bluuebunny/crossref_metadata_2025 huggingface dataset:
0302 Recovery Sleep in University Students
Authors: Spaeth Andrea , Glavin Emily
Published: May 2022

Introduction

Poor sleep hygiene is common in American college students, with the majority reporting insufficient sleep. Previous studies suggest that many students extend sleep during the weekend to recover sleep debt accrued during the week. In the current study we objectively measured sleep to determine if weekend catch-up sleep was practiced. We also provided students with a 9h sleep opportunity in order to observe how an extended sleep period affected sleep architecture.

Methods

Students (N=36, 20 women, 19.9±1.7 years) participated in the study from September 2019-March 2020. Sleep-wake behavior was assessed for two weeks using wrist actigraphy and a twice-daily diary. During this two-week period, participants wore at-home polysomnography (PSG) on two non-consecutive nights. For these two nights, in counterbalanced order, participants were instructed to follow their typical sleep pattern or to extend their sleep opportunity to 9h. Within-subjects ANOVA were used to compare sleep between week (Sunday-Thursday) and weekend (Friday and Saturday) nights as well as between typical and 9h PSG nights.

Results

Compared to week nights, participants went to bed 35 minutes later and woke up 58 minutes later on weekend nights (ps<0.01). Measures of sleep duration and sleep continuity were comparable (ps>0.10) between week and weekend nights and indicated that students averaged less than 7h of sleep per night (6.3±1.0h on week nights and 6.7±1.1h on weekend nights). Self-report measures of sleep quality and daytime sleepiness were also comparable between week and weekend nights (ps>0.05). When instructed to extend their sleep opportunity to 9h, participants exhibited high adherence and increased total sleep time by 88 minutes compared to the typical night (p<0.05). This increase in sleep was due to significant increases in time spent in all four stages of sleep (NREM S1-3 and REM sleep, ps<0.05).

Conclusion

In this study, students did not utilize weekend nights to extend sleep in order to recover accumulated sleep debt from the week. When provided with a 9h sleep opportunity, participants were physically able to extend sleep and exhibited high quality sleep, suggesting that the primary driver of insufficient sleep in this population is a lack of sleep opportunity rather than impaired sleep ability.

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0306 Normative Data of Cyclic Alternating Pattern across the Lifespan
Authors: Migueis Debora , Lopes Maria-Cecilia , Spruyt Karen , Lacerda Glenda
Published: May 2022

Introduction

Cyclic alternating pattern (CAP) is a marker of sleep instability, and neuroplasticity. Slow wave sleep has been described as a stable period, and CAP can be a marker of funcional delta sleep. The aim of this review was to evaluate the normative data of CAP parameters according to the aging process in healthy subjects.

Methods

Two authors independently searched databases using PRISMA guidelines through a systematic review and meta-analysis. Subgroup analysis and tests for heterogeneity were conducted. Descriptive statistics were used for the analysis of CAP variables. Meta-analyses were performed by using Comprehensive Meta- Analysis software. Data extracted from tables provide

Results

We found the evolution of CAP rate across the lifespan. Squares and diamond represent the CAP mean while bars represent the CAP range between 95% CI values according to each age range. We analysed 168 healthy individuals by CAP analyses. Scoring of CAP can begin at 3 months of life, when K-complexes, delta bursts, or spindles can be recognized. Rate of CAP increased with age, mainly during the first 2 years of life, then decreased in adolescence, and increased in the elderly. The A1 CAP subtype and CAP rate were high in school-aged children during slow-wave sleep (SWS). Our meta-analysis registered the lowest CAP rate in infants younger than 2 years old and the highest in the elderly.

Conclusion

The normative data of CAP in NREM sleep can be connected with brain maturation.The CAP rate increased with age and sleep depth, especially during SWS. These data in sleep disorders can be a treatment goal. CAP may reflect neurodiversity of endophenotype and human cronobiotypes. Further studies about CAP subtypes are needed.

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0308 The stability of slow wave sleep and EEG microstructure measures across two consecutive nights of laboratory polysomnography in cognitively normal older adults
Authors: Mullins Anna , Parekh Ankit , Kam Korey , Bubu Omonigho , Schoenholz Reagan , Patel Shayna , Kovasyuk Zanetta , Castillo Bresne , Roberts Zachary , Rapoport David , Ayappa Indu , Varga Andrew , Osorio Ricardi
Published: May 2022

Introduction

Healthy and sleep disordered populations show high night-to-night variability of polysomnographic (PSG) macrostructure metrics, however there is evidence of stability in EEG microstructure. In-laboratory PSG is critical to gold standard measures of sleep physiology but multi-night investigations are resource heavy and burdensome to participants. Given the theoretical link between sleep and Alzheimer's disease (AD) pathology (tau and β-amyloid burden), we assessed the night-to-night reliability of sleep macrostructure and EEG microstructure in a group of cognitively normal elderly participating in aging and memory studies.

Methods

107 participants (mean = 67±8 yrs., range [54-84 yrs.], 72% female) attended 2 consecutive nights PSG scored according to AASM guidelines for sleep staging, respiratory and leg movement events. Midline EEG (Fz, Cz and Pz referenced to average mastoid signals) were analyzed in 98 participants using an automatic algorithm (DETOKS) for detection of relative slow wave (0.5-4Hz) activity (SWA), NREM2 spindle and K-complexes (KC) densities. Differences between night 1 and 2 for total sleep time (TST), slow wave sleep (SWS), rapid eye movement (REM), stage 2 (%NREM 2), sleep efficiency (SE), apnea hypopnea (AHI) and periodic limb movement (PLM) indices, and EEG microstructure were assessed using t-tests and Wilcoxon rank sum tests where appropriate. Two-way intraclass correlations (ICC) for single unit and absolute agreement were used to determine variability between nights for all measures.

Results

Night 2 PSGs showed significantly greater TST (6.3 vs 6.8 hours, p<0.001), %REM (17.5 vs 19.7, p<0.001), SE (84.9 vs 87.4%, p<0.02) and SWA (Fz:76.8 vs 78.0%, p<0.01). There were no significant differences between nights for %SWS, %NREM2, AHI, PLMs, spindle and KC densities. ICC and 95% confidence interval estimates were low for TST(0.28), %REM(0.32) and SE(0.32), moderate for %SWS(0.67) and %NREM2(0.59), good for AHI(0.78), SWA(Fz:0.86) and KCs(Fz:0.85), and excellent for PLMs(0.91) and spindles (Pz:0.97).

Conclusion

SWS, SWA, spindles, KC’s, AHI and PLM indices show good to excellent intra-individual stability across two consecutive nights of PSG. Although there were differences in %REM, SE and SWA, these were numerically small and perhaps functionally or clinically less significant. One night of in-lab PSG is enough to provide reliable estimates of individuals’ SWS, SWA, spindles, KC’s and sleep disorders.

Support (If Any)

Funding NIH R21AG055002, K24HL109156, R01AG056682, R01AG056531
0310 Sleep Health Characteristics in Sedentary Desk-Based Workers
Authors: Cheruka Caitlin , Egeler Mara , Kubala Andrew , Vogan Olivia , Patel Sanjay , Hall Martica , Jakicic John , Perera Subashan , Gibbs Bethany Barone , Kline Christopher
Published: May 2022

Introduction

Many occupations consist of predominantly desk-based work, which leads to prolonged periods of sitting during the workday. Excessive periods of sedentary behavior could have a negative impact on health outcomes, including sleep. The purpose of this study was to characterize sleep health in a sample of sedentary desk-based workers.

Methods

This secondary analysis of baseline data from an ongoing clinical trial included 125 inactive adults with elevated, nonmedicated blood pressure and desk-based occupations (49.6% female, age=43.9±10.6 y, 85.6% White race, body mass index [BMI]=30.9±6.4 kg/m²). Sleep was assessed using validated questionnaires (e.g., Pittsburgh Sleep Quality Index [PSQI], Insomnia Severity Index [ISI]) and 7 nights of actigraphy. Six dimensions of sleep health (regularity, satisfaction, alertness, timing, efficiency, and duration) were categorized as “good” or “poor”; a composite score summed good sleep health dimensions on a scale of 0-6.

Results

The mean sleep health score was 4.7±1.1; 24.8% of participants met “good” criteria for all 6 sleep health dimensions. The most common “good” sleep health dimensions were efficiency (89.0%) and alertness (87.2%); the least common was regularity (60%). The mean PSQI score was 5.5±3.0, and 41.6% had poor sleep quality (PSQI >5); a trend was observed in adults with poor sleep quality to have lower sleep health (p=0.055). The mean ISI score was 7.1±4.7, and 40% had at least mild-severity insomnia symptoms (ISI ≥8); those with insomnia symptoms had significantly lower sleep health compared to those without insomnia symptoms (p=0.04). Sleep health was not significantly correlated with age, BMI, systolic blood pressure, diastolic blood pressure, mean arterial pressure, or mean daily sedentary behavior (each r≤ .08, p≥0.38) and did not differ between males and females (p=0.26). However, White adults had significantly better sleep health compared to their non-White counterparts (6.4% Black, 5.6% Asian, 2.4% other) (p<0.001).

Conclusion

This sample of sedentary desk-based workers presented generally good sleep health. This warrants future investigations comparing adults with different levels of occupational activity and non-desk-based occupations to understand why highly sedentary behavior is associated with negative health outcomes.

Support (If Any)

This study was funded by National Institutes of Health (NIH) grants R01HL134809 and R01HL147610.
0311 The day after: how does a poor sleep perception affect pain during the night?
Authors: Morelhao Priscila , Fernandes Guilherme , Dokkedal-Silva Vinícius , Pires Gabriel , Tufik Sergio , Andersen Monica
Published: May 2022

Introduction

Senescence generates repercussions on sleep, including increased difficulty to initiate and maintain sleep, more awakenings, diurnal naps, and a propensity to polyphasic sleep. These disorders might be more common in older individuals with musculoskeletal pain. In this sense, the relationship between sleep and pain is considered to be bidirectional. However, it is unclear in the literature whether feeling pain during the night could be associated with poor subjective sleep quality. Our objective was to describe a measurement model that appropriately conveys the link between sleep and feeling pain at night.

Methods

A cross-sectional analysis was conducted, using a dataset from the 2015 São Paulo Epidemiological Sleep Study (EPISONO), including only individuals aged 60 years or more. Two constructs were formulated: an objective sleep quality construct, based on the polysomnography (PSG) performed on all EPISONO volunteers and a subjective sleep quality construct, formed by the self-reported answers in the Pittsburgh Sleep Quality Index (PSQI) and Insomnia Severity Index (ISI). Musculoskeletal pain was assessed by 1. Did you feel any pain during the night? 2. Did you wake up feeling pain? (Possible answers: “Yes” or “No”). We used exploratory factor analysis and structural equation modelling to identify the significant variables.

Results

A total of 152 older adults was analyzed in this study. The PSQI and ISI indicate poor perception of sleep or a high frequency of sleep complaints in proportion to their score, the resulting latent factor was labelled poor sleep perception. The exploratory factor analysis assessed the measurement models of the latent factors and resulted in the inclusion of sleep-related variables: wake after sleep onset, sleep efficiency, total sleep time, latency to sleep onset and amount of N1 stage in the objective sleep quality factor. However, this factor was not associated with felling pain during the night and woke up with pain.

Conclusion

Our findings suggest that poor sleep perception was associated with feeling pain at night in older adults. These results contribute for the improvement of future clinical evaluations of patients presenting musculoskeletal pain and sleep complaints and highlight the importance of considering both factors simultaneously during treatment.

Support (If Any)

The study was supported by Associação Fundo de Incentivo à Pesquisa (AFIP) and Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES Finance Code 001 to GLF) and Conselho Nacional de Desenvolvimento Científico Tecnológico (CNPq–Grant #133397/2017-3, #141445/2021-1 to GLF); MLA and ST are Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) fellowship recipients.
0317 Interaction of Sleep and Emotion Across the Menstrual Cycle
Authors: Meers Jessica , Bower Joanne , Nowakowski Sara , Alfano Candice
Published: May 2022

Introduction

Women experience increased risk for sleep and affective disorders compared to men, attributed in part to monthly oscillations in sex hormones. Emotional functioning worsens during the perimenstrual phase. There is increasing evidence that sleep continuity also decreases during this phase. Thus, this study examined the interactive effects of sleep and menstrual phase on emotion across two menstrual cycles in healthy women.

Methods

Participants (N=51, 43% Caucasian) aged 18-35 (m=23.67) completed actigraphy and daily sleep/emotion diaries over two menstrual cycles (m days=51.29). Cycles were identified via date of menses and urinary ovulation detection, and coded into four phases: perimenstrual, mid-follicular, periovulatory, and mid-luteal. The perimenstrual phase was defined the 3 days prior to and the 3 days following menses onset. Variables included diary and actigraphic total wake time (TWT), daily ratings of positive (happy, calm, enthusiastic) and negative (angry, afraid, sad) affect using a 9-point scale. Relationships between phase, sleep, and emotion were estimated using multistep hierarchical linear modeling. Pandemic-related stress and daily US and region-specific COVID-19 case counts were included as covariates in adjusted models.

Results

Mean menstrual cycle length was 28.61±2.69 days. Menstrual phase was first entered into models as predictors for sleep and emotion variables independently. The perimenstrual phase positively predicted anger (p<.001) but no other emotions. Additionally, the perimenstrual phase predicted higher rates of TWT, such that diary-reported TWT was 8-16 minutes longer during the perimenstrual (m=67.54, SE=3.37) compared to other phases (p<.001). Actigraphic TWT was also increased by 4-7 minutes (m=61.54, SE=3.37) in the perimenstrual phase (p<.001). A second model included the interaction term, TWT*phase to the original model. Positive emotions were .05-.10 points lower (p’s=.006-.02) when TWT was greater in the perimenstrual phase.

Conclusion

Menstruating women experienced greater rates of anger and sleep disruption during the perimenstrual phase compared to other phases. When poor sleep occurred during the perimenstrual phase, however, women reported reduced positive emotions. Sleep disruptions, particularly occurring during the perimenstrual phase, may be an important intervention target for women at risk for affective disorders. Future studies should be mindful to assess menstrual phases when assessing sleep and circadian rhythm.

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0320 Sex Differences in Sleep Quality and Biomarker Levels in Service Members and Veterans with Chronic Mild Traumatic Brain Injury
Authors: Guedes Vivian , Mithani Sara , Gottshall Jackie , Lai Chen , Devoto Christina , Gill Jessica , Kenney Kimbra , Werner J Kent
Published: May 2022

Introduction

Sleep disorders are highly prevalent in military populations and are frequently associated with a history of traumatic brain injury (TBI). Despite the recent increase in female representation in the military, few studies have focused on sex differences in sleep quality in military populations. In this study, we examined biological sex differences in self-reported sleep quality and blood levels of protein biomarkers of TBI in a cohort of service members and veterans with chronic mild TBI (mTBI).

Methods

Participants (n=1,121) were enrolled in the Chronic Effects of Neurotrauma Consortium (CENC)/Long Term Impact of Military Brain Injury Consortium (LIMBIC) study. Females (n=147) and males (n=974) were classified into control (n=192, no TBI history) or mTBI (n=929, positive history of mTBI) groups. Self-reported sleep quality was assessed using PSQI (Pittsburgh Sleep Quality Index). Plasma levels of glial fibrillary acidic protein (GFAP), neurofilament light chain (NfL), Tau, interleukin (IL)-10, IL-6, and tumor necrosis factor-alpha (TNFα) were analyzed using a Simoa HD-X analyzer.

Results

Regression models revealed higher PSQI scores in females than males (ß(SE)=1.36(0.40), p =0.001) and in the TBI group (ß(SE)=1.97(0.36), p<0.001) in comparison to controls. TBI x sex interaction was not statistically significant. Within the mTBI group, females had higher PSQI scores (p=0.031) and GFAP levels (p<0.001) than males, which remained significant when controlling for demographics, number of mTBIs, and time since last mTBI. No other significant differences in biomarker levels were observed. In men, but not women, higher levels of GFAP were associated with lower PSQI scores (ß(SE)=-1.38(0.43), p=0.001).

Conclusion

Our findings suggest sex differences in sleep quality after mTBI, providing insights into possible mechanisms underlying the development of chronic symptoms in military populations. Our results support the need for considering biological sex in the development of personalized therapeutic strategies for chronic TBI-related sleep disorders.

Support (If Any)

This work was supported by grant funding from: The U.S. Army Medical Research and Material Command, from the U.S. Department of Veterans Affairs Long-term Impact of Military-related Brain Injury Consortium/Chronic Effects of Neurotrauma Consortium under Award No.1I01CX002097-01 and the U.S Department of Defense under Award No.W81XWH-18-PH/TBIRP-LIMBIC.
0321 Poor Agreement Among Self-Reported and Objective Sleep Deficiency Assessments in Older Persons
Authors: Miner Brienne , Yaggi Henry , Gill Thomas , Doyle Margaret , Stone Katie , Redline Susan , Ensrud Kristine , Blackwell Terri , Knauert Melissa
Published: May 2022

Introduction

Many traditional sleep questionnaires were developed in younger populations and may have poor sensitivity to detect objective sleep deficiency in older persons due to atypical presentations, aging-related decreases in symptom awareness, and different expectations about health.

Methods

In a secondary analysis of data from the Osteoporotic Fractures in Men (MrOS; Sleep Visit 1) and the Study of Osteoporotic Fractures (SOF Visit 9), we evaluated the prevalence of objective sleep deficiency among persons with scores in the normal range on traditional sleep questionnaires (Pittsburgh Sleep Quality Index [PSQI] <6 and Epworth Sleepiness Scale [ESS] <11). Objective sleep deficiency was established based on presence of sleep-disordered breathing (SDB; apnea hypopnea index [at >4% desaturation] per hour of sleep ≥15 on polysomnography), insufficient sleep duration (average sleep duration <6 hours on actigraphy), or impairment in daytime sustained attention/alertness (falling in the worst quartile of Digit Vigilance Test scores for the sex-specific cohort).

Results

Average ages were 76±6 and 84±4 years in men and women, respectively. Among men with normal scores on the PSQI and ESS, 359/1527 (25%) had SDB, 428/1519 (28%) had insufficient sleep duration, and 346/1527 (23%) had impaired daytime attention/alertness. Among women with normal scores on both the PSQI and ESS, 72/185 (40%) had SDB, 318/1332 (24%) had insufficient sleep duration, and 140/546 (26%) had impaired daytime attention/alertness.

Conclusion

A substantial proportion of older men and women with normal scores on traditional sleep questionnaires have objective sleep deficits, suggesting a need to develop instruments to improve detection of sleep deficiency in this population.

Support (If Any)

American Academy of Sleep Medicine Foundation, Yale Claude D. Pepper Older Americans Independence Center, Patterson Trust, National Institute on Aging
0323 Gender-Specific Differences in Self-Reported Factors Attributed to Sleep Disruption
Authors: Ruder Michael , Gahan Luke , Raymann Roy , Watson Nathaniel , Gottlieb Elie
Published: May 2022

Introduction

Women are more likely to report sleep difficulties. There are many ways for sleep to be disrupted (social influences, external sensory stimuli, somatic cues) but limited data exists on the relative burden of these disruptors. The purpose of the present analysis was to compare the occurrence of disruptors between males and females of equal ages.

Methods

We used self-reported data from the PSG-validated SleepScore mobile app to analyze the relative occurrence of a variety of sleep disruptors in an age- and gender-balanced sample of users (39,560 male and 39,560 female, median age=41, SD=15). Fisher's exact test was used to examine whether gender was a significant factor in the likelihood of reporting each disruptor. Disruptors were categorized as follows: somatic cues included hot flashes/thermal discomfort, chronic pain, bathroom visits, and heartburn; external sensory stimuli included temperature, light, and noise; social influences included: bed partner, pet, and children. All p < 0.00001 results are reported.

Results

Women were significantly more likely than males to report at least one sleep disruptor (Odds ratio (OR): 2.29, prevalence: 90% vs 80%) and were more likely to report sleep disruption attributed to external stimuli (OR: 1.61, prevalence: 54% vs 42%), somatic cues (OR: 1.66, prevalence: 68% vs 56%), and social influences (OR: 1.95, prevalence: 50% vs 34%). Among somatic cues, women were more likely than males to report hot flashes/thermal discomfort (OR: 3.42), chronic pain (OR: 2.32), bathroom visits (OR: 1.24), and heartburn (OR: 1.14). Among external sensory stimuli, women were more likely than males to report sleep disruption attributed to sound (OR: 1.58), light (OR: 1.54), and temperature (OR: 1.54). Among social influences related disruptive factors, women were more likely than males to report sleep disruption attributed to pets (OR: 2.31), bed partners (OR: 1.65), and children (OR: 1.62).

Conclusion

The present analysis found that women reported higher rates of regular disruption for every cause. These findings highlight the role of gender in sleep-health reporting behavior and mirror other findings showing lower symptom reporting and healthcare utilization among males.

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0328 Social Jetlag Decreases Across the Lifespan: A Longitudinal Big Data Analysis of Objective Sleep
Authors: Gottlieb Elie , Gahan Luke , Danoff-Burg Sharon , Rus Holly , Watson Nathaniel , Raymann Roy
Published: May 2022

Introduction

Changes in social zeitgebers across the lifespan likely impact the interplay between biological and social clocks that fosters the circadian misalignment seen in social jetlag. Extant literature is limited to self-reported methods and cross-sectional designs and suggests older adulthood may be associated with a reduction in social jetlag given declining social obligations occurring after retirement. Using longitudinal ecologically-valid data, we examined the association between age as a continuous measure and social jetlag. We also examined whether work cessation is associated with a reduction in social jetlag.

Methods

Data from 2,446 users (mean age: 52.2 +/- 15.8, 51.8% female) across 473,113 nights were included in the analysis 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. Social jetlag (expressed in minutes) was defined as the difference between midsleep times on week and weekend days from a user’s total recording period. Linear regressions were used for the analysis. Age was examined as a both continuous variable, and as a dummy variable in a subsequent analyses in a subgroup of older adults, serving as a proxy for pre– (n = 604, age: 54-64, mean age: 60.5 +/- 2.8) and post-retirement (n = 428, age: 65-75, mean age: 69.9 +/- 2.8).

Results

Linear regressions revealed a significant negative association between overall age and social jetlag, whereby older age was associated with a reduction in social jetlag (ß=-0.64, SE=0.082, p<0.0001). In agreement with this finding, post-retirement age was associated with a significant reduction in social jetlag (ß=-15.31, SE=3.78, p<0.0001) as compared to pre-retirement.

Conclusion

The present analysis showed that social jetlag decreases across the lifespan, and its reduction appears to be amplified following retirement. Our findings are in-line with prior work demonstrating the reduction, but not extinction, of social jetlag in older adulthood.

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0329 Social Jetlag and Increased BMI: A Population-Based Study Using a Contactless Sleep Measurement Application
Authors: Watson Nathaniel , Gahan Luke , Raymann Roy , Gottlieb Elie
Published: May 2022

Introduction

Social jetlag involves delayed bed and wake times on weekends relative to weekdays. Resulting circadian rhythm disruption, sleep disturbance, and shortened sleep have untoward consequences for human health and performance. Elevated BMI is associated with habitual short sleep and circadian disruption, as seen in shift workers. Studies assessing the relationship between social jetlag and BMI often rely on self-reported sleep patterns, or measure sleep objectively with a worn device for short periods of time. We assessed the relationship between social jetlag and BMI in a novel manner using longitudinal, ecologically valid assessments (measured in subjects typical home environment) using the PSG-validated contactless, sonar-based SleepScore mobile application.

Methods

A total of 357 individuals across 130,120 nights monitored their sleep with the contactless SleepScore mobile application (ages 18-87, mean age, 46.7% females). Social jetlag was determined in a well-established manner by subtracting the mean objective sleep midpoint on weekdays from the mean objective sleep midpoint on weekends. Body mass index (BMI) was self-reported and defined as kg/m2. Chronotype was subjectively assessed with a 5-item question ranging from definitely morning-type to definitely evening-type. Chronotype, age and gender were included in the analysis as confounds.

Results

Mean social jetlag was 26.6 min (95% CI 22.2 – 31.0). Linear regression revealed a significant association between social jetlag and BMI (ß=0.025, SE=0.012, p<0.05) after adjustment for age, gender and chronotype. Thus, for every one-minute increase in social jetlag, there was a 0.025 kg/m2 increase in BMI. For expository purposes, a social jetlag of 60 minutes would increase BMI by 1.5 kg/m2.

Conclusion

In our population-based sample of individuals using a sonar-based contactless consumer sleep technology to objectively measure sleep we found a positive association between a well-validated measure of social jetlag and BMI, such that increased social jetlag portended increased BMI. This is consistent with previous reports demonstrating the untoward effect of social jetlag on human health and metabolism. The longitudinal and ecologically valid nature of our sleep measurement adds to the veracity of our growing understanding of the problem with social jetlag.

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SleepScore Labs
0333 Gender and Menopausal Status Correlate with Sleep Surgery Outcome
Authors: Taheri Nazlie , Hong Yeon , Abdelwahab Mohammad , Huang Allen , Fleury Thomaz , Liu Stanley
Published: May 2022

Introduction

With recognized anatomic and physiological differences between males and females, it is critical to describe outcomes of sleep surgery with respect to gender. The objective of this study is to compare the subjective and objective outcomes of phase I sleep surgery with respect to gender and age.

Methods

This was a retrospective review of adult subjects who presented to a single center for surgical evaluation of OSA from January 2019 to June 2021. Only subjects undergoing phase I surgery (turbinate reduction, septoplasty, nasal valve surgery, DOME, tonsillectomy, preservation palatopharyngoplasty, tongue base reduction, genioglossus advancement, and upper airway stimulation), who also had complete pre and post-operative PSG data were included. Objective measures were post operative apnea hypopnea index (AHI), oxygen desaturation index (ODI), and lowest oxygen saturations (LOS). Subjective outcomes include Epworth Sleepiness Scale (ESS), and Nasal Obstruction and Septoplasty Effectiveness (NOSE) questionnaires. The groups were matched for age and pre-operative BMI.

Results

Twenty-six subjects met inclusion criteria, of which 12 were female and 13 were males. Of the females 5 were post-menopausal. The average male pre-operative AHI, ODI, lowest SpO2, and ESS were 34.4± 28.7, 30.2±28.3, 80.7±6.6, and 10.3±5.6 respectively. Pre-operative values for females were, 31.9±19.2, 18.47±20.4, 82.8±8.4, and 12.5±4.8 respectively. The average AHI reduction in males was 25.5± 29.1, and for females it was 8.3±21.0 (p=0.042). Specific to post-menopausal females, Average AHI reduction was 8.3± 21.0 and 20.2±16.6 for pre-menopausal females (p=0.01). The average ESS reduction in males was 3.1±3.2 (p=0.22) and for females 5.5±5.4 (p=0.001).

Conclusion

In this cohort, pre-menopausal women have higher objective surgical success rate (Sher’s criteria) after phase I surgery as compared to post-menopausal women. Men respond more favorably than women to phase I surgery based on AHI reduction, but not with ESS. Gender and menopause status are important factors in evaluating efficacy of sleep surgery.

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0334 The Role of Race-Gender Intersectionality in Associations between Insomnia Patterns and Late-Life Memory Trajectories
Authors: Zaheed Afsara , Chervin Ronald , Zahodne Laura
Published: May 2022

Introduction

Difficulty initiating sleep (DIS) may be a stronger predictor of neurodegenerative risk than other insomnia symptoms. This study examined whether longitudinal patterns of DIS are associated with subsequent memory trajectories, and whether associations differ across non-Hispanic Black and White men and women.

Methods

12,565 participants in the Health and Retirement Study (Mage=67.8±9.1, 59.1% women) who self-identified as non-Hispanic Black (14.5%) or non-Hispanic White were included. DIS (“How often do you have trouble falling asleep?”) at three biennial waves (2002-2006) was dichotomized (“never/rarely/sometimes”=0, “often”=1). Participants were categorized into three mutually exclusive groups: low (reference group), persistent, and variable DIS. Episodic memory was assessed using a 10-item word list recall test at five biennial waves (2008-2016). Latent growth curves modeled associations between DIS patterns and subsequent memory level and change, adjusting for sociodemographics (model 1), health conditions (model 2), and depressive symptoms (model 3) in 2002. Stratified models compared associations across White men, Black men, White women, and Black women.

Results

Compared to low DIS, persistent (β=-0.03, p<.001) or variable (β=-0.07, p<.001) DIS was associated with worse subsequent memory in models 1 and 2. The effect of variable (β=-0.05, p<.001), but not persistent (β=-0.01, p=.271), DIS remained in model 3. Persistent DIS was most prevalent among White women (5.4% vs. 2.4-4%), and variable DIS was most prevalent among Black women (24.1% vs. 14-22.2%). Persistent DIS was only significantly associated with memory among White women (β=-0.04, p=.003 vs. β=-0.04, p=.324 for Black Men; β=-0.03, p=.087 for White men; and β=0.01, p=.859 for Black women). Variable DIS was most strongly associated with memory among Black men (β=-0.141, p=.003), followed by White men (β=-0.09, p<.001), White women (β=-0.06, p<.001) and Black women (β=-0.06, p=.064). There were no associations between DIS patterns and memory change.

Conclusion

While links between persistent DIS and subsequent memory may reflect negative cognitive effects of depression, variable DIS may presage worse memory above and beyond depression. Race/gender differences in the prevalence and predictive value of DIS patterns for subsequent cognitive function highlight the value of an intersectional lens. Gender disparities in DIS may be more prominent than racial disparities.

Support (If Any)

NIA F31AG067717 (PI: Zaheed)
0340 Non-Surgical Maxillary Expansion Using A Novel Oral Appliance System
Authors: Heckman Seth , Katz Daniel , Kushida Clete
Published: May 2022

Introduction

Complete Airway Repositioning and Expansion (CARE; Vivos Therapeutics, USA) consists of a series of dental devices that cause gradual expansion of the airway over an 18-month course used to treat mild-to-moderate obstructive sleep apnea. In this retrospective database review we sought to determine whether airway and obstructive sleep apnea (OSA) parameters changed via treatment as measured without the appliance in their mouths.

Methods

After IRB exemption by the Mount Sinai Health System IRB (STUDY-21-01561) we conducted a retrospective review of the Vivos database. Demographics, pre-, mid-, or post-treatment maxillary dimensions, and pre-, mid-, or post- treatment sleep study parameters were reviewed. CBCT parameters for trans-palatal width (TPW) and total three dimensional (3D) airway volume were analyzed along with available AHI data.

Results

There were 786 patients with complete radiographic datasets. The median (interquartile range) age was 49 (36-59) years, and half were female. Both the median TPW of 33.5 (31.0-35.3) mm and median 3D volume of 19,752 (15965-25042) mm3 increased, to 35.0(33.0-37.5) mm and 21919 (17484-27711) mm3, respectively. These increases were significantly different (p<0.001 in both measures by related-samples Wilcoxon signed rank test). A subset of patients had complete sleep study data (N=139). For those patients with pre- and post-treatment studies who had also completed at least 18 months of therapy (N=37), the TPW increased by a median of 2.50 (1.00-3.50) mm and the 3D volume by a median of 3092 (1006-6480) mm3. Overall, the number of patients with no OSA went from 4 to 13 and the number of patients with severe OSA went from 10 to 3. Twenty-five patients (65%) had improved AHI, and 15 (41%) had their AHI improve by 50% or more (all of these were decreased to an AHI <20).

Conclusion

This retrospective database review showed that OSA patients treated with BOAT improved their OSA with concomitant increases in maxillary dimensions. Further analyses of these data, and future prospective clinical trials are warranted to better understand this novel OSA treatment.

Support (If Any)

Support from Vivos Therapeutics in the form of granting access to their database and compensated clinical advisors.
0342 Use of a Diffused Fragrance Before Bed May Contribute to Improved Objective and Perceived Sleep
Authors: Rus Holly , Danoff-Burg Sharon , Weaver Morgan , Rodriguez Rodolfo , Gavrilova Larisa , Gottleib Elie , Lillford Stephen , Raymann Roy
Published: May 2022

Introduction

This study examined if a diffused fragrance used at home before bedtime would contribute to sleep improvement in a sample of healthy females. Existing evidence regarding the sleep-promoting properties of fragrances often has been anecdotal or based on clinical research, thereby limiting the generalizability and ecological validity of results.

Methods

26 women with self-reported interest in air care to support healthy sleep participated in a 9-week field study. A within-subjects, counterbalanced intervention design was implemented, comparing 3 weeks of nightly product use to 3 weeks without using the product after a baseline period. Intervention consisted of the use of a fragrance diffuser and fragrance by Reckitt’s Scientific Platform Fragrance Research for at least an hour at the participants’ preferred settings in the room where they spent the most time before going to bed. Sleep was measured objectively with SleepScore Max every night. Self-report data were collected at bedtime, in the morning, and after each measurement period. Multilevel regression and paired t-tests were used to test for statistical significance.

Results

Across all participants there were 835 nights of tracked sleep. Participants (100% female, age 21 to 55, average 36 years old) showed improvement in both objective and perceived sleep during the intervention. Participants got more deep sleep, spent a greater proportion of the night in deep sleep, and had an improved BodyScore, a measure of deep sleep (ps<.05). Additional objective improvements were related to sleep consistency: fewer awakenings during the night, less time awake during the night, and better sleep maintenance (ps<.05). Self-report results complemented the objective findings. Participants felt sleepier at bedtime, felt they woke up less often and spent less time awake after initially falling asleep, reported better sleep quality, and experienced better mood both at bedtime and in the morning (ps<.05). No significant negative impacts were seen on sleep in the objective and self-report measures.

Conclusion

Using the fragrance diffuser before bed may contribute to improvement of many aspects of sleep within this study population of females without underlying sleep conditions. Objectively improved sleep outcomes were supported by self-report, showing multifaceted benefits of the diffused fragrance on sleep.

Support (If Any)

Reckitt
0348 Sleep Staging Using End-to-End Deep Learning Model Based on Nocturnal Sound for Smartphones
Authors: Hong Joonki , Tran Hai , Jeong Jinhwan , Jang Hyeryung , Yoon In-Young , Hong Jung Kyung , Kim Jeong-Whun
Published: May 2022

Introduction

Convenient sleep tracking with mobile devices such as smartphones is desirable for people who want to easily objectify their sleep. The objective of this study was to introduce a deep learning model for sound-based sleep staging using audio data recorded with smartphones during sleep.

Methods

Two different audio datasets were used. One (N = 1,154) was extracted from polysomnography (PSG) data and the other (N = 327) was recorded using a smartphone during PSG from independent subjects. The performance of sound-based sleep staging would always depend on the quality of the audio. In practical conditions (non-contact and smartphone microphones), breathing and body movement sounds during night are so weak that the energy of such signals is sometimes smaller than that of ambient noise. The audio was converted into Mel spectrogram to detect latent temporal frequency patterns of breathing and body movement sound from ambient noise. The proposed neural network model consisted of two sub-models. The first sub-model extracted features from each 30-second epoch Mel spectrogram and the second one classified sleep stages through inter-epoch analysis of extracted features.

Results

Our model achieved 70 % epoch-by-epoch agreement for 4-class (wake, light, deep, rapid eye movement) stage classification and robust performance across various signal-to-noise conditions. More precisely, the model was correct in 77% of wake, 73% of light, 46% of deep, and 66% of REM. The model performance was not considerably affected by existence of sleep apnea but degradation observed with severe periodic limb movement. External validation with smartphone dataset also showed 68 % epoch-by-epoch agreement. Compared with some commercially available sleep trackers such as Fitbit Alta HR (0.6325 in mean per-class sensitivity) and SleepScore Max (0.565 in mean per-class sensitivity), our model showed superior performance in both PSG audio (0.655 in mean per-class sensitivity) and smartphone audio (0.6525 in mean per-class sensitivity).

Conclusion

To the best of our knowledge, this is the first end (Mel spectrogram-based feature extraction)-to-end (sleep staging) deep learning model that can work with audio data in practical conditions. Our proposed deep learning model of sound-based sleep staging has potential to be integrated in smartphone application for reliable at-home sleep tracking.

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0350 At-home Sample Collection for Measurement of Diurnal Rhythms of Urinary Cortisol and Melatonin
Authors: Daumeyer Natalie , Kreitzberg Daniel , Gavin Kathleen , Seixas Azizi , Bauer Timothy
Published: May 2022

Introduction

Sleep- and stress-related hormones (e.g., melatonin, cortisol) can be measured from dried urine samples collected at-home and sent for laboratory testing. These measures may be used to identify patterns of circadian alignment, peak nocturnal melatonin levels as well as a cortisol awakening response. The purpose of this analysis was to describe diurnal patterns and reference ranges from a 4-timepoint serial assessment of urinary cortisol and melatonin in a large cohort of at-home self collected samples.

Methods

This retrospective analysis evaluated data from 3,966 individuals who used an at-home Sleep and Stress Test (Everlywell, Inc.) between September 28, 2017 and July 14, 2021. Individuals provided four urine samples according to habitual sleep patterns: upon waking (T1), two hours after waking (T2), prior to the evening meal (T3), and at bedtime (T4). Melatonin and cortisol distributions were normalized to creatinine and log transformed to approximate normal distributions to define respective reference ranges (two standard deviations above and below the log transformed mean) and reverted to original units for reporting.

Results

71% (n=2,832) of users were female and mean age was 42.8 (sd=12.0) years. Mean (sd) urinary values were as follows: Cortisol: T1, 29.3 (37.9) ug/g Cr; T2, 47.2 (49.8); T3, 14.9 (36.3); T4. 8.38 (26.9). Melatonin: T1, 745 (3208) ug/g Cr; T2, 169 (1189); T3, 45 (620); T4, 155 (1701). For cortisol, only 4-5% of samples fell outside the defined reference ranges across time points. Melatonin was more variable with 23% and 15% falling outside the reference range at time points T3 and T4, respectively. A majority of individuals’ peak cortisol occurred at T2 (67.4%), and melatonin at T1 (85.2%).

Conclusion

This analysis demonstrates measurable physiological diurnal patterns for cortisol and melatonin using at-home self-collection for dried urine tests. This provides evidence that at-home sample collection kits using dried urine spots are a viable tool for assessing diurnal patterns of sleep and stress. Future controlled studies are needed to evaluate the utility in identifying abnormal patterns associated with shift-work or sleep disorders.

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0353 Estimated Sleep-Wake Patterns Obtained from a Large U.S. Sample by Home-Based Under-Mattress Monitoring Devices
Authors: Zitser Jennifer , Cotton-Clay Andrew , Baron Susan , Easwar Venkat , Kinsolving Arthur , Kahn Philippe , Kushida Clete
Published: May 2022

Introduction

Sharing the bed with a partner is common among adults and is likely to impact sleep in multiple ways. However, polysomnograms are performed without a bed partner and objective data on co-sleeping couples are extremely rare. This study aimed to investigate the effects of a bed partner's presence on objective sleep parameters.

Methods

Sleep data from 5190 users (43% female, 14% unspecified gender, mean age 47) and their bed partners were collected through a commercially-available home sleep monitoring device (Sleeptracker-AI Monitor, Fullpower Technologies, California, USA). The device passively monitors sleep using piezo-electric sensors that register the forces exerted through the mattress. Subjects with at least 10 weekday sleep recordings with a bed partner present for at least an hour, and at least 10 weekday sleep recordings without a bed partner present at all during the period from 08/2021 to 11/2021 were included. Estimated total sleep time (TST), wake after sleep onset (WASO), sleep efficiency (SE), and light, deep, and REM sleep were analyzed comparing between the nights with and without a bed partner.

Results

The mean (standard deviation) across subject averages of estimated TST (min), WASO (min), SE (%), and light, deep and REM sleep (min) with a bed partner were: TST 417.2(44.5), WASO 47.2(24.9), SE 89.5(6.4), light sleep 255.4(34.2), deep sleep 56.7(11.9) and REM sleep 105.2(17.5) and without a bed partner were: TST 414.7(49.2)-*, WASO 40.7(20.5)-*, SE 90.7(5.8)+*, light sleep 243.6(38.0)-*, deep sleep 62.9(12.9)+* and REM sleep 108.2(19.0)+*; a (+) indicates an increase and (-) a decrease in the sleep parameter between nights with and without a bed partner, and (*) signifies p < 0.05 by paired t-test.

Conclusion

When the bed partner is absent, an individual’s sleep architecture shows on average a higher sleep efficiency, with less awake time but also less total sleep; more minutes spent in deep and REM sleep, and less in light sleep. This suggests a less interrupted night, perhaps due to fewer disruptions from the partner, where the individual has enough continuity in his/her sleep to transition to deeper stages. Further work will add the effect of a bedpartner in AHI and snoring.

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0354 The Feasibility of Research Using In-Home Polysomnography for 20 Nights Across 25 Days
Authors: Ariyibi Bisola , Lambing Kari , Bender Amy , Gerardy Bethany
Published: May 2022

Introduction

Several studies have studied sleep with polysomnography (PSG) in the laboratory across multiple days but there is a paucity of research using lab-quality PSG in the home where the sleep environment is much different. In this study, we assessed the feasibility of conducting research while recording PSG in the home across multiple nights under real-world conditions.

Methods

Twenty-one participants volunteered to participate in the study and wore in-home PSG using the Cerebra Sleep System which used gel electrodes to record EEG, EOG, EMG, ECG, and a chest effort belt for 20 nights across 25 days. Participants completed baseline questionnaires (pre – and post-study), daily activities, sleep disturbances, and any skin sensitivities via online morning and evening questionnaires.

Results

Eighteen participants (age 40.2±10.5; 9 females) completed at least 18 nights of recordings and were included in the final analysis. PSG was recorded for 375 nights with an average of 20.1 nights (±3.5) recorded per participant across 24.3 days (± 2.9). Three participants withdrew from the study due to a change in work schedule (3 nights), skin sensitivity issues (5 nights), and lack of motivation (10 nights). There were 100% completion rates for questionnaires at baseline, 98% completion rates for morning questionnaires, and 93% completion rates for evening questionnaires. Participants reported skin sensitivities on 36.4% of the nights but were typically not reported again at the evening session. When there was a complaint, most of the irritations were minor with 27.1% having residual stickiness from the electrodes, 26.1% redness, and 17.5% imprints. For more of the major complaints, they were less common with 5% reporting soreness or irritation and 3.3% swelling.

Conclusion

We found that data collection from electronic questionnaires was good. Skin irritations were reported about a third of the time but typically went away across the day. These results highlight the feasibility of doing research using in-home PSG for multiple nights and the utility of collecting electronic questionnaire data for in-home research.

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