bluuebunny/crossref_metadata_2025 huggingface dataset:
037 Subjective sleep and objective cognition in middle-aged and older adults: Does sex matter?
Authors: Curtis Ashley , Schmiedeler Anthony , Jagannathan Sadhika , Connell Maggie , Atkinson Angela , Miller Mary Beth , McCrae Christina S
Published: May 2021

Introduction

Worse sleep has been linked to cognitive dysfunction in aging populations. There are known sex differences in the prevalence and presentation of both sleep disturbance and cognitive impairment, but research investigating sex differences in the associations between sleep and objective cognition is limited and inconclusive. We examined sex as a moderator of associations between self-reported sleep and objective cognitive performance in middle-aged/older adults.

Methods

Sixty-four adults aged 50+ (Mage= 63.8, SD=7.7; 33 men/31 women) who were cognitively healthy (no mild cognitive impairment, dementia or neurological disorders) completed an online survey (via Qualtrics) measuring self-reported sleep (Pittsburgh Sleep Quality Index; PSQI). Participants completed online cognitive tasks (via Inquisit) measuring inhibition (Stroop task; interference reaction time scores), attentional orienting (Posner Endogenous Cueing Task; reaction time difference between invalidly cued and validly cued trials), and working memory (Sternberg task; proportion correct). Multiple regressions examined whether PSQI subscores (sleep quality, sleep duration, sleep efficiency) were independently associated with or interacted with sex in their associations with cognition, controlling for age and education.

Results

Sex interacted with sleep quality in the association with endogenous attentional orienting (p=.01, R-squared=.10). Specifically, worse sleep quality was associated with worse attentional orienting in women (B=22.73, SE=9.53, p=.02) but not men (p=.24). Sex interacted with PSQI-sleep duration (p=.03, R-squared=.08) and PSQI-sleep efficiency (p=.03, R-squared=.08) in the association with inhibition performance. Specifically, worse sleep duration (B=235.28, SE=77.51, p=.004) and sleep efficiency (B=211.73, SE=68.70, p=.003) were associated with worse interference scores in men but not women (ps>.05). No variables were associated with working memory.

Conclusion

In middle-aged and older adults, sex moderates associations between self-reported sleep and objective cognition, depending on the sleep parameter and cognitive ability assessed. Findings suggest that women are more vulnerable to the effects of poor sleep quality on spatial attention, whereas men are more vulnerable to the effects of shorter sleep duration and worse overall sleep fragmentation on ability to inhibit task-irrelevant stimuli. Future studies should investigate sex-specific associations between sleep and cognition over time in order to better understand the prospective trajectories of these processes during aging.

Support (if any):
048 Increased Cognitive Load Under Stress Modulates Sleep Spindles and Slow Oscillations in a Sleep-Stage Dependent Manner
Authors: Natraj Nikhilesh , Neylan Thomas , Yack Leslie , Mathalon Daniel , Richards Anne
Published: May 2021

Introduction

The effect of increased cognitive load especially under duress has been known to affect brain rhythms in humans. However, this effect has been shown primarily in the awake brain; the effect of stressful cognitive load on sleep rhythms is yet unclear. We leveraged a unique opportunity to understand the effect of cognitive load under laboratory stress on sleep spindles and slow oscillations that are hallmark rhythms of NREM sleep.

Methods

Cortical 6-channel EEG nap data were collected from 45 subjects over two separate days: after a control session without laboratory stressors and after an experimental session in which they underwent fear condiitoning and negative-emotional-image viewing sessions. We detected sleep spindles (11-13Hz over frontal regions and 13-16Hz over centroposterior regions) and slow oscillations (0.16–1.25Hz oscillations) as discrete events at each of the six electrodes, and staged them by the sleep hypnogram. We evaluated the spindle rate in N2 sleep and the proportion of slow oscillations nested with a spindle in N3 sleep.

Results

Over all 6 EEG electrodes, N2 spindle rates increased on average by 14% in the experimental session compared to the control session (mixed-effect models p<0.001). In addition, over all 6 electrodes, the proportion of slow oscillations in N3 nested with a spindle increased by 2.3% in the experimental session compared to the control session (mixed effect model, p=0.005).

Conclusion

We show for the first time how increased cognitive load under stressful laboratory conditions affects sleep rhythms. Such an increased response in sleep might correspond to a continued emotional response due to the cognitive load under duress. Ongoing work seeks to tie these findings to possible emotional memory consolidation.

Support (if any)

VA Career Development Award to Dr. Richards (5IK2CX000871-05)
063 Differential Impact of Sleep Duration on Nocturnal Blood Pressure Dipping Between Men and Women
Authors: Bigalke Jeremy , Greenlund Ian , Nicevski Jennifer , John-Henderson Neha , Carter Jason
Published: May 2021

Introduction

There is growing evidence that poor sleep may have a greater impact on the development of cardiovascular complications in women compared to men. However, most studies that have evaluated the impact of sex on sleep insufficiencies and blood pressure (BP) have not utilized ambulatory BP, and often rely more heavily on subjective sleep diaries as opposed to objective sleep assessment. The purpose of this study was to examine the impact of sex on the relationship between objectively measured sleep and nocturnal BP dipping. We hypothesized that poor sleep would be associated with decreased nocturnal BP dipping, and that this association would be stronger in women.

Methods

Total sleep time (TST) and sleep efficiency (SE) were monitored in fifty adults (31 men, 19 women; 36±3 years; 26±1 kg/m2) utilizing wrist actigraphy monitoring over the course of 5–14 days (Avg: 10±0 days). On a separate occasion, participants underwent a 24-hour ambulatory BP recording session. Independent samples T-tests were used to compare characteristics between sexes. Partial correlations controlling for age and BMI were utilized to probe relationships between sleep and nocturnal BP dipping.

Results

TST and SE were not different between sexes. However, women exhibited reduced mean arterial pressure (MAP: 86±1 vs. 90±1 mmHg, P=0.026) compared to men. Partial correlation revealed a significant relationship between TST and the magnitude of nocturnal MAP dipping in the sample population (R = 0.460, P<0.001). When stratified by sex, this significant relationship persisted in men (R = 0.610, P<0.001), but not women (R = 0.108, P>0.05). In contrast, no relationship was observed between SE and nocturnal MAP dipping (R = -0.052, P>0.05) for the sample population. Similarly, SE did not correlate with nocturnal MAP dipping in men (R = -0.080, P>0.05) or women (R = 0.045, P>0.05).

Conclusion

Contrary to our initial hypothesis, our results demonstrate that actigraphy-based TST is associated with nocturnal BP dipping in healthy men, but not women. This suggests a relation between impaired nocturnal BP regulation and habitual sleep duration, potentially predisposing men to an increased overall risk for cardiovascular complications.

Support (if any)

National Institutes of Health (HL-098676 and HL-122919)
067 Causal Communication Across the Electrode Manifold During Slow Oscillations
Authors: Niknazar Hamid , Malerba Paola , Mednick Sara
Published: May 2021

Introduction

The slow oscillation (0.5-1Hz, SO) is the most studied sleep waveform and reflects sleep homeostasis and is crucial for memory consolidation. It is not clear how SO causally affects brain networks. We used the effective connectivity technique to investigate causal information flow across the electrode manifold during the SO.

Methods

Night sleep EEG signals of 59 adult participants were recorded and visually scored into five sleep stages. We used three EEG channels for each region including frontal, central, parietal, and occipital. SOs were detected automatically and signals from one second before to one second after the SO’s troughs were used for estimating effective connectivity in SO and non-SO windows. Windowing technique and generalized partial directed coherence were employed to estimate causal information flow (CIF) between selected brain regions. The Linear mixed-effect (LME) method was used to model the peaks of the CIF based on different predictors including SO channel, source and sink of CIF, and distance between each of SO channel, source and sink regions.

Results

The results of CIF estimation showed two peaks of CIF about 250ms before and after the SO’s trough, but no difference between CIF in SO’s trough and non-SO windows. We found no effect of source and sink regions, and their distance on CIF (p-value > 0.05). However, distance between SO channel to source and sink region (p-value < 0.05) significantly predicted CIF. The coefficients of the LME model showed a direct effect of distance between SO channel to sink region and opposite effect of distance between SO channel to source region on CIF peaks.

Conclusion

The results showed there were significant changes of brain regions causal communication during SOs and these changes were affected by the distance of SO channel to sink and source region of CIF. Channels that are closer to the SO send more information and regions farther from the SO channel receive more information. Based on the results, we hypothesize that the SO brain networks are optimized to facilitate communication between regions that are far apart.

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069 Chronic pain in Veterans with TBI is associated with decreased EEG slow wave coherence during NREM sleep
Authors: Balba Nadir , Reynolds Christina , Modarres Mo , McBride Alisha , Yildiz Selda , Heinricher Mary , Lim Miranda
Published: May 2021

Introduction

Chronic pain and sleep disturbances are intricately linked to one another, especially in individuals with a history of traumatic brain injury (TBI) who are at greater risk for both symptoms. Although prior studies have analyzed differences in sleep electroencephalogram (EEG) in these clinical populations, the association between sleep EEG slow wave coherence and pain complaints is not fully examined or known. Our novel slow wave coherence approach may provide new insights into the relationship between TBI, chronic pain, and sleep

Methods

Ninety-six veterans were recruited and enrolled under a VA IRB-approved protocol. Participants completed a semi-structured clinical interview to determine their history of TBI, Symptom Impact Questionnaire Revised (SIQR), a measure of chronic pain complaints, and underwent an attended overnight in-lab polysomnogram (PSG). We developed a novel computational signal processing algorithm to identify and quantify EEG slow waves within 100 ms bins across the 6 standard PSG EEG channels. When a slow wave was simultaneously observed in 4 or more of the 6 leads, slow wave coherence was inferred, and a percentage of slow wave coherence across each of the sleep stages was then calculated for each subject.

Results

In our sample, 65 participants (67.7%) endorsed experiencing chronic pain lasting 3 months or longer, and 54 had a history of TBI (56.3%). Participants endorsing chronic pain had a significantly lowered percent of EEG slow wave coherence during NREM sleep than subjects without chronic pain (p = 0.01). NREM EEG slow wave coherence did not correlate with SIQR scores in subjects without TBI (r = -0.03, p = 0.90), but was significantly negatively correlated in subjects with TBI (r = -0.32, p = 0.02).

Conclusion

EEG slow wave coherence during NREM sleep is correlated with chronic pain complaints in Veterans with a history of TBI, and could be indicative of neuronal dysfunction during sleep. Further research on slow wave coherence is warranted to understand the underlying mechanisms for the association between chronic pain and poor sleep following TBI.

Support (if any)

D01 W81XWH-17-1-0423
070 Respiratory, cardiac, EEG, BOLD signals and functional connectivity over multiple microsleep episodes
Authors: Soon Chun Siong , Vinogradova Ksenia , Ong Ju Lynn , Calhoun Vince , Liu Thomas , Zhou Juan Helen , Ng Kwun Kei , Chee Michael
Published: May 2021

Introduction

Brief intrusions of unintended sleep can occur in various contexts, for example during resting-state fMRI scans. In addition to changes in neural activity, such microsleep episodes are also associated with shifts in respiration and heartrate. Here we investigated how these concurrent changes alter the dynamics of the BOLD signal in the brain and estimates of functional connectivity.

Methods

Ten participants underwent 6 runs of 20 minute resting-state fMRI scans with concurrent respiration, PPG and EEG recording. Realtime eye-closure monitoring combined with post eye-opening self-reports were used to identify microsleep episodes of different durations.

Results

During microsleep, sustained reductions were observed in arousal as assessed by EEG (ratio of alpha to delta and theta bands), as expected. In comparison, cortical BOLD signal exhibited more complex, temporally multiphasic changes which were consistent across different microsleep durations from 4 to 44s: (i) an initial sleep-onset dip reaching a nadir after ~6s, followed by (ii) an increase above wake baseline that plateaued till awakening. On awakening, (iii) a transient positive bump occurred up to 6s, followed by (iv) an undershoot below baseline lasting ~30s. While seen across the whole brain, these changes showed regional variations, e.g., the signal plateau in the thalamus remained below wake baseline. Sleep onset and awakening were also associated with respective reductions and increases in respiration and heart rate, which affect blood oxygen levels. Brain functional connectivity estimates were altered by the frequency of falling asleep, and this was not resolved by global signal regression.

Conclusion

Falling asleep and awakening are shown here to be associated with large, widespread BOLD signal changes consistent across varied durations of microsleep. These signal changes are intimately intertwined with shifts in respiration and heart rate, which are influenced by common brainstem nuclei controlling sleep. These autonomic contributions to ‘brain signal’ changes at microsleep onset and awakening are integral to sleep, and urge the integration of autonomic and central nervous system contributions to BOLD signal into frameworks for understanding brain function using fMRI. In addition, the correlation between frequency of microsleep and extent of altered functional connectivity highlight the need to minimize sleep during resting state scans.

Support (if any)

NMRC/STaR/015/2013
083 Circadian Preference is Associated with Impulsivity at Both the Trait and State Level
Authors: Hasler Brant , Wallace Meredith , Graves Jessica , Pedersen Sarah
Published: May 2021

Introduction

Impulsivity is a multifaceted construct with well-documented risk for substance use problems. A circadian preference towards eveningness has been linked to trait, global impulsivity. Here we extend existing literature by investigating whether eveningness is associated with multiple facets of impulsivity at both trait- and state-level impulsivity. We also examined these associations utilizing daily measures of sleep timing and duration.

Methods

The primary sample included 78 moderate-to-heavy social drinkers (aged 21–35, 100% White men) with circadian preference data (Composite Scale of Morningness: CSM). Five facets of impulsivity were assessed via the UPPS-P, both at baseline (full scale) and up to 6 times per day over 10 days (reduced scale). Daily sleep timing (midsleep) and duration were assessed via self-report over 10 days. Multilevel models were used to examine between- and within-person associations, accounting for covariates and correcting for multiple comparisons.

Results

Between-person models found that eveningness was associated with multiple facets of impulsivity, at trait (lack of perseverance) and state levels (negative urgency, positive urgency, lack of perseverance, and lack of premeditation). However, average midsleep and duration were generally unrelated to impulsivity when accounting for circadian preference. Within-person models in the primary sample largely paralleled the between-person findings. In a larger, more diverse sample (29.1% self-identified as Black, 29.7% female) without CSM data, later midsleep timing was associated with greater mean state-level impulsivity across multiple facets. These effects largely appear to be driven by White women.

Conclusion

A circadian preference for eveningness is strongly associated with multiple facets of impulsivity, at both trait- and state-levels, potentially increasing risk for substance use. This association does not appear to be driven by actual daily sleep timing and/or duration. Future research with objective measures of sleep in larger, more diverse samples will be important to clarify implications for sleep-focused prevention and/or treatment of substance use.

Support (if any)

Supported by grants from NIH (R01AA026249; K01 AA021135), as well as a Foundation Grant from ABMRF/The Foundation for Alcohol Research.
100 Effect of 3 consecutive nights of alcohol on sleep variables: Preliminary report
Authors: Carskadon Mary , Saletin Jared , Gredvig-Ardito Caroline , McGeary John
Published: May 2021

Introduction

The effects of a moderate dose of alcohol one hour before bedtime on sleep have not often been studied nor is the effect across nights well known. We therefore sought to test whether such effects as sleep disruption, increased early-night slow wave sleep (SWS), and reduced early-night REM sleep would be sustained across nights.

Methods

Twenty-five healthy participants (13 male; ages 22–69 yr, mean = 35) reporting moderate drinking kept a fixed sleep schedule (8–9 h TIB, confirmed by actigraphy) for about one week before two 3-night sleep studies in the lab separated by ≥ 3 days. Participants drank either mixer alone or a beverage containing alcohol targeting a breath alcohol content (BrAC) of 0.08% in a counter-balanced order over 45 min ending 1 hr before lights out. Sleep was scored using Rechtschaffen & Kales (1968) rules in 30-sec epochs. Mixed-effects models examined beverage type, study night, and the interaction of beverage and night for 13 variables: sleep efficiency, sleep latency, REM latency, and full-night percent of Stage 1, Stage 2, SWS, and REM sleep; and percent of SWS and REM sleep by thirds of night.

Results

A significant effect of Night was seen for sleep efficiency (F(2,120)=3.79; p=.025) and sleep latency (F(2,120)=5.19;p=.007), both lower on N1, as well as for REM latency, longer on N1 (F(2,120)=6.52;p=.002). REM latency was longer with alcohol (F(1,120)=14.16; p<.000) and no interaction was apparent. St2% was higher (F(1,120)=4.47; p=.037) and REM% lower (F(1,120)=4.41; p=.038) with alcohol, whereas overnight SWS% was unaffected; none showed an effect of night or an interaction. SWS% in the first (F(1,120)=10.51; p=.002) and second thirds (F(1,120)=8.27; p=.005) of the night was higher with alcohol and unaffected in the last third. REM% in the first third alone was higher with alcohol (F(1,120)=10.71; p=.01).

Conclusion

These findings show only modest effects of pre-sleep alcohol consumption (targeting 0.08% BrAC) on subsequent sleep in healthy drinkers, with no evidence of a cumulative impact across three nights. We aim to increase the sample size and examine effects on next-day cognitive function in subsequent analyses.

Support (if any)

R01AA025593
102 Single-Prolonged Stress as a Model of PTSD in Mice: Effects on Sleep and Anxiety
Authors: Gutowsky Katelyn , Jones Carolyn , Lim Miranda
Published: May 2021

Introduction

Sleep problems are common in humans with post-traumatic stress disorder (PTSD). Rapid eye movement (REM) sleep is involved in processing emotional memories; it is often disrupted in those with PTSD, and may be related to increased anxiety. Single prolonged stress (SPS) is a protocol used to model PTSD in rats, however little is known about how this model impacts sleep in mice. Prior research suggests SPS produces short term disturbances in REM sleep and increases in anxiety-like behavior, but further validation of this model is needed to understand how SPS impacts sleep and anxiety-like behaviors in mice specifically, as they have greater potential for transgenic manipulation

Methods

C57BL6/J mice underwent a SPS protocol in which they were tube-restrained for 2 hours, followed by a 15 minute forced swim in a group, ether exposure until loss of consciousness, and 10 days of social isolation. Following SPS, mice were tested for anxiety-like behavior in a light-dark box and sleep was measured from surgically implanted EEG and EMG leads. Time spent in wake, REM sleep, and non-REM sleep was quantified for 24 continuous hours in SPS and Control mice.

Results

There were no significant effects of SPS on the amount of time spent in any vigilance state, or in sleep-wake transitions. However, SPS-exposed mice showed significantly more anxiety-like behavior. EEG power spectra were analyzed in relevant frequency bands during each sleep state, and exploratory analyses were conducted

Conclusion

Minimal effects on sleep macroarchitecture were seen in mice 10 days after SPS. It is possible that sleep disturbances seen immediately after trauma exposure (such as in prior studies in rats) may have diminished over time. Further studies will need to include additional timepoints and analysis of sleep microarchitecture following SPS, and in other mouse models of PTSD, in order to more comprehensively examine changes in sleep.

Support (if any)

VA CDA #IK2 BX002712, Portland VA Research Foundation, Medical Research Foundation
113 Effects of Sleep on Intrusive Symptoms and Emotion Reactivity in a Laboratory-Based Film Analogue Study
Authors: Nguyen Anna Marie , Campbell Rebecca , Vance Abigail , Leen-Feldner Ellen
Published: May 2021

Introduction

Recent literature highlights the need to focus on the impact of intrusive symptoms as a possible risk factor for the development and maintenance of PTSD. Cognitive and sleep models also contribute to the further understanding of intrusive symptoms. Further emotion work emphasizes that disgust is an emotion closely associated with the emergence of posttraumatic stress symptomology following traumatic events.

Methods

This study utilized a film eliciting disgust to examine the effects of acute sleep deprivation on the intensity of intrusive symptoms and emotion reactivity. Forty-nine college students were randomly assigned to sleep as usual or an acute sleep deprivation after watching a disturbing film. It was hypothesized that, relative to the control group, participants who were acutely sleep deprived would report higher frequency of intrusive symptoms and higher negative valence.

Results

Findings were partially consistent with hypotheses. There were no group or interaction effects on intrusive symptoms, although participants across both groups reported significant decreases in negative valence and intrusive symptoms across the study (F(1, 47) = 10.30, p < 0.01). There was a significant interaction effect between sleep group and self-reported negative valence, where individuals in the sleep deprived group reported significantly higher valence than individuals in the control group, despite significant decreases in negative valence over time (F(1, 48) = 7.869, p < 0.01).

Conclusion

Possible mechanisms that may contribute to the significant difference in valence may be due to higher order emotion regulation strategies that are compromised due to sleep loss. However, the significant decreases in negative valence and intrusive symptoms over time may be due to methodological factors or the type of sleep manipulation. Further work can address these challenges by using a larger sample size or examining the effects of chronic, partial sleep deprivation.

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116 Behavioral Attention Raw Scores Best Differentiate Cognitive Resilience and Vulnerability to Sleep Loss
Authors: Yamazaki Erika , Brieva Tess , Casale Courtney , Antler Caroline , Goel Namni
Published: May 2021

Introduction

There are substantial, stable individual differences in cognitive performance resulting from sleep restriction (SR) and total sleep deprivation (TSD). The best method for defining cognitive resilience and vulnerability to sleep loss remains an unanswered, yet important question. To investigate this, we compared multiple approaches and cutoff thresholds to define resilience and vulnerability using the 10-minute Psychomotor Vigilance Test (PVT).

Methods

Forty-one healthy adults (ages 21-49; mean±SD, 33.9±8.9y; 18 females) participated in a 13-night experiment [2 baseline nights (10h-12h time-in-bed, TIB), 5 SR nights (4h TIB), 4 recovery nights (12h TIB), and 36h TSD]. The PVT was administered every 2h during wakefulness. PVT lapses (reaction time [RT]>500 ms) and 1/RT (response speed) were measured. Resilient and vulnerable groups were defined by three approaches: average performance during SR1-5, average performance change from baseline to SR1-5, and variance in performance during SR1-5. Within each approach, resilient/vulnerable groups were defined by +/- 1 standard deviation and by the top and bottom 12.5%, 20%, 25%, 33%, 50%. Bias-corrected and accelerated bootstrapped t-tests compared PVT performance between the resilient and vulnerable groups during baseline and SR1-5. Kendall’s tau correlations compared the ranking of individuals in each group.

Results

T-tests revealed that the resilient and vulnerable PVT lapses groups, defined by all three approaches, had significantly different mean PVT lapses at all cutoffs. Resilient and vulnerable PVT 1/RT groups, defined by raw scores and by change from baseline, had significantly different mean PVT 1/RT at all cutoffs. However, resilient/vulnerable PVT 1/RT groups defined by variance only differed at the 33% and 50% cutoffs. Notably, raw scores at baseline significantly differed between resilient/vulnerable groups for both PVT measures. Variance vs. raw scores and variance vs. change from baseline had the lowest correlation coefficients for both PVT measures.

Conclusion

Defining resilient and vulnerable groups by raw scores during SR1-5 produced the clearest differentiation between resilient and vulnerable groups at every cutoff threshold for PVT lapses and response speed. As such, we propose that using PVT raw score is the optimal approach to define resilient and vulnerable groups for behavioral attention performance during sleep loss.

Support (if any)

ONR Award No.N00014-11-1-0361;NIH UL1TR000003;NASA NNX14AN49G and 80NSSC20K0243;NIH R01DK117488
128 Raw Scores Best Differentiate Resilience and Vulnerability to Sleep Loss for Cognitive Throughput and Working Memory
Authors: Brieva Tess , Casale Courtney , Yamazaki Erika , Antler Caroline , Goel Namni
Published: May 2021

Introduction

Substantial individual differences exist in cognitive deficits due to sleep restriction (SR) and total sleep deprivation (TSD), but the best approach to define such resilience and vulnerability remains a critical question. We compared multiple approaches and cutoff thresholds to define resilience and vulnerability using the Digit Symbol Substitution Task (DSST) and the Digit Span Task (DST).

Methods

Forty-one healthy adults (mean±SD ages,33.9±8.9y) participated in a 13-night experiment [two baseline nights (10h-12h time-in-bed, TIB), 5 SR nights (4h TIB), 4 recovery nights (12h TIB), and 36h TSD]. The DSST [measuring cognitive throughput] and DST [measuring working memory] were administered every 2h during wakefulness. Resilient/vulnerable groups were defined by average performance (DSST: number correct; DST: total correct from forward and backward versions) during SR1-5, average performance change from baseline during SR1-5, and variance in performance during SR1-5. Within each approach, groups were defined by +/-1 standard deviation (SD) and the top and bottom 12.5%, 20%, 25%, 33%, 50%. Bias-corrected and accelerated bootstrapped t-tests compared performance between resilient and vulnerable groups during baseline and SR1-5. Kendall’s tau correlations compared the ranking of individuals in each group.

Results

T-tests showed significant differences between resilient/vulnerable groups at all raw score cutoffs for DSST and DST performance during SR and at baseline. Change from baseline t-tests showed significant differences during SR between the DSST groups only at 12.5%, 20%, and SD whereas DST t-tests showed significant differences at all cutoffs. Variance t-tests revealed a significant difference between the DSST groups only at 25% during SR. For the DSST, the variance vs. change from baseline comparison at all cutoffs and between raw score vs. change from baseline for the SD cutoff showed moderate correlations, and for the DST, the raw score vs. change from baseline correlation was moderate for 25% and 33%.

Conclusion

The resilient/vulnerable groups defined by raw score were more consistent than those defined by change from baseline or variance, and raw score did not track these approaches well. As such, raw score is the optimal approach to define cognitive throughput and working memory performance resiliency/vulnerability during sleep loss.

Support (if any)

ONR Award No. N00014-11-1-0361;NIH UL1TR000003;NASA NNX14AN49G and 80NSSC20K0243;NIH R01DK117488
132 Impact of Experimentally Shortened Sleep on Meal Timing in Adolescents
Authors: Duraccio Kara , Whitacre Catharine , Beebe Dean
Published: May 2021

Introduction

Short sleep increases the risk for obesity in adolescents. One potential mechanism relates to when eating occurs, rather than what or how much is eaten. This study investigated the impact of shortened sleep on meal timing and late evening eating in adolescents.

Methods

93 healthy 14- to17-year-olds (62% female) completed a within-subject counterbalanced experimental sleep manipulation, engaging in shortened sleep (SS; 6.5 hours/night in bed) or healthy sleep (HS; 9.5 hours/night in bed), each for five nights, with order randomized. Sleep timing was verified through wrist-worn actigraphy. During each sleep period, adolescents completed 2-3 dietary recalls. Repeated-measure T-tests assessed the sleep manipulation effect on averaged times of the first and last eating episode, number of eating episodes after 8:00pm, and range of the daily eating period.

Results

Youth averaged 2.2 hours/night longer sleep during HS than SS (p<.001). The timing of the first eating episode was similar across conditions, relative to the clock (SS=08:51, HS=08:52) and to time since waking (SS=1.8hr, HS=1.9hr). The timing of the last eating episode averaged later on the clock during SS (20:34) than HS (19:38; p<.001), resulting in a longer eating period (SS=11.7hr, HS=10.8hr, p<.001). Youth averaged more eating episodes after 8:00pm during SS (0.87) than HS (0.59, p<.001). The gap between last eating episode and sleep onset was larger in SS (4.1hr) than HS (2.8hr; p<.001). Notably, on average, adolescents last eating episodes during SS (20:34) were earlier than sleep onset in either condition, and were even 2 hours earlier than when they fell asleep during HS (M=22:30). In exploratory analyses, these effects did not systematically vary by experimental order of the sleep conditions, family income, or participant age, sex, or norm-referenced body mass index.

Conclusion

Shortened sleep resulted in adolescents eating later and lengthening the daily period of time in which they ate, despite typically stopping eating well before sleep onset during healthy sleep. Late evening eating and long daily eating periods have been strongly associated with weight gain, which may help explain the link between shortened sleep and increased obesity risk in adolescents.

Support (if any)

R01HL120879
133 The Effects of Chronic Sleep Restriction on Human Oculomotor Behavior
Authors: Evans Erin , Tyson Terence , Costedoat Gregory , Stone Leland
Published: May 2021

Introduction

Oculomotor behavioral metrics change according to time awake and circadian phase following a distinct pattern of impairment. Acute sleep deprivation (ASD) causes large decreases in pursuit initiation and steady-state gain, and a compensatory increase in saccadic rate without any systematic change in saccadic size. It also causes large deficits in visual processing of direction and speed, and impaired saccade dynamics. Such deterioration likely reflects changes in both higher cortical and brainstem function, explaining in-part how sleep loss and circadian misalignment affect cognition. It is unclear how oculomotor behavior might change according to chronic sleep restriction (CSR). Here, we measured the same eye-movement metrics during CSR.

Methods

Twelve healthy participants (6 females) kept a fixed wake-time sleep-wake schedule, at home for four weeks (weeks 1 and 3 = 9h time in bed (TIB); weeks 2 and 4 randomized to 5h or 9h TIB; actigraphy confirmed). Following weeks two and four, participants completed a 13-hour laboratory visit under dim light (<15 lux), where they maintained a semi-recumbent posture and were provided with hourly isocaloric snacks. A visual tracking task was performed hourly to assess pursuit and saccadic responses and visual motion processing. Performance metrics were computed using MATLAB, including pursuit gain (eye speed/target speed), the rate and amplitude of catch-up saccades, and the accuracy and precision of direction and speed processing.

Results

As expected, we found a small but significant (t(11)=-2.17, p<0.03) reduction in pursuit gain (mean+/-SEM: -0.028 +/-0.013 with a large (t(11)=2.96, p<0.01) increase in saccadic rate (0.37 +/-0.13 Hz). However, surprisingly, we found a significant (t(11)=-2.52, p<0.03) decrease in the amplitude of catch-up saccades (-0.15 +/-0.06 deg). The only systematic alteration to visual motion processing was a small reduction in horizontal-vertical asymmetry, which was previously observed with ASD.

Conclusion

A week of CSR to 5h is associated with only mild impairment in smooth pursuit eye movements with little impact on visual motion processing. However, CSR caused a maladaptive decrease in saccade amplitude that was not observed during ASD. Eye-movement metrics reveal differential neurological effects of CSR versus ASD.

Support (if any)

Force Health Protection Program, ONR (SAA2402925-1), NASA Human Research Program, and agreement NNX17AE07A
136 Sleep and Porphyromonas gingivalis K-Capsular IgG Serotypes: A Study in the Old Order Amish
Authors: Spector Anna , Wadhawan Abhishek , Constantine Niel , Ryan Kathy , Mohyuddin Iqra , Dagdag Aline , Brenner Lisa , Daue Melanie , Schifferle Robert , Ernst Robert , Mitchell Braxton , Reynolds Mark , Postolache Teodor
Published: May 2021

Introduction

Sleep problems and periodontal disease have a bidirectional relationship and are independently linked with depression, dementia, and metabolic disease. Inadequate sleep can worsen inflammation, a hallmark of periodontal disease, and the activation of the immune system can alter sleep/wake cycles. A key player in periodontal disease is Porphyromonas gingivalis, a bacteria that can translocate to the brain and induce miRNA’s. Antibodies to P. gingivalis capsular virulence factors, K1-7, have been used to estimate P. gingivalis virulence. This study was conducted to explore cross-sectional associations between seropositivity of K serotypes of P. gingivalis and measures of self-reported impairment in sleep. If identified, these links would provide a rationale to initiate causality and mediation studies. We hypothesized that sleep impairment is positively associated with P. gingivalis K IgG serointensity.

Methods

880 Old Order Amish aged 44.8 (SD: 17.2 years); 360 men (40.91%), 520 women (59.09%) responded to an adapted Pittsburgh-Sleep-Quality-Index questionnaire. IgG serointensity to 7 K-capsular P. gingivalis serotypes were measured with ELISAs. We tested for the association of log-transformed serotype IgG intensity and positivity (successively defined as within the top 5% and 25% for each serotype) with sleep parameters (as binary and continuous variables) using linear and logistic regressions, adjusting for age and sex.

Results

We confirmed no hypothesized associations between any of the sleep problems on the PSQI and K serotype serointensity and seropositivity. Exploratory analysis returned a negative association of log-transformed K3 IgG with daytime sleepiness (p=0.01); however, this did not resist adjustment for multiple comparisons and was inconsistent with the direction of the hypothesis.

Conclusion

Strengths of the study include the reduced smoking prevalence in the Amish and the relatively homogenous lifestyle, reducing confounding. The results imply P. gingivalis serotypes are not associated with sleep disturbance. Limitations are self-reporting of sleep, cross-sectional approach and limited generalizability. Results do not support an association between P. gingivalis K serotypes and sleep-problems.

Support (if any)

MVM-CoRE
138 Short Sleep and Insomnia as Independent Predictors of Obesity, Hypertension, and Diabetes
Authors: Knowlden Adam , Grandner Michael
Published: May 2021

Introduction

Epidemiological evidence of short sleep’s (<6 hours) association with negative cardiometabolic health outcomes continues to mount; yet, the complex relationship between sleep and health is still not well-understood. Sleep problems, such as short sleep and insomnia, are often analyzed as a singular construct at the population level; however, it has been proposed that, although these two sleep problems likely overlap, they are separate phenomena. The purpose of this study was to: (1) determine if short sleep and insomnia were independent constructs; and to (2) evaluate whether short sleep and insomnia predicted obesity, hypertension, and diabetes.

Methods

Analyses were based on the 2015-2016 National Health and Nutrition Examination Survey (NHANES). NHANES employs a complex, multistage, probability sampling design to survey a representative sample of non-institutionalized U.S. adults (≥18 years). Data related to short (<6), normal (7-8), and long (9+) sleep duration, insomnia (present: mild, moderate, severe), hypertension (present: previous hypertension/hypertension medications/blood pressure in the hypertensive range), and diabetes (present: history of diabetes/fasting blood sugar of 130+) were extracted for analysis. Age, sex, and obesity (body mass index, 30.0+) were entered as covariates into the models.

Results

Among the subjects, 0.08% were normal sleepers with insomnia; 0.21% were short sleep with insomnia; and, 0.59% had insomnia with short sleep. Short sleep without insomnia (OR=1.35; p<.001), normal sleep with insomnia (OR=1.56; p<.001), and short sleep with insomnia (OR=1.64; p<.001) uniquely predicted obesity. As well, short sleep without insomnia (OR=1.23; p=0.004) as well as short sleep with insomnia (OR=1.21; p<0.001) independently predicted hypertension. Furthermore, short sleep with (2.01; p<0.001) and without (OR=1.48; p<0.001) insomnia as well as normal sleep with insomnia (p=0.007) uniquely predicted diabetes.

Conclusion

Findings from this study suggested short sleep and insomnia are independent constructs, uniquely predicting obesity, hypertension, and diabetes. Short sleep and insomnia neither mediated nor moderated one another, implying these two sleep outcomes are not additive in nature, but are instead separate health problems. The distinction between short sleep and insomnia may have important epidemiological and clinical implications.

Support (if any)

N/A
141 Screen-based activities predict delayed sleep timing within and between adolescents
Authors: Reichenberger David , Master Lindsay , Buxton Orfeu , Hale Lauren , Chang Anne-Marie
Published: May 2021

Introduction

Daytime and evening screen use have been associated with poor sleep health among adolescents, especially delayed sleep timing. However, most studies only investigate associations between adolescents rather than within the same person across multiple nights. Our multilevel modeling approach allows for assessment of connection between screen use and subsequent sleep timing.

Methods

We analyzed approximately five days of data from the Fragile Families and Child Wellbeing Study, a longitudinal birth cohort (n=475 adolescents, 15.4±0.5 years old). Adolescents wore wrist actigraphy devices and completed daily surveys reporting how many hours across the day they engaged in screen-based activities (e.g., communicating with friends, playing video games) and whether they engaged in screen-based activities in the hour before bed. Screen use was separated into within- and between-person variables predicting sleep onset and midpoint that night. Multilevel models with random intercepts for each sleep outcome adjusted for school days, bedtime routines, adolescent demographics, and family socioeconomic status.

Results

Within-person results showed that on days when adolescents played video games more than their daily average±SE (79±3 min) sleep onset was delayed (5±2 min, p<0.01) and midpoint was delayed (4±2 min, p<0.03) for each additional hour. Between-person results showed that adolescents who played video games had delayed sleep onset (9±4 min, p<0.02) and midpoint (7±3 min, p<0.04) for each hour spent playing across the day. Adolescents who spent time using screens to communicate with friends had delayed sleep onset (11±3 min, p<0.01) and midpoint (9±3 min, p<0.01) for each hour across the day. Adolescents who were more likely to use screens to communicate with friends or play video games before bed had delayed sleep onset (29±13 min, p<0.03) and midpoint (24±12 min, p<0.05). Other screen-based activities such as watching videos were not associated with sleep timing.

Conclusion

Daytime and evening screen-based activities may not uniformly delay sleep. Adolescents who engage in social or interactive screen-based activities may delay sleep timing more than day-to-day variation alone. Future research should evaluate how attributes of screen-based socializing and interactivity affect sleep health.

Support (if any)

R01HD073352 (to LH), R01HD36916, R01HD39135, R01HD40421
152 Prospective associations between pre-sleep electronics use and same-night sleep in healthy school-aged children
Authors: So Christine , Gallagher Matthew , Palmer Cara , Alfano Candice
Published: May 2021

Introduction

Electronic media devices are ubiquitous in modern society and believed to adversely affect nighttime sleep. Cross-sectional research provides evidence of robust associations but prospective findings are limited and mixed. In this study, we examined the impact of specific types of electronics devices and overall use on objective and subjective sleep parameters the same night across one week.

Methods

The sample consisted of school-aged children (N=55) between the ages of 7 to 11 years. Hierarchical linear modeling was used to assess the impact of pre-bedtime electronics use on sleep the same night across 5 weekday nights. A sleep diary was used to record pre-bed electronic devices used and subjective sleep parameters. Objective sleep variables were assessed concurrently via actigraphy.

Results

The usage of different types of electronic media varied significantly between and within children across the five days. However, neither total electronics usage nor any individual type of device was found to significantly predict self-reported or objective sleep parameters the same night.

Conclusion

The extent to which the use of electronic media specifically within an hour of bedtime impacts sleep in school-aged children remains unclear. Future research should investigate these relationships using more robust methodology, including prospective designs and examination of relevant contextual and environmental factors.

Support (if any)

This study was funded by the National Institute of Mental Health [grant number #R21 MH099351] awarded to the last author.
160 Underlying Factors Contributing to Sleep Health Among Middle-aged and Older Adults
Authors: Lorenz Rebecca , Chandola Varun , Auerbach Samantha , Orom Heather , Li Chin-Shang , Chang Yu-Ping
Published: May 2021

Introduction

Although poor sleep is not inherent with aging, an estimated 50-70 million adults in the US have insufficient sleep. Sleep duration is increasingly recognized as incomplete and insufficient. Instead, sleep health (SH), a multidimensional concept describing sleep/wake patterns that promote well-being has been shown to better reflect how sleep impacts the individual. Therefore, focusing on the underlying factors contributing to sleep health may provide the opportunity to develop interventions to improve sleep health in middle-age and older adults.

Methods

Data from the 2014 wave of the Health and Retirement Study (HRS) were used. Sample size was restricted to those who completed an additional questionnaire containing sleep variables. A derivation of the SH composite was constructed using eight selected sleep variables from the HRS data based on the five dimensions of sleep: Satisfaction, Alertness, Timing, Efficiency, and Duration. Total score ranged from 0-100, with higher scores indicating better SH. Weighting variables were based on complex sampling procedures and provided by HRS. Machine learning-based framework was used to identify determinants for predicting SH using twenty-six variables representing individual health and socio-demographics. Penalized linear regression with elastic net penalty was used to study the impact of individual predictors on SH.

Results

Our sample included 5,163 adults with a mean age of 67.8 years (SD=9.9; range 50-98 years). The majority were female (59%), white (78%), and married (61%). SH score ranged from 27-61 (mean=50; SD=6.7). Loneliness (coefficient=-1.92), depressive symptoms (coefficient=-1.28), and physical activity (coefficient=1.31) were identified as the strongest predictors of SH. Self-reported health status (coefficient=-1.11), daily pain (coefficient=-0.65), being middle-aged (coefficient=-0.26), and discrimination (coefficient=-0.23) were also significant predictors in this model.

Conclusion

Our study identified key predictors of SH among middle-aged and older adults using a novel approach of Machine Learning. Improving SH is a concrete target for health promotion through clinical interventions tailored towards increasing physical activity and reducing loneliness and depressive symptoms among middle-aged adults.

Support (if any)

This study was supported by National Heart, Lung, and Blood Institute (NHLBI) UB Clinical Scholar Program in Implementation Science to Achieve Triple Aims-NIH K12 Faculty Scholar Program in Implementation Science