bluuebunny/crossref_metadata_2025_split huggingface dataset:
119 Behavioral Attention and Sleepiness Display Robust Stable Relationships Across Sleep Loss but not Across Recovery
Authors: Goel Namni , Casale Courtney , Brieva Tess , Antler Caroline , Yamazaki Erika 
Published: May 2021

Abstract

Introduction
The 10-minute and 3-minute versions of the Psychomotor Vigilance Test (PVT10 and PVT3) and the Karolinska Sleepiness Scale (KSS) are commonly used to assess objective behavioral attention deficits and subjective sleepiness in response to sleep loss, respectively. However, the precise time course of relationships between behavioral attention and subjective sleepiness across sleep loss and recovery remains unknown but is critical for determining whether objective and subjective measures track each other. Repeated measures correlation (rmcorr) examined within-individual association between these measures throughout a highly controlled sleep deprivation study.

Methods
Forty-one healthy adults (ages 21-49;mean±SD, 33.9±8.9y;18 females) participated in a 13-night experiment consisting of two baseline nights (10h-12h time-in-bed, TIB) followed by 5 sleep restriction (SR) nights (4h TIB), 4 recovery nights (12h TIB), and 36h total sleep deprivation (TSD). A neurobehavioral test battery, including the PVT10, PVT3, and KSS, was administered every 2h during wakefulness. Rmcorr compared PVT10 [lapses (reaction time [RT] &gt;500ms) and 1/RT (response speed)], PVT3 (lapses [RT&gt;355ms], 1/RT), and KSS scores by examining correlations by day (e.g., Baseline day 2) and time point (e.g., 1000h-2000h). Rmcorr ranges: r=0.1:small; r=0.3:moderate; r=0.5:large.

Results
Generally, the correlations between the PVT10 and KSS and the PVT3 and KSS showed a similar pattern for lapses and 1/RT. PVT lapses and KSS scores showed small or non-significant correlations during baseline and recovery, whereas SR and TSD showed moderate correlations. PVT 1/RT and KSS scores showed moderate correlations during baseline, moderate to large correlations during SR and TSD, but small correlations during recovery. PVT10 and PVT3 1/RT showed stronger correlations with KSS scores than lapses. Additionally, all relationships showed moderate to large correlations by time point across the study.

Conclusion
Overall, the relationship between behavioral attention and sleepiness was stronger across sleep loss (SR or TSD) relative to fully rested states while it was consistently relatively strong at specific times of day throughout the study. In contrast to published literature, there is a remarkably stable relationship between an individual’s objective behavioral attention performance and perceptions of sleepiness during sleep loss, which is not evident during recovery or at baseline.

Support (if any)
ONR Award No. N00014-11-1-0361;NIH UL1TR000003;NASA NNX14AN49G and 80NSSC20K0243;NIH R01DK117488
151 Sex Differences in the Maturational Trajectories of Sleep Spindles in the Transition from Childhood to Adolescence
Authors: Ricci Anna , He Fan , Younes Magdy , Calhoun Susan , Fang Jidong , Houser Lyndsey , Vgontzas Alexandros , Liao Duanping , Bixler Edward , Fernandez-Mendoza Julio 
Published: May 2021

Abstract

Introduction
Sleep spindles occur as bursts of EEG activity in the sigma (11-16 Hz) frequency range and are purported biomarkers of cortical development. However, the few studies examining maturational changes in sleep spindles are limited by small samples and/or short follow-up periods. Thus, large longitudinal population-based studies are needed to determine their developmental trajectories as the child transitions to adolescence.

Methods
We analyzed the sleep EEG of 572 un-medicated subjects aged 6-21 (47.6% female, 25.9% racial/ethnic minority), of whom 332 were 5-12 years at baseline and followed-up at ages 12-22. Multivariable-adjusted models tested the cross-sectional and longitudinal trajectories of sleep spindle density, frequency, and power.

Results
From age 6 to 21, the trajectory of sleep spindle density was best fit by a quadratic model (p=0.02), particularly in males (p-quadratic=0.05). Females maintained more stable levels of sleep spindle density (p-linear=0.26), as shown by a longitudinal increase 37.6% lower than males by age 14 (p=0.01). Sleep spindle frequency increased (p-linear&lt;0.01), while sleep spindle power decreased (p-linear&lt;0.01), from age 6 to 21. The trajectory of sleep spindle frequency diverged between females (p-linear&lt;0.01) and males (p-quadratic=0.02), in whom it plateaued by age 15 onwards. Females had experienced a longitudinal increase in sleep spindle frequency 2.4% higher than males by age 20-22 (p=0.05). Males had experienced a steeper decreasing slope in sleep spindle power (p-linear&lt;0.01) than females (p-linear=0.12), as confirmed by a longitudinal decline 25.4% greater than females by age 19 (p=0.02).

Conclusion
Sleep spindle metrics follow distinct maturational trajectories from each other and from other EEG oscillations (e.g., slow wave activity). The increase in sleep spindle density from childhood to early adolescence coupled with the linear increase in sleep spindle frequency from childhood to young adulthood may represent the emergence of fast sleep spindles, which appears to occur earlier in females. Overall, males experience greater maturational changes in all sleep spindle metrics and sex differences become prominent in young adulthood, when males show lower sleep spindle density and sleep spindle frequency, indicative of less fast sleep spindles.

Support (if any)
NIH Awards Number R01MH118308, R01HL136587, R01HL97165, R01HL63772, UL1TR000127
163 Actigraphy-measured circadian factors and mortality in US adults: Results from the NHANES
Authors: Lin Zhuozhi , Rojo-Wissar Darlynn , Nestadt Paul , Urbanek Jacek , Di Junrui , Zipunnikov Vadim , Spira Adam 
Published: May 2021

Abstract

Introduction
Chronotype is a potentially modifiable contributor to human well-being and longevity, with eveningness commonly linked to poorer outcomes. We examined the relationship between actigraphy-measured chronotype and all-cause mortality in a nationally representative sample of US adults. We also examined the association between social jetlag, a measure of circadian misalignment, and all-cause mortality.

Methods
Data were from 2,256 participants ≥50 from the National Health and Nutrition Examination Survey 2003-2006 cohorts. Participants were asked to wear a hip-worn Actigraph 7164 uni-axial activity monitor for 7 days, and to remove the device for sleep. Objectively-measured bedtime (OBT) was computed as the start of the non-wear period with the longest duration within each 24h period. Duration of the in-bed period (OBT-D) was computed as the hours from OBT to the end of the in-bed period. Midpoint of OBT (OBT-M) was computed as the midpoint between OBT and the end of the in-bed period. Chronotype was estimated using the average OBT-M separately for weekdays, weekends (Friday and Saturday nights), and all days combined. A weekend OBT-M corrected for sleep debt for participants with weekend OBT-D&gt;weekday OBT-D was also computed. The following formula was applied to correct for sleep debt: weekend OBT-M minus ((weekend OBT-D minus weekday OBT-D)/2). Consistent with previous research, OBT-Ms were categorized into intermediate (≥3:30am & ≤4:30am), morningness (&lt;3:30am), and eveningness (&gt;4:30am) chronotypes. Social jetlag was defined as the difference between weekend and weekday OBT-Ms and expressed in hours. Survey-weighted Cox proportional hazard models were used to examine the relationship between circadian factors and all-cause mortality. There were 642 deaths, excluding accidental deaths.

Results
Adjusted for age, sex, race, SES, BMI, smoking and drinking status, comorbidities, and average OBT-D, an eveningness chronotype (i.e., weekend OBT-M corrected for sleep debt) was associated with a greater hazard of death compared to an intermediate chronotype (HR=1.68, 95% CI=1.25, 2.26). There were no other significant associations.

Conclusion
Evening-oriented chronotype is associated with greater mortality risk in adults aged ≥50. To our knowledge, this is the first study to report the link between chronotype, estimated objectively via actigraphy, and all-cause mortality in a nationally representative sample.

Support (if any)
NIH grant 5T32MH014592-39.
173 The Bidirectional Relationships Between Sleep, Psychological Stress, and Negative Mood in Daily Life among Healthy Latinx Adults
Authors: Alcantara Carmela , Giorgio Luciana , Diaz Sarah , Morris Melanie , He Yun , Li Gen , Schwartz Joseph , Basner Robert , Redline Susan , Davidson Karina 
Published: May 2021

Abstract

Introduction
While psychological stress is adversely linked to sleep, the bidirectional and temporal relationships between sleep and psychological stress in the context of daily life are largely understudied, particularly among Latinxs. We examined the bidirectional relationships between daily sleep duration, sleep quality, perceived stress, and negative mood in Latinx adults.

Methods
Between 2016-2019, healthy Latinxs (N=42), defined as those without any major physical or psychiatric morbidities, and free from polysomnography-assessed sleep disorders, were recruited from a community sample in New York. Participants naïve to study hypotheses completed 40 consecutive days of actigraphy and ecological momentary assessment of psychological stress and negative mood (depressed, anxious mood) using a 0 (not at all) to 10 (extremely) scale, contributing 1713 observations. Daily sleep duration was measured via wrist-actigraphy, and perceived daily sleep quality (1[very bad] to 4[very good]) was assessed via morning self-report. Sources of daily stress, including sociocultural stress, were collected once each evening. Multi-level modeling was used to examine within-person effects and temporal associations with adjustment for day of the week.

Results
Mean age=37.2 (SD=11.8), 69.1% women, 36.6% unemployed, 64.3% immigrant, and 38.1% Spanish-speaking. Non-specific stress (43%), work (28%), and family/relationship (21%) stress were the most common sources of daily stress. Discrimination and immigration stress were rarely reported as daily sources of stress (1.2%). Mean nightly sleep duration was 403.9 minutes (±81.3). Preliminary lagged linear mixed models indicated that a 60-minute increase in sleep duration during the night predicted a -.12 change in stress ratings (SE=.001,p&lt;.0001) the next day, as well as -.06 change in anxious mood (SE=.001,p=.003). Better perceived sleep quality on a 4-point scale during the night predicted lower stress ratings (ß=-.11,SE=.05,p=.04) and less anxious mood (ß=-.13,SE=.05,p=.01) the next day. A one-point higher rating of depressed mood during the day predicted a -.03 decrease in perceived sleep quality that night (SE=.01,p&lt;.05).

Conclusion
Overall, these results imply distinct associations of sleep with both anxiety and depressed mood. Longer sleep duration and improved perceived sleep quality were associated with subsequent decreased stress and anxiety. Increased depressed mood predicted worse sleep quality that night. Future research should identify the mechanisms of action for these differential associations.
Support (if any):
190 Changing national trends in sleep and related features among Korean adults between 2009 and 2018
Authors: Yoon Jee-Eun , Kim Daeyoung , Yang Kwang Ik , Chu Min Kyung , Yun Chang-Ho 
Published: May 2021

Abstract

Introduction
Sleep patterns have been linked to various heath disease. Evaluating population-level trend of sleep could provide a comprehensive population health-forecasting model that has the potential to inform targeted interventions. Therefore, we aimed to examine the cross-sectional differences in sleep characteristics among Korean adults during a 9-year period of 2009-2018.

Methods
The data in this study were derived from two nationwide survey regarding sleep and headache in the representative sample of Korean adult population, namely the Korean Sleep Headache Study phase I (2009) and II (2018). The survey was conducted through door-to-door visit and face-to-face interview by using structured questionnaires. Total of 2,836 participants from Phase I (47.9±16.4 years old; female, 50.2%) and 2,501 participants (47.9±16.4 years old; female, 50.3%) from Phase II gave informed consents and completed the survey. For this study, we excluded those who worked as shift workers and missing data. From the MCTQ, we collected participants’ sleep schedule during workdays and free days over the past four weeks. Average sleep duration was a weighted mean of sleep duration on workdays and free days. Poor sleep quality was defined as PSQI &gt;5. Excessive daytime sleepiness and Depression are performed with ESS and PHQ-9, respectively.

Results
During the 9 years, average sleep duration decreased by 21 minutes, especially more reduction on free days (workday: 7:17±1:58 vs. 7:06±1:06, p &lt;0.001; free days 8:04±2:32 vs. 7:49±1:23, p &lt;0.001). People go to sleep and wake up earlier on workday (workday 23:39±1:50 vs. 23:25±1:30, p &lt;0.001; free days 23:51±2:11 vs. 23:25±2:11, p &lt;0.001), whereas they go to bed earlier and wake up later on free days compared to past (workday 6:52±1:36 vs. 6:37±1:11, p &lt;0.001; 7:42±2:04 vs. 7:49±1:42 p =0.023). Social jetlag was increased by 5 minutes (0:46±1:35 vs. 0:51±0:52, p =0.028). There was the difference of age on the habitual sleep-wake rhythm and sleep related symptoms. Also, short or long sleep duration was associated with a significant increase in each health outcomes.

Conclusion
Decreased sleep duration seems to be on the rise in the general adult population, which lead to a poor health status. Interventions to promote adequate sleep is urgently needed.
Support (if any):
206 Changes in Sleep Due to the COVID Pandemic Associated with Sleep Environment
Authors: Holbert Cameron , Kennedy Kathryn , Killgore William , Wills Chloe , Grandner Michael 
Published: May 2021

Abstract

Introduction
The COVID-19 pandemic has resulted in adverse impacts on sleep for many people. The physical environment has been a focus for health-related behaviors during the pandemic since movement restrictions have led to a heightened awareness of the living environment. This study examined whether those whose physical environment was more disruptive to sleep systematically experienced more pandemic-related sleep problems.

Methods
A sample of N=419 US adults completed online surveys (mostly during the summer months) about sleep and COVID-19 experiences. Participants were asked the degree to which they endorsed statements that due to the pandemic, (1) they were able to keep a regular schedule, (2) they had more problems falling asleep, (3) they had more problems with nighttime awakenings, (4) they experienced more daytime sleepiness, and (5) they napped more. Sleep environment was assessed using the Assessment of Sleep Environment (ASE), a 13-item questionnaire that quantifies the degree to which sleep is disrupted environmental influences (scores range from 0-39). Ordinal logistic regression analyses, with degree of agreement with statements about changing sleep due to the pandemic as outcome, ASE score as independent variable, and age and sex as covariates.

Results
Worse sleep environment was associated with a decreased likelihood of being able to keep a regular schedule (oOR=0.96, p&lt;0.04) and an increased likelihood of more problems falling asleep (oOR=1.04, p&lt;0.02), problems with nighttime awakenings (oOR=1.03, p&lt;0.02), daytime sleepiness (oOR=1.03, p&lt;0.03), and napping (oOR=1.03, p&lt;0.04). Post-hoc analyses examine contributions of individual items, and the one that was independently most associated with changes in sleep was sleeping environment being too warm.

Conclusion
Those with a more disruptive sleep environment experienced a greater degree of problematic sleep problems as a result of the COVID-19 pandemic. The fact that these assessments largely took place in warmer months may explain why sleeping environments being “too warm” was especially salient.

Support (if any)
R01MD011600, R01DA051321
210 Changes in Dream Recall During the COVID-19 Pandemic: Associations with Sleep, Stress and Dream Content
Authors: Wills Chloe , Kennedy Kathryn , Bastien Célyne , Ruby Perrine , Killgore William D S , Grandner Michael 
Published: May 2021

Abstract

Introduction
During the COVID-19 pandemic, individuals have faced unprecedented events, which are often stressful. Stress has an important impact on dreams, and stress-induced sleep difficulties may also impact dream recall. The present study evaluated associations between sleep, stress and dream content on dream recall during the pandemic.

Methods
A sample of N=419 US adults completed online surveys about sleep and COVID-19 experiences. Participants were asked if they remember more, fewer or about the same amount of dreams as before the pandemic. They were also asked whether the pandemic was associated with more stress, a more regular schedule, improved sleep, worse sleep, more early insomnia, more middle-of-the-night insomnia, more sleepiness, and more naps. They also completed the Insomnia Severity Index, Fatigue Severity Scale, Epworth Sleepiness Scale, Brief Index of Sleep Control, Assessment of Sleep Environment, GAD-7 anxiety scale, and PHQ9 depression scale. Multinomial logistic regressions examined correlates of increased or decreased recall (versus same), adjusted for age, sex, and race/ethnicity.

Results
Those who experienced greater schedule regularity were less likely to report decreased recall (RRR=0.50,p&lt;0.0005), as were those who reported sleep improvement (RRR=0.48,p=0.006). Those whose sleep worsened were more likely to report both increased (RRR=1.64,p=0.003) and decreased (RRR=2.16,p&lt;0.0005) recall. Those suffering maintenance insomnia were more likely to report both increased (RRR=1.70,p=0.001) and decreased (RRR=2.68,p&lt;0.0005) recall, as did those who reported more daytime sleepiness (Increased RRR=1.57,p=0.006; Decreased RRR=1.94,p=0.001). Those whose dream content was more negative were more likely to report both increased (RRR=4.05,p&lt;0.005) and decreased (RRR=3.35,p&lt;0.0005) recall, as did those who reported less negative content (Increased RRR=4.20,p&lt;0.0005; Decreased RRR=5.05,p&lt;0.0005). Similarly, those who reported more positive dream content reported both increased (RRR=17.37,p&lt;0.0005) and decreased (RRR=7.14,p=0.02) recall, as did those who reported less positive content (Increased RRR=4.49,p&lt;0.0005; Decreased RRR=5.59,p&lt;0.0005). Less recall was associated with greater insomnia severity (RRR=1.08,p=0.001), fatigue (RRR=1.04,p=0.001), sleepiness (RRR=1.09,p=0.01), COVID stress (RRR=1.67,p=0.03), anxiety (RRR=1.08,p=0.01), and depression (RRR=1.06,p=0.007), worse sleep environment (RRR=1.06,p=0.005), and less sleep control (RRR=0.56,p=0.001).

Conclusion
The results of this survey suggest that a sudden decrease in dream recall in reaction to a new stress could be considered as a pejorative indicator regarding sleep quality and mental health.

Support (if any)
R01MD011600, R01DA051321
214 Longitudinal Changes in Sleep Duration, Timing, Variability, and Stages during the COVID-19 Pandemic: Large-Scale Fitbit Data
Authors: Grandner Michael , Rezaei Naghmeh 
Published: May 2021

Abstract

Introduction
The COVID-19 pandemic has resulted in societal-level changes to sleep and other behavioral patterns. Objective, longitudinal data would allow for a greater understanding of sleep-related changes at the population level.

Methods
N= 163,524 deidentified active Fitbit users from 6 major US cities contributed data, representing areas particularly hard-hit by the pandemic (Chicago, Houston, Los Angeles, New York, San Francisco, and Miami). Sleep variables extracted include nightly and weekly mean sleep duration and bedtime, variability (standard deviation) of sleep duration and bedtime, and estimated arousals and sleep stages. Deviation from similar timeframes in 2019 were examined. All analyses were performed in Python.

Results
These data detail how sleep duration and timing changed longitudinally, stratified by age group and gender, relative to previous years’ data. Overall, 2020 represented a significant departure for all age groups and both men and women (P&lt;0.00001). Mean sleep duration increased in nearly all groups (P&lt;0.00001) by 5-11 minutes, compared to a mean decrease of 5-8 minutes seen over the same period in 2019. Categorically, sleep duration increased for some and decreased for others, but more extended than restricted. Sleep phase shifted later for nearly all groups (p&lt;0.00001). Categorically, bedtime was delayed for some and advanced for others, though more delayed than advanced. Duration and bedtime variability decreased, owing largely to decreased weekday-weekend differences. WASO increased, REM% increased, and Deep% decreased. Additional analyses show stratified, longitudinal changes to sleep duration and timing mean and variability distributions by month, as well as effect sizes and correlations to other outcomes.

Conclusion
The pandemic was associated with increased sleep duration on average, in contrast to 2019 when sleep decreased. The increase was most profound among younger adults, especially women. The youngest adults also experienced the greatest bedtime delay, in line with extensive school-start-times and chronotype data. When given the opportunity, the difference between weekdays and weekends became smaller, with occupational implications. Sleep staging data showed that slightly extending sleep minimally impacted deep sleep but resulted in a proportional increase in REM. Wakefulness during the night also increased, suggesting increased arousal despite greater sleep duration.

Support (if any)
This research was supported by Fitbit, Inc.