms were assessed using Patient Health Questionnaire-9. Multiple logistic regression was used to estimate the odds ratio after adjusting for confounding factors. Moreover, social jetlag and continuous depression scores were evaluated using linear regression and generalized additive models.

RESULTS

The proportion of the participants who had >2 h of social jetlag was 10.26 %. Depressive symptoms increased as social jetlag increased. Multiple logistic regression analysis showed that the adjusted OR (95 % confidence interval) for 1 to 2 h of social jetlag was 1.355 (0.891-2.059) and for >2 h was 1.859 (1.084-3.187), which <1 h was reference.

LIMITATIONS

This study used a cross-sectional design and measurements were based on self-reported scales.

CONCLUSION

This study found that social jetlag and depressive symptoms were significantly related in the Korean working population.

NREM-REM alternation complicates transitions from napping to non-napping behavior in a three-state model of sleep-wake regulation

The temporal structure of human sleep changes across development as it consolidates from the polyphasic sleep of infants to the single nighttime sleep episode typical in adults. Experimental studies have shown that changes in the dynamics of sleep need may mediate this developmental transition in sleep patterning, however, it is unknown how sleep architecture interacts with these changes. We employ a physiologically-based mathematical model that generates wake, rapid eye movement (REM) and non-REM (NREM) sleep states to investigate how NREM-REM alternation affects the transition in sleep patterns as the dynamics of the homeostatic sleep drive are varied. To study the mechanisms producing these transitions, we analyze the bifurcations of numerically-computed circle maps that represent key dynamics of the full sleep-wake network model by tracking the evolution of sleep onsets across different circadian (∼ 24 h) phases. The maps are non-monotonic and discontinuous, being composed of branches that correspond to sleep-wake cycles containing distinct numbers of REM bouts. As the rates of accumulation and decay of the homeostatic sleep drive are varied, we identify the bifurcations that disrupt a period-adding-like behavior of sleep patterns in the transition between biphasic and monophasic sleep. These bifurcations include border collision and saddle-node bifurcations that initiate new sleep patterns, period-doubling bifurcations leading to higher-order patterns of NREM-REM alternation, and intervals of bistability of sleep patterns with different NREM-REM alternations. Furthermore, patterns of NREM-REM alternation exhibit variable behaviors in different regimes of constant sleep-wake patterns. Overall, the sequence of sleep-wake behaviors, and underlying bifurcations, in the transition from biphasic to monophasic sleep in this three-state model is more complex than behavior observed in models of sleep-wake regulation that do not consider the dynamics of NREM-REM alternation. These results suggest that interactions between the dynamics of the homeostatic sleep drive and the dynamics of NREM-REM alternation may contribute to the wide interindividual variation observed when young children transition from napping to non-napping behavior.

Circadian rhythms and disorders of the timing of sleep

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.

Chronotype at the beginning of secondary school and school timing are both associated with chronotype development during adolescence

The misalignment between late chronotypes and early school start times affect health, performance and psychological well-being of adolescents. Here we test whether, and how, the baseline chronotype (i.e. chronotype at the beginning of secondary school) and the school timing affect the magnitude and the direction of the developmental change in chronotype during adolescence. We evaluated a sample of Argentinian students (n = 259) who were randomly assigned to attend school in the morning (07:45 a.m.–12:05 p.m.), afternoon (12:40 p.m.–05:00 p.m.) or evening (05:20 p.m.–09:40 p.m.) school timings. Importantly, chronotype and sleep habits were assessed longitudinally in the same group of students along secondary school (at 13–14 y.o. and 17–18 y.o.). Our results show that: (1) although chronotypes partially align with class time, this effect is insufficient to fully account for the differences observed in sleep-related variables between school timings; (2) both school timing and baseline chronotype are independently associated with the direction and the magnitude of change in chronotype, with greater delays related to earlier baseline chronotypes and later school timings. The practical implications of these results are challenging and should be considered in the design of future educational timing policies to improve adolescents’ well-being.

The CLASS Study (Circadian Light in Adolescence, Sleep and School): protocol for a prospective, longitudinal cohort to assess sleep, light, circadian timing and academic performance in adolescence

BACKGROUND

During adolescence, sleep and circadian timing shift later, contributing to restricted sleep duration and irregular sleep-wake patterns. The association of these developmental changes in sleep and circadian timing with cognitive functioning, and consequently academic outcomes, has not been examined prospectively. The role of ambient light exposure in these developmental changes is also not well understood. Here, we describe the protocol for the Circadian Light in Adolescence, Sleep and School (CLASS) Study that will use a longitudinal design to examine the associations of sleep-wake timing, circadian timing and light exposure with academic performance and sleepiness during a critical stage of development. We also describe protocol adaptations to enable remote data collection when required during the COVID-19 pandemic.

METHODS

Approximately 220 healthy adolescents aged 12-13 years (school Year 7) will be recruited from the general community in Melbourne, Australia. Participants will be monitored at five 6 monthly time points over 2 years. Sleep and light exposure will be assessed for 2 weeks during the school term, every 6 months, along with self-report questionnaires of daytime sleepiness. Circadian phase will be measured via dim light melatonin onset once each year. Academic performance will be measured via national standardised testing (National Assessment Program-Literacy and Numeracy) and the Wechsler Individual Achievement Test-Australian and New Zealand Standardised Third Edition in school Years 7 and 9. Secondary outcomes, including symptoms of depression, anxiety and sleep disorders, will be measured via questionnaires.

DISCUSSION

The CLASS Study will enable a comprehensive longitudinal assessment of changes in sleep-wake timing, circadian phase, light exposure and academic performance across a key developmental stage in adolescence. Findings may inform policies and intervention strategies for secondary school-aged adolescents.

ETHICS AND DISSEMINATION

Ethical approval was obtained by the Monash University Human Research Ethics Committee and the Victorian Department of Education. Dissemination plans include scientific publications, scientific conferences, via stakeholders including schools and media.

STUDY DATES

Recruitment occurred between October 2019 and September 2021, data collection from 2019 to 2023.

Beyond the limits of circadian entrainment: Non-24-hour sleep-wake disorder, shift work, and social jet lag

While the vast majority of humans are able to entrain their circadian rhythm to the 24-hour light-dark cycle, there are numerous individuals who are not able to do so due to disease or societal reasons. We use computational and mathematical methods to analyze a well-established model of human circadian rhythms to address cases where individuals do not entrain to the 24-hour light-dark cycle, leading to misalignment of their circadian phase. For each case, we provide a mathematically justified strategy for how to minimize circadian misalignment. In the case of non-24-hour sleep-wake disorder, we show why appropriately timed bright light therapy induces entrainment. With regard to shift work, we explain why reentrainment times following transitions between day and night shifts are asymmetric, and how higher light intensity enables unusually rapid reentrainment after certain transitions. Finally, with regard to teenagers who engage in compensatory catch-up sleep on weekends, we propose a rule of thumb for sleep and wake onset times that minimizes circadian misalignment due to this type of social jet lag. In all cases, the primary mathematical approach involves understanding the dynamics of entrainment maps that measure the phase of the entrained rhythm with respect to the daily onset of lights.

Chronodisruption and Ambulatory Circadian Monitoring in Cancer Patients: Beyond the Body Clock

Purpose of Review

Circadian rhythms impose daily rhythms a remarkable variety of metabolic and physiological functions, such as cell proliferation, inflammation, and DNA damage response. Accumulating epidemiological and genetic evidence indicates that circadian rhythms’ disruption may be linked to cancer. The integration of circadian biology into cancer research may offer new options for increasing cancer treatment effectiveness and would encompass the prevention, diagnosis, and treatment of this disease.

Recent Findings

In recent years, there has been a significant development and use of multi-modal sensors to monitor physical activity, sleep, and circadian rhythms, allowing, for the very first time, scaling accurate sleep monitoring to epidemiological research linking sleep patterns to disease, and wellness applications providing new potential applications.

Summary

This review highlights the role of circadian clock in tumorigenesis, cancer hallmarks and introduces the state-of-the-art in sleep-monitoring technologies, discussing the eventual application of insights in clinical settings and cancer research.

Association of Delayed Sleep/Wake Rhythm with Depression During the First COVID-19 Lockdown in France

PURPOSE

The containment of the population during the COVID-19 pandemic led to the emergence or recurrence of psychiatric conditions and sleep disorders. The influence of sleep/wake rhythm on mental health is well known. The objective of our study was to evaluate the link between the shift in sleep/wake rhythm and the presence of depressive symptoms during the March to May 2020 lockdown in the French population.

PARTICIPANTS AND METHODS

Participants (n = 2513) were recruited via newspapers and social networks in March 2020. We evaluated i) the chronotype before and during the lockdown, assessed by the change in mid-sleep time on work-free days corrected for sleep debt on workdays (delta MSFsc); ii) morningness-eveningness circadian preference (Horne & Ostberg questionnaire); iii) depressive symptoms (Patient Health Questionnaire-9, PHQ-9). The delta MSFsc and the PHQ-9 score were compared between circadian preference types. A multivariate model adjusted for age, sex, circadian preference, housing type, and marital status was used to assess the influence of delta MSFsc on the PHQ-9 score in the whole population.

RESULTS

The population consisted of 77% women, of median (IQR) age 39 (30-48) years. Compared with the pre-lockdown period, the median (IQR) MSFsc was shifted by 30 (0-66) min during the lockdown, with a significant difference between evening [60 (15-120) min], morning [15 (0-46) min] and neutral [30 (0-70) min] circadian type individuals, p < 0.001. One-third of all participants had moderate to severe depressive symptoms (PHQ-9 ≥ 10). A 1-hour shift in MSFsc was associated with a 0.50-point increase [95% CI (0.28; 0.72), p < 0.001] in the PHQ-9.

CONCLUSION

A phase delay in the chronotype was observed in the general population during lockdown. Such disruption was associated with depressive symptoms but the direction of the relationship remains hypothetical. The impact on mental health of preventive measures targeting the sleep/wake rhythm in this context needs further evaluation.

Are elite track and field athletes on track? The impact of COVID-19 outbreak on sleep behavior and training characteristics

The Covid-19 outbreak forced many governments to enter a nationwide lockdown. The aim of this study was to evaluate, by means of a survey, changes in sleep parameters and physical activity characteristics of elite track and field athletes in three periods: before the lockdown (T0), during the lockdown (09th March – 03rd May 2020, T1) and the first month after the lockdown (T2). This study was conducted from May 2020 to June 2020 and data were collected using an offline survey with 89 elite track and field athletes (mean age: 24.7 ± 5.4; n = 43 males; n = 46 females). The survey consisted of demographic data and questions on physical activity and sleep behavior at T0, T1 and T2. Athletes reported lower sleep quality scores at T1 compared to T0 and T2 (p < 0.0001) and registered delayed bedtime, wake-up time and longer sleep latency during the lockdown compared to pre-lockdown and post-lockdown whereas no changes in total sleep time were reported. No inter-group differences were detected in sleep characteristics between short- and long-term disciplines and between genders. The weekly training volume decreased from 16.1 ± 5.7 hours at T0 to 10.7 ± 5.7 hours at T1 (p < 0.0001) whereas no significant differences were detected in training volume during the lockdown in relation to the square footage of the house (p = 0.309). Alcohol (p = 0.136) and caffeine intake (p = 0.990) and use of electronic devices (p = 0.317) were similar pre-, during, and post-lockdown. The unprecedented circumstances of the Covid-19 pandemic had negative impacts on the Italian track and field athletes’ sleep and training volumes.

Time spent in outdoor light is associated with mood, sleep, and circadian rhythm-related outcomes: A cross-sectional and longitudinal study in over 400,000 UK Biobank participants

BACKGROUND

Light has powerful effects on mood, sleep, and the circadian system. Humans evolved in an environment with a clear distinction between day and night, but our modern environments have blurred this distinction. Negative effects of light exposure at night have been well characterized. The importance of daytime light exposure has been less well characterized. Here we examine the cross-sectional and longitudinal associations of time spent in daytime outdoor light with mood, sleep, and circadian-related outcomes.

METHODS

Participants were drawn from the UK Biobank cohort, a large study of UK adults (n = 502,000; 37-73 years old; 54% women).

RESULTS

UK Biobank participants reported spending a median of 2.5 daylight hours (IQR = 1.5-3.5 h) outdoors per day. Each additional hour spent outdoors during the day was associated with lower odds of lifetime major depressive disorder (95% CI OR:0.92-0.98), antidepressant usage (OR:0.92-0.98), less frequent anhedonia (OR:0.93-0.96) and low mood (OR:0.87-0.90), greater happiness (OR:1.41-1.48) and lower neuroticism (incident rate ratio, IRR:0.95-0.96), independent of demographic, lifestyle, and employment covariates. In addition, each hour of daytime light was associated with greater ease of getting up (OR:1.46-1.49), less frequent tiredness (OR:0.80-0.82), fewer insomnia symptoms (OR:0.94-0.97), and earlier chronotype (adjusted odds ratio; OR:0.75-0.77). Auto-Regressive Cross-Lagged (ARCL) models were used to examine the longitudinal association of time spent in outdoor light at baseline with later mood-, sleep- and circadian-related outcomes reported at time point 2. Overall, longitudinal associations support cross-sectional findings, though generally with smaller effect sizes.

LIMITATIONS

Future studies that examine the intensity of daytime light exposure at the ocular level are needed.

CONCLUSIONS

Our findings suggest that low daytime light exposure is an important environmental risk factor for mood, sleep, and circadian-related outcomes.

Extracting Circadian and Sleep Parameters from Longitudinal Data in Schizophrenia for the Design of Pragmatic Light Interventions

Sleep and circadian rhythm dysfunction is prevalent in schizophrenia, is associated with distress and poorer clinical status, yet remains an under-recognized therapeutic target. The development of new therapies requires the identification of the primary drivers of these abnormalities. Understanding of the regulation of sleep-wake timing is now sufficiently advanced for mathematical model-based analyses to identify the relative contribution of endogenous circadian processes, behavioral or environmental influences on sleep-wake disturbance and guide the development of personalized treatments. Here, we have elucidated factors underlying disturbed sleep-wake timing by applying a predictive mathematical model for the interaction of light and the circadian and homeostatic regulation of sleep to actigraphy, light, and melatonin profiles from 20 schizophrenia patients and 21 age-matched healthy unemployed controls, and designed interventions which restored sleep-circadian function. Compared to controls, those with schizophrenia slept longer, had more variable sleep timing, and received significantly fewer hours of bright light (light > 500 lux), which was associated with greater variance in sleep timing. Combining the model with the objective data revealed that non 24-h sleep could be best explained by reduced light exposure rather than differences in intrinsic circadian period. Modeling implied that late sleep offset and non 24-h sleep timing in schizophrenia can be normalized by changes in environmental light-dark profiles, without imposing major lifestyle changes. Aberrant timing and intensity of light exposure patterns are likely causal factors in sleep timing disturbances in schizophrenia. Implementing our new model-data framework in clinical practice could deliver personalized and acceptable light-dark interventions that normalize sleep-wake timing.

Personalized sleep-wake patterns aligned with circadian rhythm relieve daytime sleepiness

Shift workers and many other groups experience irregular sleep-wake patterns. This can induce excessive daytime sleepiness that decreases productivity and elevates the risk of accidents. However, the degree of daytime sleepiness is not correlated with standard sleep parameters like total sleep time, suggesting other factors are involved. Here, we analyze real-world sleep-wake patterns of shift workers measured with wearables by developing a computational package that simulates homeostatic sleep pressure – physiological need for sleep – and the circadian rhythm. This reveals that shift workers who align sleep-wake patterns with their circadian rhythm have lower daytime sleepiness, even if they sleep less. The alignment, quantified by the sleep parameter, circadian sleep sufficiency, can be increased by dynamically adjusting daily sleep durations according to varying bedtimes. Our computational package provides flexible and personalized real-time sleep-wake patterns for individuals to reduce their daytime sleepiness and could be used with wearables to develop smart alarms.

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Sleep-wake patterns measured by wearables are analyzed with a mathematical model

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A new sleep parameter CSS measures the circadian alignment of sleep-wake patterns

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Sleep-wake patterns more aligned with circadian rhythm decrease daytime sleepiness

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Our computational package calculates the CSS to provide personalized sleep schedules

Reopening after lockdown: The influence of working-from-home and digital device use on sleep, physical activity, and wellbeing following COVID-19 lockdown and reopening

Study Objectives

COVID-19 lockdowns drastically affected sleep, physical activity, and wellbeing. We studied how these behaviors evolved during reopening the possible contributions of continued working from home and smartphone usage.

Methods

Participants (N = 198) were studied through the lockdown and subsequent reopening period, using a wearable sleep/activity tracker, smartphone-delivered ecological momentary assessment (EMA), and passive smartphone usage tracking. Work/study location was obtained through daily EMA ascertainment.

Results

Upon reopening, earlier, shorter sleep and increased physical activity were observed, alongside increased self-rated stress and poorer evening mood ratings. These reopening changes were affected by post-lockdown work arrangements and patterns of smartphone usage. Individuals who returned to work or school in-person tended toward larger shifts to earlier sleep and wake timings. Returning to in-person work/school also correlated with more physical activity. Contrary to expectation, there was no decrease in objectively measured smartphone usage after reopening. A cluster analysis showed that persons with relatively heavier smartphone use prior to bedtime had later sleep timings and lower physical activity.

Conclusions

These observations indicate that the reopening after lockdown was accompanied by earlier sleep timing, increased physical activity, and altered mental wellbeing. Moreover, these changes were affected by work/study arrangements and smartphone usage patterns.

Case Report: Embedding "Digital Chronotherapy" Into Medical Devices-A Canine Validation for Controlling Status Epilepticus Through Multi-Scale Rhythmic Brain Stimulation

Circadian and other physiological rhythms play a key role in both normal homeostasis and disease processes. Such is the case of circadian and infradian seizure patterns observed in epilepsy. However, these rhythms are not fully exploited in the design of active implantable medical devices. In this paper we explore a new implantable stimulator that implements chronotherapy as a feedforward input to supplement both open-loop and closed-loop methods. This integrated algorithm allows for stimulation to be adjusted to the ultradian, circadian and infradian patterns observed in patients through slowly-varying temporal adjustments of stimulation and algorithm sub-components, while also enabling adaption of stimulation based on immediate physiological needs such as a breakthrough seizure or change of posture. Embedded physiological sensors in the stimulator can be used to refine the baseline stimulation circadian pattern as a "digital zeitgeber," i.e., a source of stimulus that entrains or synchronizes the subject's natural rhythms. This algorithmic approach is tested on a canine with severe drug-resistant idiopathic generalized epilepsy exhibiting a characteristic diurnal pattern correlated with sleep-wake cycles. Prior to implantation, the canine's cluster seizures evolved to status epilepticus (SE) and required emergency pharmacological intervention. The cranially-mounted system was fully-implanted bilaterally into the centromedian nucleus of the thalamus. Using combinations of time-based modulation, thalamocortical rhythm-specific tuning of frequency parameters as well as fast-adaptive modes based on activity, the canine experienced no further SE events post-implant as of the time of writing (7 months). Importantly, no significant cluster seizures have been observed either, allowing the reduction of rescue medication. The use of digitally-enabled chronotherapy as a feedforward signal to augment adaptive neurostimulators could prove a useful algorithmic method in conditions where sensitivity to temporal patterns are characteristics of the disease state, providing a novel mechanism for tailoring a more patient-specific therapy approach.

In-person vs home schooling during the COVID-19 pandemic: Differences in sleep, circadian timing, and mood in early adolescence

During the COVID-19 pandemic, schools around the world rapidly transitioned from in-person to remote learning, providing an opportunity to examine the impact of in-person vs remote learning on sleep, circadian timing, and mood. We assessed sleep-wake timing using wrist actigraphy and sleep diaries over 1-2 weeks during in-person learning (n = 28) and remote learning (n = 58, where n = 27 were repeat assessments) in adolescents (age M ± SD = 12.79 ± 0.42 years). Circadian timing was measured under a single condition in each individual using salivary melatonin (Dim Light Melatonin Onset; DLMO). Online surveys assessed mood (PROMIS Pediatric Anxiety and Depressive Symptoms) and sleepiness (Epworth Sleepiness Scale - Child and Adolescent) in each condition. During remote (vs in-person) learning: (i) on school days, students went to sleep 26 minutes later and woke 49 minutes later, resulting in 22 minutes longer sleep duration (all P < .0001); (ii) DLMO time did not differ significantly between conditions, although participants woke at a later circadian phase (43 minutes, P = .03) during remote learning; and (iii) participants reported significantly lower sleepiness (P = .048) and lower anxiety symptoms (P = .006). Depressive symptoms did not differ between conditions. Changes in mood symptoms were not mediated by sleep. Although remote learning continued to have fixed school start times, removing morning commutes likely enabled adolescents to sleep longer, wake later, and to wake at a later circadian phase. These results indicate that remote learning, or later school start times, may extend sleep and improve some subjective symptoms in adolescents.

Weekly and seasonal variation in the circadian melatonin rhythm in humans: Entrained to local clock time, social time, light exposure or sun time?

A recent elegant study published in this journal (Zerbini, Winnebeck & Merrow, J Pineal Res, e12723, 2021) reported data on weekly and seasonal changes in circadian timing, as assessed by the melatonin rhythm in dim light in a population that was exposed to a change from standard time to day light saving time. The authors highlight a one hour earlier timing of melatonin onset in summer compared with winter and a 20 minutes delay on work-free days compared with work days. The variations in the timing of the melatonin rhythm are reported in standard time and the authors imply that the data are consistent with synchronization to midday and that "we know that humans entrain to sun time." Here, we show that their extensive data are most parsimoniously explained by entrainment to local clock time and associated light exposure rather than "sun time," indexed by either dawn or midday.

Modeling the Influence of Chronic Sleep Restriction on Cortisol Circadian Rhythms, with Implications for Metabolic Disorders

Chronic sleep deficiency is prevalent in modern society and is associated with increased risk of metabolic and other diseases. While the mechanisms by which chronic sleep deficiency induces pathophysiological changes are yet to be elucidated, the hypothalamic–pituitary–adrenal (HPA) axis may be an important mediator of these effects. Cortisol, the primary hormone of the HPA axis, exhibits robust circadian rhythmicity and is moderately influenced by sleep and wake states and other physiology. Several studies have explored the effects of acute or chronic sleep deficiency (i.e., usually from self-selected chronic sleep restriction, CSR) on the HPA axis. Quantifying long-term changes in the circadian rhythm of cortisol under CSR in controlled conditions is inadequately studied due to practical limitations. We use a semi-mechanistic mathematical model of the HPA axis and the sleep/wake cycle to explore the influence of CSR on cortisol circadian rhythmicity. In qualitative agreement with experimental findings, model simulations predict that CSR results in physiologically relevant disruptions in the phase and amplitude of the cortisol rhythm. The mathematical model presented in this work provides a mechanistic framework to further explore how CSR might lead to HPA axis disruption and subsequent development of chronic metabolic complications.

The interindividual variability of sleep timing and circadian phase in humans is influenced by daytime and evening light conditions

Human cognitive functioning shows circadian variations throughout the day. However, individuals largely differ in their timing during the day of when they are more capable of performing specific tasks and when they prefer to sleep. These interindividual differences in preferred temporal organization of sleep and daytime activities define the chronotype. Since a late chronotype is associated with adverse mental and physical consequences, it is of vital importance to study how lighting environments affect chronotype. Here, we use a mathematical model of the human circadian pacemaker to understand how light in the built environment changes the chronotype distribution in the population. In line with experimental findings, we show that when individuals spend their days in relatively dim light conditions, this not only results in a later phase of their biological clock but also increases interindividual differences in circadian phase angle of entrainment and preferred sleep timing. Increasing daytime illuminance results in a more narrow distribution of sleep timing and circadian phase, and this effect is more pronounced for longer photoperiods. The model results demonstrate that modern lifestyle changes the chronotype distribution towards more eveningness and more extreme differences in eveningness. Such model-based predictions can be used to design guidelines for workplace lighting that help limiting circadian phase differences, and craft new lighting strategies that support human performance, health and wellbeing.