bluuebunny/crossref_metadata_2025_split huggingface dataset:
0198 Remote Saliva Sample Collection for Dim Light Melatonin Onset (DLMO) Measurement in Urban Children with Asthma During the COVID-19 Pandemic
Authors: Carskadon Mary , Gredvig-Ardito Caroline , Kopel Sheryl , Mitchell Daphne Koiniss 
Published: May 2022

Abstract

Introduction
The COVID-19 pandemic has challenged researchers to use remote data collection. Our project includes determining DLMO phase, requiring a family-friendly without face-to-face interaction. We describe here our protocol, experiences, lessons learned, and findings from the first 15 participants.

Methods
Fifteen urban-dwelling children with moderate to severe persistent asthma [7 girls, ages 7 (n=1) to 10 years; and 8 boys, 8 or 9 years] and caregiver (CG) participated. CG tracked bedtimes and risetimes in daily diaries for 10-14 days; average bedtimes from 5 nights preceding saliva collection were used to determine timing for 10 half-hourly samples. CG and child were oriented and then watched a demo video. A “spit-kit” was delivered to the home the afternoon of the study. Kits included a small cooler bag with bottle of water, 10 numbered and 5 spare Salivette tubes (Starstedt, Germany), plastic bag, dark wraparound glasses with securing strap, and log sheet. Data collection began with a zoom call with staff, CG, and child to reiterate the instructions, answer questions, and observe the first sample. Thereafter, a staff member telephoned the caregiver every 30 minutes to prompt the next sample and query whether glasses had been kept on. CG placed kit outside the home for morning pick up. Samples were centrifuged and frozen (-20°) until sending to the assay lab (SolidPhase, Portland, ME) for melatonin radioimmunoassay (Alpco, Windham, NH).

Results
DLMO phase was determined with a 4pg/ml threshold for 11 children. DLMO phases (mtime=21:46±68 min) and average bedtimes (mtime=20:40±88min) were positively correlated (r=.87). Challenges identified for missed DLMOs included: one child supervised by a teenaged sibling (not CG); one child/CG identified as potentially uncooperative. The other two “misses” likely arose from low saliva quantity, inconsistencies with staff training, and inadequate description of requirements for wearing glasses. Procedure modifications included strategies tailored to families’ needs, experiences, and home environment that can challenge adherence to protocol, greater emphasis on wearing glasses, and cartoon reminder card and scales added to kit. Subsequent samples were successful.

Conclusion
Our approach was effective for determining DLMO phase in children using a remote approach with careful application of methods.

Support (If Any)
R01HL142058, P20GM139743
0202 Predicting Sleep Inertia in a Biomathematical Model of Fatigue and Performance: A Novel Approach
Authors: McCauley Mark , McCauley Peter , Kalachev Leonid , van Dongen Hans 
Published: May 2022

Abstract

Introduction
Biomathematical models of fatigue typically include sleep inertia as an additive process during wakefulness. However, there is predictive information to be gained from tracking the propensity for sleep inertia through sleep periods. We propose a novel approach involving a neurobiological sleep inertia process with relatively fast dynamics (in the order of several minutes) interacting with the much slower dynamics of the established processes of sleep/wake regulation. This sleep inertia process is captured by the addition of two ordinary differential equations (ODEs) in the model framework of McCauley and colleagues (2009, 2013, 2021) – one for wakefulness to track impairment from sleep inertia, and one for sleep to track the propensity for sleep inertia upon awakening. A single time constant is introduced to control the dynamic behavior of these ODEs to capture the dynamics of sleep inertia.

Methods
398 healthy young adults (ages 21–49 years) each participated in one of eight multi-day laboratory studies of total sleep deprivation, sustained sleep restriction, or simulated shift work. At 2–4 hour intervals while awake, participants performed a Psychomotor Vigilance Test (PVT), for which number of lapses (RT&gt;500ms) was assessed, and rated their sleepiness on the Karolinska Sleepiness Scale (KSS). Sleep periods were recorded polysomnographically. Data were divided into a calibration set (five studies) used to estimate a single new model parameter capturing sleep inertia, and a validation set (three studies) used to independently verify model validity.

Results
Based on the calibration data set, the sleep inertia time constant estimate was 0.71h±0.01. Based on the validation data set, goodness-of-fit root-mean-square-error was 2.28 for PVT and 0.733 for KSS, indicating high predictive accuracy. A dynamic buildup and then decline of predicted propensity for sleep inertia during sleep emerged, peaking 2–3h into the sleep period.

Conclusion
The model expansion with a one-parameter sleep inertia process captured the transient effect of sleep inertia accurately across a range of sleep deprivation, sleep restriction, and simulated shift work scenarios. The emerging dynamic of sleep inertia propensity during sleep is consistent with findings on the magnitude of sleep inertia as a function of sleep duration and stage of awakening.

Support (If Any)
WSU HPC
0205 Sleep Need: More Influential on Health and Daytime Function than Sleep Duration?
Authors: Scott Hannah , Appleton Sarah , Reynolds Amy , Gill Tiffany , Melaku Yohannes , Adams Robert , Catcheside Peter , Perlis Michael 
Published: May 2022

Abstract

Introduction
Most prior research into relationships between sleep and health and daytime functioning have focused on average sleep duration or efficiency and ignored individual differences in sleep need. This study tested if sleep need is more strongly correlated with self-rated health and daytime function than sleep duration.

Methods
Data were drawn from the 2019 Sleep Health Foundation online survey of adult Australians (N=2,044, aged 18-90 years). Hierarchical multiple regressions assessed variance explained (R2 and R2 change) by demographics (Model 1: age, sex, BMI), self-reported sleep duration (Model 2: Model 1 + weighted variable of typical weekday/weekend sleep duration), and individual sleep need (Model 3: Model 2+ rating on a 5-point scale to ‘how often you get enough sleep to feel your best the next day’) on daytime function items for fatigue, concentration, motivation, and overall self-rated health (visual-analog scale from 0-100).

Results
Sleep need explained an additional 17.5–18.7% of the variance in fatigue, concentration, motivation, and health rating (all p &lt; 0.001 for R2 change) in Model 3. In contrast, Model 2 showed that sleep duration alone only explained an additional 2.0–4.1% variance in these outcomes after accounting for demographic variables. Findings were similar when stratified by sex. Sleep need also explained greater variance for older adults than for younger and middle-aged adults, especially on health rating (Model 3: R2 change = 0.11 for ages 18-24y, 0.14 for 45-54y, 0.27 for 75y+).

Conclusion
Sleep need appears to explain considerably more variance in daytime function and self-rated health than sleep duration. The effect of sleep need on other daytime consequences, and in clinical populations, needs further exploration. Validated assessments of sleep need are also needed to elucidate its importance for understanding the effect of sleep on health and functioning.

Support (If Any)
The 2019 Sleep Health Foundation online survey was supported by the not-for-profit Sleep Health Foundation using an unrestricted grant from Merck Sharp & Dohme (Australia) which did not inform nor restrict study design, methodology, or presentation.
0210 Social rhythm regularity: Associations with sleep, circadian, mental health, and alcohol use outcomes in adolescents
Authors: Tracy Eunjin , Buysse Daniel , Soehner Adriane , Hasler Brant 
Published: May 2022

Abstract

Introduction
Circadian rhythms and sleep regularity relate to a range of negative health outcomes, such as mental illness and substance abuse including binge drinking. According to the social zeitgeber hypothesis, the timing of key modifiable daily behaviors serves as time cues that entrain circadian rhythms, ostensibly stabilizing them and thereby improving health. The cross-day stability in timing of these behaviors (i.e., social rhythm regularity) is measured by SRM5; however, studies have not tested whether SRM5 correlates with circadian rhythm regularity based on physiological measures, such as dim light melatonin onset (DLMO). The current study examined whether SRM5 was associated with: (1) the regularity of circadian rhythms and/or sleep regularity metrics, and (2) sleep quality, depression, and binge drinking.

Methods
Late adolescents aged 18 to 22 years old who drink alcohol (n = 36; 61.1% female, Mage = 21.26) completed a self-reported sleep diary (including SRM5 items for first contact, start work, and dinner time), wore a wrist actigraph for 14 days, and completed 2 overnight visits to assess DLMO. We used the self-reported data to calculate SRM5 and standard deviation (StDev); actigraphy data to calculate composite phase deviation (CPD), social jet lag (SJL), and interdaily stability (IS); and DLMO data to calculate the stability of the circadian phase (Sunday minus Thursday). Participants also completed surveys that assessed global sleep quality, depressive symptoms, and frequency of binge drinking. Correlational analysis and hierarchical linear regression modeling were used.

Results
Higher SRM5 scores (i.e., higher social rhythm regularity) were associated with higher regularities of mid-sleep timing (r = –.48, p &lt; .001) and total sleep duration (r = –.41, p = .01) based on StDev metrics but were not associated with IS (r = 13, p = .45), CPD (r = –.19, p = .28), SJL (r = –.07, p = .68), and stability of DLMO (r = –.003, p = .99). A post-hoc analysis found that higher stability of the “out of bed” item of SRM5 was related to higher stability of DLMO (b = –.11, se = .05, p = .03, r2 = .33). Higher SRM5 scores were associated with better sleep quality (b = –.73, se = .30, p = .02, r2 = .21), but were not with depressive symptoms or binge drinking

Conclusion
In contrast with the social zeitgeber hypothesis, SRM5 was not associated with circadian rhythm regularity measured by DLMO. However, social rhythm regularity is an important factor in predicting better sleep quality. This study provides a foundation for future research with better power to determine the extent to which social rhythms influence circadian stability and to better understand why social rhythm regularity relates to sleep quality.

Support (If Any)
This research was supported by the NIH NIAAA (R21AA023209-02 ), NHLBI (T32HL082610), and NIMH (T32MH019986)
0216 Environmental bright light exposure is associated with sleep timing: the Multi-Ethnic Study of Atherosclerosis
Authors: Clarkson-Townsend Danielle , Rotter Jerome , Rich Stephen , Redline Susan , Sofer Tamar 
Published: May 2022

Abstract

Introduction
Light influences sleep via the circadian system, but few studies have examined objective light exposure and sleep outcomes in the general population. We investigated the relationship between daily average time above 1,000 lux white light (TALT1000), a proxy for outdoor light exposure, and actigraphy measures of sleep timing and regularity in the Multi-Ethnic Study of Atherosclerosis (MESA).

Methods
Light and actigraphy data collected over 5+ days (wrist-worn Actiwatch Spectrum) were analyzed. Relationships between TALT1000 and dichotomized sleep timing measures (sleep midpoint regularity, defined as &lt;30 minutes variability in sleep timing; late sleep onset, defined as 12AM or later) were evaluated with logistic regression models, adjusted for age, self-reported race/ethnicity, sex, federal poverty level, partner status, employment, smoking, BMI, depression score, sleep duration, day length by month and site, chronotype, number of days measured, ActiWatch off-wrist time, and average physical activity during active period. Stratified analyses for employment status and sleep duration were also conducted. Covariates associated with quartiles of TALT1000 were evaluated with ordinal logistic regression.

Results
2,135 MESA participants with valid actigraphy data were included (mean age=68.6 years, 53.8% female, mean TALT1000=61 minutes, mean sleep midpoint variability=70.6 minutes). There was a dose-response relationship between quartiles of TALT1000 and sleep timing regularity, with participants in the highest quartile of TALT1000 exposure (equivalent to 90+ minutes daily bright light exposure) having 87.7% increased odds of sleep timing regularity (adjOR=1.88, CI=1.35-2.62); the highest quartile of TALT1000 was also associated with a 41% decreased odds of sleep onset timing ≥12AM (adjOR=0.59, CI=0.43-0.81). Age, race/ethnicity, partner status (single), and day length were negatively associated, while BMI, sex (male), earlier chronotype, and physical activity were positively associated with quartiles of TALT1000 (p&lt;0.05).

Conclusion
Greater average bright light exposure is associated with greater sleep timing regularity and earlier sleep onset in a large sample of U.S. adults. Future analyses will investigate timing of light exposure and associated multi-omic signatures.

Support (If Any)
NIH-NHLBI T32HL007901, R35HL135818, R01HL098433, R24HL114473, 75N92019R002.
0223 Sleep during layovers of different lengths after long-haul flying across multiple time zones in different geographic directions
Authors: Arsintescu Lucia , Hilditch Cassie , Gregory Kevin , Kato Kenji , Flynn-Evans Erin 
Published: May 2022

Abstract

Introduction
Long-haul pilots experience high levels of fatigue and circadian disruption due to long work hours and trans-meridian travel. The aim of this study was to characterize sleep timing and duration during layovers of different lengths after crossing multiple time zones.

Methods
All pilots flying long-haul operations from a single airline were eligible to participate. While following their normal work schedule within airline operations, pilots collected data for ~2 weeks including at least two long-haul rotations, with rest days and layovers. Participants wore an Actiwach (Phillips Respironics) throughout the entire study period and completed a sleep diary (at bedtime and upon waking up). Based on the data, we categorized layovers as follows: layover type 1: 34 h after crossing five time zones in westward direction; layover type 2: 34 h, no time zone change; layover type 3: 55 h after crossing six time zones in eastward direction. Each flight left the home base at the same time of day (23:00) and the flight duration was between 10.5 and 12 h. We calculated descriptive statistics for each category.

Results
Forty-four long-haul pilots participated in the study (5 female; mean age 44.25 ± 10.06 yrs; mean flight hours 9834.3 ± 5334.1 h). We found that for layover type 1, the mean sleep duration (h) per 24 h was 6.90 (±1.04), mean sleep efficiency (%) was 81.08 (±10.89), and mean Wake After Sleep Onset (WASO, min) was 33.23 (±20.42); for layover type 2, the mean sleep duration (h) per 24 h was 6.91 (±1.06), mean sleep efficiency (%) was 81.71 (±6.80), and mean WASO (min) was 30.10 (±11.00); for layover type 3, the mean sleep duration (h) was 7.07 (±1.32), mean sleep efficiency (%) was 83.93 (±6.04), and mean WASO (min) was 36.94 (±17.95).

Conclusion
Our preliminary analyses showed that sleep duration and sleep efficiency were similar for the layovers of the same length regardless of time zone change. Additional analyses will be conducted to investigate sleep on additional layovers of different lengths and the effects of sleep obtained during layover on the performance and alertness on the return flights.

Support (If Any)
This research was supported by the NASA System-Wide Safety Program.
0227 The effect of light on circadian entrainment for shifting from day to night flight operations
Authors: Shattuck Nita , Matsangas Panagiotis , Reily James , McDonough Meghan , O'Hagan Donnla , Giles Kathleen 
Published: May 2022

Abstract

Introduction
A midair collision during a routine nighttime air refueling training mission in the early morning hours of December 6, 2018, resulted in the tragic deaths of six Marine aircrew members and the loss of two US Marine Corps aircraft. Fatigue and the transition from day to night flights were called out as a problem area that continues to plague aviation commands. The goal of this study was to provide recommendations to the fleet regarding the limitations and best practices for shifting aviators from day to night operations to mitigate aviator fatigue and facilitate circadian re-alignment.

Methods
Longitudinal (10-day) within-subject assessment of aviators (N=9) in hybrid conditions. Aviators completed validated questionnaires for sleepiness and workload. Performance was assessed in simulated flight scenarios (one morning and three night sessions). The efficacy of a single 4-hour exposure of blue-enriched white light (~1000 lux) was assessed with the dim-light melatonin onset procedure. The study protocol attempted to replicate the work and rest patterns of aviators in the field who work during the day but could potentially be required to quickly shift their schedules to support night flight operations.

Results
The circadian phase of all participants was successfully delayed an average of 1.3 hours (range: 0.88-1.93 hours). Despite the lack of control over light exposure or other activities over the study period, participants reported less sleepiness and reduced subjective workload with improved flight performance.

Conclusion
Conclusions from the literature review and our study indicate that circadian entrainment in complex military operational settings should use light management as the dominant method for shifting the circadian clock. Based on these conclusions, we developed general recommendations and two circadian synchronization plans for aircrew switching from day to night operations. One plan shows a schedule that prepares for night operations by steadily shifting the daily schedule over multiple days. The other plan shows a schedule for aircrew who are required to shift from day to night operations abruptly without notice.

Support (If Any)
Supported by the Assistant Commandant of the Marine Corps.
0235 A Systematic Review of Sleep Health and Outpatient Opioid Use Disorder Treatment in Adults
Authors: Hernandez Estefania , Griggs Stephanie 
Published: May 2022

Abstract

Introduction
Opioid Use Disorder (OUD) affects 2 million people in the United States and poor sleep health (satisfaction, alertness, timing, efficiency, and duration) is a primary driver of medication-assisted treatment (MAT) failure and relapse. It is known that people in therapy for OUD have a high prevalence of sleep problems (&gt;75%) and poorer sleep health compared to people without OUD (e.g., lower sleep efficiency, shorter duration, and more awakenings). However, sleep health is not routinely assessed. Thus, in this systematic review, we examined original studies on sleep health within the context of adults receiving outpatient MAT for OUD.

Methods
We conducted a systematic review of original research on sleep health in adults receiving outpatient treatment for OUD. Multiple electronic databases (PubMed, PsycINFO, and CINAHL) were searched for relevant studies published in English from the establishment of each database to September 14, 2021. Quality was assessed with the Mixed Methods Appraisal Tool (v. 2001).

Results
Sixty two studies were selected including 17,913 adults with OUD and 604 comparison participants without OUD (mean age = 37.4 ± 6.6 years; 54.1% male). Sixty-one studies were quantitative (50 cross sectional, 6 longitunal, 5 interventional) and 1 was mixed methods. Participants with OUD had poorer satisfaction (Pittsburgh Sleep Quality Index mean 7.4 ± 2.2 v. 4.7 ± 2.3), shorter polysomnography (PSG) measured total sleep time (336.6 ± 41.4 mins (5.6 h) v. 411.8 ± 33.3 mins (6.8 h), spent less time in PSG measured slow wave N3 sleep (7.2 ± 5.8% v. 13.4 ± 6.4%), and had a lower percentage of PSG measured rapid eye movement sleep (14.6 ± 4.6% v. 21.7 ± 4.0%) than comparison participants without OUD.

Conclusion
Studies were predominantly observational ranging from a period of 1-2 nights to 2 years with participants at various points in treatment. More work is needed to understand the multidimensional depth of sleep health in adults with OUD. Optimizing sleep health in adults with OUD may improve their addiction trajectory and should be a priority in practice and research.

Support (If Any)
American Academy of Sleep Medicine (220-BS-19).
0238 Perceived Childhood Neighborhood Safety and Sleep Health during Adulthood
Authors: Gaston Symielle , Alhasan Dana , Harmon Quaker , Baird Donna , Jackson Chandra 
Published: May 2022

Abstract

Introduction
Neighborhood safety has been cross-sectionally associated with sleep health at different life stages. However, few studies have investigated childhood neighborhood safety and adulthood sleep despite the possibility that childhood neighborhood safety may serve as a modifiable target for primordial prevention of poor sleep health.

Methods
Using data from 1,611 Black/African-American women enrolled in the Study of Environment, Lifestyle and Fibroids, we investigated associations between perceived childhood neighborhood safety and adulthood sleep. Participants reported safety of their childhood neighborhoods as unsafe vs. safe at ages 5,10, and 15 years. Participants also self-reported current (ages 23-35 years) sleep duration and quality (i.e., frequently wake feeling unrested [≥4 days/week] and frequent insomnia symptoms [≥15 days/month of difficulty falling or staying asleep]). Adjusting for childhood socioeconomic characteristics, log binomial models estimated prevalence ratios (PRs) and 95% confidence intervals (CIs). For perceived safety at ages 10 and 15 years, we applied inverse probability weights to models to adjust for perceived neighborhood safety at prior ages.

Results
Mean age ± standard deviation was 29 ± 3.5 years. Prevalence of residence in a childhood neighborhood perceived as unsafe increased with age (Age 5- 20%, Age 10- 22%, Age 15- 31%), and 17% reported an unsafe neighborhood at every age. Both short sleep duration (&lt;7 hours) and frequently waking feeling unrested during adulthood were reported by approximately 60% of women, and 10% reported frequent insomnia symptoms. Participants in perceived unsafe vs. safe neighborhoods at every age were more likely to frequently wake feeling unrested as adults (PR=1.12 [95% CI: 1.00-1.25]). Perceived unsafe neighborhood at ages 5 and 15 years was associated with frequent insomnia symptoms and frequently waking feeling unrested, respectively. Perceived unsafe neighborhood at age 10 years was marginally associated with a higher prevalence of both frequently waking feeling unrested (PR=1.11 [0.98-1.27]) and frequent insomnia symptoms (PR=1.58 [0.99-2.52]) during adulthood.

Conclusion
Perceived unsafe neighborhood during childhood was associated with poorer sleep during adulthood among a cohort of young Black women.

Support (If Any)
Division of Intramural Research, National Institutes of Health (NIH), National Institute of Environmental Health Sciences (Z1AES103325[CLJ] and 1ZIAES049013[DB]), and the American Recovery and Reinvestment Act funds designated for NIH research