bluuebunny/crossref_metadata_2025 huggingface dataset:
229 Sleep-wake behavior, meal timings and digital media duration of Indians during COVID-19 Lockdown
Authors: Pande Babita , Sinha Meenakshi , Sinha Ramanjan
Published: May 2021

Introduction

Lockdown and stay home order has been imposed on people in many countries including India to prevent the community transmission of COVID-19 pandemic. However this social restriction led to disturbed daily routine and lifestyle behaviour that is needed to be attended for proper therapeutic management of overall health during such crisis. The impact of lockdown on the most apparent behavioral changes viz. sleep-wake behaviour, major meal timings, and digital screen duration of Indians were investigated. In addition the effects of gender and age were explored.

Methods

After seeking permission from Ethical Institution, an online questionnaire based survey was circulated within India in the first week of May, 2020 for which total 1511 male and female (age ≥18 years) subjects participated. The sleep-wake behavior observed were sleep-wake timings, sleep duration, mid sleep time (MST) as function of lockdown, and social (lockdown) jetlag (SJL = MST before lockdown-MST during lockdown).

Results

The sleep onset-wakeup and meal times were significantly delayed during lockdown, which was more pronounced in younger age group. The sleep duration increased, specifically in young individuals during lockdown. Females showed more delayed sleep onset-waking times and first meal timing with longer sleep duration during lockdown. Increased digital media duration was observed in all age groups, primarily in males. The younger age group and specifically female reported higher SJL and delayed MST. A positive association was obtained between sleep duration & first meal time, and SJL & major meal timings/screen duration, and a significant negative relationship of sleep duration and SJL with age.

Conclusion

The study shows delayed sleep-wake schedule, meal timings and increased digital media duration among Indians during COVID-19 lockdown compared to before lockdown. Also, gender and age emerged as important mediating factors for this alteration. The pandemic has given opportunity to sleep more and compensate for the sleep. In spite of that, the higher social jetlag in young age group and female showed the compromised sleep and maladaption with societal timing. These findings have applied implications in sleep health during longer social isolation conditions and for proper therapeutic management.

Support (if any)

No
239 Changes in Children’s Schoolyear and Summer Sleep during the COVID-19 Pandemic
Authors: Burkart Sarah , Parker Hannah , Von Klinggraeff Lauren , Hunt Ethan , Jones Alexis , Dugger Roddrick , Reesor-Oyer Layton , Beets Michael , Weaver R Glenn , Armstrong Bridget
Published: May 2021

Introduction

In spring 2020, elementary schools closed to minimize the spread of COVID-19. Questionnaire data suggest children’s sleep was impacted during the pandemic, yet device-based data (i.e. accelerometry) on this topic is lacking. The purpose of this study was to examine children’s sleep during the COVID-19 pandemic (i.e. spring and summer 2020) compared to previous data collected from the same children during each of the two previous years (spring and summer 2018 and 2019).

Methods

68 children (age = 9.9±1.2 years, 56% Black, 53% male) previously recruited for an observational cohort study wore a Fitbit Charge 2 on their wrist during the spring and summer from 2018-2020 (i.e. six 30-day measurement periods). We used multilevel mixed models to examine how children’s sleep patterns changed during the pandemic accounting for previous trajectory (i.e. 2018 to 2019). Models included age, sex, and race as covariates.

Results

Children had an average of 84 nights of sleep data across all six 30-day measurement periods. In the spring of the pandemic, children slept 24.6 minutes more (95%CI = 11.6, 37.5) compared to previous springs. During the pandemic summer, they slept 40.0 minutes more (95%CI = 24.6, 58.5) compared to previous summers. Sleep midpoint was 117.1 minutes later (95%CI = 103.6, 130.6) in the spring during the pandemic and 46.0 minutes later (95% CI = 26.9, 65.2) in the summer during the pandemic compared to previous years. Sleep efficiency improved slightly by 1.3% (95% CI = 0.7, 1.9) and 3.6% (95% CI = 2.7, 4.5) in spring and summer, respectively, during the pandemic compared to previous years.

Conclusion

During the COVID-19 pandemic, children slept longer after accounting for previous developmental trends. Notably, the shift in sleep timing during the pandemic was nearly two hours later in the spring compared to previous years, potentially due to the lack of structure usually provided by school. Later sleep timing is independently associated with poor health behaviors (e.g., nutrition, physical activity, screen time). Future studies should examine if these changes in sleep persist over time and have potential long-term effects on children’s health.

Support (if any)

R21HD095164 (PI Weaver) & UofSC COVID-19 Research Initiative Grant (PI Armstrong)
240 Habitual Sleep Changes Following COVID-19 Outbreak
Authors: Eyal Shuli , Altman Yuval , Baharav Anda
Published: May 2021

Introduction

The ongoing COVID-19 pandemic emerges as one of the most impressive and strenuous events of the century, with unthinkably huge global effects. We aimed at analyzing if and how does the pandemic affect sleep and related behaviors.

Methods

We reviewed 48,047 nights recorded in the US with the Sleeprate application by 3,381 users during a period of 2 years, December 2018-November 2020. Nightly data included perceived and measured sleep parameters. In addition, users reported their perceived daytime stress and sleepiness. We analyzed the monthly variability of the studied parameters and compared their values during the COVID-19 period of March-November 2020 (CP) with those in the previous corresponding period in 2019, the pre-COVID-19 period (PCP).

Results

Starting March 2020, wake-up time (WUT) was significantly delayed relative to PCP. WUT in April 2020 was the latest (8:06AM±2:12hours, mean±SD, p<.000), being an hour later than in April 2019. This delay started to diminish in June 2020, reaching 7:27AM±2:10 hours by November 2020, which was not significantly higher than during PCP. Bedtime (BT) exhibited similar behavior, yet it returned to PCP times faster. Delayed BT and WUT on weekends were observed during CP as well as PCP. No consistent differences in sleep duration or sleep efficiency were detected between CP and PCP. Subjective sleep satisfaction was higher in CP relative to PCP. However, daytime sleepiness and daytime stress were also higher during most of CP compared to PCP.

Conclusion

Our data, based on digital in-app sleep diaries coupled with perceived sleep parameters, demonstrate the pandemic’s effects on sleep behavior in the US. Users in this study adapted to the new circumstances with delayed sleep schedule, while not reducing the sleep opportunity. The higher sleep satisfaction may be connected to later sleep schedules, allowing a wake-up time that fits better human biological clocks. The reported increased stress and sleepiness further portray the uncertainty and turbulence characterizing the pandemic’s effects on populations life during the pandemic. As good sleep is linked with immune response efficacy, higher quality of life, and improved mood, the importance of sleep must not be overlooked, especially during the pandemic.

Support (if any):
247 Automated sleep staging using wrist-worn device and deep neural networks
Authors: Sridhar Niranjan , Ghoreyshi Atiyeh , Myers Lance , Owens Zachary
Published: May 2021

Introduction

Heart rate is well-known to be modulated by sleep stages. If clinically useful sleep scoring can be performed using only cardiac rhythms, then existing medical and consumer-grade devices that can measure heart rate can enable low-cost sleep evaluations.

Methods

We trained a neural network which uses dilated convolutional blocks to learn both local and long range features of heart rate extracted from ECG R-wave timing to predict for every non-overlapping 30s epoch of the input the probabilities of the epoch being in one of four classes—wake, light sleep, deep sleep or REM. The largest probability is chosen as the network’s class prediction and used to form the hypnogram. We used the Sleep Heart Health Study (SHHS) and Multi-Ethnic Study of Atherosclerosis Study (MESA) and Physionet Computing in Cardiology (CinC) dataset (over 10000 nights) for training and evaluation. Then we deployed the algorithm on PPG based heart rate measured by a wrist-worn device worn by subjects in a free-living setting.

Results

On the held out test SHHS dataset (800 nights, 561 subjects), the overall 4-class staging accuracy was 77% and Cohen’s kappa was 0.66. On the CinC dataset (993 nights, 993 subjects), the overall 4 class accuracy was 72% and Cohen’s kappa was 0.55. The study on free-living subjects is underway and these novel results will be collated and presented upon completion.

Conclusion

We hope these results build more trust in automated heart rate based sleep staging and encourage further research into its clinical application in screening and diagnosis of sleep disorders. Low cost, high efficacy devices which can be used in longitudinal studies can lead to breakthroughs in clinical applications of sleep staging for early diagnosis of chronic conditions and novel treatment endpoints.

Support (if any)

We recently published the training/testing of the algorithm as well a population level analysis showing differences in predicted sleep stages between disease cohorts. The article was published in NPJ Digital Medicine in Aug 2020. The study on free living subjects is currently underway and these new results will be presented at the sleep conference. Preliminary results indicate high concordance with our published results.
249 Overnight heart rate variability depends on age, gender, and day of the week: a field observation using a smart bed platform
Authors: Barr Shawn , Sohn Kwanghyun , Garcia Gary
Published: May 2021

Introduction

Heart rate variability (HRV) is commonly used to assess the activity of the autonomic nervous system (ANS). ANS function changes, reflected in HRV, result from factors including lifestyle, aging, cardiorespiratory illnesses, sleep state, and physiological stress. Despite broad interest in HRV, few studies have established normative overnight HRV values for a large population. To better understand population level HRV changes, ecologically-valid, overnight sleep SDNN (standard deviation of all normal heartbeat intervals, lower HRV is reflected by lower SDNN) values have been analyzed for a large sample of Sleep Number 360 smart bed users.

Methods

Overnight SDNN values were obtained over the course of 18.2M sleep sessions from 379,225 sleepers (48 ± 14.7 sessions/user). 50.9 percent of sleepers were female. The age was normally distributed with mean ± SD of 52.8 ± 12.7 years (range 21 to 84). Heartbeat intervals used to compute SDNN were extracted from a ballistocardiogram (BCG). BCG-based HRV estimation during sleep has previously been validated against ECG-based HRV with an R-square of 0.5.

Results

Using a Generalized Linear Model, significant cross-sectional associations with SDNN were observed for three variables of interest: age, gender, and day-of-the-week. For sleepers under 50, SDNN declined at a rate of about 2.1 ms/year, then leveled off for sleepers aged 50-65, and increased slightly thereafter. Women under 50 displayed lower, more slowly declining, SDNN values than men, but this trend reversed for sleepers over 50. Throughout the week, SDNN values followed a U-shaped (women) or L-shaped (men) pattern, where values were highest during the weekend and lowest at mid-week.

Conclusion

Using a smart bed to unobtrusively measure overnight SDNN values for a large set of sleepers in an ecologically valid environment, reveals significant effects of age, gender, and day of the week on overnight SDNN.

Support (if any):
256 Spectrophotometric Properties of 31 Different Commercially Available Blue Blocking Glasses Under Electric Room Lighting
Authors: Rupple Destiny , Mason Brooke , Tubbs Andrew , Fernandez Fabian-Xosé , Grandner Michael
Published: May 2021

Introduction

Blue blocking glasses are often marketed to promote relaxation, sleep, and circadian health by attenuating melatonin-suppressing light exposure. But these glasses represent a wide range of tint and other lens properties. Further, the utility of these glasses under ecologically valid indoor conditions (where light is typically generated from overhead broadspectrum fluorescent lamps) is still unclear, especially across various products.

Methods

A calibrated spectroradiometer (Ocean Insight), cosine corrector, optic fiber, and software package were used to measure the absolute irradiance (uW/cm^2/nm) emitted from overhead fluorescent lighting in a closeted dark room. Thirty-one commercially available blue blockers were individually placed between the cosine corrector and the luminaire, at a standardized distance and angle, where intensity was measured and analyzed. Each lens was evaluated individually relative to the light source under identical conditions. Then, lenses were collapsed by type into the following groups: red-tinted lenses (RTL), orange-tinted lenses (OTL), orange-tinted lenses with blue reflectivity (OBL), brown-tinted lenses (BTL), yellow-tinted lenses (YTL), and clear reflective blue lenses (RBL).

Results

There was significant variation in light-blocking across lens types (one-way ANOVA, p < 0.0001). On average, RTL and BTL restricted 59% of the visible light measured from 380-780nm. OTL blocked 47% of the light in this range, while OBL blocked 29%. Both YTL and RBL blocked 14% of the exposure. When narrowing the range of light to 440-530nm (the part of the spectrum most likely to produce a response from melanopsin-expressing retinal ganglion cells), we estimated the following performance: the RTL and OTL blocked close to 100% of the light, OBL blocked 98%, BTL blocked 80%, YTL blocked 33%, and RBL blocked 15%. These differences were statistically significant (one-way ANOVA, p < 0.0001). Individual lenses performed variably within groups, but these differences were small.

Conclusion

Focusing on the portion of the visible spectrum most likely to suppress melatonin secretion, RTL and OTL blocked exposure the best, followed by OBL, BTL, YTL, and (lastly) RBL.

Support (if any)

R01MD011600, R01DA051321
257 How Much Blue Do Blue-Blockers Block if Blue-Blockers Do Block Blue?
Authors: Mason Brooke , Tubbs Andrew , Killgore William , Fernandez Fabian-Xosé , Grandner Michael
Published: May 2021

Introduction

Short-wavelength light (440-530nm) can suppress endogenous melatonin secretion from the pineal gland. This has been observed in realworld settings when people use electronic media at night that emits light from this part of the visible spectrum. Blue-blocking glasses are a possible intervention to reduce blue light exposure. The present study evaluated the ability of commercially available blue-blockers to block blue light emitted by LEDs.

Methods

A calibrated spectroradiometer (Ocean Insight), cosine corrector, optic fiber, and software package were used to measure the absolute irradiance (uW/cm^2/nm) generated from a blue light source (Phillips Go Lite Blu) in an otherwise completely dark room. Thirty-one different commercially-available blue-blockers were individually placed between the cosine corrector and the light source at a standardized distance, and then intensity was measured and analyzed. Lenses were evaluated with regards to the amount of blue light they suppressed both individually and grouped by lens tint: red-tinted lenses (RTL), orange-tinted lenses (OTL), orange-tinted lenses with blue reflectivity (OBL), brown-tinted lenses (BTL), yellow-tinted lenses (YTL), and clear lenses with blue reflectivity (RBL).

Results

RTL blocked 100% of the short-wavelength light, while OTL and OBL blocked 99%, BTL blocked 66%, YTL blocked 38%, and RBL blocked 11% of it. This represented a statistically significant between-group difference (one-way ANOVA, < 0.0001). Within groups, there was variability in performance among individual lenses, though this variability was small compared to the between-group differences.

Conclusion

The RTL, OTL, and OBL block light best capable of suppressing melatonin secretion at night (440-530 nm); with slightly less efficacy, BTL and YTL also restricted much of the light exposure. Lastly, RBL were not effective at curtailing short-wavelength light. Those looking to optimize blue-blocking capabilities should use RTL, OTL, and OBL, rather than other lens types.

Support (if any):
262 Comparing Two Methods for Scoring Wrist Actigraphy to Polysomnography for Estimating Total Sleep Time in Healthy Men
Authors: Tussey Emma , Rynders Corey , Swanson Christine
Published: May 2021

Introduction

This analysis assessed whether manually setting rest (i.e., time in bed) intervals prior to using a proprietary software package (Actiware, version 6.09) to analyze wrist actigraphy data improved estimates of total sleep time (TST) compared to polysomnography (PSG).

Methods

The Phillips Actiwatch 2 and PSG (reference method) were used to calculate TST on two separate nights in twelve men (age=28.3 ± 5.7). Participants had an 8-hour sleep opportunity on night one and a 5-hour sleep opportunity and on night two. Estimates of TST from actigraphy data were calculated using two scoring methods. For scoring method 1, we allowed the software to automatically choose rest intervals and then applied a proprietary algorithm to calculate TST. For scoring method 2, we manually entered rest intervals using a published decision tree that incorporates activity, light, event marker, and sleep diary data. After the rest intervals were set in method 2, the proprietary algorithm was applied to calculate TST. Mean bias and limits of agreement (LOA) from Bland-Altman plots compared TST derived from both actigraphy scoring methods to PSG estimates.

Results

On night 1 (n=8) TST measured by PSG was 398.4 ± 40.6 minutes, compared to 395.5 ± 70.9 minutes using actigraphy scoring method 1 and 396 ± 44.5 minutes using scoring method 2. Mean bias was similar when comparing both scoring methods to PSG, but the LOA were wider in method 1 compared to method 2 (method 1 vs. PSG: -2.9 [-110.4, 104.7]; method 2 vs. PSG: -2.4 [-66.5, 61.7]; minutes). On night 2 (n=12) TST determined by PSG was 283.3 ± 11.2 minutes, compared to 302.1 ± 84.4 minutes using actigraphy scoring method 1 and 273.1 ± 14.5 minutes using scoring method 2. Again, LOA for TST estimated by actigraphy scoring method 1 were wider compared to scoring method number 2 (method 1 vs. PSG: 18.8 [-136.9, 174.6]; method 2 vs. PSG: -10.2 [-35.1, 14.8]).

Conclusion

These data demonstrate that applying a decision tree to manually set time in bed intervals prior to running analyses in the software results in better agreement when estimating TST from wrist actigraphy compared to PSG.

Support (if any)

UL1RR025780, K23AR070275.
277 Tunable White Light for Elders (TWLITE): A feasibility study of a home-based sleep intervention
Authors: Jones Carolyn , Reynolds Christina , Olson Randall , Bontrager Ashten , Lambert Sophia , Balba Nadir , Weymann Kristianna , Kaye Jeffrey , Wilkerson Andrea , Elliott Jonathan , Lim Miranda
Published: May 2021

Introduction

Sleep disturbances are common in elderly patients and may contribute to disease progression in certain populations (e.g., Alzheimer’s Disease). Light therapy is a simple and cost-effective intervention to improve sleep. Primary barriers to light therapy are 1) poor acceptability to use of devices and 2) inflexibility of current devices to deliver beyond a fixed spectrum and throughout the entirety of the day. However, dynamic, tunable lighting integrated into the native home lighting system can maximize short-wavelength light in the morning and minimize short-wavelength light in the evening, thus entraining circadian rhythms and treating sleep disturbances, and overcome these limitations. We determined the feasibility of implementing a whole-home tunable lighting system as a potential sleep intervention.

Methods

Tunable LED lights were installed throughout the homes of healthy older adults already enrolled in an existing study with embedded home assessment platforms (ORCATECH study; n=4 subjects in n=3 homes). In ORCATECH, continuous data on room location, activity, sleep, and general health parameters are collected at minute-to-minute resolution over months to years of participation. This single arm longitudinal design collected participants’ light usage in addition to ORCATECH outcome measures. Primary outcomes for this pilot study included the feasibility and patient acceptability. Exploratory outcomes were sleep metrics (sleep time, latency, efficiency), mobility (room transitions and actigraphy), and overall health indices (weekly body weight, self-report general health questionnaires) both pre- and post-intervention.

Results

Two subjects terminated the study citing technical difficulties with the lights and a preference for brighter illumination. Of the remaining 2 participants, sleep metrics were explored over a 12-month period spanning pre- and post-installation of lights. Nightly duration in bed was compared with minute-to-minute room entry data and actigraphy with high inter-measure reliability.

Conclusion

These data support that tunable whole-home lighting systems are reasonably acceptable and feasibly implemented using an automated platform for continuous data collection. Quantification of sleep over long periods of time is robust and reliable in the home environment of elderly subjects. These results will inform implementation of future large-scale lighting intervention studies in patients at risk for developing Alzheimer’s Disease.

Support (if any)

Hartford Gerontological Center Interprofessional Award, Pacific Northwest National Laboratory, OHSU ORCATECH
283 Travel Factors in Away Games: A Case Study of a Women’s College Basketball Team
Authors: Pradhan Sean , Alton Devin
Published: May 2021

Introduction

Previous investigations in professional basketball, football, and other sports have shown meaningful effects of factors like rest and length of a team’s road trip on overall performance, with detriments being attributed to travel. However, prior research in the context of college basketball has been relatively scant. Thus, the current study extends the literature by performing a case study on the impact of such travel factors on a women’s college basketball team.

Methods

Data from a total of 110 road games played over the last 10 seasons from 2010 to 2020 by a National Association of Intercollegiate Athletics (NAIA) women’s college basketball team were collected from the college’s athletics site. We examined the influence of consecutive games played away, days in between games, back-to-back games, and miles traveled by the team on game outcomes and team performance. Specifically, we inspected box-score statistics, such as points scored, points allowed, shooting percentages (i.e., field-goal, free-throw, and three-point), rebounds, blocks, steals, assists, personal fouls, and turnovers. We performed a series of generalized regressions controlling for the team and opponent winning percentages entering each game, along with the opponent’s home time zone. Although neutral site games were excluded from our analyses, such events were still considered in determining the number of consecutive games played away from home.

Results

Our analyses revealed that the team scored significantly more points (p = .03), and won more games (p = .04) when traveling fewer miles away from their home city. We also found that fewer consecutive games played away were related to significantly more blocks of opponent shots (p = .02). Ultimately, the team shot significantly higher from the field when there were more days in between games (p = .03).

Conclusion

Findings from the present study reveal that certain aspects of team performance on the road appear to be influenced by miles traveled from the college’s home city, consecutive games played away, and days in between games. Results could be applied beyond the current context, whereby college basketball teams could utilize such findings to mitigate the impact of travel on athletes.

Support (if any)

None
301 Evaluation of Fatigue and Healthy Lifestyle Practices among New York State Law Enforcement Professionals
Authors: Endee Lisa , Rozensky Russell , Smith Stephen
Published: May 2021

Introduction

An important risk factor for drowsy driving is shift work, and law enforcement, an occupation known for its atypical work schedules, is a highly vulnerable occupation. A connection between fatigue and unintentional injuries among police officers has been observed (Vila, 2006), but data supporting the connection is limited. Understanding how sleep and lifestyle practices impact this population’s driving performance and job safety is critical to officer safety.

Methods

An online survey was disseminated to New York State law enforcement agencies by the Governor’s Traffic Safety Committee to assess sleep health and lifestyle practices among law enforcement personnel. Statistical analysis included data cleaning, basic and advanced statistical testing.

Results

7,366 survey invitations were distributed, 1,171 were returned (15.9% response rate), and after data cleaning, 1,038 surveys were included in the analysis. Respondents reported from various state, county, and local agencies, holding titles from Police Officer to Senior Management. More than 30% of officers reported driving 5 hours or more during their shift, with 12% driving greater than 7 hours. 65% of respondents reported having experienced drowsy driving. Although, 34% reported never having received education about drowsy driving. On work days, only 40% of respondents obtain 7 hours of sleep or more. On days off, 23.6% reported sleeping 6 hours or less. Work, stress, and family responsibilities were reported as having a significant impact on sleep. Almost 87% reported at least one medical issue. Daytime sleepiness (47.4%), fatigue (42.6%), and poor memory (26.8%) were reported daily. Only 23.8% and 29.3% of respondents received education on sleep or heart health, respectively. The majority (81.7%) reported they would consider education in a variety of health-related programs.

Conclusion

Our findings indicate that poor sleep (60%), high stress (22.7%), and anxiety (16.8%) are a concern amongst officers. Poor cardiovascular health was also noted, based on reports of obesity (34.1%), high blood pressure (23.5%), and high cholesterol (22.4%). This research supports the need for prioritizing health education programs within law enforcement agencies.

Support (if any)

Funded by The National Highway Traffic Safety Administration with a grant from The New York State Governor’s Traffic Safety Committee.
318 Area Deprivation and Sleep Health among White, Black, and Hispanic/Latina Women
Authors: Gaston Symielle , Lawrence Kaitlyn , Sandler Dale , Jackson Chandra
Published: May 2021

Introduction

Although neighborhood environments have been shown to affect sleep health, few studies have directly measured multiple indicators of both neighborhood deprivation and sleep while considering modification by race/ethnicity.

Methods

Among 49,833 eligible U.S. women enrolled in the Sister Study from 2003 to 2009, we investigated associations between neighborhood deprivation (e.g., percentage of residents unemployed, household crowding) and multiple sleep dimensions. Participants’ addresses were linked to U.S. census block group level Area Deprivation Index rankings (range: 1–100) for the year 2000, and participant rankings were divided into quintiles where the highest quintile represented the highest deprivation level. Participants self-reported habitual sleep duration, sleep debt, frequent napping, and insomnia symptoms. Adjusting for sociodemographic and clinical characteristics, we used Poisson regression with robust variance to estimate prevalence ratios (PRs) and 95% confidence intervals (CIs) for sleep dimensions among participants within quintiles (Qs) 2–5 vs. Q1. Interaction terms were used to assess modification by race/ethnicity.

Results

Mean age ± standard deviation was 55 ± 9 years. Women with higher neighborhood deprivation were more likely to self-identify as a racial/ethnic minority and had higher unadjusted prevalence of poor sleep dimensions. After adjustment, higher ADI was positively associated with very short sleep (≤5 hours), and race/ethnicity was a modifier (e.g., race-stratified results for Q5 vs. Q1:PRWhite=1.31 [95% CI: 1.14–1.51], PRBlack=0.91 [0.71–1.18], PRHispanic/Latina= 1.17 [0.68–2.04], p-interaction <0.05). Although race/ethnicity did not modify remaining associations, women with higher neighborhood deprivation also had a higher prevalence of sleep debt, frequent napping, and insomnia symptoms. When compared to White women with the lowest neighborhood deprivation, Black women across all deprivation levels and Hispanic/Latina women in Q2-Q5 were substantially more likely to report each poor sleep dimension (PR range: 1.21 to 5.01).

Conclusion

A multidimensional measure of neighborhood deprivation was associated with poor sleep and sleep disparities among a diverse cohort of U.S. women.

Support (if any):
340 Improving maternal sleep via cognitive behavioral intervention: A randomised controlled trial from pregnancy to 2 years postpartum
Authors: Bei Bei , Pinnington Donna , Quin Nina , Shen Lin , Blumfield Michelle , Wiley Joshua , Drummond Sean , Newman Louise , Manber Rachel
Published: May 2021

Introduction

Maternal sleep disturbance is common during pregnancy and postpartum periods. This study evaluated the feasibility and efficacy of a scalable cognitive behavioural therapy (CBT) sleep intervention tailored for these periods.

Methods

This is a two-arm, parallel-group, single-blind, superiority randomised controlled trial. Nulliparous women without major medical/psychiatric conditions were randomised 1:1 to CBT or active control of equal frequency/duration. All participants received a 1-hr telephone session and automated multimedia emails from the 3rd trimester until 6 months postpartum. Outcomes were assessed with validated instruments at gestation weeks 30 (baseline) and 35 (pregnancy endpoint), and postpartum months 1.5, 3, 6 (postpartum endpoint), 12, and 24.

Results

163 eligible participants (age M +/- SD = 33.35 +/- 3.42) were randomised. The CBT intervention was well accepted, with no reported adverse effect. Intention-to-treat analyses showed that compared to active control, receiving CBT was associated with lower insomnia severity and sleep disturbance (two primary outcomes), and lower sleep-related impairment at the pregnancy endpoint (p-values ≤ .001), as well as at 24 months postpartum (p ranges .012-.052). Group differences across the first postpartum year were nonsignificant. Women with elevated insomnia symptoms at baseline benefitted substantially more from CBT (vs control), including having significantly lower insomnia symptoms throughout the first postpartum year. Group differences in symptoms of depression or anxiety were nonsignificant.

Conclusion

A scalable CBT sleep intervention is efficacious in buffering against sleep disturbance during pregnancy, with long-term benefits to maternal sleep, especially for women with sleep complaints during pregnancy. The intervention holds promise for implementation into routine perinatal care.

Support (if any)

Data collection was supported by Rob Pierce Grant-in-Aid and Helen Bearpark Scholarship from Australasian Sleep Association, Strategic Grant Scheme from Monash University, and the Royal Women’s Hospital Foundation. Intervention materials were adapted from those developed via a National Institute of Health R01 grant (NR013662). Bei (APP1140299) and Wiley (APP1178487) are supported by National Health and Medical Research Council Fellowships, and Pinnington, Quin, Shen by Australian Postgraduate Awards by Department of Education and Training. The funder of the study had no role in study design, data collection, data analysis, data interpretation, or writing of the report.
358 Daridorexant Improves Sleep in Patients with Mild/Moderate Obstructive Sleep Apnea
Authors: Boof Marie-Laure , Fietze Ingo , Lederer Katharina , Guern Anne-Sophie , Lemoine Vincent , Ufer Mike , Dingemanse Jasper
Published: May 2021

Introduction

Daridorexant is a dual orexin receptor antagonist developed for the treatment of insomnia. The effect of the highest phase-3 dose of 50 mg daridorexant on nighttime respiratory function was evaluated in patients with mild/moderate obstructive sleep apnea (OSA). This study showed that repeated doses of daridorexant had no clinically meaningful effect on the apnea-hypopnea index (AHI) or on peripheral oxygen saturation. In the same study, the effect on objective sleep parameters was also explored by polysomnography (PSG).

Methods

In this randomized, double-blind, placebo-controlled, two-period, crossover study, daridorexant or placebo was administered in each period once daily for 5 consecutive nights to 28 patients. Treatment difference (daridorexant – placebo) for total sleep time (TST), latency to persistent sleep (LPS), and wake after sleep onset (WASO) was analyzed for Night 5 using linear mixed-effects modeling. In addition, sleep was further explored based on sleep duration during each hour of PSG recording, duration of the different sleep phases (rapid eye movement [REM], non-REM [including N1 to N3 sleep stages]), as well as number and mean/longest duration of awakenings.

Results

Of 28 patients enrolled, 25 completed the study and were included in the analysis (n=15/10 with mild/moderate OSA; mean [standard deviation] AHI: 16.3 [8.2] events/h). One patient had mild insomnia symptoms at baseline. Compared to placebo, daridorexant prolonged mean TST by 38.8 min (90% confidence interval: 19.7–57.9), shortened mean LPS by 17.2 min (-35.5–1.02), and reduced mean WASO by 31.0 min (-47.3 to 14.7). Sleep architecture was maintained as no treatment differences in the duration of the evaluated sleep stages were observed when normalized to TST. Sleep duration was prolonged in the second part of the night. mean and longest duration of awakenings were decreased by a mean (90% CI) of 2.0 min (-3.1 to 0.9) and 16.3 min (-24.1 to -8.6), respectively, without treatment difference for the total number of awakenings.

Conclusion

Daridorexant improved objective sleep parameters in patients with mild to moderate OSA without modifying sleep architecture.

Support (if any)

Funded by Idorsia Pharmaceuticals Ltd.
360 Efficacy of CBT-I and its Components on Health-Related Quality of Life Outcomes in Older Adults
Authors: Showen Kelly , O’Hora Kathleen , Hernandez Beatriz , Lazzeroni Laura , Zeitzer Jamie , Friedman Leah , Posner Donn , Kushida Clete , Yesavage Jerome , Goldstein-Piekarski Andrea
Published: May 2021

Introduction

Insomnia affects 30–48% of older adults and impairs health-related quality of life (HRQoL). Numerous studies report Cognitive Behavioral Therapy (CBT-I) as an effective non-pharmacological treatment for insomnia symptoms, with few examining the impact of CBT-I on mental and physical aspects of HRQoL. While limited research suggests that CBT-I leads to improvements in HRQoL, the impact of the cognitive versus behavioral components of CBT-I on HRQoL is unknown.

Methods

128 older adults with insomnia (mean age=69, 66% female, 19% minority) were randomized to receive cognitive therapy (CT), behavior therapy (BT), or CBT-I. The Short Form (36) Health Survey (SF-36) was collected at baseline, post-treatment and six-month follow-up. Split-plot linear mixed models with age and sex as covariates to assess within and between subject changes were used to test intervention, time, and interaction effects on the mental health and physical well-being domains of HRQoL. Significance for all effects was defined as p < 0.05. The effect size (d) was calculated by dividing the difference between means by the root-mean-squared error of the mixed effects model.

Results

The mental health-related QoL improved over time independent of treatment (Main effect of time: F(2, 202) = 6.51, p < 0.002). The interaction failed to reach significance (Interaction: F(4, 202) = 1.19, p = .31). Simple effects revealed significant improvements among CBT-I participants at six months (p = .02, d = .53) and CT participants at post-treatment (p = .00, d = .79) and six months (p = .03, d = .66), but not among BT participants for either time point (p = .32, d = .24; p = .16, d = .35). Treatment did not improve physical health-related QoL over time (F(2, 202) = 1.01, p = .37) nor was there a significant interaction (F(4, 202) = .46, p = .76).

Conclusion

These findings suggest that CBT-I, particularly the CT component, may be effective in improving mental health-related QoL outcomes for older adults with insomnia. In contrast, neither CBT-I nor its component treatments were effective in improving physical health-related QoL.

Support (if any)

NIMHR01MH101468-01; Mental Illness Research, Education, and Clinical Center (MIRECC) at the VAPAHCS
362 Efficacy of Sleep hygiene advices for individuals with poor sleep quality
Authors: Johnson Saumy , Al Abdulkareem Dr Sami
Published: May 2021

Introduction

Though sleep hygiene practice is a promising approach to individuals with poor sleep quality, less research has been done in different ethnic population regarding the effect of sleep hygiene in individuals with poor sleep quality. Aim: To investigate the efficacy of sleep hygiene among individuals with poor sleep quality

Methods

Methodology: This was a prospective study of 250 participants from different ethnic populations using the Pittsburgh Sleep Quality Index (PSQI). Sleep hygiene advices were given online to the individuals with poor sleep quality (PSQI > 5). Post- test of PSQI score was done after 8 weeks following the Sleep hygiene practices. Survey was done online through google forms and the score was calculated and the level pf sleep quality was sent to the participants (good or poor). A cut of value of PSQI 5 was taken in to consideration. .Questionnaire was sent to participants through snowball sampling.

Results

Results There were 250 participants in this study and the sleep quality index was found to be significantly different (p<0.001) between pre- and post-intervention (Sleep hygiene advice). Age was 30.21±10.70 (mean ± SD) years and there were 157 (63%) females and 93 (37%) males. There were participants from 16 countries, majority responses from India, Saudi and Philippines. PSQI was 8.58 ± 2.49 before the sleep hygiene advice and 5.74± 1.86 post sleep hygiene practice. There was a significant improvement in the sleep quality. Significant correlation was seen between global PSQI score and the 7 components of the PSQI scoring.

Conclusion: Conclusion

Sleep hygiene can help in improving the sleep quality of individuals with poor sleep quality

Support (if any):
368 Durability of Tx Response to Zolpidem using a Partial Reinforcement Regimen: Does this strategy require contingent reinforcement?
Authors: Perlis Michael , Morales Knashawn , Vargas Ivan , Muench Alexandria , Seewald Mark , D’Antonio Breanna , Grandner Michael
Published: May 2021

Introduction

In 2015, partial reinforcement (PR) was assessed as an alternative approach to maintenance therapy with zolpidem. The method being: once a treatment response is obtained over the course of 1-month’s Tx with QHS dosing (Phase-1), Tx response can maintained over time with a PR regimen (Phase-2 [nightly pill/capsule use with 50% of capsules having medication and 50% having only inert filler]). In that study, it was assumed that Phase1 QHS dosing was required 1) to maximize treatment responding and 2) for the conditioning of pharmacologic responses to the medication vehicle (capsule). In the present study, these assumptions were tested by including both QHS and PR arms into Phase-1.

Methods

In Phase-1 (1 month), subjects were randomized to the QHS or PRS conditions (2QHS:1PRS). In Phase-2 (3 months), the PRS group continued forward without a change in the treatment regimen (variable dose [VD-VD]) and the QHS group was re-randomized to either continued QHS Tx (full dose [FD-FD]) or to PRS Tx [FD-VD]). Both study phases were evaluated for treatment responses rates and for average change in TWT (SL+WASO+EMA).

Results

55 subjects (age 61.2+/-8.1, 64% female, & 73% white) were enrolled into Phase-1; 39 were randomized to the QHS condition and 16 to the PRS condition. In Phase-1, 77% (QHS) and 50% (PRS) exhibited treatment responses (p=0.09) where the average change in TWT was similar by group (QHS was -43min [CI -76,-9] and PRS was -76min [CI -138,-14];p=0.35). In Phase-2, 73% (FD-FD), 57% (FD-VD), and 88% (VD-VD) exhibited continued treatment responses (p=0.22) where the average improvement of TWT continued with FD-FD and remained stable for FD-VD and VD-VD (p<0.01).

Conclusion

These data, while preliminary, suggest that QHS (vs. PRS) dosing produces more treatment responders and similar initial effects on sleep continuity during Phase-1, comparable maintenance of treatment response over time, and continued improvement on sleep continuity during Phase-2. These results suggest that partial reinforcement can maintain effects but cannot allow for the additional clinical gains afforded by continuous treatment. Given this, it may be the case that the partial reinforcement technique could be improved upon by extending phase from 1 to 2–4 months.

Support (if any):
372 Sleep Hygiene Compliance and Sleep in Young Adult Drinkers with Insomnia: A Daily Analysis
Authors: Miller Mary Beth , Curtis Ashley , Hall Nicole , Everson Adam , Park Chan Jeong , Martinez Leticia , Freeman Lindsey , McCrae Christina S
Published: May 2021

Introduction

Empirical evidence linking sleep hygiene practices to subsequent sleep parameters – and the extent to which those compare to evidence-based practices such as stimulus control – is limited. This study examined the daily impact of recommendation compliance on sleep in a sample of young adult drinkers with insomnia.

Methods

Young adults (18-30y; N=56, 75% female) who met diagnostic criteria for insomnia and reported past-month binge drinking wore wrist actigraphy and completed online sleep diaries for 7+ days (492 reports). Diaries assessed compliance with nine sleep hygiene recommendations: to limit naps; limit caffeine; avoid caffeine after 12p; avoid tobacco, alcohol, vigorous exercise, and heavy meals within 2 hours of bedtime; avoid bright light within 30 minutes of bedtime; and utilize a bedtime routine. If participants reported wake after sleep onset, diaries also assessed if they had gotten out of bed and returned to bed only when sleepy (partial stimulus control instructions). Multilevel models examined three outcomes: sleep quality, self-reported sleep efficiency, and actigraphy-measured sleep efficiency (α=.05/3≤.017). Covariates included gender; college enrollment; weekday versus weekend; and between-person differences in insomnia severity, hazardous drinking, and average compliance,

Results

Participants self-reported better sleep efficiency on days that they avoided naps (B=3.64, p=.004; 95% CI=1.20, 6.08). They also self-reported better sleep quality (B=0.40, p<.001; 95% CI=0.19, 0.60) and sleep efficiency (B=3.94, p<.001; 95% CI=1.76; 6.12) on days that they followed stimulus control. Surprisingly, they reported worse sleep quality (B=-0.28, p=.017; 95% CI=-0.51, -0.05) and sleep efficiency (B=-3.74, p=.002; 95% CI=-6.08, -1.40) on days that they avoided alcohol use before bedtime. No variables were significantly associated with actigraphy-based sleep efficiency. At the between-person level, participants reporting more at-risk drinking reported worse sleep quality (B=-0.04, p=.017; 95% CI=-0.08, -0.01).

Conclusion

Data provide empirical support for recommendations that young adult drinkers with insomnia avoid naps and get out of bed during nighttime awakenings. Although heavier drinkers reported worse sleep quality than lighter drinkers, they also reported better subjective (but not objective) sleep on nights they drank close to bedtime. We speculate that this is due to later bedtimes on heavy-drinking nights.

Support (if any)

University of Missouri Research Board (PI Miller)
379 Do Depressive Symptoms Mediate the Association Between Insomnia and Physical Activity?
Authors: Walker Jamie , Campbell Rebecca , Vargas Ivan
Published: May 2021

Introduction

Insomnia and depression are highly comorbid and have been shown to be independently associated with lower levels of physical activity. It is not clear, however, if being less physically active is a risk factor for or consequence of depression and insomnia. The factors that explain the associations between insomnia, depression, and physical activity are likely complex and overlapping. For example, insomnia may predict inactivity by impacting one’s energy levels, leaving them too tired to exercise. Insomnia may also interfere with one’s motivation to exercise due to low mood, as insomnia is associated with the development of depressive symptoms. The purpose of the present study was to explore whether depression mediated the link between insomnia and low levels of physical activity.

Methods

A national online survey was conducted from April-June 2020. Participants completed surveys to assess demographics, mood, sleep, and physical activity. Depressive symptoms were estimated with the Center for Epidemiologic Studies Depression Scale (CES-D). Insomnia symptoms were estimated with the Insomnia Severity Index (ISI). Physical activity levels were estimated with the International Physical Activity Questionnaire (IPAQ). Analyses were conducted using multiple linear regression, with separate models for depression, insomnia, and the combination of the two, on levels of physical activity.

Results

3,952 adults (Mage = 46.9 years) completed the survey. According to the unadjusted models, greater insomnia symptoms were associated with greater depressive symptoms (b = 0.4523, SE = 0.019593, p < .001), and lower levels of physical activity (b = -38.741, SE = 18.236, p = 0.0337). The relationship between insomnia and physical activity was no longer significant, however, when controlling for depression (b = -6.140, SE = 19.274, p = 0.75). According to the mediation analyses, there was an indirect effect of insomnia on physical activity that was explained by differences in depressive symptoms (Sobel Test = -4.895, SE = 6.518, p < .001).

Conclusion

Our findings support previous research indicating associations between symptoms of insomnia and depression and physical activity. Future research should examine if these same results hold using a longitudinal design.

Support (if any)

Vargas: K23HL141581