Brighter nights and darker days predict higher mortality risk: A prospective analysis of personal light exposure in >88,000 individuals.

Light enhances or disrupts circadian rhythms, depending on the timing of exposure. Circadian disruption contributes to poor health outcomes that increase mortality risk. Whether personal light exposure predicts mortality risk has not been established. We therefore investigated whether personal day and night light, and light patterns that disrupt circadian rhythms, predicted mortality risk. UK Biobank participants (N = 88,905, 62.4 ± 7.8 y, 57% female) wore light sensors for 1 wk. Day and night light exposures were defined by factor analysis of 24-h light profiles. A computational model of the human circadian pacemaker was applied to model circadian amplitude and phase from light data. Cause-specific mortality was recorded in 3,750 participants across a mean (±SD) follow-up period of 8.0 ± 1.0 y. Individuals with brighter day light had incrementally lower all-cause mortality risk (adjusted-HR ranges: 0.84 to 0.90 [50 to 70th light exposure percentiles], 0.74 to 0.84 [70 to 90th], and 0.66 to 0.83 [90 to 100th]), and those with brighter night light had incrementally higher all-cause mortality risk (aHR ranges: 1.15 to 1.18 [70 to 90th], and 1.21 to 1.34 [90 to 100th]), compared to individuals in darker environments (0 to 50th percentiles). Individuals with lower circadian amplitude (aHR range: 0.90 to 0.96 per SD), earlier circadian phase (aHR range: 1.16 to 1.30), or later circadian phase (aHR range: 1.13 to 1.20) had higher all-cause mortality risks. Day light, night light, and circadian amplitude predicted cardiometabolic mortality, with larger hazard ratios than for mortality by other causes. Findings were robust to adjustment for age, sex, ethnicity, photoperiod, and sociodemographic and lifestyle factors. Minimizing night light, maximizing day light, and keeping regular light-dark patterns that enhance circadian rhythms may promote cardiometabolic health and longevity.

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.

Greater sensitivity of the circadian system of women to bright light, but not dim-to-moderate light.

Women typically sleep and wake earlier than men and have been shown to have earlier circadian timing relative to the light/dark cycle that synchronizes the clock. A potential mechanism for earlier timing in women is an altered response of the circadian system to evening light. We characterized individual-level dose-response curves for light-induced melatonin suppression using a within-subjects protocol. Fifty-six participants (29 women, 27 men; aged 18-30 years) were exposed to a range of light illuminances (10, 30, 50, 100, 200, 400, and 2000 lux) using melatonin suppression relative to a dim control (<1 lux) as a marker of light sensitivity. Women were free from hormonal contraception. To examine the potential influence of sex hormones, estradiol and progesterone was examined in women and testosterone was examined in a subset of men. Menstrual phase was monitored using self-reports and estradiol and progesterone levels. Women exhibited significantly greater melatonin suppression than men under the 400-lux and 2000-lux conditions, but not under lower light conditions (10-200 lux). Light sensitivity did not differ by menstrual phase, nor was it associated with levels of estradiol, progesterone, or testosterone, suggesting the sex differences in light sensitivity were not acutely driven by circulating levels of sex hormones. These results suggest that sex differences in circadian timing are not due to differences in the response to dim/moderate light exposures typically experienced in the evening. The finding of increased bright light sensitivity in women suggests that sex differences in circadian timing could plausibly instead be driven by a greater sensitivity to phase-advancing effects of bright morning light.

A Protocol to Determine Circadian Phase by At-Home Salivary Dim Light Melatonin Onset Assessment.

Internal circadian phase assessment is increasingly acknowledged as a critical clinical tool for the diagnosis, monitoring, and treatment of circadian rhythm sleep-wake disorders and for investigating circadian timing in other medical disorders. The widespread use of in-laboratory circadian phase assessments in routine practice has been limited, most likely because circadian phase assessment is not required by formal diagnostic nosologies, and is not generally covered by insurance. At-home assessment of salivary dim light melatonin onset (DLMO, a validated circadian phase marker) is an increasingly accepted approach to assess circadian phase. This approach may help meet the increased demand for assessments and has the advantages of lower cost and greater patient convenience. We reviewed the literature describing at-home salivary DLMO assessment methods and identified factors deemed to be important to successful implementation. Here, we provide specific protocol recommendations for conducting at-home salivary DLMO assessments to facilitate a standardized approach for clinical and research purposes. Key factors include control of lighting, sampling rate, and timing, and measures of patient compliance. We include findings from implementation of an optimization algorithm to determine the most efficient number and timing of samples in patients with Delayed Sleep-Wake Phase Disorder. We also provide recommendations for assay methods and interpretation. Providing definitive criteria for each factor, along with detailed instructions for protocol implementation, will enable more widespread adoption of at-home circadian phase assessments as a standardized clinical diagnostic, monitoring, and treatment tool.

Pilot feasibility testing of biomathematical model recommendations for personalising sleep timing in shift workers.

Sleep disturbances and circadian disruption play a central role in adverse health, safety, and performance outcomes in shift workers. While biomathematical models of sleep and alertness can be used to personalise interventions for shift workers, their practical implementation is undertested. This study tested the feasibility of implementing two biomathematical models-the Phillips-Robinson Model and the Model for Arousal Dynamics-in 28 shift-working nurses, 14 in each group. The study examined the overlap and adherence between model recommendations and sleep behaviours, and changes in sleep following the implementation of recommendations. For both groups combined, the mean (SD) percentage overlap between when a model recommended an individual to sleep and when sleep was obtained was 73.62% (10.24%). Adherence between model recommendations and sleep onset and offset times was significantly higher with the Model of Arousal Dynamics compared to the Phillips-Robinson Model. For the Phillips-Robinson model, 27% of sleep onset and 35% of sleep offset times were within ± 30 min of model recommendations. For the Model of Arousal Dynamics, 49% of sleep onset, and 35% of sleep offset times were within ± 30 min of model recommendations. Compared to pre-study, significant improvements were observed post-study for sleep disturbance (Phillips-Robinson Model), and insomnia severity and sleep-related impairments (Model of Arousal Dynamics). Participants reported that using a digital, automated format for the delivery of sleep recommendations would enable greater uptake. These findings provide a positive proof-of-concept for using biomathematical models to recommend sleep in operational contexts.

Using Mendelian Randomisation methods to understand whether diurnal preference is causally related to mental health.

Late diurnal preference has been linked to poorer mental health outcomes, but the understanding of the causal role of diurnal preference on mental health and wellbeing is currently limited. Late diurnal preference is often associated with circadian misalignment (a mismatch between the timing of the endogenous circadian system and behavioural rhythms), so that evening people live more frequently against their internal clock. This study aims to quantify the causal contribution of diurnal preference on mental health outcomes, including anxiety, depression and general wellbeing and test the hypothesis that more misaligned individuals have poorer mental health and wellbeing using an actigraphy-based measure of circadian misalignment. Multiple Mendelian Randomisation (MR) approaches were used to test causal pathways between diurnal preference and seven well-validated mental health and wellbeing outcomes in up to 451,025 individuals. In addition, observational analyses tested the association between a novel, objective measure of behavioural misalignment (Composite Phase Deviation, CPD) and seven mental health and wellbeing outcomes. Using genetic instruments identified in the largest GWAS for diurnal preference, we provide robust evidence that early diurnal preference is protective for depression and improves wellbeing. For example, using one-sample MR, a twofold higher genetic liability of morningness was associated with lower odds of depressive symptoms (OR: 0.92, 95% CI: 0.88, 0.97). It is possible that behavioural factors including circadian misalignment may contribute in the chronotype depression relationship, but further work is needed to confirm these findings.

Unanticipated daytime melatonin secretion on a simulated night shift schedule generates a distinctive 24-h melatonin rhythm with antiphasic daytime and nighttime peaks.

The daily rhythm of plasma melatonin concentrations is typically unimodal, with one broad peak during the circadian night and near-undetectable levels during the circadian day. Light at night acutely suppresses melatonin secretion and phase shifts its endogenous circadian rhythm. In contrast, exposure to darkness during the circadian day has not generally been reported to increase circulating melatonin concentrations acutely. Here, in a highly-controlled simulated night shift protocol with 12-h inverted behavioral/environmental cycles, we unexpectedly found that circulating melatonin levels were significantly increased during daytime sleep (p < .0001). This resulted in a secondary melatonin peak during the circadian day in addition to the primary peak during the circadian night, when sleep occurred during the circadian day following an overnight shift. This distinctive diurnal melatonin rhythm with antiphasic peaks could not be readily anticipated from the behavioral/environmental factors in the protocol (e.g., light exposure, posture, diet, activity) or from current mathematical model simulations of circadian pacemaker output. The observation, therefore, challenges our current understanding of underlying physiological mechanisms that regulate melatonin secretion. Interestingly, the increase in melatonin concentration observed during daytime sleep was positively correlated with the change in timing of melatonin nighttime peak (p = .002), but not with the degree of light-induced melatonin suppression during nighttime wakefulness (p = .92). Both the increase in daytime melatonin concentrations and the change in the timing of the nighttime peak became larger after repeated exposure to simulated night shifts (p = .002 and p = .006, respectively). Furthermore, we found that melatonin secretion during daytime sleep was positively associated with an increase in 24-h glucose and insulin levels during the night shift protocol (p = .014 and p = .027, respectively). Future studies are needed to elucidate the key factor(s) driving the unexpected daytime melatonin secretion and the melatonin rhythm with antiphasic peaks during shifted sleep/wake schedules, the underlying mechanisms of their relationship with glucose metabolism, and the relevance for diabetes risk among shift workers.

High sensitivity and interindividual variability in the response of the human circadian system to evening light.

Before the invention of electric lighting, humans were primarily exposed to intense (>300 lux) or dim (<30 lux) environmental light-stimuli at extreme ends of the circadian system's dose-response curve to light. Today, humans spend hours per day exposed to intermediate light intensities (30-300 lux), particularly in the evening. Interindividual differences in sensitivity to evening light in this intensity range could therefore represent a source of vulnerability to circadian disruption by modern lighting. We characterized individual-level dose-response curves to light-induced melatonin suppression using a within-subjects protocol. Fifty-five participants (aged 18-30) were exposed to a dim control (<1 lux) and a range of experimental light levels (10-2,000 lux for 5 h) in the evening. Melatonin suppression was determined for each light level, and the effective dose for 50% suppression (ED50) was computed at individual and group levels. The group-level fitted ED50 was 24.60 lux, indicating that the circadian system is highly sensitive to evening light at typical indoor levels. Light intensities of 10, 30, and 50 lux resulted in later apparent melatonin onsets by 22, 77, and 109 min, respectively. Individual-level ED50 values ranged by over an order of magnitude (6 lux in the most sensitive individual, 350 lux in the least sensitive individual), with a 26% coefficient of variation. These findings demonstrate that the same evening-light environment is registered by the circadian system very differently between individuals. This interindividual variability may be an important factor for determining the circadian clock's role in human health and disease.

Wearable light spectral sensor optimized for measuring daily α-opic light exposure.

Light has many non-visual effects on human physiology, including alterations in sleep, mood, and alertness. These effects are mainly mediated by photoreceptors containing the photopigment melanopsin, which has a peak sensitivity to short wavelength ('blue') light. Commercially available light sensors are commonly wrist-worn and report photopic illuminance and are calibrated to perceive visual brightness and hence cannot be used to investigate the non-visual impacts of light. In this paper, we report the development of a wearable spectrophotometer designed to be worn as a pendant or affixed to clothing to capture spectral power density data close to eye level in the visible wavelength range 380-780 nm. From this, the relative impact of a given light stimulus can be determined for each photoreceptive input in the human eye by calculating effective illuminances. This device showed high accuracy for all effective illuminances while measuring a range of commonly encountered light sources by calibrating for directional response, dark noise, sensor saturation, non-linearity, stray-light and spectral response. Features of the device include IoT-integration, onboard data storage and processing, Bluetooth Low Energy (BLE) enabled data transfer, and cloud storage in one cohesive unit.

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.

A classification approach to estimating human circadian phase under circadian alignment from actigraphy and photometry data.

The time of dim light melatonin onset (DLMO) is the gold standard for circadian phase assessment in humans, but collection of samples for DLMO is time and resource-intensive. Numerous studies have attempted to estimate circadian phase from actigraphy data, but most of these studies have involved individuals on controlled and stable sleep-wake schedules, with mean errors reported between 0.5 and 1 hour. We found that such algorithms are less successful in estimating DLMO in a population of college students with more irregular schedules: Mean errors in estimating the time of DLMO are approximately 1.5-1.6 hours. We reframed the problem as a classification problem and estimated whether an individual's current phase was before or after DLMO. Using a neural network, we found high classification accuracy of about 90%, which decreased the mean error in DLMO estimation-identifying the time at which the switch in classification occurs-to approximately 1.3 hours. To test whether this classification approach was valid when activity and circadian rhythms are decoupled, we applied the same neural network to data from inpatient forced desynchrony studies in which participants are scheduled to sleep and wake at all circadian phases (rather than their habitual schedules). In participants on forced desynchrony protocols, overall classification accuracy dropped to 55%-65% with a range of 20%-80% for a given day; this accuracy was highly dependent upon the phase angle (ie, time) between DLMO and sleep onset, with the highest accuracy at phase angles associated with nighttime sleep. Circadian patterns in activity, therefore, should be included when developing and testing actigraphy-based approaches to circadian phase estimation. Our novel algorithm may be a promising approach for estimating the onset of melatonin in some conditions and could be generalized to other hormones.

Increased sensitivity of the circadian system to light in delayed sleep-wake phase disorder.

KEY POINTS: This is the first study to demonstrate an altered circadian phase shifting response in a circadian rhythm sleep disorder. Patients with delayed sleep-wake phase disorder (DSWPD) demonstrate greater sensitivity of the circadian system to the phase-delaying effects of light. Increased circadian sensitivity to light is associated with later circadian timing within both control and DSWPD groups. DSWPD patients had a greater sustained pupil response after light exposure. Treatments for DSWPD should consider sensitivity of the circadian system to light as a potential underlying vulnerability, making patients susceptible to relapse. ABSTRACT: Patients with delayed sleep-wake phase disorder (DSWPD) exhibit delayed sleep-wake behaviour relative to desired bedtime, often leading to chronic sleep restriction and daytime dysfunction. The majority of DSWPD patients also display delayed circadian timing in the melatonin rhythm. Hypersensitivity of the circadian system to phase-delaying light is a plausible physiological basis for DSWPD vulnerability. We compared the phase shifting response to a 6.5 h light exposure (∼150 lux) between male patients with diagnosed DSWPD (n = 10; aged 20.8 ± 2.3 years) and male healthy controls (n = 11; aged 22.4 ± 3.3 years). Salivary dim light melatonin onset (DLMO) was measured under controlled conditions in dim light (<3 lux) before and after light exposure. Correcting for the circadian time of the light exposure, DSWPD patients exhibited 31.5% greater phase delay shifts than healthy controls. In both groups, a later initial melatonin phase was associated with a greater magnitude phase shift, indicating that increased circadian sensitivity to light may be a factor that contributes to delayed phase, even in non-clinical groups. DSWPD patients also had reduced pupil size following the light exposure, and showed a trend towards increased melatonin suppression during light exposure. These findings indicate that, for patients with DSWPD, assessment of light sensitivity may be an important factor that can inform behavioural therapy, including minimization of exposure to phase-delaying night-time light.

Modeling the adenosine system as a modulator of cognitive performance and sleep patterns during sleep restriction and recovery.

Sleep loss causes profound cognitive impairments and increases the concentrations of adenosine and adenosine A1 receptors in specific regions of the brain. Time courses for performance impairment and recovery differ between acute and chronic sleep loss, but the physiological basis for these time courses is unknown. Adenosine has been implicated in pathways that generate sleepiness and cognitive impairments, but existing mathematical models of sleep and cognitive performance do not explicitly include adenosine. Here, we developed a novel receptor-ligand model of the adenosine system to test the hypothesis that changes in both adenosine and A1 receptor concentrations can capture changes in cognitive performance during acute sleep deprivation (one prolonged wake episode), chronic sleep restriction (multiple nights with insufficient sleep), and subsequent recovery. Parameter values were estimated using biochemical data and reaction time performance on the psychomotor vigilance test (PVT). The model closely fit group-average PVT data during acute sleep deprivation, chronic sleep restriction, and recovery. We tested the model's ability to reproduce timing and duration of sleep in a separate experiment where individuals were permitted to sleep for up to 14 hours per day for 28 days. The model accurately reproduced these data, and also correctly predicted the possible emergence of a split sleep pattern (two distinct sleep episodes) under these experimental conditions. Our findings provide a physiologically plausible explanation for observed changes in cognitive performance and sleep during sleep loss and recovery, as well as a new approach for predicting sleep and cognitive performance under planned schedules.

Sex difference in the near-24-hour intrinsic period of the human circadian timing system.

The circadian rhythms of melatonin and body temperature are set to an earlier hour in women than in men, even when the women and men maintain nearly identical and consistent bedtimes and wake times. Moreover, women tend to wake up earlier than men and exhibit a greater preference for morning activities than men. Although the neurobiological mechanism underlying this sex difference in circadian alignment is unknown, multiple studies in nonhuman animals have demonstrated a sex difference in circadian period that could account for such a difference in circadian alignment between women and men. Whether a sex difference in intrinsic circadian period in humans underlies the difference in circadian alignment between men and women is unknown. We analyzed precise estimates of intrinsic circadian period collected from 157 individuals (52 women, 105 men; aged 18-74 y) studied in a month-long inpatient protocol designed to minimize confounding influences on circadian period estimation. Overall, the average intrinsic period of the melatonin and temperature rhythms in this population was very close to 24 h [24.15 ± 0.2 h (24 h 9 min ± 12 min)]. We further found that the intrinsic circadian period was significantly shorter in women [24.09 ± 0.2 h (24 h 5 min ± 12 min)] than in men [24.19 ± 0.2 h (24 h 11 min ± 12 min); P < 0.01] and that a significantly greater proportion of women have intrinsic circadian periods shorter than 24.0 h (35% vs. 14%; P < 0.01). The shorter average intrinsic circadian period observed in women may have implications for understanding sex differences in habitual sleep duration and insomnia prevalence.

Aversion to light is associated with impulsivity.

Exposure to bright light can be visually aversive. This study explored the association between light aversion and various facets of impulsivity. A total of 1,245 participants completed the UPPS-Impulsive Behavior Scale to assess five facets of impulsivity. Additionally, participants responded to questions regarding their aversion to light (e.g., how aversive do you find bright light?). Spearman's correlation coefficients (rho) revealed that individuals who find light physically aversive, or who experience a negative physical response to exposure (e.g., nausea or headache) triggered by bright indoor light or sunlight, tend to act impulsively under extreme negative and positive affect. Individuals who experience a negative physical response to exposure display greater premeditation, indicating a higher likelihood of considering the potential consequences of their actions. Moreover, these individuals score lower on sensation-seeking, suggesting a reduced inclination to seek out thrilling or novel experiences. These results reveal a complex relationship between light aversion and impulsivity, where those who find light aversive tend to be less impulsive in general, but more impulsive under extreme positive or negative affect.

Power Analysis for Human Melatonin Suppression Experiments.

In humans, the nocturnal secretion of melatonin by the pineal gland is suppressed by ocular exposure to light. In the laboratory, melatonin suppression is a biomarker for this neuroendocrine pathway. Recent work has found that individuals differ substantially in their melatonin-suppressive response to light, with the most sensitive individuals being up to 60 times more sensitive than the least sensitive individuals. Planning experiments with melatonin suppression as an outcome needs to incorporate these individual differences, particularly in common resource-limited scenarios where running within-subjects studies at multiple light levels is costly and resource-intensive and may not be feasible with respect to participant compliance. Here, we present a novel framework for virtual laboratory melatonin suppression experiments, incorporating a Bayesian statistical model. We provide a Shiny web app for power analyses that allows users to modify various experimental parameters (sample size, individual-level heterogeneity, statistical significance threshold, light levels), and simulate a systematic shift in sensitivity (e.g., due to a pharmacological or other intervention). Our framework helps experimenters to design compelling and robust studies, offering novel insights into the underlying biological variability in melatonin suppression relevant for practical applications.

Sleep regularity is a stronger predictor of mortality risk than sleep duration: A prospective cohort study.

Abnormally short and long sleep are associated with premature mortality, and achieving optimal sleep duration has been the focus of sleep health guidelines. Emerging research demonstrates that sleep regularity, the day-to-day consistency of sleep-wake timing, can be a stronger predictor for some health outcomes than sleep duration. The role of sleep regularity in mortality, however, has not been investigated in a large cohort with objective data. We therefore aimed to compare how sleep regularity and duration predicted risk for all-cause and cause-specific mortality. We calculated Sleep Regularity Index (SRI) scores from > 10 million hours of accelerometer data in 60 977 UK Biobank participants (62.8 ±â€…7.8 years, 55.0% female, median[IQR] SRI: 81.0[73.8-86.3]). Mortality was reported up to 7.8 years after accelerometer recording in 1859 participants (4.84 deaths per 1000 person-years, mean (±SD) follow-up of 6.30 ±â€…0.83 years). Higher sleep regularity was associated with a 20%-48% lower risk of all-cause mortality (p < .001 to p = 0.004), a 16%-39% lower risk of cancer mortality (p < 0.001 to p = 0.017), and a 22%-57% lower risk of cardiometabolic mortality (p < 0.001 to p = 0.048), across the top four SRI quintiles compared to the least regular quintile. Results were adjusted for age, sex, ethnicity, and sociodemographic, lifestyle, and health factors. Sleep regularity was a stronger predictor of all-cause mortality than sleep duration, by comparing equivalent mortality models, and by comparing nested SRI-mortality models with and without sleep duration (p = 0.14-0.20). These findings indicate that sleep regularity is an important predictor of mortality risk and is a stronger predictor than sleep duration. Sleep regularity may be a simple, effective target for improving general health and survival.

Adaptation of sleep to daylight saving time is slower in people consuming a high-fat diet.

Adaptation of the circadian clock to the environment is essential for optimal health, well-being, and performance. Animal models demonstrate that a high-fat diet impairs circadian adaptation to advances of the light-dark cycle; it is unknown whether this occurs in humans. Utilizing a natural experiment that occurs when humans must advance their behaviors to an earlier hour for daylight saving time (DST), we measured the influence of diet on sleep/wake timing relative to dim-light melatonin onset time. Students with a lower-fat diet rapidly altered their sleep-wake timing to match the imposed time change, whereas those with a high-fat diet were slower to adapt to the time change. Moreover, a faster shift in timing after DST was associated with higher general health, lower body mass index, and higher grade point average. These data suggest that diet may influence the speed of sleep and circadian adaptation, which could have implications for health and performance.

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.