ObjectivesMany sleep-wake behaviors have been associated with cognition. We examined a panel of sleep-wake/activity characteristics to determine which are most robustly related to having low cognitive performance in midlife. Secondarily, we evaluate the predictive utility of sleep-wake measures to screen for low cognitive performance.MethodsThe outcome was low cognitive performance defined as being >1 standard deviation below average age/sex/education internally normalized composite cognitive performance levels assessed in the Hispanic Community Health Study/Study of Latinos. Analyses included 1006 individuals who had sufficient sleep-wake measurements about 2years later (mean age=54.9, standard deviation= 5.1; 68.82% female). We evaluated associations of 31 sleep-wake variables with low cognitive performance using separate logistic regressions.ResultsIn individual models, the strongest sleep-wake correlates of low cognitive performance were measures of weaker and unstable 24-hour rhythms; greater 24-hour fragmentation; longer time-in-bed; and lower rhythm amplitude. One standard deviation worse on these sleep-wake factors was associated with ∼20%-30% greater odds of having low cognitive performance. In an internally cross-validated prediction model, the independent correlates of low cognitive performance were: lower Sleep Regularity Index scores; lower pseudo-F statistics (modellability of 24-hour rhythms); lower activity rhythm amplitude; and greater time in bed. Area under the curve was low/moderate (64%) indicating poor predictive utility.ConclusionThe strongest sleep-wake behavioral correlates of low cognitive performance were measures of longer time-in-bed and irregular/weak rhythms. These sleep-wake assessments were not useful to identify previous low cognitive performance. Given their potential modifiability, experimental trials could test if targeting midlife time-in-bed and/or irregular rhythms influences cognition.

Abstract A potential contributor to insufficient sleep among college students is their daily schedule, with sleep sacrificed for other waking activities. We investigated how daily schedules predict day-to-day sleep-wake timing in college students. 223 undergraduate college students (M±SD = 19.2±1.4 years, 37% females) attending a Massachusetts university in the US between 2013–2016 were monitored for approximately 30 days during semester. Sleep-wake timing was measured using daily online sleep diaries and wrist-actigraphy. Daily schedules were measured using daily online diaries that included self-reported timing and duration of academic, exercise-based, and extracurricular activities, and duration of self-study. Linear mixed models were used to examine the association between sleep-wake patterns and daily schedules at both the between-person and within-person levels. An earlier start time of the first-reported activity predicted earlier sleep onset (between and within: p<.001) and shorter total sleep time (within: p<.001) for the previous night, as well as earlier wake onset on the corresponding day (between and within: p<.001). A later end time of the last-reported activity predicted later sleep onset (within: p=.002) and shorter total sleep time (within: p=.02) on that night. A more intense daily schedule (i.e., greater total duration of reported activities) predicted an earlier wake onset time (between: p=.003, within: p<.001), a later sleep onset time (within: p<.001), a shortened total night-time sleep duration (between: p=.03, within: p<.001), and greater sleep efficiency (within: p<.001). These results indicate that college students may organize their sleep and wake times based on their daily schedule.

This chapter explores the causes, consequences, and countermeasures of jet lag, mistimed sleep, and sleep inertia. Jet lag can occur when rapidly crossing multiple time zones (e.g., trans-meridian travel for long-haul pilots). The desynchrony between the body's biological clock, or circadian rhythm, and the new day-night cycle can lead to indigestion, sleep disturbances, fatigue, and cognitive impairments. Mistimed sleep can also occur within a time zone. In the case of night shiftwork, sleep is displaced to the daytime which leads to poor sleep and increased fatigue at night due to the combination of pressures from the two-process model of sleep regulation: sleep loss (homeostatic pressure) and being awake when the body is promoting sleep (circadian pressure). There is also a third process of sleep regulation called sleep inertia, which refers to the brief period of fatigue and impaired cognitive performance experienced after waking. Sleep inertia can be a fatigue risk for transportation workers who work on-call (e.g., emergency services) or who nap on shift (e.g., long-haul truck drivers) and are required to perform a safety-critical task soon after waking. For each of these fatigue risks, strategic exposure to bright light can be used to help realign sleep timing and to promote alertness.

EDITORIAL article Front. Endocrinol., 22 August 2023Sec. Neuroendocrine Science Volume 14 - 2023 | https://doi.org/10.3389/fendo.2023.1268940

Light is the predominant signal for the human circadian clock to synchronize to the solar 24-h day through an active process called entrainment. Modern light profiles are characterized by exposure to both natural daylight and artificial lighting. A mismatch between these self-selected light profiles and the solar day-night alternation can disrupt the circadian system, resulting in acute and chronic effects for health and safety. In this chapter, we describe (i) how entrainment works in the real world, illustrating the major role of light for this process; (ii) ways in which the circadian system can be disrupted by (external) factors such as irregular sleep, shift work, daylight saving time, and longitudinal position in a time zone; and (iii) how field studies have used light interventions to reduce direct and indirect effects of circadian disruption in ecological settings.

The availability of electrical light has altered modern light exposure, affecting the synchronization process ('entrainment') of the circadian clock to the natural light-dark cycle. The discrepancy between the natural light-dark cycle and self-selected light exposure has raised the question whether humans entrain to sun time (as most organisms do) vs. social time. None of the studies addressing this question have been conducted in the US in a large-scale, nationally representative sample. In this brief report, we aimed at estimating the relationship between individual chronotype (the result of the entrainment process) and longitude position in a time zone, using 12 years (2003-2014) of pooled diary data (n = 50,753) from the American Time Use Survey (ATUS). Chronotype was estimated based on mid-sleep time on weekends (MSFWe), a proxy that was previously shown to replicate known age and sex differences in chronotype in the ATUS. Longitude position was derived from state-level information (e.g., average state border outline). Regression results showed a progressive delay in MSFWe from east to west within three of the four US continental time zones (delay per degree of longitude): Eastern, 1.8 min; Central, 1.2 min; Mountain, 2.4 min (all p < .01). The findings suggest that humans entrain to sun time, leading to an increasing discrepancy between social time and biological time ("circadian misalignment") towards the west of a time zone. Such a misalignment induced by where people live within a time zone may affect a large share of the population, with implications for health and safety.

Growing evidence shows that sex differences impact many facets of human biology. Here we review and discuss the impact of sex on human circadian and sleep physiology, and we uncover a data gap in the field investigating the non-visual effects of light in humans. A virtual workshop on the biomedical implications of sex differences in sleep and circadian physiology led to the following imperatives for future research: i) design research to be inclusive and accessible; ii) implement recruitment strategies that lead to a sex-balanced sample; iii) use data visualization to grasp the effect of sex; iv) implement statistical analyses that include sex as a factor and/or perform group analyses by sex, where possible; v) make participant-level data open and available to facilitate future meta-analytic efforts.

Hintergrund Adnextumore in der Schwangerschaft werden entweder als Zufallsbefund oder akutes Ereignis diagnostiziert und betreffen ca. eine von 500 Schwangerschaften. Dabei steht die Torsion des Corpus luteum, insbesondere in Assoziation mit einem ovariellen Überstimulationssyndrom an erster Stelle. Dermoidzysten sind der zweithäufigste Befund, erscheinen jedoch meist asymptomatisch, wobei 20% aller Teratome in der Schwangerschaft diagnostiziert werden.

STUDY OBJECTIVES:Sleep regularity predicts many health-related outcomes. Currently, however, there is no systematic approach to measuring sleep regularity. Traditionally, metrics have assessed deviations in sleep patterns from an individual's average; these traditional metrics include intra-individual standard deviation (StDev), interdaily stability (IS), and social jet lag (SJL). Two metrics were recently proposed that instead measure variability between consecutive days: composite phase deviation (CPD) and sleep regularity index (SRI). Using large-scale simulations, we investigated the theoretical properties of these five metrics. METHODS:Multiple sleep-wake patterns were systematically simulated, including variability in daily sleep timing and/or duration. Average estimates and 95% confidence intervals were calculated for six scenarios that affect the measurement of sleep regularity: "scrambling" the order of days; daily vs. weekly variation; naps; awakenings; "all-nighters"; and length of study. RESULTS:SJL measured weekly but not daily changes. Scrambling did not affect StDev or IS, but did affect CPD and SRI; these metrics, therefore, measure sleep regularity on multi-day and day-to-day timescales, respectively. StDev and CPD did not capture sleep fragmentation. IS and SRI behaved similarly in response to naps and awakenings but differed markedly for all-nighters. StDev and IS required over a week of sleep-wake data for unbiased estimates, whereas CPD and SRI required larger sample sizes to detect group differences. CONCLUSIONS:Deciding which sleep regularity metric is most appropriate for a given study depends on a combination of the type of data gathered, the study length and sample size, and which aspects of sleep regularity are most pertinent to the research question.

After a flight across multiple time zones, most people show a transient state of circadian misalignment causing temporary malaise known as jetlag disorder. The severity of the elicited symptoms is postulated to depend mostly on circadian factors such as the number of time zones crossed and the direction of travel. Here, we examined the influence of prior expectation on symptom severity, compared to said “classic” determinants, in order to gauge potential psychosocial effects in jetlag disorder. To this end, we monitored jetlag symptoms in travel-inexperienced individuals (n=90, 18-37y) via detailed questionnaires twice daily for one week before and after flights crossing >3 time zones. We found pronounced differences in individual symptom load that could be grouped into 4 basic symptom trajectories. Both traditional and newly devised metrics of jetlag symptom intensity and duration (accounting for individual symptom trajectories) recapitulated previous results of jetlag prevalence at about 50-60% as well as general symptom dynamics. Surprisingly, however, regression models showed very low predictive power for any of the jetlag outcomes. The classic circadian determinants, including number of time zones crossed and direction of travel, exhibited little to no link with jetlag symptom intensity and duration. Only expectation emerged as a parameter with systematic, albeit small, predictive value. These results suggest expectation as a relevant factor in jetlag experience - hinting at potential placebo effects and new treatment options. Our findings also caution against jetlag recommendations based on circadian principles but insufficient evidence linking circadian re-synchronization dynamics with ensuing symptom intensity and duration. Significance Statement Jetlag disorder afflicts millions of travelers each year - a nuisance on holiday trips but also a danger in safety and performance-critical operations. For effective prevention and treatment, it is critical to understand what influences jetlag severity, i.e. jetlag symptom intensity and duration. In contrast to what guidelines state, in our study, we did not find that symptom severity could be explained by the number of time zones crossed or travel direction. Rather, travelers’ expectations about how long and strongly they will suffer from jetlag symptoms was the only factor systematically predicting jetlag severity. If this holds true not only for subjective but also objective symptoms, we need to revisit assumptions about how circadian desynchronization relates to experienced jetlag symptoms.

Decision-making in organizations is often complex and involves groups, which have access to the pool of perspectives and knowledge their members hold individually. However, groups frequently fail to use their full decision-making potential. The concept of integrative complexity (IC) captures how complex decision-making profits from the differentiation and integration of diverse perspectives and knowledge. In a laboratory experiment with 4 conditions ( N = 12 groups of 4 students per condition), we found that group dissent enhanced differentiation and a stepwise recapitulation of the group discussion enhanced integration, thereby raising group-level IC. Dissent groups who performed a stepwise recapitulation reached the highest levels of group IC compared to ordinary dissent groups, consent groups, and individuals working alone. They also exceeded their own best member and achieved an equal level of IC to that of the best members of nominal groups. The study contributes to the body of research identifying factors that support groups in exploiting their potential and reaching more informed decisions and judgments.

Hintergrund In 0,1% aller Schwangerschaften treten Malignome auf. Lymphome sind hierbei die viert-häufigsten und stellen durch unspezifische Symptome ähnlich Schwangerschafts-assoziierten Beschwerden und eingeschränkten Bildgebungsmöglichkeiten eine besondere Herausforderung in der Diagnosestellung dar. Das diffuse großzellige B-Zell-Lymphom tritt als häufigstes Non-Hodgkin-Lymphom in der Schwangerschaft auf [1].

The study aimed to explore chronotype-specific effects of two versus four consecutive morning or night shifts on sleep-wake behavior. Sleep debt and social jetlag (a behavioral proxy of circadian misalignment) were estimated from sleep diary data collected for 5 weeks in a within-subject field study of 30 rotating night shift workers (29.9 ± 7.3 years, 60% female). Mixed models were used to examine whether effects of shift sequence length on sleep are dependent on chronotype, testing the interaction between sequence length (two vs. four) and chronotype (determined from sleep diaries). Analyses of two versus four morning shifts showed no significant interaction effects with chronotype. In contrast, increasing the number of night shifts from two to four increased sleep debt in early chronotypes, but decreased sleep debt in late types, with no change in intermediate ones. In early types, the higher sleep debt was due to accumulated sleep loss over four night shifts. In late types, sleep duration did not increase over the course of four night shifts, so that adaptation is unlikely to explain the observed lower sleep debt. Late types instead had increased sleep debt after two night shifts, which was carried over from two preceding morning shifts in this schedule. Including naps did not change the findings. Social jetlag was unaffected by the number of consecutive night shifts. Our results suggest that consecutive night shifts should be limited in early types. For other chronotypes, working four night shifts might be a beneficial alternative to working two morning and two night shifts. Studies should record shift sequences in rotating schedules.

Cross-sectional observations have shown that the timing of eating may be important for health-related outcomes. Here we examined the stability of eating timing, using both clock hour and relative circadian time, across one semester (n = 14) at daily and monthly time-scales. At three time points ~ 1 month apart, circadian phase was determined during an overnight in-laboratory visit and eating was photographically recorded for one week to assess timing and composition. Day-to-day stability was measured using the Composite Phase Deviation (deviation from a perfectly regular pattern) and intraclass correlation coefficients (ICC) were used to determine individual stability across months (weekly average compared across months). Day-to-day clock timing of caloric events had poor stability within individuals (~ 3-h variation; ICC = 0.12–0.34). The timing of eating was stable across months (~ 1-h variation, ICCs ranging from 0.54–0.63), but less stable across months when measured relative to circadian timing (ICC = 0.33–0.41). Our findings suggest that though day-to-day variability in the timing of eating has poor stability, the timing of eating measured for a week is stable across months within individuals. This indicates two relevant timescales: a monthly timescale with more stability in eating timing than a daily timescale. Thus, a single day’s food documentation may not represent habitual (longer timescale) patterns.