Effects of a 1-hour per night week-long sleep extension in college students on cardiometabolic parameters, hydration status, and physical activity: A pilot study.

OBJECTIVES: Short sleep duration is associated with poor physical health in college students. Few studies examine the effects of sleep extension on physical health in this population, who are susceptible to sleep loss. We examined health effects of a 1-week, 1-hour nightly sleep extension in college students. METHODS: Twelve healthy undergraduate college students (83% female; age 20.2 ± 1.5years) completed a study consisting of sleeping typically for 1week ("Habitual"), then extending sleep by ≥1 hour/night during the second week ("Extension"). Sleep and physical activity actigraphy were collected throughout. Following each week, participants completed cardiometabolic assessments including a meal response and provided a urine sample for markers of hydration. RESULTS: In Extension compared to Habitual, average sleep duration increased (mean change±SEM, +42.6 ± 15.1 minutes; p = .005), while subjective sleepiness (-1.8 ± 0.8 units; p = .040), systolic blood pressure (-6.6 ± 2.8 mmHg; p = .037), postprandial glucose area under the curve (-26.5 ± 10.2 mg/dL × h; p = .025) and time to baseline (-83.0 ± 46.4 minutes; p = .031) after the meal response, sedentary time (-44.3 ± 15.7 minutes; p = .018), and percentage of wake in moderate-to-vigorous activity (-0.89% ± 0.35%; p = .030) decreased. Participants who increased average sleep duration by ≥20 minutes (n = 9) were better hydrated according to urine osmolality (-187.0 ± 68.4 mOsm/kg; p = .026) and specific gravity (-0.01 ± 0.002 g/mL; p = .012) and had reduced odds of dehydration according to urine osmolality (≥800 mOsm/kg; -67%; OR=0.03; p = .035). CONCLUSIONS: This pilot study's findings suggest that sleep extension may improve cardiometabolic functioning and hydration, and alter sedentary behavior and physical activity, in college students. Sleep extension may be employed to improve multiple aspects of health in this sleep-deprived population.

Performance of an open machine learning model to classify sleep/wake from actigraphy across ∼24-hour intervals without knowledge of rest timing.

GOAL AND AIMS: Commonly used actigraphy algorithms are designed to operate within a known in-bed interval. However, in free-living scenarios this interval is often unknown. We trained and evaluated a sleep/wake classifier that operates on actigraphy over ∼24-hour intervals, without knowledge of in-bed timing. FOCUS TECHNOLOGY: Actigraphy counts from ActiWatch Spectrum devices. REFERENCE TECHNOLOGY: Sleep staging derived from polysomnography, supplemented by observation of wakefulness outside of the staged interval. Classifications from the Oakley actigraphy algorithm were additionally used as performance reference. SAMPLE: Adults, sleeping in either a home or laboratory environment. DESIGN: Machine learning was used to train and evaluate a sleep/wake classifier in a supervised learning paradigm. The classifier is a temporal convolutional network, a form of deep neural network. CORE ANALYTICS: Performance was evaluated across ∼24 hours, and additionally restricted to only in-bed intervals, both in terms of epoch-by-epoch performance, and the discrepancy of summary statistics within the intervals. ADDITIONAL ANALYTICS AND EXPLORATORY ANALYSES: Performance of the trained model applied to the Multi-Ethnic Study of Atherosclerosis dataset. CORE OUTCOMES: Over ∼24 hours, the temporal convolutional network classifier produced the same or better performance as the Oakley classifier on all measures tested. When restricting analysis to the in-bed interval, the temporal convolutional network remained favorable on several metrics. IMPORTANT SUPPLEMENTAL OUTCOMES: Performance decreased on the Multi-Ethnic Study of Atherosclerosis dataset, especially when restricting analysis to the in-bed interval. CORE CONCLUSION: A classifier using data labeled over ∼24-hour intervals allows for the continuous classification of sleep/wake without knowledge of in-bed intervals. Further development should focus on improving generalization performance.

Why so slangry (sleepy and angry)? Shorter sleep duration and lower sleep efficiency predict worse next-day mood in adolescents.

PURPOSE: The goal of this study was to evaluate the relationships of actigraphic nighttime sleep duration and quality with next-day mood among urban adolescents using a micro-longitudinal design. METHODS: A subsample (N = 525) of participants from the Fragile Families & Child Wellbeing Study (mean age: 15.4 years; 53% female; 42% Black non-Hispanic, 24% Hispanic/Latino, 19% White non-Hispanic) in the United States between 2014 and 2016 concurrently wore a wrist actigraphic sleep monitor and rated their daily mood in electronic diaries for about 1 week. Multilevel models tested the within-person temporal associations of nightly sleep duration and sleep maintenance efficiency with next-day reports of happiness, anger, and loneliness. The models also tested the between-person associations of sleep variables and mood. Models adjusted for sociodemographic and household characteristics, weekend, and school year. RESULTS: After nights when adolescents obtained longer sleep duration than their usual, they reported lower ratings of anger (B = -.03, p < .01) the next day. After nights when adolescents had higher sleep maintenance efficiency than their usual, they reported higher ratings of happiness (B = .02, p < .01) the next day. Adolescents who had longer average sleep duration reported lower ratings of anger (B = -.08, p < .01) and loneliness (B = -.08, p < .01) compared to others. There was no within-person association of sleep duration or efficiency with loneliness. Sleep duration was not associated with happiness between adolescents, and sleep maintenance efficiency was not associated with any mood measure between adolescents. CONCLUSIONS: Improvements to nightly sleep may help increase happiness and decrease anger the following day in adolescents. Promoting sleep health is recommended to improve mood.

Neighborhood Disadvantage Is Associated with Lower Quality Sleep and More Variability in Sleep Duration among Urban Adolescents.

Differential social and contextual environments may contribute to adolescent sleep disparities, yet most prior studies are limited to self-reported sleep data and have not been conducted at a national level, limiting the variation in neighborhood contexts. This study examined the association between neighborhood disadvantage and objective measures of adolescent sleep. A racially and geographically diverse sample of American adolescents (N = 682) wore wrist-worn accelerometers, "actigraphs," for ≥ 5 nights. Neighborhood disadvantage was calculated using a standardized index of neighborhood characteristics (proportion of female-headed households, public assistance recipients, households in poverty, adults without high school degrees, and unemployed). Adolescents in more disadvantaged neighborhoods spent more time awake after falling asleep (4.0 min/night, p < .05), a greater percentage of nighttime sleep intervals awake (1%, p < .01), and had less consistent sleep duration (11.6% higher standard deviation, p < .05). Sleep duration and timing did not differ across neighborhood groups. These findings demonstrate that adolescents who live in more disadvantaged neighborhoods have lower quality, less consistent sleep.

Interindividual differences in attentional vulnerability moderate cognitive performance during sleep restriction and subsequent recovery in healthy young men.

We investigated whether interindividual attentional vulnerability moderates performance on domain-specific cognitive tasks during sleep restriction (SR) and subsequent recovery sleep. Fifteen healthy men (M ± SD, 22.3 ± 2.8 years) were exposed to three nights of baseline, five nights of 5-h time in bed SR, and two nights of recovery sleep. Participants completed tasks assessing working memory, visuospatial processing, and processing speed approximately every two hours during wake. Analyses examined performance across SR and recovery (linear predictor day or quadratic predictor day2) moderated by attentional vulnerability per participant (difference between mean psychomotor vigilance task lapses after the fifth SR night versus the last baseline night). For significant interactions between day/day2 and vulnerability, we investigated the effect of day/day2 at 1 SD below (less vulnerable level) and above (more vulnerable level) the mean of attentional vulnerability (N = 15 in all analyses). Working memory accuracy and speed on the Fractal 2-Back and visuospatial processing speed and efficiency on the Line Orientation Task improved across the entire study at the less vulnerable level (mean - 1SD) but not the more vulnerable level (mean + 1SD). Therefore, vulnerability to attentional lapses after SR is a marker of susceptibility to working memory and visuospatial processing impairment during SR and subsequent recovery.

Changes in Subjective Motivation and Effort During Sleep Restriction Moderate Interindividual Differences in Attentional Performance in Healthy Young Men.

PURPOSE: The effects of sleep restriction on subjective alertness, motivation, and effort vary among individuals and may explain interindividual differences in attention during sleep restriction. We investigated whether individuals with a greater decrease in subjective alertness or motivation, or a greater increase in subjective effort (versus other participants), demonstrated poorer attention when sleep restricted. PARTICIPANTS AND METHODS: Fifteen healthy men (M±SD, 22.3±2.8 years) completed a study with three nights of 10-hour time in bed (baseline), five nights of 5-hour time in bed (sleep restriction), and two nights of 10-hour time in bed (recovery). Participants completed a 10-minute psychomotor vigilance task (PVT) of sustained attention and rated alertness, motivation, and effort every two hours during wake (range: 3-9 administrations on a given day). Analyses examined performance across the study (first two days excluded) moderated by per-participant change in subjective alertness, motivation, or effort from baseline to sleep restriction. For significant interactions, we investigated the effect of study day2 (day*day) on the outcome at low (mean-1 SD) and high (mean+1 SD) levels of the moderator (N = 15, all analyses). RESULTS: False starts increased across sleep restriction in participants who reported lower (mean-1 SD) but not preserved (mean+1 SD) motivation during sleep restriction. Lapses increased across sleep restriction regardless of change in subjective motivation, with a more pronounced increase in participants who reported lower versus preserved motivation. Lapses increased across sleep restriction in participants who reported higher (mean+1 SD) but not preserved (mean-1 SD) effort during sleep restriction. Change in subjective alertness did not moderate the effects of sleep restriction on attention. CONCLUSION: Vigilance declines during sleep restriction regardless of change in subjective alertness or motivation, but individuals with reduced motivation exhibit poorer inhibition. Individuals with preserved subjective alertness still perform poorly during sleep restriction, while those reporting additional effort demonstrate impaired vigilance.

A randomized trial to decrease risk for diabetes among Cambodian Americans with depression: Intervention development, baseline characteristics and process outcomes.

BACKGROUND: Depression and antidepressant medications are associated with increased risk for type 2 diabetes. It is not known if diabetes can be prevented in the setting of depression. Cambodian Americans have high rates of both depression and diabetes. This paper reports intervention development, experimental design, baseline characteristics, and process outcomes of diabetes prevention interventions for Cambodian Americans with depression, "Diabetes Risk Reduction through Eat, Walk, Sleep and Medication Therapy Management" (DREAM). METHODS: Participants were aged 35-75, Khmer speaking, at high risk for developing diabetes, and met criteria for likely depression by either a) antidepressant medication and/or b) elevated depressive symptoms at two timepoints during a study eligibility period. Treatment arms were: 1) community health educator (CHE) delivered lifestyle intervention called Eat, Walk, Sleep (EWS), 2) EWS plus pharmacist/CHE-delivered medication therapy management (EWS + MTM), and, 3) social services (SS; control). RESULTS: 188 participants were randomized. Treatment fidelity was high (98% checklist adherence) and on a scale from 0 to 3, participants reported high EWS treatment satisfaction (M = 2.9, SD = 0.2), group cohesion (M = 2.9, SD = 0.3), and therapeutic alliance to CHEs (M = 2.9, SD = 0.2) and to pharmacists (2.9, SD = 0.3). Attendance was challenging but highly successful; in EWS, 99% attended ≥ one session and 86% completed ≥ 24 sessions, M = 27.3 (SD = 3.7) sessions. Of those randomized to EWS + MTM, 98% attended at least one MTM session and 77%) completed ≥ 4 sessions. Retention was high, 95% at 12-month and 96% at 15-month assessments. CONCLUSIONS: The interventions were successfully implemented. Lessons learned and suggestions for future trials are offered. ClinicalTrials.gov identifier: NCT02502929.

Effects of sleep extension on sleep duration, sleepiness, and blood pressure in college students.

OBJECTIVES: Sleep is a major lifestyle factor that may change dramatically when students begin college. Sleep duration has been shown to influence cardiometabolic health. We investigated the feasibility of sleep extension in college students to increase actigraphically measured sleep duration and the association of sleep extension with daytime sleepiness and blood pressure. DESIGN: This was a within-participant experimental study. SETTING: The study setting was 14-day at-home study and 3 in-lab visits. PARTICIPANTS: The participants included in this study were healthy undergraduate students (n=53; mean age 20.5 ± 1.1 years; 70% female). INTERVENTION: Participants maintained a habitual sleep schedule during week 1 and then were instructed to extend their sleep duration by at least 1 hour per night for week 2. MEASUREMENTS: Sleep measures included wrist actigraphy and daytime sleepiness assessed by the Epworth Sleepiness Scale (ESS) and by daily diary. Cardiovascular measures included blood pressure (BP) and heart rate (HR). ESS, BP and HR were measured during lab visits on days 7 and 14. Multilevel modeling was used to test the effects of extension on sleep duration, daytime sleepiness, BP and HR. RESULTS: Participants increased sleep duration during week 2 by 43.0 ± 6.2 standard error minutes per night, compared with week 1 (p<.001). Furthermore, 41 of 53 participants (77%) increased their sleep duration by >15 minutes per night (p<.001). Participants reported less daytime sleepiness on weekly ESS (p<.05) and daily log ratings (p<.001) after sleep extension; and systolic BP was significantly reduced by 7.0 ± 3.0 mmHg (p<.05). CONCLUSION: This study demonstrates that substantive sleep extension is feasible in college students and can positively impact their sleep and cardiovascular health.

Four nights of sleep restriction suppress the postprandial lipemic response and decrease satiety.

Chronic sleep restriction, or inadequate sleep, is associated with increased risk of cardiometabolic disease. Laboratory studies demonstrate that sleep restriction causes impaired whole-body insulin sensitivity and glucose disposal. Evidence suggests that inadequate sleep also impairs adipose tissue insulin sensitivity and the NEFA rebound during intravenous glucose tolerance tests, yet no studies have examined the effects of sleep restriction on high-fat meal lipemia. We assessed the effect of 5 h time in bed (TIB) per night for four consecutive nights on postprandial lipemia following a standardized high-fat dinner (HFD). Furthermore, we assessed whether one night of recovery sleep (10 h TIB) was sufficient to restore postprandial metabolism to baseline. We found that postprandial triglyceride (TG) area under the curve was suppressed by sleep restriction (P = 0.01), but returned to baseline values following one night of recovery. Sleep restriction decreased NEFAs throughout the HFD (P = 0.02) and NEFAs remained suppressed in the recovery condition (P = 0.04). Sleep restriction also decreased participant-reported fullness or satiety (P = 0.03), and decreased postprandial interleukin-6 (P < 0.01). Our findings indicate that four nights of 5 h TIB per night impair postprandial lipemia and that one night of recovery sleep may be adequate for recovery of TG metabolism, but not for markers of adipocyte function.

Bidirectional, Daily Temporal Associations between Sleep and Physical Activity in Adolescents.

This study evaluated the daily, temporal associations between sleep and daytime physical activity and sedentary behavior among adolescents from the Fragile Families & Child Wellbeing Study. A sub-sample of the cohort at age 15 (N = 417) wore actigraphy monitors for one week during the school year from which we derived daily minutes in sedentary and moderate-to-vigorous physical activity (MVPA) and nighttime sleep measures. Multilevel models tested temporal associations of nightly sleep onset, offset, duration, and sleep maintenance efficiency, with daily MVPA and sedentary behavior. More MVPA than an individual's average was associated with earlier sleep onset (p < 0.0001), longer duration (p = 0.03), and higher sleep maintenance efficiency (p < 0.0001). On days with more sedentary behavior than an individual's average, sleep onset and offset were delayed (p < 0.0001), duration was shorter (p < 0.0001), and sleep maintenance efficiency was higher (p = 0.0005). Conversely, nights with earlier sleep onset predicted more next-day sedentary behavior (p < 0.0001), and nights with later sleep offset and longer sleep duration were associated with less MVPA (p < 0.0001) and less sedentary time (p < 0.0001, p = 0.004) the next day. These bidirectional associations between sleep and physical activity suggest that promoting MVPA may help to elicit earlier bedtimes, lengthen sleep duration, and increase sleep efficiency, critical for healthy adolescent development.

Two nights of recovery sleep restores the dynamic lipemic response, but not the reduction of insulin sensitivity, induced by five nights of sleep restriction.

Chronic inadequate sleep is associated with increased risk of cardiometabolic diseases. The mechanisms involved are poorly understood but involve changes in insulin sensitivity, including within adipose tissue. The aim of this study was to assess the effects of sleep restriction on nonesterified fatty acid (NEFA) suppression profiles in response to an intravenous glucose tolerance test (IVGTT) and to assess whether 2 nights of recovery sleep (a "weekend") is sufficient to restore metabolic health. We hypothesized that sleep restriction impairs both glucose and lipid metabolism, specifically adipocyte insulin sensitivity, and the dynamic lipemic response of adipocyte NEFA release during an IVGTT. Fifteen healthy men completed an inpatient study of 3 baseline nights (10 h of time in bed/night), followed by 5 nights of 5 h of time in bed/night and 2 recovery nights (10 h of time in bed/night). IVGTTs were performed on the final day of each condition. Reductions in insulin sensitivity without a compensatory change in acute insulin response to glucose were consistent with prior studies (insulin sensitivity P = 0.002; acute insulin response to glucose P = 0.23). The disposition index was suppressed by sleep restriction and did not recover after recovery sleep (P < 0.0001 and P = 0.01, respectively). Fasting NEFAs were not different from baseline in either the restriction or recovery conditions. NEFA rebound was significantly suppressed by sleep restriction (P = 0.01) but returned to baseline values after recovery sleep. Our study indicates that sleep restriction impacts NEFA metabolism and demonstrates that 2 nights of recovery sleep may not be adequate to restore glycemic health.

Later high school start times associated with longer actigraphic sleep duration in adolescents.

Study Objectives: High school start times (SSTs) directly impact adolescents' sleep timing and duration. This study investigated the associations between SSTs and actigraphically-measured 24-hour sleep duration, sleep onset, sleep offset and sleep quality. Methods: This study included 383 adolescents (Mage = 15.5, SDage = 0.6 years) participating in the age 15 wave of the Fragile Families & Child Wellbeing Study, a national birth cohort study sampling from 20 large US cities. Multilevel models used daily observations (N = 1116 school days, Mdays = 2.9, SDdays = 1.4 per adolescent) of sleep and SSTs from concordant daily diary and actigraphy. Results: A diverse range of SSTs were included in our analyses (MSST = 08:08, SDSST = 39 minutes, RangeSST = 06:00-11:05), and are presented in the following categories for ease of interpretation: before 07:30, 07:30-07:59, 08:00-08:29, and 08:30 or later. Adolescents starting school at 08:30 or later exhibited significantly longer actigraphically-assessed 24-hour sleep duration (by 21-34 minutes, p < .05) and later sleep offset (by 32-64 minutes, p < .001) when compared with the adolescents grouped by earlier SSTs. SSTs were also analyzed continuously for comparison with existing literature, and results indicated that every 1-hour delay in SST was significantly associated with 21 minutes longer 24-hour sleep duration (p < .001), 16 minutes later sleep onset (p < .01), and 39 minutes later sleep offset (p < .001). All models controlled for covariates including socioeconomic status. Conclusion: These findings support pediatric and public health expert recommendations for SSTs after 08:30. In our diverse national urban sample, adolescents with SSTs at 08:30 or later, compared with adolescents with earlier SSTs, had significantly longer actigraphy-measured sleep.

Longitudinal associations of childhood bedtime and sleep routines with adolescent body mass index.

Study Objectives: Having a regular, age-appropriate bedtime and sufficient sleep from early childhood may be important for healthy weight in adolescence. This study aimed to (1) identify heterogeneous groups of children by bedtime and sleep routines and (2) test longitudinal associations of childhood bedtime and sleep routine groups with adolescent body mass index (BMI). Methods: We analyzed longitudinal data from the Fragile Families and Child Wellbeing Study, a national birth cohort from 20 US cities (N = 2196). Childhood bedtime and sleep routines were assessed by mothers' reports of their children's presence and timing of bedtimes, adherence to bedtimes, and habitual sleep duration at ages 5 and 9. At age 15, these adolescents reported their height and weight, which were used to calculate BMI z-score. Results: Latent Class Analysis revealed four groups of childhood bedtime and sleep routines: No Bedtime Routine Age 5 (Group 1), No Bedtime Routine Age 9 (Group 2), Borderline Bedtimes Ages 5 and 9 (Group 3), and Age-Appropriate Bedtime and Sleep Routines Ages 5 and 9 (Group 4, reference). Compared with adolescents in the reference group, those in the No Bedtime Routine Age 9 (Group 2) had +0.38 SD greater BMI (95% CI = [0.13 to 0.63]), above the level for overweight (1.02 SD BMI/85th percentile). Associations persisted after adjusting for age 3 BMI and sociodemographic characteristics. Conclusions: Results demonstrate heterogeneity in childhood bedtime routine groups and their associations with adolescent BMI. Future studies should focus on whether childhood sleep behavior interventions promote healthier sleep and weight in later life course stages.

High school start times after 8:30 am are associated with later wake times and longer time in bed among teens in a national urban cohort study.

OBJECTIVES: High school start times are a key contributor to insufficient sleep. This study investigated associations of high school start times with bedtime, wake time, and time in bed among urban teenagers. DESIGN: Daily-diary study nested within the prospective Fragile Families and Child Wellbeing Study. SETTING: Twenty US cities. PARTICIPANTS: Four hundred thirteen teenagers who completed ≥1 daily diary report on a school day. MEASUREMENTS: Participating teens were asked to complete daily diaries for 7 consecutive days. School-day daily diaries (3.8±1.6 entries per person) were used in analyses (N=1555 school days). High school start time, the main predictor, was categorized as 7:00-7:29 am (15%), 7:30-7:59 am (22%), 8:00-8:29 am (35%), and 8:30 am or later (28%). Multilevel modeling examined the associations of school start times with bedtime, wake time, and time in bed. Models adjusted for age, sex, race/ethnicity, household income, caregiver's education, and school type. RESULTS: Teens with the earliest high school start times (7:00-7:29 am) obtained 46 minutes less time in bed on average compared with teens with high school start times at 8:30 am or later (P<.001). Teens exhibited a dose-response relationship between earlier school start times and shorter time in bed, primarily due to earlier wake times (P<.05). Start times after 8:30 am were associated with increased time in bed, extending morning sleep by 27-57 minutes (P<.05) when compared with teens with earlier school start times. CONCLUSION: Later school start times are associated with later wake times in our large, diverse sample. Teens starting school at 8:30 am or later are the only group with an average time in bed permitting 8 hours of sleep, the minimum recommended by expert consensus for health and well-being.