bluuebunny/crossref_metadata_2025 huggingface dataset:
127 Cognitive Throughput, Behavioral Attention, and Sleepiness Show Robust Relationships During Sleep Loss but Not During Recovery
Authors: Brieva Tess , Antler Caroline , Yamazaki Erika , Casale Courtney , Goel Namni
Published: May 2021

Introduction

The Digit Symbol Substitution Task (DSST) is a frequently used measure to determine cognitive throughput responses to sleep loss. However, the specific time course of relationships between cognitive throughput and behavioral attention [using the 10-minute Psychomotor Vigilance Test (PVT10)] and subjective sleepiness [using the Karolinska Sleepiness Scale (KSS)] across sleep loss and recovery remains unknown yet is critical for assessing whether tasks involving learning and those without learning track each other. Repeated measures correlation (rmcorr) examined within-individual associations between measures of these tests 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 DSST, the KSS, and the PVT10, was administered every 2h during wakefulness. Rmcorr analyses compared DSST [number correct], KSS score, and PVT10 performance [lapses (reaction time [RT] >500ms) and 1/RT (response speed)] by examining correlations by day (e.g., Baseline day 2) and by time point (e.g., 1000h-2000h). Rmcorr ranges were as follows: r=0.1: small; r=0.3: moderate; r=0.5: large.

Results

During SR and TSD, correlations were significant, ranging from moderate to large, with the strongest correlation occurring during TSD. By contrast, baseline and recovery correlations were not significant or were small for DSST relative to PVT10 lapses, PVT10 response speed, or KSS scores. Additionally, all three pairs showed moderate to large correlations by time point across the entire study.

Conclusion

The various test measure relationships were consistently strong at specific times of day throughout the study. In addition, the associations between cognitive throughput and behavioral attention and sleepiness were strongest during sleep loss, particularly during TSD, suggesting that these measures are most acutely attuned to neurobehavioral changes resulting from sleep loss. The lack of a significant relationship at baseline and at recovery may be due to the learning effect reported for the DSST that is not present for the PVT10 or KSS.

Support (if any)

ONR Award No. N00014-11-1-0361;NIH UL1TR000003;NASA NNX14AN49G and 80NSSC20K0243;NIH R01DK117488
129 Greater NREM Sleep Rebound in Response to Experimental Sleep Disturbance Associated with Higher Inflammatory Resolution in Humans
Authors: Engert Larissa , Dubourdeau Marc , Dang Rammy , Mullington Janet , Haack Monika
Published: May 2021

Introduction

Sleep disturbances deteriorate immune function by not only affecting pro-inflammatory pathways, but also inflammatory resolution pathways, which actively terminate inflammation. It is assumed that slow wave sleep (SWS) amount and slow wave activity (SWA) convey the immune-supportive functions of sleep. We investigated whether changes in SWS induced by experimental sleep disturbance followed by recovery sleep predict changes in inflammatory resolution mediators.

Methods

The randomized controlled within-subjects trial (N=24, 20-42 years, 12 women) consisted of two 19-day in-hospital protocols (experimental sleep disturbance/control). After three nights of baseline sleep (8h/night), participants in the experimental sleep disturbance condition were exposed to three cycles of three nights of disturbed sleep (delayed sleep-onset, hourly sleep disruption, advanced sleep-offset) followed by one night of 8h-recovery sleep. The protocol ended with three nights of recovery sleep. In the control condition, participants had uninterrupted sleep (8h/night). Sleep (PSG) and resolvin lipid mediators in plasma (1100h, LC-MS/MS) were assessed at baseline, during the last cycle of sleep disturbance, and during/after the first and third night of final recovery sleep. Data were analyzed using generalized linear mixed models and Pearson/Spearman correlations.

Results

As expected, SWS amount decreased during experimental sleep disturbance and increased during the first recovery sleep night (p<.001). Similarly, resolvin (Rv) D2 and RvD3 decreased during sleep disturbance and RvD2 increased with subsequent recovery sleep (p<.001). The SWS response did not correlate with the resolvin response to sleep disturbance or to recovery sleep. However, the NREM sleep response correlated with the resolvin response during the third recovery sleep night, i.e., a greater NREM response was associated with a greater RvD2 and RvD3 response (r=.68, p=.002; r=.58, p=.012). In contrast, a greater REM sleep response was associated with a lower resolvin response (r=−.63, p=.005; r=−.66, p=.003).

Conclusion

These data suggest that during recovery from sleep disturbance, NREM rather than REM sleep promotes inflammatory resolution, thereby acting as the sleep state that protects against low-grade systemic inflammation, which has been frequently observed as a consequence of sleep disturbances. Analysis whether SWA is related to inflammatory resolution is in progress.

Support (if any)

NIH/NINDS R01-NS091177; NIH/NCRR UL1-RR02758, M01-RR01032; German Research Foundation (DFG) EN1291/1-1.
140 Short and Long Sleep Duration, Poor Sleep Quality, and Later Sleep are Associated with Lower Odds of Adolescents Eating Breakfast
Authors: Mathew Gina , Reichenberger David , Buxton Orfeu , Hale Lauren , Chang Anne-Marie
Published: May 2021

Introduction

Sleep health is linked to dietary choices, and skipping breakfast is associated with risk of negative health outcomes in adolescents. However, there is a lack of research on whether dimensions of sleep at night predict adolescents eating breakfast the next day. We investigated within- and between-person associations of multiple aspects of sleep with adolescent breakfast consumption.

Methods

Data were collected from a subset of the age 15 wave of the Fragile Families and Child Wellbeing Study (n=590). Teens wore an actigraphy device and completed daily surveys for ~1 week (mean=5.9 days). Surveys assessed subjective sleep quality (low–high) and consumption of breakfast (no/yes). Mixed models assessed whether actigraphy-measured sleep timing (onset, midpoint, and offset) and subjective sleep quality predicted odds of breakfast consumption in both within- and between-person models. A curvilinear association between sleep duration and breakfast consumption was also assessed. Irregularity of sleep duration and timing were tested as additional predictors, calculated as SD per person (in between-person models only). Analyses included random intercepts for participants and covariates: school day, boredom, loneliness, happiness, depressive symptoms, sex, race/ethnicity, body mass index, and household income.

Results

Within-person analyses revealed a significant curvilinear association between sleep duration and breakfast consumption, such that on nights when teens slept shorter or longer than their average, they had lower odds of eating breakfast the next day (p=.005). Additionally, on nights when teens had a later sleep midpoint or offset than their usual, they tended to skip breakfast the next day (both p<.05). Between-person models showed that teens who on average had later sleep timing (onset, midpoint, and offset) and who reported lower sleep quality had lower odds of eating breakfast (all p<.04). Lastly, teens with greater irregularity of sleep duration and sleep timing (midpoint and offset) had lower odds of eating breakfast (all p<.009).

Conclusion

Findings indicate that multiple dimensions of adolescent sleep health, including long and short sleep duration, later sleep timing, and poorer sleep quality, are associated with lower odds of eating breakfast. These sleep and dietary behaviors in adolescence may consequently impact future metabolic health.

Support (if any)

R01HD073352
144 Temporal and Bidirectional Associations between Objectively Measured Physical Activity and Sleep in Preschoolers
Authors: Laurent Christine St , Holmes Jennifer , Andre Chloe , Spencer Rebecca
Published: May 2021

Introduction

Physical activity (PA) and sleep contribute to overall health in early childhood. To explore the interactive relationships of these behaviors in older children and adults, previous studies have examined temporal between- and within-person associations through micro-longitudinal designs. However, such analyses have not been conducted in early childhood, when behaviors are guided by adult caregivers. The purpose of this analysis was to examine temporal and bidirectional associations between SED, PA, and sleep in preschool children.

Methods

Wake (activity counts/min and percent time in SED, light PA [LPA], and moderate-to-vigorous PA [MVPA]) and overnight sleep (sleep duration, sleep efficiency [SE], mid-sleep point [MSP]) were assessed via wrist-based actigraphy (mean = 10.4 days and 9.8 nights) and recorded as repeated (daily) measures. Multilevel models with lagged effects and AR(1) error covariance structure were used to examine the temporal associations between wake and sleep measures and adjusted for age, sex, socioeconomic status, and nap frequency.

Results

With PA measures as predictors, between-person associations were positive between activity counts and SE (p=0.004), SED and SE (p=0.004), LPA and sleep duration (p=0.005), and negative between LPA and MSP (p=0.039) and MVPA and SE (p=0.003). Within-person associations were positive between activity counts and sleep duration (p=0.010), activity counts and SE (p=0.018), MVPA and sleep duration (p=0.003), MVPA and SE (p=0.004), and negative between SED and SE (p=0.034) and LPA and sleep duration (p=0.045). With sleep measures as predictors, associations were positive between sleep duration and LPA (p<0.001) and SE and SED (p=0.008), and negative between MSP and LPA (p=0.009), SE and activity counts (p=0.001), and SE and MVPA (p=0.003). Within-person associations were positive between SE and activity counts (p=0.001) and SE and MVPA (p=0.001), and negative between sleep duration and LPA (p=0.001) and SE and SED (p=0.012).

Conclusion

Generally, days with higher levels of activity or sleep were not associated with greater subsequent sleep or PA. Conversely, when participants obtained greater PA or sleep compared to their individual average, some beneficial associations were evident. These findings demonstrate some evidence of temporal associations between PA and sleep, although the bidirectional nature was not conclusive.

Support (if any)

NIH R01 HL111695
145 Aerobic Fitness Is Associated with Advanced Circadian Rhythms in Adolescents
Authors: Neikrug Ariel , Radom-Aizik Shlomit , Chen Ivy , Stehli Annamarie , Lui Kitty , Chappel-Farley Miranda , Lim Alexandra , Mander Bryce , Benca Ruth
Published: May 2021

Introduction

Aerobic fitness facilitates brain synaptic plasticity, which influences global and local sleep expression. While it is known that sleep patterns/behavior and non-rapid eye movement (NREM) sleep slow wave activity (SWA) tracks brain maturation, little is known about how aerobic fitness and sleep interact during development in youth. The aim of this pilot was to characterize relationships among aerobic fitness, measures of global/local sleep expression, and habitual sleep patterns in children and adolescents. We hypothesized that greater aerobic fitness would be associated with better sleep quality, indicated by increased SWA.

Methods

20 adolescents (mean age=14.6±2.3 years old, range 11-17, 11 females) were evaluated for AF (peak VO2 assessed by ramp-type progressive cycle ergometry in the laboratory), habitual sleep duration and efficiency (continuous 7-14 day actigraphy with sleep diary), and topographic patterns of spectral power in slow wave, theta, and sleep spindle frequency ranges in non-rapid eye movement (NREM) sleep using overnight polysomnography with high-density electroencephalography (hdEEG, 128 channels).

Results

Significant relationships were observed between peak VO2 and habitual bedtime (r=-0.604, p=0.013) and wake-up time (r=-0.644, p=0.007), with greater fitness associated with an earlier sleep schedule (going to bed and waking up earlier). Peak VO2 was a significant predictor of slow oscillations (0.5-1Hz, p=0.018) and theta activity (4.5-7.5Hz, p=0.002) over anterior frontal and central derivations (p<0.001 and p=0.001, respectively) after adjusting for sex and pubertal development stage. Similar associations were detected for fast sleep spindle activity (13-16Hz, p=0.006), which was greater over temporo-parietal derivations.

Conclusion

Greater AF was associated with earlier habitual sleep times and with enhanced expression of developmentally-relevant sleep oscillations during NREM sleep. These data suggest that AF may 1) minimize the behavioral sleep delay commonly seen during adolescence, and 2) impact topographically-specific features of sleep physiology known to mechanistically support neuroplasticity and cognitive processes which are dependent on prefrontal cortex and hippocampal function in adolescents and adults.

Support (if any)

NCATS grant #UL1TR001414 & PERC Systems Biology Fund
146 Better Aerobic Fitness Is Associated with Distinct Sleep Characteristics in Adolescents
Authors: Neikrug Ariel , Radom-Aizik Shlomit , Chen Ivy , Stehli Annamarie , Lui Kitty , Chappel-Farley Miranda , Lim Alexandra , Mander Bryce , Benca Ruth
Published: May 2021

Introduction

Aerobic fitness facilitates brain synaptic plasticity, which influences global and local sleep expression. While it is known that sleep patterns/behavior and non-rapid eye movement (NREM) sleep slow wave activity (SWA) tracks brain maturation, little is known about how aerobic fitness and sleep interact during development in youth. The aim of this pilot was to characterize relationships among aerobic fitness, measures of global/local sleep expression, and habitual sleep patterns in children and adolescents. We hypothesized that greater aerobic fitness would be associated with better sleep quality, indicated by increased SWA.

Methods

20 adolescents (mean age=14.6±2.3 years old, range 11-17, 11 females) were evaluated for AF (peak VO2 assessed by ramp-type progressive cycle ergometry in the laboratory), habitual sleep duration and efficiency (continuous 7-14 day actigraphy with sleep diary), and topographic patterns of spectral power in slow wave, theta, and sleep spindle frequency ranges in non-rapid eye movement (NREM) sleep using overnight polysomnography with high-density electroencephalography (hdEEG, 128 channels).

Results

Significant relationships were observed between peak VO2 and habitual bedtime (r=-0.604, p=0.013) and wake-up time (r=-0.644, p=0.007), with greater fitness associated with an earlier sleep schedule (going to bed and waking up earlier). Peak VO2 was a significant predictor of slow oscillations (0.5-1Hz, p=0.018) and theta activity (4.5-7.5Hz, p=0.002) over anterior frontal and central derivations (p<0.001 and p=0.001, respectively) after adjusting for sex and pubertal development stage. Similar associations were detected for fast sleep spindle activity (13-16Hz, p=0.006), which was greater over temporo-parietal derivations.

Conclusion

Greater AF was associated with earlier habitual sleep times and with enhanced expression of developmentally-relevant sleep oscillations during NREM sleep. These data suggest that AF may 1) minimize the behavioral sleep delay commonly seen during adolescence, and 2) impact topographically-specific features of sleep physiology known to mechanistically support neuroplasticity and cognitive processes which are dependent on prefrontal cortex and hippocampal function in adolescents and adults.

Support (if any)

NCATS grant #UL1TR001414 & PERC Systems Biology Fund
147 Within-Family Dynamics Influencing Parent and Child Sleep Quality and Nighttime Activities
Authors: Hanley Brigid , Gorovoy Suzanne , Chamberlain Stihlyn , Bhushan Bharat , Ghani Sadia , Killgore William D S , Wills Chloe , Grandner Michael
Published: May 2021

Introduction

Increasing efforts have focused on child sleep due to its benefits to academics and physical/mental health. Less understood are the within-family dynamics that drive sleep-related behavior.

Methods

Data were obtained from the 2014 National Sleep Foundation Sleep in America Poll (N=1102 parent/child dyads). Variables including age, gender, sleep quality (Excellent/Good/Fair/Poor), evening activities including reading, TV-watching, and online browsing/gaming (Never/Rarely/Sometimes/Often) were reported for parent and child. Ordinal logistic regressions examined child nighttime activity as outcome and nighttime activities (entered simultaneously in the model, adjusted for each other) as independent variables, adjusted for parent and child age, sex, and sleep quality.

Results

Worse sleep quality in parents was associated with worse sleep quality in their children. Moreover, increased likelihood of child television-watching at night was not associated with parental sleep quality, but it was associated with child sleep quality, with “Fair” and “Poor” sleepers more likely to watch TV (Fair: oOR=1.7,p=0.018; Poor: oOR=8.0,p=0.001). Child television-watching was not associated with likelihood of parental reading, but it was associated with likelihood of parental online browsing/gaming (Rarely oOR=1.7,p=0.001; Sometimes oOR=2.3,p<0.0005; Often oOR=1.9,p=0.004) and parental TV-watching (Rarely oOR=2.6,p<0.0005; Sometimes oOR=5.4,p<0.0005; Often oOR=13.3,p<0.0005). Child online browsing/gaming was also not associated with parental sleep quality but it was associated with child sleep quality (Fair oOR=2.3,p=0.001; Poor oOR=4.8,p=0.009) and parental reading (Rarely oOR=1.5,p=0.04; Often oOR=1.6,p=0.03), TV-watching (Rarely oOR=2.3,p=0.004; Sometimes oOR=2.8,p<0.0005; Often oOR=4.6,p<0.0005) and online browsing/gaming (Rarely oOR=2.8,p<0.0005; Sometimes oOR=5.0,p<0.0005; Often oOR=7.8,p<0.0005). Child reading was not associated with parent or child sleep quality or parental online browsing/gaming, but it was related to parental TV-watching (Sometimes oOR=1.45,p=0.04; Often oOR=1.6,p=0.02) and reading (Rarely oOR=2.4,p<0.0005; Sometimes oOR=4.4,p<0.0005; Often oOR=6.9,p<0.0005).

Conclusion

Children who do not sleep well have parents who do not sleep well. Further, parents who read are more likely to have children who read, and parents on screens are more likely to have children on screens. Interventions targeted to parents may lead to better sleep habits in children.

Support (if any):
161 Sleep, Emotion, and Physical Activity in Older Adults Who Engage in Resonant Breathing Biofeedback
Authors: Nasseri Noor , Lagman Hanna , Simon Katharine , Zhang Jing , Mednick Sara
Published: May 2021

Introduction

Resonant breathing (RB) biofeedback increases rhythmic heart-respiration coherence patterns and has been associated with improved emotional wellbeing, physiological health, and sleep quality (Lehrer et al, 2000). Sleep quality declines with age, which leads to emotion dysregulation, cognitive impairment, and poor physical health (Crowley, 2011). However, limited research has investigated the sleep characteristics of older adults who practice RB-biofeedback. Therefore, our study investigates this population’s sleep characteristics, emotional stability, and physical health.

Methods

Thirty-one healthy participants (24 Female; M=54.68 years, SD=9.74) who self-identified as RB-biofeedback experts completed a series of online questionnaires assessing history, frequency, and duration of practice, sleep (habits and quality), physical activity (frequency, duration, and intensity), and mood (depression symptoms). They also reported their typical coherence level achieved, which is a numerical composite value associated with the heart rhythm’s uniform sine-wave pattern at approximately .1HZ (McCraty et al., 2010).

Results

Using bivariate correlations, we found that poor sleep quality was positively correlated with stress (r = .954, p = .001), poor sleep hygiene (r = .591, p < .001), severe sleepiness (r = .518, p = .003), emotion dysregulation (r = .511, p = .004), depressive symptoms (r = .089, p < .001), and negatively correlated with subjective happiness (r = .511, p < .003). Severe sleepiness was negatively correlated with older adults’ enhanced physical fitness (r = .612, p < .001), and poor sleep hygiene was positively correlated with depressive symptoms (r = .503, p = .004). We found no significant correlations between coherence level, mood, physical activity, or sleep measures.

Conclusion

We found significant associations between healthy sleep habits and emotional wellbeing. Those with better sleep quality and more positive sleep habits also had fewer depression symptoms. Moreover, those categorized as more athletic reported lower levels of severe sleepiness, suggesting that physical activity may be a protective factor for sleep in older adults. We did not find a relation between coherence level and sleep, or physical activity. These null results may be due to the high expertise level of the subject sample. Future studies should compare results to older adults who do not practice RB-biofeedback.

Support (if any)

Undergraduate Research Opportunity Program
175 Household and Transnational Caregiving and Sleep in Latinx Adults: The modifying effects of employment status
Authors: Giorgio Luciana , Alcantara Carmela
Published: May 2021

Introduction

Although caregiving is associated with shorter sleep durations and worse sleep quality, particularly among employed individuals, these studies have mostly examined household (i.e., child, adult) and domestic caregiving among majority non-Latinx White samples. Sending remittances, a form of transnational caregiving whereby financial support is provided to relatives in one’s country of origin, is associated with positive mental health among Latinxs, yet its association with sleep remains unexamined. We examined the association of household and transnational caregiving with sleep duration and quality, and explored the moderating effects of employment status on these relationships.

Methods

Using cross-sectional data of healthy Latinx adults in New York City (N=188), we conducted separate age and gender-adjusted linear regressions or logistic regressions to examine the association of caregiving and sleep duration, and poor sleep quality, respectively. Sleep duration (continuous) and sleep quality (fairly/very poor) were measured using two items from the PSQI. Household caregiving was defined as caregiving for children or adults in the household. Transnational caregiving was operationalized as sending remittances. Moderation was tested using employment status*caregiving cross-products in adjusted models.

Results

Participants were Mage=37.61(SD=14.07), 71.3% employed, 66.5% female, and 59.6% immigrants. Overall, 14.9% were household caregivers and 28.72% sent remittances. Household caregiving was not significantly associated with sleep duration or quality. Those who sent remittances reported on average sleeping 27.63 minutes less than non-remitters (b=-27.63,SE=13.93,p<0.05). Sending remittances was associated with 2.30 increased odds of reporting poor sleep quality (OR:2.30; 95%CI:1.03-5.14.) Employment status was a significant moderator (p<0.05). Among those who were employed, sending remittances was associated with 3 times higher odds of poor sleep quality (OR:3.00;95%CI:1.46-10.59) and 48.94 fewer minutes of sleep duration than non-remitters (b=-48.94,SE=15.72,p<0.05). These relationships were not observed among unemployed Latinxs.

Conclusion

Transnational caregivers were more likely to report shorter sleep duration and poorer sleep quality than their counterparts, and this was only observed among employed vs. unemployed Latinxs. Household caregiving was not significantly associated with sleep. Employed transnational caregivers may have multiple jobs that further constrain opportunities for longer and high-quality sleep. Future studies should examine potential upstream factors (e.g., working conditions) that may limit employed, transnational caregivers’ ability to obtain adequate sleep.

Support (if any):
179 Insomnia Symptoms in Latinx emerging adults: The role of perceived discrimination
Authors: Soto Pablo , Dzierzewski Joseph , Ramos Mayra , Dautovich Natalie , Corona Rosalie
Published: May 2021

Introduction

An individual’s culture presents unique risk and protective factors related to sleep outcomes. Similarly, emerging adulthood also represents a unique developmental period as it relates to sleep. The study of cultural factors during emerging adulthood is critical for better understanding the development of sleep dysfunction in vulnerable segments of the population. The present study investigated the association between perceived discrimination and insomnia symptoms in Latinx emerging adults. We hypothesized that perceived discrimination would result in higher insomnia symptom presentation above and beyond anxiety and depressive symptoms.

Methods

Participants included 198 (73.7% female; mean age=18.96) college-aged individuals self-identifying as Hispanic/Latinx who completed an online survey that assessed perceived racial/ethnic discrimination (Everyday Discrimination Scale; EDS), anxiety symptoms (General Anxiety Disorder Scale; GAD-7), depression symptoms (Patient Health Questionnaire; PHQ-9), and insomnia symptoms (Insomnia Severity Index; ISI). A three-block hierarchical regression was used to assess the impact of perceived discrimination on the presentation of insomnia symptomology above and beyond demographic characteristics and anxiety and depressive symptoms.

Results

The final model significantly predicted insomnia symptom presentation, F(5, 191)=26.379, p<.001, R2=.408. When age and gender identity were entered into the model they did not significantly predict insomnia symptoms F(2, 194)=.199, p=.82, R2=.002. Blocks 2, anxiety and depression symptoms (∆R2=.388), and 3, perceived discrimination (∆R2=.018), accounted for significant change in variance. In the final model, perceived discrimination significantly predicted insomnia symptoms (β=.151) above and beyond age (β=.016), gender identity (β= -.085), anxiety (β= -.075), and depression (β=.621).

Conclusion

Results suggest that discrimination among Hispanic/Latinx emerging adults is a unique contributor that may explain some of the higher prevalence rates of insomnia symptomology in this segment of the population. As such, it would be beneficial to tailor existing approaches aimed at improving sleep outcomes by accounting for stressors that could result from or influence discrimination against the individual and incorporate other cultural factors into treatment protocols.

Support (if any)

National Institute on Aging (K23AG049955, PI: Dzierzewski).
192 Self-reported sleep features in the Italian population across the first and second wave of the COVID-19 pandemic
Authors: De Rosa Oreste , Cellini Nicola , Conte Francesca , Malloggi Serena , Giganti Fiorenza , Ficca Gianluca
Published: May 2021

Introduction

Several studies have shown the negative impact of COVID-19-related confinement measures (spring 2020) on sleep features and quality. Here we aim to follow-up on these data by assessing self-reported sleep characteristics during the second wave of the pandemic (autumn 2020) in Italy, where the government responded with a second, partial, lockdown.

Methods

Using a longitudinal approach, 214 participants (Mage=36.78±14.2y; 159F) who had participated in a previous survey (April 2020 – Total Lockdown, TL) completed the same online survey from November 10th to December 1st (Partial Lockdown, PL). In each survey, participants had to respond to a set of questionnaires, including the Pittsburgh Sleep Quality Index (PSQI), referring to their current situation and, retrospectively, to their situation before the lockdown, resulting in four time-points (pre-TL, TL, pre-PL, PL).

Results

Linear mixed-model analysis showed that bedtime was delayed from pre-TL (23:46) to TL (24:42) and then linearly advanced in pre-PL (24:02) and PL (23:56). The same pattern emerged for rise time (pre-TL: 07:48, TL: 9:05, pre-PL: 8:28, PL: 7:58) and time in bed, which increased from pre-TL (8h4min) to TL (8h24min) and then linearly decreased (pre-PL: 8h15m, PL: 8h2m). Subjective sleep quality decreased in the two lockdowns compared to the period with no restrictions. The proportion of poor sleepers (PSQI>5) increased from 39.7% (pre-TL) to 48.6% in TL and again from 36.9% (pre-PL) to 47.7% in PL.

Conclusion

Sleep habits and quality showed different profiles across four time-points of the COVID-19 pandemic and related restrictive measures. Sleep timing alterations appeared during the first lockdown, recovered after the confinement period, and almost returned to baseline during the second lockdown (likely due to a normalization of working schedules). Instead, subjective sleep quality markedly worsened during both lockdowns relative to the preceding respective months. These data suggest that subjective sleep quality is particularly sensitive to changes in life habits and psychological factors, independently of sleep habits. Considering that the pandemic situation may continue for several months, there is a need for interventions targeting sleep quality.

Support (if any)

N/A
203 Changing Sleep During the COVID Pandemic Associated with Daytime Cognitive Function
Authors: Jajoo Anjalee , Kennedy Kathryn , Lujan Matthew , Killgore William , Wills Chloe , Grandner Michael
Published: May 2021

Introduction

The novel Coronavirus has caused major disruptions to sleep and cognitive function of many individuals. The present study evaluated the degree to which daytime cognitive dysfunction may be related to worsening sleep.

Methods

Data from adults aged 18 and older in the 2020 Coronavirus and Impact on Dreams (CovID) study were used. Individuals were asked “how would you rate your sleep quality overall” and answered with “very good, fairly good, fairly bad, or very bad.” Subjects were asked if it takes “30 minutes or more to fall asleep” and answered with how frequently that happened. In addition, participants were asked how often they wake up during the night. Participants were then asked how much they think their sleep problems have contributed to daytime functioning and answered on a scale of 0 to 5, from “not at all” to “very much,” respectively.

Results

46% of the sample did not report problems with daytime cognitive function, while 33%, 12%, and 9% reported mild, moderate, and severe problems, respectively. Those who reported that they have kept a regular schedule during the pandemic were 83% less likely to report greater daytime cognitive dysfunction (95%CI:0.08,0.37, p<0.0005). Those who indicated that overall their sleep worsened or improved did not demonstrate a difference in likelihood of daytime cognitive problems. Regarding specific sleep experiences, those who reported more problems falling asleep due to the pandemic were 8.2 times more likely to report daytime cognitive dysfunction (95%CI:3.53,19.07, p<0.0005) and those who reported more problems with morning awakenings were 5.7 times more likely (95%CI:2.10,15.56, p<0.001). Those who reported that they were sleepier as a result of the pandemic were 9.3 times as likely to report daytime cognitive dysfunction (95%CI:3.53,24.46, p<0.0005) and those who reported taking more naps were 4.4 times more likely (95%CI:1.90,10.40, p<0.001).

Conclusion

In general, people who reported increased sleepiness, a less regular schedule, more insomnia, and more napping were more likely to experience daytime cognitive dysfunction during the COVID-19 pandemic.

Support (if any)

R01MD011600, R01DA051321
211 Pandemic-Related Sleep Changes Associated with COVID-Related General, Financial, Food, Housing, Family and Relationship Stress
Authors: Kennedy Kathryn , Seixas Azizi , Jean-Louis Giardin , Killgore William , Wills Chloe , Grandner Michael
Published: May 2021

Introduction

The COVID-19 pandemic has caused widespread disruption and stress for people of all ages and circumstances around the world. This study investigates the relationship between general and specific stressors and various dimensions of sleep health.

Methods

A sample of N=419 US adults completed online surveys about sleep and COVID-19 experiences. Participants were asked whether they experienced increased general, financial, food, housing, family and relationship stress due to the COVID-19 pandemic. They were also asked whether they experienced a more regular schedule, improved sleep, worsened sleep, more early insomnia, more middle-of-the-night insomnia, more daytime sleepiness, and more naps due to the COVID-19 pandemic. Ordinal logistic regressions with sleep change as outcome and stress variable as predictor were adjusted for age, sex, and race/ethnicity.

Results

COVID-19-related general, financial, food, housing, family, and relationship stress were all associated with a decreased likelihood of maintaining a more regular schedule (oOR=0.52-0.67, all p<0.001) and improved sleep (oOR=0.56-0.67, all p<0.001). They were also all associated with a greater likelihood of worsened sleep (oOR=1.48-2.41, all p<0.001), early insomnia (oOR=1.63-1.85, all p<0.001), middle-of-the-night insomnia (oOR=1.40-2.00, all p<0.001), and daytime sleepiness (oOR=1.58-2.07, all p<0.001). Increased napping was also associated with more COVID-related financial, food, and housing stress (oOR=1.33-1.55, all p<0.005).

Conclusion

Regular sleep schedules can be disrupted by stressors directly, or by the anxiety that so often accompanies stress. Stressed individuals may experience increased difficulty falling asleep, or more nighttime arousals, or find themselves waking up earlier than usual, all as a result of ruminating thoughts, stress-induced nightmares, or outside disturbances. Disruption to sleep at night often results in increased daytime sleepiness and fatigue, with a higher chance of napping. This study reports the significant association of some of these with COVID-19 pandemic-related stress. More individuals now find themselves working from home with greater flexibility in their schedules, but this has not necessarily led to better sleep. The impact of the pandemic on various health outcomes as a result of stress is still to be revealed.

Support (if any):
218 BIDEN WON, BUT SLEEP LOST IN THE 2020 US ELECTION
Authors: Gahan Luke , Ruder Michael , O’Mullane Brian , Watson Nathaniel , Raymann Roy
Published: May 2021

Introduction

The 2020 US Presidential Election captivated the US public resulting in record turnout. In the months preceding the elections COVID-19, racial injustice and the economic downturn had a daily impact on the lives of voters. In this research, we analyze the sleep behavior of Americans in the lead up to the Presidential Elections. We examine specifically the nights of the Presidential and Vice-Presidential Debates and Election Night.

Methods

We examined sleep data from the PSG-validated SleepScore Mobile Application, which uses a non-contact sonar-based method to objectively capture sleep-related metrics and self-reported lifestyle data. The data set included 123,723 nights (5,967 users residing in the US, aged 18-85, mean age: 46.6 +/- 16.7 years, 52.3% female). Data from September 1st until November 3rd were included. This covered the nights of the Presidential Debates (Tuesday 09/29/2020 and Thursday 10/22/2020) and the Vice-Presidential Debate (Wednesday 10/07/2020). Election night was Tuesday, November 3, 2020. Self-reported stress level (0-24 scale) and alcohol consumption (0-9 drinks) were measured using digital slider scales. Mixed Effect Modelling was used for analysis.

Results

The night of the 1st Presidential debate saw a change in sleep-related behavior with users going to bed 9.5 minutes later, as compared to a regular Tuesday Night. This resulted in a decrease in both TST (11.5 mins, p<0.001) and TIB (11.8 mins, p<0.001). Interestingly, neither the the 2nd Presidential Debate, nor the Vice Presidential Debate resulted in significant differences in sleep behavior. On election night users went to bed 14.5 (p<0.001) min later on average, as compared to a normal Tuesday Night. This resulted in a decrease in both TIB (24.3 mins, p<0.001) and TST (19.2 mins, p<0.001). Self-report data showed a 13.3% (p<0.001) increase in stress level on election night and 34.4% (p<0.001) increase alcohol consumption Importantly, election night was two nights after the end of Daylight Savings Time (DST), Sunday, November 1st.

Conclusion

This analysis shows the 2020 US Presidential election negatively impacted US population sleep. The impact was most pronounced on election night, but also observed following the first Presidential debate. The effect of DST on these findings is unknown but surmised to be meaningful.

Support (if any):
219 Comparing Sleep Amount and Quality for People Working from Home with and Without Minor Dependents during the COVID-19 Pandemic
Authors: Cordoza Makayla , Kaizi-Lutu Marc , Jones Christopher , Mange Ami , Dinges David
Published: May 2021

Introduction

The global pandemic due to the novel coronavirus (COVID-19) has had unprecedented effects on society, in particular for those who are also working with children in the household. The aim of this analysis was to evaluate sleep amount and sleep quality during the COVID-19 pandemic compared to before COVID-19 for those working from home with minor household dependents.

Methods

We developed the “Anonymous Survey on Confinement during the COVID-19 Pandemic”, a national survey for individuals ≥18 years of age hosted on the Penn Medicine Clinical Research website from May 16th to November 11th, 2020. This 200 question survey captured demographics and multiple dimensions of health and well-being, including stress, sleep, eating behaviors, and coping activities. Respondents who indicated they were working from home were stratified by whether they were living with ≥1 minor dependent vs no dependents. Separate ordinal logistic regression models were used to evaluate associations between living with a minor dependent and sleep amount (less, same, more) and disturbed quality (none, less, same, more) during, compared to before, COVID-19 controlled for age, sex, ethnicity, and annual income.

Results

A total of 232 respondents (n=182 no dependents, n=50 dependents, 84.9% Caucasian) reported working from home, the majority of which had been in confinement (95.7%). Respondents with dependents were younger (mean age 38.9±13.5 vs 47.4±18.0, p=0.002) and mostly female (86% vs 76.9%, p=0.03). On average, reported days worked/week (3.5±2.4 days) and hours worked/day (5.5±4.17 hours) were similar regardless of dependents. Comparing those without to those with minor dependents, there were no significant differences in log odds of getting enough sleep (β=-0.38, p=0.25) or worse sleep quality (β=0.41, p=0.22) during the COVID-19 pandemic compared to before COVID-19. Respondents with dependents reported a higher log odds of taking longer to fall asleep during COVID-19 (β=0.71, p=0.045), and higher stress (β=-0.65, p=0.04).

Conclusion

In this mostly Caucasian female sample of people working from home, having minor dependents in the household did not significantly impact sleep amount or quality compared to no minor household dependents. However, respondents with dependents reported longer time to fall asleep and were more stressed.

Support (if any)

MC/CJ are supported by NHLBI (T32 HL007713).
220 Sleep schedule changes during the COVID-19 pandemic: Relations to circadian preferences
Authors: Ruder Michael , Gahan Luke , O’Mullane Brian , Watson Nathaniel , Raymann Roy
Published: May 2021

Introduction

The COVID-19 pandemic profoundly altered individual lifestyles, reducing commutes and restricting nocturnal in-person socialization. We examine whether the stay-at-home orders and the attendant increase in sleep scheduling autonomy, impact bedtimes and waketimes and influence circadian preference alignment.

Methods

We compared bedtimes and wake times during the 4 weeks before and after a March 19th, 2020 stay-at-home order announcement. Data from the PSG-validated SleepScore Mobile Application were analyzed. Users answering a circadian preference question (a five-point Likert scale ranging from “definitely a morning person” to “definitely an evening person”) who also recorded 10 or more nights of sleep both before and after the March 19th announcement were included in the analysis. The data set included 69,656 total nights of sleep from 1,487 users: 51.0% female, age range 18 to 91 years (mean = 50.3 +/- 30.3). Differences in average bedtime and wake time before and after March 19th were compared using paired sample t-tests. Associations between circadian preference and changes in bedtime and wake time were examined using Spearman’s correlation coefficient.

Results

All five circadian preference groups showed a significant delay in both bedtime and wake time (p < .01) after the March 19th announcement. Greatest delays were observed in those reporting the strongest eveningness preference, with median bedtimes being 17 minutes later and wake times 33 minutes later. Delays were smallest in users with the strongest morningness preference, with bedtimes being 7 minutes later and wake times 12 minutes later. Wake time delay was significantly greater than bedtime delay for evening types (p < 0.001) but not morning types. Eveningness preference was associated with greater bedtime delay (Spearman correlation = 0.098, p <0.001) and wake time delay (Spearman correlation= 0.178, p < 0.000001).

Conclusion

The stay-at-home order provided many individuals more freedom to choose their sleep schedule. This increased sleep scheduling autonomy was associated with delayed bedtimes and wake times for each circadian preference group, with the evening-types exhibiting the greatest shift towards a later sleep schedule. We conclude that stay-at-home orders allowed evening types to choose sleep schedules more aligned with their natural tendencies.

Support (if any):
223 Sleep Duration and Sleep Quality in Chronic Cannabis Users and Non-Users
Authors: Tse Caroline , Stewart Alicia , Ordaz-Johnson Omar , Herzig Maya , Gagnon Jacqueline , Emens Jonathan , Shea Steven , Bowles Nicole
Published: May 2021

Introduction

Cannabis use is on the rise in the United States, with 10% of adults reporting cannabis use in the past 30 days. Users commonly report consuming cannabis to improve sleep despite the lack of research that supports an association between cannabis use and sleep. In this pilot study we sought to examine objective measures of sleep duration and sleep quality among non- and chronic-cannabis users, and any patterns in relation to the time since consumption of cannabis.

Methods

Chronic cannabis users (cannabis used 2 or more times/week) and non-users provided up to 2-weeks of actigraphy (ActiGraph wGT3X-BT), worn on the wrist and verified by sleep diary. Chronic cannabis users also reported the date, time, amount, and route of their cannabis use. Mixed-effects models with participant as a random factor were used to examine: 1) the relationship between daily sleep parameters in cannabis non-users vs. users; and 2) the elapsed time between cannabis use and time in bed in chronic cannabis users.

Results

Chronic cannabis users (n=6) and non-users (n=7) collectively provided 151 nights of sleep. Participant characteristics (38.5% female; age, 25.8 years ± 4 years; BMI, 23.4 kg/m2 ± 3.4 kg/m2) did not significantly differ between groups. Cannabis use was associated with decreased total sleep time (measured in hours, ß=-0.58, p<0.001) and increased wake after sleep onset (WASO, ß=32.79, p=0.005), but not with the number of awakenings (ß=6.02, p=0.068). Among chronic cannabis users, cannabis use within two hours of bed was associated with increased sleep latency compared to use greater than two hours (ß=6.66, p=0.026). There was no association between time of cannabis use and WASO (p=0.621) or the number of awakenings (p=0.617).

Conclusion

In this pilot study of objectively measured sleep, we found that chronic cannabis use compared to non-use is associated with decreased sleep duration of otherwise healthy adults. Cannabis used closer to bedtime is associated with increased sleep latency. Additional studies that are able to assess the mode and dosage of use are needed to further understand the effects of cannabis and its components on sleep.

Support (if any)

KL2TR002370, AASM, Oregon Institute of Occupational Health Sciences
228 The Association of Prior Mental Health Conditions with COVID-19-related Sleep Changes
Authors: Kasraeian Kimiya , Petrov Megan
Published: May 2021

Introduction

Among persons with mental health conditions, the impact of the COVID-19 pandemic on sleep health is underexplored. The present study investigated whether sleep changes related to the COVID-19 pandemic differed among individuals with mood and/or anxiety disorders compared to individuals without these disorders.

Methods

A 25-minute online survey, distributed globally to adults aged >18y through social media advertising from 5/28/2020-7/10/2020, examined the association of mental health diagnoses with COVID-19 related sleep changes. Participants reported prior history of mood and anxiety disorders, and pre-COVID-19 and current sleep patterns including bedtime, wake time, total sleep time (TST), sleep efficiency (SE:[TST/time in bed*100%], and nightmare frequency/wk. ANOVA models comparing mental health disorder groups (no diagnoses, mood disorders, anxiety disorders, mood and anxiety disorders) on mean differences in sleep changes were conducted.

Results

Among 1,048 participants, 71.5% reported no prior mood and/or anxiety disorders9.3% reported anxiety disorders only, 4.3% reported prior mood disorders only, and 14.9% reported both mood and anxiety disorders. There were significant group differences in total sleep time (F (3,670)=4.6, p=0.003) and sleep efficiency (F (3,670) =2.8, p=0.038) such that individuals with both mood and anxiety disorders experienced greater decreases in total sleep time (Mean Difference: 39.0min, SE=13.0) and sleep efficiency (Mean Difference=3.8%, SE=1.6) compared to individuals without any mood or anxiety disorders. In addition, the model for nightmare frequency per week was significant (F(3,654)=5.6, p=0.001) such that individuals with both anxiety and mood disorders (Mean Difference=1.1, SE=0.4) and individuals with mood disorders only (Mean Difference=1.1, SE=0.4) reported greater increases in nightmare frequency compared to participants without any mood or anxiety disorders. There were no group differences in bedtime and wake time.

Conclusion

Among a global sample, COVID-19 pandemic-related sleep health significantly worsened among individuals with prior mood and anxiety disorders relative to individuals without these disorders.

Support (if any):