bluuebunny/crossref_metadata_2025 huggingface dataset:
0334 Hippocampal Development, Slow Wave Activity, and Nap-Dependent Memory Consolidation in Early Childhood
Authors: Lokhandwala S , Allard T , Riggins T , Spencer R M
Published: May 2020

Introduction

Naps support memory consolidation in early childhood. In adults, nap-dependent declarative consolidation is associated with SWA. SWA increases from early childhood into adulthood, and the shift of SWA from occipital to frontal distribution (F/O-ratio) is a marker of brain maturation. Thus, we explored how electrophysiological and structural characteristics of brain development relate to nap-dependent declarative learning in early childhood.

Methods

Twelve preschool-age children (8 female, M=48 months, SD=0.44) have completed three sessions (~1wk apart) within a larger study. In the first two sessions, children completed a visuo-spatial task before and after a 2-hr nap or wake interval. During the third visit, children underwent MRI assessment. Using PSG, SWA was measured in the delta band over frontal and occipital regions for nREM2 and nREM3 sleep.

Results

While F/O-ratio of SWA does not currently predict the F/O-ratio of cortical thickness (r(12)=.383, p=.219), right parahippocampal thickness positively correlates with F/O-ratio of SWA in nREM2 (r(12)=.591, p=.043). Nonetheless, children’s performance change following the nap was not associated with either parahippocampal thickness or F/O-ratio of SWA in any sleep stage (all ps>.538). However, performance in children who showed a post-nap benefit (n=5) positively correlated with right parahippocampal thickness (r(5)=.915, p=.029). This was not the case for children who did not show a post-nap benefit (r(7)=-.199, p=.668).

Conclusion

Although the F/O-ratio of SWA did not predict a similar ratio of cortical thickness, the association between right parahippocampal thickness and F/O-ratio of SWA is evidence that development of SWA parallels cortical development. While there is no overall association between post-nap performance and brain development characteristics, the relation between performance and right parahippocampal thickness in children showing a nap benefit suggests that memory during this age may depend on structural (rather than electrophysiological) brain development changes.

Support

NIH R21 HD094758 & NSF BCS 1749280
0340 Regional Changes in Sleep Electroencephalography Power in Youth with Sleep-Disordered Breathing: A High-Density EEG Study
Authors: Myers A , Matthews C , Kille T , Riedner B , Flaherty B , Jones S
Published: May 2020

Introduction

Daytime neurobehavioral impairments are commonly associated with sleep disordered breathing (SDB) in children. However, a large number of studies have shown only minimal differences in sleep between children with SDB relative to control children, suggesting that sleep dysfunction is not responsible for daytime impairment. Importantly, however, previous studies have measured sleep EEG using only frontal scalp electrodes, failing to capture the regional features of sleep that are prominent during development. Here we measure sleep using hdEEG in SDB and healthy children to determine if regional sleep impairment is related to daytime neurobehavioral performance.

Methods

Overnight high-density electroencephalography (hdEEG, 256 channels) was recorded in 17 children with sleep disordered breathing (SDB) (age: M = 8.46, SD = 1.82, AHI: M = 11.3, SD = 8.6, 53% female) and 17 age and sex matched controls (age: M = 8.47, SD = 1.66, AHI: M = 1.5, SD = .64). Attentional capacity was assessed using the Test of Variables of Attention (TOVA) before and after sleep. Group differences in sleep macrostructure variables were assessed using unpaired t-tests. All-night spectral analysis was performed for NREM sleep and averaged across groups. Topographic differences between groups were assessed using statistical non-parametric mapping. Pearson correlations were used to determine associations between sleep and TOVA variables.

Results

Sleep macrostructure did not differ between groups. All-night spectral density analysis revealed a global increase in high-frequency activity in N2N3 and N3, in the alpha band (8-12 Hz, p<0.05). Global alpha power was higher in SDB youth, although this effect reached significance during N3 in a large cluster of posterior channels (N=55, p=.02).

Conclusion

Elevated alpha during NREM is frequently considered a correlate of nonrestorative sleep. In this sample of youth with SDB, posterior alpha is robustly increased during the deepest stage of NREM sleep. In this small sample, however, alpha power did not predict performance on an attentional task sensitive to the effects of impaired sleep.

Support

R21 HD092986-02 to SJ
0341 Preliminary Effects of a Music Intervention on Actigraphy-Measured Sleep Among Older Adults with Dementia
Authors: Mu C , Lee S , Risal P G , Vigoureux T F , Bugos J , Meng H
Published: May 2020

Introduction

Music may benefit sleep and daytime alertness by decreasing stress, increasing attention, and potentially, slowing the progression of dementia. This study examined preliminary effects of a group-based music intervention on sleep health among older adults with dementia.

Methods

Participants were older adults with dementia living in an assisted living facility (n=9; Mage=80.11; Mrange=63−89 years). Cohort 1 (n=4) received the intervention in the morning and cohort 2 (n=5) received the intervention in the afternoon. Participants completed a 4-week intervention protocol (12 sessions) along with a one-week actigraphy sleep assessment before and after the intervention. Informed by sleep literature, we constructed a composite sleep health score encompassing Regularity, Satisfaction or quality, Alertness, Timing, Efficiency, and Duration (higher scores indicating more daily sleep problems). Using descriptive statistics and multilevel modeling, we evaluated preliminary effects of the intervention on overall sleep health and each of the sleep dimensions.

Results

Six out of nine participants exhibited a decrease in overall sleep problems at post-intervention. All 4 participants in cohort 1 showed improvement in overall sleep health at post-intervention. Specifically, in cohort 1, participants exhibited a decline in nightly sleep problems, decreased daytime nap duration, and number of naps. In contrast, while two out of five participants in cohort 2 exhibited improvement in overall sleep health, the remainder of the participants exhibited no improvement in daily sleep problems, especially in nap domains. Across cohorts, those younger in age, with vascular dementia, lower weight, and not taking sleep or hypertension related medications tended to respond better to the intervention.

Conclusion

Our preliminary results demonstrate the feasibility and potential benefit of a group-based music intervention in improving overall sleep health among older patients with dementia. Implications for conducting community-based non-pharmacological interventions to improve sleep and daytime functioning among older adults with dementia will be discussed.

Support

This work was supported, in part, by the Florida Department of Health Ed and Ethel Moore Alzheimer’s Disease Research Award (PI: Meng, Grant #9AZ28).
0350 Characterizing Continuous Changes in Spectral Dynamics of Sleep EEG as a Function of Age
Authors: Kim H , Prerau M , Redline S
Published: May 2020

Introduction

Sleep is a continuous and dynamic physiological process. Current research practice, however, limits our ability to observe electroencephalography (EEG) oscillation dynamics by breaking sleep into discrete stages. In this study, we propose a novel quantitative framework that represents population-level changes in sleep EEG spectral dynamics as a function of age, preserving the information-rich spectral dynamics of sleep data. Rather than relying on sleep stages, our approach uses slow-oscillation power (SO-power) as an objective, continuous-valued correlate of sleep depth.

Methods

We analyzed the EEG signal (Fz-Cz, 256 Hz sampling rate) from a subset of the Multi-Ethnic Study of Atherosclerosis (MESA) study participants (n = 2056, 53.6% female, age: mean 69.37 ± 9.12, range 54 - 94) who underwent polysomnography. For each subject, we computed the sleep EEG multitaper spectrogram and extracted the total baseline-normalized SO-power (0.1 - 1.5 Hz). We next computed mean EEG spectral power as a function of SO-power, which we then tracked across all subjects as a function of age in sliding windows.

Results

The population analysis shows apparent, continuous changes in time-frequency domain features of the EEG as a function of a sleep depth along with age, that would be otherwise lost in traditional analyses. Moreover, by analyzing the directionality of the SO-power, we show that there is no apparent difference in neural activity during deepening sleep and lightening sleep; thus EEG sleep state is likely non-directional.

Conclusion

Our results show that state-based sleep dynamics of the EEG power spectrum can comprehensively be represented using SO-power as a surrogate of sleep depth. This representation identifies state-based activity independent of the temporal evolution of sleep architecture. As such, it is a powerful tool for analysis and phenotyping of EEG activity in large cohorts.

Support

The Biomedical Global Talent Nurturing Program through the Korea Health Industry Development Institute, funded by the Ministry of Health & Welfare, Republic of Korea (HI19C1065) to HK, National Institute of Neurological Disorders and Stroke (NINDS, R01 NS-096177) to MP.
0352 A Large-Scale EEG Study at Home to Objectivise Effects of Ageing on Slow Wave Sleep and Process S
Authors: El Kanbi K , Thorey V , Artemis L , Chouraki A , Trichet T , Pinaud C , Debellemaniere E , Arnal P J
Published: May 2020

Introduction

Several studies have shown slow wave sleep (SWS) is altered with ageing. However, most of these studies have been conducted in-lab and usually over a single night. In this study, we assessed the evolution of process S with ageing by analysing the dynamics of endogenous and auditory-evoked slow waves in a large population.

Methods

300 participants (200 M, 20 - 70 y.o.) were selected from volunteers users wearing a sleep headband for at least 3 nights, meeting the criteria of high signal quality and having no subjective sleep complaints nor being shift-workers. The Dreem headband is a connected device able to monitor EEG signals as well as pulse and movement and performs sleep staging in real-time automatically. Slow waves were detected as large negative deflections on the filtered EEG signals during NREM sleep. The auditory evoked slow waves were done using a previously validated closed-loop procedure.

Results

In our study, age was strongly correlated with N3 sleep duration (r=-0.34, p<0.0001), slow wave amplitude (r=-0.25, p<0.0001), and slow wave density (r=-0.40, p<0.0001). The slope of the slow wave activity, representing the process S here, was significantly decreased (r=-0.32, p<0.0001). This effect was mainly due to changes in the density of slow waves in the first 2 hours of sleep (r=-0.41, p<0.0001). Finally, our results show a decrease in the probability of auditory evoked slow waves (r=-0.43, p<0.0001).

Conclusion

These results confirmed the in-lab studies showing a heterogeneous alteration of homoeostatic process S with age, as well as a general decrease of slow wave occurrences, that is observed in parallel of a decrease of the probability of evoking slow waves, suggesting a global change in the system responsible for slow wave generation.

Support

This study was supported by Dreem sas and ANR, FLAG ERA 2015, HPB SLOW-Dyn
0360 Neighborhood Disadvantage is Associated with Lower Quality Sleep and More Variability in Weeknight Sleep Duration Among Urban Adolescents
Authors: Nahmod N G , Master L , McClintock H F , Hale L , Buxton O M
Published: May 2020

Introduction

Differential social and contextual environments may contribute to adolescent sleep disparities. Yet, most prior studies are limited to self-reported sleep data, and the actigraphic studies of sleep are not conducted at a national level, thus limiting the variation in neighborhood contexts. This study examined the association between neighborhood disadvantage and actigraphic assessment of adolescent sleep.

Methods

Participants (682 adolescents, mean age 15.4 years) were racially/ethnically diverse (44% Black, 26% Hispanic, 17% White, 14% other race/ethnicity), sampled from 20 large US cities in the Fragile Families and Child Wellbeing Study. Neighborhood disadvantage was calculated from American Community Survey 2015 census data using the Standardized Neighborhood Deprivation Index (SNDI), consolidating five variables (proportion of female-headed households, public assistance recipients, households in poverty, adults without high school degrees, and unemployed) into an index. SNDI quartiles 1-3 fell below national averages of SNDI variables (“most disadvantaged”) and were compared to quartile 4 (“least disadvantaged”). Sleep indicators (duration, quality, and timing) were measured over ≥5 nights using wrist-worn accelerometers. Separate multilevel models estimated differences in sleep indicators, adjusting for weekday/weekend and summer/school year. General linear models used within-person standard deviations of sleep indicators (controlling for number of days) to test for associations between neighborhood disadvantage and consistency of weeknight sleep patterns. Models adjusted for individual-level sociodemographic covariates (age, sex, race/ethnicity, household income, caregiver education, and family structure).

Results

In fully adjusted models, adolescents living in more disadvantaged neighborhoods spent more time awake after falling asleep (4.0 minutes/night, p<0.05), spent greater percentage of nighttime sleep intervals awake (1%, p<.01), and had less consistent sleep duration (11.7% higher standard deviation, p<.05). Sleep duration and timing did not differ across neighborhood groups.

Conclusion

Living in more disadvantaged neighborhoods is associated with lower quality adolescent sleep; more research is needed to identify causal mechanisms.

Support

Research was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (NICHD) of the National Institutes of Health (NIH), award numbers R01HD073352 (PI: Hale), R01HD36916, R01HD39135, and R01 HD40421, and private foundations. The content is the responsibility of the authors and does not represent official NIH views.
0379 Green Space Exposure and Sleep Duration Among Supplemental Nutrition Assistance Program Participants
Authors: Grigsby-Toussaint D , Shin J
Published: May 2020

Introduction

Emerging empirical evidence suggests green space exposure is protective against insufficient sleep. Limited studies exist, however, exploring the relationship between greenspace exposure and sleep among low income populations in the United States.

Methods

Using a sample of Supplemental Nutrition Assistance Program (SNAP) participants (n=104) recruited from Champaign County, Illinois, we examined the relationship between self-reported sleep duration and exposure to green space. Sleep duration was determined using the question, “On average, how many hours did you sleep each night during the past 4 weeks?” Green space exposure was determined using satellite imagery from the National Aeronautic Space Administration (NASA) normalized difference vegetation index (NDVI). An NDVI score was assigned to each participant based on residential geo-referenced data. Multiple linear regression was performed in SPSS to explore the relationship between self-reported sleep duration and green space.

Results

Higher number of hours of sleep within a 24-hour period was positively associated with higher scores for greenspace exposure (β=0.091, P=0.02), controlling for age, gender, smoking status, education, alcohol consumption, and sleep quality. Sleep duration was negatively associated with age (β=-0.03, P=0.007), but positively associated with sleep quality (β=0.856, P=0.008).

Conclusion

In a sample of SNAP participants, exposure to green space was associated with more hours of sleep per night. Additional studies with larger, and more geographically diverse samples of low income adults are needed to determine whether this relationship is robust.

Support

USDA UNC/DUKE BECR Center
0384 Do Nurses with High Blood Pressure Have More Sleep Disturbances Than Their Peers?
Authors: Santiago B P , Messman B A , Slavish D C , Alkire C , Wardle-Pinkston S , Dietch J R , Kelly K , Ruggero C R , Taylor D J
Published: May 2020

Introduction

Nurses work in stressful environments and often have rotating work schedules, which may put them at risk for disturbed sleep and health. Poor quality and short sleep duration are strong risk factors for high blood pressure (HBP). Yet few studies have examined these associations in nurses, who may be a particularly at-risk sample. To address this gap, we examined group differences in self-reported and actigraphy-assessed sleep among nurses with and without self-reported HBP.

Methods

Participants were 392 nurses (91.8% female; 77.8% white, mean age = 39.54) recruited for a parent study. Participants completed baseline questionnaires including the Pittsburgh Sleep Quality Index (PSQI), followed by 14 days of actigraphy and sleep diaries to prospectively assess 14-day mean total sleep time (TST) and sleep efficiency (SE). An independent samples t-tests was used to assess group differences in sleep variables by HBP status. Linear regression was used to further examine the association between HBP status on sleep variables when controlling for age, race, gender, ethnicity, and body mass index (BMI).

Results

Twenty-nine (7%) nurses endorsed having clinically-diagnosed HBP. Nurses with HBP had higher global PSQI scores (indicating worse sleep quality; t=2.71, p=0.007), compared to nurses who did not report HBP, with a mean difference of 1.24. When adjusting for covariates, the association between HBP and the PSQI became marginally significant (p=0.054). There were no group differences in sleep diary or actigraphy TST or SE by HBP status, nor did HBP predict these sleep variables when controlling for covariates.

Conclusion

We found that nurses who reported having clinically diagnosed HBP had poorer global sleep quality. Although limited by self-reported history of HBP diagnosis, and low endorsement of HBP in our sample, our results corroborate other findings which suggest there is a strong association between high blood pressure and disturbed sleep. Future studies should examine these associations in larger samples, assess blood pressure directly, and experimentally examine the effects of HBP treatment on sleep quality.

Support

NIH/NIAID R01AI128359-01
0398 Demographic Differences in the Degree of Discrepancy Between Sleep Diary and Actigraphy Measures of Sleep
Authors: Scott B , Crawford M , Slavish D , Messman B , Wardle-Pinkston S , Dietch J , Kelly K , Ruggero C , Taylor D
Published: May 2020

Introduction

The accurate estimation of sleep is critical for understanding who is most at risk for sleep disorders and associated disease outcomes. Individuals who overestimate sleep disturbances may be at increased risk for insomnia. A few studies have shown demographic differences in the accuracy of sleep estimation when comparing subjective and objective measures; however, the previous literature is inconsistent and focuses primarily on older adults. We sought to replicate these studies in a large sample of nurses using 14 days of sleep diary and actigraphy measures.

Methods

Participants were 392 nurses (91.8% female; 77.8% white, mean age = 39.54) recruited for a larger study. Participants completed 14 days of actigraphy and sleep diaries to prospectively assess total sleep time (TST) and sleep efficiency (SE). Discrepancy between diary and actigraphy measures was calculated by subtracting actigraphy measures from diary measures. Linear regression was used to examine how age, race (0 = race other than white, 1 = white), gender (1 = male, 2 = female), ethnicity (1= non-Hispanic/Latinx, 2 = Hispanic/Latinx) predicted degree of sleep discrepancy.

Results

The average discrepancy between diary and actigraphy TST was 30.29 minutes (SD = 29.28), and the average discrepancy between diary and actigraphy SE was 4.16% (SD = 5.66). Race and ethnicity did not predict amount of TST or SE discrepancy. However, younger individuals had more discrepancy in both TST (b = -0.48, p < .001) and SE (b = -0.09, p < .001). Men also had a greater discrepancy in both TST (b = -10.90, p < .05) and SE (b = -2.56, p < .05).

Conclusion

Men and younger individuals had greater discrepancies between diary and actigraphy measures of sleep. This is in contrast to some previous research showing that elderly women tend to display greater discrepancies between subjective and objective measures of sleep. It is essential that future research explore the discrepancies between subjective and objective measures of sleep in larger and more demographically diverse samples. Establishing a better understanding of this relationship is crucial, as it may have significant implications for the diagnosis and treatment of insomnia.

Support

NIH/NIAID R01AI128359-01
0400 Habitual Sleep, Circadian Misalignment, and Cardiovascular Risk Factors Among Late Adolescents
Authors: Ji X , Wang Y , Saylor J , Patterson F , Ruggiero L
Published: May 2020

Introduction

Emerging evidence suggests the potential role of sleep in cardiovascular disease (CVD) risk. Sleep variability and circadian misalignment may represent understudied sleep dimensions, particularly among late adolescents. This study investigated the associations of habitual sleep, circadian misalignment, night-to-night sleep variability with CVD risk factors among late adolescents.

Methods

Using a cross-sectional design, we enrolled 58 healthy, college students (19.22±1.06 years old). Participants completed a 7-day sleep diary, the Pittsburgh Sleep Quality Index (PSQI) and Epworth Sleepiness Scale. Circadian misalignment was assessed using the weekend-weekday differences in sleep duration and midsleep time. Sleep variability was calculated as intra-individual standard deviation of sleep durations. The number of CVD risk factors (BMI, waist circumference, blood pressure, fasting glucose and lipid profile) above subclinical/clinical thresholds was used as a proxy of overall risk. Logistic and generalized linear regression tested the relationships.

Results

Forty-two participants (73%) had at least one elevated CVD risk factors and 19 (34%) were short sleepers (<7 h). On average, the midsleep shifted 54 minutes later on weekends and the intraindividual sleep variability was 1.31 hours. After controlling for age, gender and race, there was a trend towards higher overall CVD risk (β=0.45±0.22, p=0.05) with a greater weekend-weekday discrepancy in sleep duration. For each CVD risk factor, a greater discrepancy in weekend-weekday midsleep times (OR=2.29±0.82, p=0.02) was estimated to increase the odds of high blood pressure. Participants with greater discrepancy in weekday-weekend sleep durations (OR=1.58±0.41, p=0.03) or excessive daytime sleepiness (OR=4.68±3.38, p=0.03) were more likely to have high BMI. Worse sleep quality (higher PSQI scores) was associated with high BMI (OR=1.36±0.19, p=0.03) and waist circumference (OR=1.40±0.24, p=0.04).

Conclusion

This study suggests that circadian misalignment, compared with other sleep characteristics, better predicts cardiovascular risk among late adolescents. Future research is needed to examine the interaction among circadian misalignment, sleep variability and sleep duration on CVD risk.

Support

American Nurse Foundation 18A01422
0406 Daytime Sleepiness in The Community: Implications for Sleep, Circadian, and Physical Health
Authors: Grandner M A , Tubbs A , Jean-Louis G , Seixas A , Hale L , Branas C , Killgore W D , Wills C C
Published: May 2020

Introduction

Daytime sleepiness impacts performance and well-being. The present study used validated measures to explore associations of community-level daytime sleepiness with sleep health, preferred sleep phase, physical inactivity, and overall health.

Methods

Data were from the Sleep and Healthy Activity, Diet, Environment, and Socialization (SHADES) study of N=1007 adults age 22-60 from the community. Daytime sleepiness was assessed with the Epworth Sleepiness Scale (ESS). Outcomes of interest included the Insomnia Severity Index (ISI), Pittsburgh Sleep Quality Index (PSQI), endorsement of a preference for an advanced or delayed sleep phase on the Sleep Disorders Symptom Check List (SDSCL), STOP-BANG sleep apnea questionnaire score, sedentary time assessed with the International Physical Activity Questionnaire (IPAQ), and the global health item on the SF-12, operationalized as excellent/good or fair/poor health. Through regression analyses, we assessed whether daytime sleepiness was independently associated with several sleep, circadian and physical health outcomes, adjusting for habitual sleep duration and sociodemographic factors like age, sex, education, and race/ethnicity.

Results

Our adjusted models indicate that daytime sleepiness was associated with insomnia (B=0.57; 95%CI: 0.50, 0.65; p<0.0001), sleep quality (B=0.34; 95%CI: 0.29, 0.39; p<0.0001), advanced sleep phase (OR=1.06; 95%CI: 1.03, 1.09; p<0.0001), delayed sleep phase (OR=1.05; 95%CI: 1.02, 1.07; p=0.0003), STOP-BANG score (B=0.08; 95%CI: 0.07, 0.10; p<0.0001), sedentary minutes (B=6.12; 95%CI: 2.77, 9.47; p=0.0004), and overall poor health (OR=1.10; 95%CI: 1.07, 1.13; p<0.0001). After additional adjustment for habitual sleep duration, all relationships were maintained.

Conclusion

Daytime sleepiness is associated with more severe insomnia, preference for advanced or delayed sleep timing, worse sleep quality, and greater risk of sleep apnea. Moreover, daytime sleepiness was associated with greater sedentary time and worse overall health. Since these relationships are independent of sleep duration, they likely do not reflect an effect of sleep deprivation.

Support

This work was supported by a grant from Jazz Pharmaceuticals. The SHADES study was funded by R21ES022931. Dr. Grandner is supported by R01MD011600.
0412 Parents Sleep Longer When School is Out for the Summer: Associations Among Parenthood, Gender, and Season
Authors: Ruder M , Rus H M , Raj A , Gahan L , O’Mullane B , Danoff-Burg S , Weaver M , Raymann R
Published: May 2020

Introduction

Seasonal effects in sleep are often attributed to day length; however, change in obligatory daily activities might also have an impact on sleep behavior. Longitudinal measurement using consumer sleep technology enables the observation of patterns in sleep behavior in the home environment. We analyzed the impact of parenthood and gender on total sleep time (TST) over the summer break period using data collected in the home.

Methods

Sleep data were collected using the SleepScore mobile application from October 2018 through October 2019, with the summer break period defined as June 25th - August 5th. U.S. age and gender matched samples of parents and non-parents were selected using Mahalanobis distance from a pool of users more likely to have school-aged children. The final samples included n=345 parents (38.7 +/- 4.5 years) and n=345 non-parents (37.8 +/- 4.7 years); both groups were 46% female. Only weeknights (n=34,323) were analyzed to maximize impact of school schedule. Linear regression and independent t-tests were used to analyze main and interaction effects for gender, parenthood, and summer break.

Results

Male gender, parenthood, and summer break were associated with decreased sleep duration (ps < .01). However, during summer break, parents exhibited an increase in TST, with mothers (+5.6 mins) having a greater increase than fathers (+1.1 mins). In contrast, adults without children showed a decrease in TST during summer break, with males having a greater reduction (-8.8 mins) than females (-6.5 mins).

Conclusion

These results suggest that parental status may play a part in seasonal sleep patterns. Contrary to the typical trend of shorter TST during summer, being a parent is associated with longer TST during summer break, with a greater increase for females. This change may be attributed to parents following a less rigid schedule when their children are not in school.

Support

N/A
0413 The Influence of Community Environment Exposure and Individual Health Behavior on Insufficient Sleep
Authors: Shin J , Grigsby-Toussaint D
Published: May 2020

Introduction

Short sleep duration is associated with the risk of various chronic diseases, and it has been hypothesized to influence health behaviors and environmental exposure such as green space and noise. However, little studies have explored this relationship, especially with the consideration of the integrated environment information. The purpose of this study is to examine the influence of environmental exposure and individuals’ health behavior on sleep duration.

Methods

We examined aggregate national-level datasets regarding health information, noise, and green space. Sleep, health behavior, and socio-demographic variables were derived from 500 cities data, and the unit of analysis was the prevalence of each variable in the census tract. The insufficient sleep was calculated by the percentage of the population who had less than 7 hours of sleep in the census block. Spatial analysis was performed for green space and noise measurement; both values were calculated within the community activity space, which is a combined area with the census urban area and census place to examine the potential activity space. Multiple linear regression analysis was performed to model the relationship.

Results

The final sample was 29,610 census tracts from 497 cities, and the average median age of each census tract was 36.02±7.085. 36.64% of insufficient sleep was reported from the entire sample. The model (R2=0.804) indicate that green space (β=-.053, p<.001) and natural noise (β=-.029, p<.001) has negatively associated with insufficient sleep; while, smoker (β=.374, p<.001), binge drinker (β=.105, p<.001), no leisure physical activity time (β=.111, p<.001), and artificial noise (β=.034, p<.001) has positive association with insufficient sleep.

Conclusion

The results indicate that a better environment source in the community mitigates the insufficient sleep population as well as individual health behavior. Further studies are needed, however, to fully disentangle the association between sleep duration and sleep quality associated with other environmental exposure.

Support

N/A
0414 Chronotype and Sleep Among Ovarian Cancer Survivors Participating in a Lifestyle Intervention
Authors: Crane T E , Skiba M B , Donzella S , Thomson C A , Parthasarathy S
Published: May 2020

Introduction

Chronotype is defined as an individual’s propensity to sleep at a specific time in a 24-hour cycle with late chronotype associated with poorer health outcomes including cancer. The role of chronotype on lifestyle behaviors remains relatively undefined in ovarian cancer. The Lifestyle Intervention for oVarian cancer Enhanced Survival study is testing whether 1205 women randomized to a diet and physical activity intervention for 24-months will have longer progression-free survival versus attention control. Here we determine the frequency and predictors of late versus early and mid chronotypes in disease-free ovarian cancer survivors.

Methods

894 ovarian cancer survivors with baseline measures were included in analyses. Chronotypes were determined using self-reported time to bed (early- < 9 pm; mid- ≥ 9 pm - ≤12 am; late- >12 am) captured through the Pittsburgh Sleep Quality Index. Demographic, diet and physical activity data were captured with validated questionnaires and BMI measured in clinic. Descriptive statistics and logistic regression, adjusted for smoking status and race, were performed.

Results

12.4% of women were late chronotype with significant differences between chronotypes observed for race, smoking history, sleep duration, and physical activity (p < 0.05). Late chronotype reported fewer hours of sleep per night (6.54 ± 1.51hrs) compared to mid (7.10± 1.31hrs) and early (7.74 ± 1.30hrs) chronotype. Blacks had higher odds of being late chronotype, OR 4.28 (95% CI 2.16-8.46). Late chronotype were more likely to report a history of smoking and lower recreational activity and had a higher mean BMI of 29.1± 6.0 kg/m2 compared to mid and early chronotype 27.8± 6.2 kg/m2 and 27.4± 5.4kg/m2, respectively. No significant differences were observed for sleep or diet quality, age, education or employment status.

Conclusion

Results of this analysis are consistent with other community-based population studies with regard to chronotype and race. Ovarian cancer is aggressive and late chronotype are more likely to have other risk factors that elevate risk of recurrence (obesity, tobacco use and inactivity. Six-month data are being analyzed by treatment arm and will provide important insights as to the role of sleep phase and lifestyle behaviors in this vulnerable population.

Support

NCT00719303; NCI R01CA186700-01A1
0416 Poor Sleep Quality Predicts Serum Markers of Neurodegeneration and Cognitive Deficits in Warriors with Mild Traumatic Brain Injury
Authors: Werner K , Shahim P , Gill J , Nakase-Richardson R , Kenney K
Published: May 2020

Introduction

Increasing evidence links neurodegeneration to traumatic brain injury (TBI), and a separate body of literature links neurodegeneration to sleep dysfunction, implicating increased toxin production and decreased glymphatic clearance. Sleep disorders affect 50% of TBI patients, yet the sleep-neurodegeneration connection in these patients remains unexplored. We hypothesized that warfighters with TBI and sleep dysfunction would have increased neuronal injury, revealing potential mechanistic underpinnings for TBI outcomes. We measured plasma biomarkers, cognitive function and sleep surveys for correlation analysis.

Methods

In a retrospective cross-sectional study of warfighters (n=113 chronic mild TBI patients), the Pittsburgh sleep quality index (PSQI) was compared with amyloid β42 (Aβ42), neurofilament light (NFL), tau, and phospho-tau (threonine 181) isolated from plasma and exosomes. Executive function was tested with the categorical fluency test. Exosomes were precipitated from plasma. Proteins were measured with the Single Molecule Array (Quanterix). Linear models were adjusted for age, ApoE, and number of TBIs.

Results

Poor sleepers with TBI (PSQI>8) had elevated NFL compared to good sleepers in plasma (p=0.007) and exosomes (p=0.00017), and PSQI directly correlated with NFL (plasma: Beta=0.23, p=0.0079; exosomes: Beta=2.19, p=0.0013) stronger than any other marker of neurodegeneration. Poor sleepers also showed higher obstructive sleep apnea (OSA) risk compared to good sleepers by STOP-BANG scores (3.6, SD=1.6 vs 2.8, SD=1.74; p=0.0014) as well as decreased categorical fluency (20.7, SD=4.1) (18.3, SD=4.6, p=.0067). Plasma tau and Aβ42 also correlated with PSQI (Beta=0.64, p=0.028, and Beta=0.40, p=0.049 respectively).

Conclusion

This is the first reported data correlating markers of neuronal injury and cognitive deficits with sleep complaints and OSA risk in patients with TBI - possibly identifying treatable pathophysiological mediators of TBI neurodegeneration. Limitations include a small sample size, lack of objective sleep measures, and inability to establish directionality due to cross-sectional design. Prospective trials will be required to further explore our proposed hypothesis. If confirmed, these findings would call for targeting sleep disorders in the TBI population to mitigate risk of neurodegeneration.

Support

This work was supported by grant funding from: Department of Defense, Chronic Effects of Neurotrauma Consortium (CENC) Award W81XWH-13-2-0095 and Department of Veterans Affairs CENC Award I01 CX001135.
0421 Decreased Actigraphic Daytime Activity is Associated with Lower Memory Performance in Cognitively-Unimpaired Individuals with Autosomal Dominant Alzheimer’s Disease
Authors: Pardilla-Delgado E , Ramirez Gomez L , Baena A Y , Montes M I , Bocanegra Y , Martinez J E , Lopera F , Quiroz Y T
Published: May 2020

Introduction

Alzheimer’s disease (AD) impacts brain regions that control circadian regulation systems such as wakefulness and daytime physical activity. Recent evidence shows that AD pathology is damaging for wake-promoting neurons. Whether early changes in wakefulness and daytime activity occur during asymptomatic stages of familial AD (fAD) remains unknown. In this study, we aimed to investigate whether daytime activity differs between cognitively-unimpaired carriers of early-onset fAD and age-matched non-carrier family members. Further, we examined the associations between daytime activity and memory performance.

Methods

A total of 25 members of the large Colombian kindred with the Presenilin1 (PSEN1) E280A mutation were included in the study (9 mutation carriers and 16 non-carriers, mean age=38.2). PSEN1 mutation carriers develop dementia before the age of 50. All subjects underwent wrist actigraphy for 7-14 days to measure daytime activity (average activity per minute and per epoch), and completed the CERAD Word List Learning and the Free and Cued Selective Reminding Test (FCSRT).

Results

Compared to non-carriers, mutation carriers had less average daytime activity (Mann-Whitney U Test p=.04). Higher average daytime activity was associated with better memory recall in both the CERAD word list delayed recall (r=.47, p=.05) and the FCRST delayed total recall (r=.53, p=.02). No associations with age were observed.

Conclusion

Our results suggest that cognitively-unimpaired mutation carriers have reduced daytime activity, years before the onset of dementia. Reduced daytime activity in carriers is also associated with lower memory performance. Our preliminary findings add to the growing evidence that circadian dysfunction is present in early AD, and may play an important role in subsequent memory impairment. Future research with large samples is needed to further examine sleep and circadian dysfunction in asymptomatic individuals at genetic risk for AD.

Support

NIA 5R01AG054671-03 to YTQ
0423 Older Age Modifies the Association Between Combined Sleep Disordered Breathing and Sleep Duration with Neurocognitive Decline in Hispanic/Latino Adults
Authors: Kaur S , Tarraf W , Wu B , Daviglus M , Shah N , Sotres-Alvarez D , Gallo L , Wohlgemuth W , Redline S , Gonzales H , Ramos A
Published: May 2020

Introduction

We aimed to determine if age or sex modifies associations between sleep-disordered breathing (SDB), sleep duration and severe phenotypes of combined SDB/sleep duration with 7-year neurocognitive change (NC) in a diverse sample of U.S. Hispanic/Latinos.

Methods

We analyzed data of 5,235 adults 50-80 years of age from SOL-INCA, an ancillary to the Hispanic Community Health Study/Study of Latinos that determines the risk factors for NC. The main outcome was NC after a mean follow-up of 7-years on measures of memory (SEVLT sum and SEVLT recall), language (word fluency), processing speed (DSS) and a cognitive impairment screener. We evaluated the effect of baseline SDB (AHI ≥ 15), sleepiness (Epworth Sleepiness Scale, ESS ≥ 10), self-reported sleep duration (i.e. <6 hours, 6-9 hours, ≥ 9 hours), age and sex on NC. Survey linear regression models with interaction terms were used to examine the relationship between SDB, sleep duration, combinations of SDB and sleep duration phenotypes and NC. Depression, vascular risk, sleep medication, and study site were entered into all models as covariates.

Results

Overall, the mean age was 56.0 years, 54.8% females, 62.2% completed high school, 17.3% had SDB, 6.6% had short sleep,and 14.8% had long sleep. Sleep duration and SDB were not associated with NC. There was a significant interaction between agexSDB+sleep duration on delayed recall (F10,599= 2.40, p=0.01) and processing speed (F10,597= 2.55, p=0.01). Combined SDB + short sleep was associated with decline in processing speed (β=-0.6, 95% CI= [-1.2, -0.1], and combined SDB+long sleep was associated with decline in verbal memory (β=-0.9, 95% CI=[-1.7, -0.2] in adults aged ≥ 65 years. There was no association in participants aged <65 years and no sex differences.

Conclusion

Age, but not sex, modified the association between SDB and sleep duration with decline on processing speed and verbal memory. Sleep interventions tailored for older adults may be useful in slowing or preventing neurocognitive decline.

Support

This work is supported by National Institute on Aging (R01AG048642, RF1AG054548, R01AG061022, and R21AG056952).
0431 Two-Way Communication Between Dreamers and Experimenters
Authors: Konkoly K R , Paller K A
Published: May 2020

Introduction

Dreams are emblematic of human sleep, but they have yet to be adequately explained. In part, this is due to the limited options available for peering into dream experiences. Mapping neural measures onto dreams is problematic when those dreams are recounted after waking. Retrospective dream reports are subject to distortion and rapid forgetting.

Methods

Here, we describe a method to overcome these obstacles through two-way communication between dreamers and experimenters. To demonstrate proof-of-concept, we presented softly spoken math problems to participants during lucid REM sleep, and they provided answers using covert physiological signals such as eye movements. We confirmed REM sleep using standard polysomnographic methods.

Results

Thus far, 3 out of 8 participants who had lucid dreams correctly answered problems during REM sleep.

Conclusion

Results document that sleeping individuals can have sufficient abilities for veridical perceptual analysis, maintaining information, computing simple answers using working memory, and expressing volitional replies. Dreamers can thus be capable of interacting and exchanging information with other individuals. In this way, the mental content experienced by the dreamer can be interrogated to characterize the phenomenological experiences and cognitive abilities of dreaming.

Support

Mind Science Foundation, National Science Foundation
0438 Automatic Nighttime Agitation and Sleep Disruption Detection Using a Wearable Ankle Device and Machine Learning
Authors: Kumar R , Feltch C , Richards K , Morrison J , Rangel A , Janney R , Shayesteh S , Allen R , Banerjee N
Published: May 2020

Introduction

Nighttime agitation behavior such as wandering and restlessness during awake and sleep in people with Alzheimer’s disease (AD) is expensive to manage and adversely affects sleep. Nighttime agitation is mostly noted by subjective caregiver reports. An automated process for this assessment would improve clinical management. Here we report on the RestEaZeTM system that uses an ankle band and machine learning to automatically classify sleep status and nighttime agitation behaviors in older adults with AD.

Methods

We collected data on 7 adults (mean: 81 years, SD: 10.6) with AD. They wore the RestEaZeTM ankle band with a 3-axis accelerometer, a 3-axis gyroscope, and three textile capacitive sensors. A trained Research Assistant (RA) continuously observed for wandering, restlessness, wake, and sleep between 5pm and 7am using the Cohen Mansfield Agitation Inventory (CMAI). We merged, and band-pass filtered the data and divided it into 10-second non-overlapping windows. CMAI labels and time-series features (scaled using StandardScaler) extracted from the RestEaZeTM data were used to train a Random Forest binary classifier. The significant features were extracted based on the impact on the p-value for the classifier. We used the Synthetic Minority Oversampling Technique (SMOTE) to balance the dataset and performed 5-fold cross-validation with a 67-33 train-test split.

Results

We report the sensitivity, specificity, accuracy, and Area-under-the Curve (AUC) for the ROC curve for the classifiers: (1) Sleep/Awake: sensitivity=0.95, specificity=0.87, accuracy=0.92, AUC=0.97; (2) Wandering/Non-Wandering: sensitivity=0.85, specificity=0.99, accuracy=0.98, AUC=0.99; and (3) Restless/Non-Restless: sensitivity=0.84, specificity=0.84, accuracy=0.84, AUC=0.92. The significant features were related to the intensity of movements.

Conclusion

Our preliminary results show the feasibility of using RestEaZeTM for quantitatively measuring nighttime agitation. These can provide clinically useful objective measures of agitation that can be automatically transmitted to clinical or research records with minimal staff time requirements.

Support

The authors acknowledge the funding support from the National Institute on Aging under award R01AG051588 and Arbor Pharmaceuticals for support for Horizant and the matching placebo.
0442 Experimenting Automatic Sleep Analysis Application in a Clinical Context
Authors: Bouchequet P , Leger D , Lebrun M , Elbaz M
Published: May 2020

Introduction

Multiplication of publications describing groundbreaking automatic sleep analysis processes and algorithms push for real-life experimentation in clinical context, outside of controlled research environments.

Methods

Various automatic sleep analysis processes from the literature were implemented and orchestrated in a streamlined workflow. Artificial Intelligence algorithms using regular statistical learning or deep learning were re-trained on our own data after repeating the ad-hoc pre-processing steps described in the corresponding articles. For this, we used polysomnographic records previously taped in our clinic, subject to adequate legal authorizations and agreements: 500 nights from single patients with various pathologies. Those trained models were then applied to newly recorded polysomnographies through a platform developed and hosted on premise. For each polysomnography, a standardized and automatized report were generated and transmitted to the clinician in charge of the analysis. This report contains algorithms outputs, including automatic staging and related statistics such as hypnodensity, quantitative electroencephalography (EEG) analysis, spindles detection and automatic diagnosis. Aggregated record statistics are displayed next to our database statistics for benchmarking purposes.

Results

For sleep staging, we not only reproduced the results of the selected literature but obtained better metrics: a 0.76 Kappa agreement vs 0.69 in the literature. This may be due to our larger training database or the quality of physiologic signals in our data. Clinicians showed interest in the automatic staging part of the analysis. They noticed algorithm errors are mostly focused on ambiguous epochs, just like visual scoring. However, they found help into automated output and explanatory variables (hypnodensity) to score those ambiguous epochs.

Conclusion

Automatic sleep analysis algorithms used as decision helping tools shows real potential and should be generalized, as long as underlying processes are published and understood by users and clinicians.

Support

Banque Publique d’Investissement.