Sleep During Pregnancy: The nuMoM2b Pregnancy and Sleep Duration and Continuity Study

Time-restricted eating (TRE) is a novel dietary intervention targeting weight loss and cardiometabolic risk factors. The impact of TRE on sleep patterns remains under-explored. This was a post hoc analysis of a parallel-arm, controlled feeding trial in 41 adults with obesity and prediabetes/diabetes, randomized to TRE (08:00 am-06:00 pm) or usual eating pattern (UEP; 08:00 am-12:00 am) for 12 weeks. We objectively determined sleep-wake patterns from 7-day wrist actigraphy data obtained at baseline and week 12. From this data, we derived total sleep time (TST) and sleep midpoint over a 24-hour period, sleep onset/offset, and sleep continuity measures. We used paired t-tests or Wilcoxon signed rank tests to compare data between baseline and week 12 within intervention arms and Mann-Whitney U tests or Wilcoxon signed rank tests to compare changes between intervention arms. 38 participants (20 UEP; 18 TRE; 93% of those randomized in the parent trial) with adequate actigraphy data (mean age 59.6 ± 7.3 years, 92% female, 92% Black, mean BMI 36.3 ± 4.7kg/m2) were analyzed. Compared to UEP, TRE increased TST by 55 minutes (p = .03). TRE shifted sleep midpoint to 44 minutes earlier, from 03:24 am to 02:40 am (p = .01), while UEP maintained the same sleep midpoint at 03:15 am. Sleep onset shifted from a median of 12:22 am to 11:52 pm in TRE (p = .03) while it remained stable in UEP (p = .97). There were no differences in sleep offset and sleep continuity within and between intervention arms. TRE increased sleep time and caused earlier sleep onset compared to UEP, revealing how the timing of eating may affect sleep timing and duration. The Time Restricted Intake of Meals Study (TRIM). URL: https://clinicaltrials.gov/study/NCT03527368?tab=history&a=4. NCT03527368.

To describe sleep characteristics of shift workers compared with day workers from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) Sueño ancillary study and test the hypothesis that shift work is associated with shorter sleep duration, worse sleep quality, greater sleep variability, and other sleep/health-related factors. Employed adults (N = 1253, mean age 46.3 years, 36.3% male) from the Sueño study were included. Measures of sleep duration, timing, regularity, and continuity were calculated from 7 days of wrist-activity monitoring. Participants provided information on demographics, employment, work schedule (day, afternoon, night, split, irregular, and rotating), sleepiness, depressive symptoms, medications, caffeine, and alcohol use. Survey linear regression adjusting for age, sex, background, site, number of jobs, and work hours was used. In age and sex-adjusted models, all shift work schedules were associated with delayed sleep timing. Night and irregular schedules were associated with shorter sleep duration, greater napping, and greater variability of sleep. Afternoon and rotating shifts were associated with lower sleep regularity. In fully adjusted models, night and irregular schedules remained associated with shorter sleep duration, later sleep midpoint, and greater variability in sleep measures compared with day schedules. Split schedules were associated with, less time in bed, less sleep fragmentation, and less wake during the sleep period than day schedules. Work schedule significantly affects sleep-wake with substantial differences between day work and other types of schedule. Detailed assessment of work schedule type not just night shift should be considered as an important covariate when examining the association between sleep and health outcomes.

Sleep duration decreases by ∼10 minutes per year throughout adolescence. A circadian phase delayand changes in homeostatic sleep regulation enable adolescents to stay up later. We determine if teens are able to increase sleep duration by advancing bedtime and whether this ability changes with age. A younger cohort of 77 participants ranging in age from 9.9 to 16.2 years were studied annually for 3 years. An older cohort of 67 participants ranging in age from 15.0 to 20.6 years was studied only once. Annually, participants kept each of 3 different time in bed (TIB) schedules (7, 8.5, and 10 hours) for 4 consecutive nights. Participants kept their habitual weekday rise times; TIB was altered by advancing bedtimes. We report polysomnography-measured sleep durations from the fourth night of the TIB schedule. Despite increases in sleep onset latency and wake after sleep onset, sleep duration increased with TIB as bedtime was advanced. Average (SE) sleep duration increased from 402.8 (1.6) minutes with 7 hours to 470.6 (2.1) minutes with 8.5 hours to 527.5 (3.0) minutes with 10 hours TIB. Sleep duration decreased with age (1.55 [0.48] minutes/year), but the TIB effect on sleep duration did not (TIB by age interaction, P = .42). Adolescents can substantially increase sleep duration by advancing bedtime, and this ability does not change between ages 10 and 21 years. Additional research is needed to determine how to translate these findings from experiment-controlled sleep schedules to real-world sleep duration increases.

Introduction Little is known about the factors during total sleep deprivation (TSD) and psychological stress that affect recovery sleep. We determined the relative contributions of cognitive and cortisol measures, which represent distinct domains, as predictors of recovery sleep timing and duration. Methods We conducted a five-day experiment under highly controlled conditions in 32 healthy adults (ages 27-53; 14 females). Salivary cortisol samples were collected during 1) TSD morning (TSD AM; after 25h of TSD) and 2) TSD evening following a modified Trier Social Stress Test, which induced psychological stress (TSD PM; after 34h of TSD). Digit Span Test (DS), Digit Symbol Substitution Test (DSST), and Psychomotor Vigilance Test (PVT) performance data were collected at 0400h, 1130h, and 1730h during TSD and averaged. Wrist actigraphy assessed sleep indices during the first recovery night following TSD (10h time in bed). Multiple linear regression models determined the impact of TSD cognitive and cortisol measures as predictors of recovery sleep timing and duration. The models and independent variables were all significant (p< 0.05). Results Sleep Onset. Each 1-point DS total # correct increase predicted a 0.042h later sleep onset and each 1 µg/dL AM cortisol increase predicted a 0.958h later sleep onset. Sleep Offset. In addition, each 1 PVT lapse increase predicted a 0.031h later sleep offset and each 1 µg/dL PM cortisol increase predicted a 1.205h earlier sleep offset. Sleep Duration. Each 1 PVT lapse increase predicted a 2.153 minute sleep duration increase, and each 1 µg/dL AM cortisol increase predicted an 87.367 minute sleep duration decrease. In addition, each 1-point DSST # correct increase predicted a 1.657 minute sleep duration decrease and each 1 µg/dL PM cortisol increase predicted a 100.535 minute sleep duration decrease. Across models, 35.8%-40.6% of the sleep timing and duration variance was explained, with r ranges between 0.598-0.637. Conclusion Our results elucidate the important roles of cognitive performance and cortisol metrics obtained during sleep loss in influencing recovery sleep timing and duration, suggesting the possibility of intervening on these measures to modify subsequent sleep. Our findings highlight hypothalamic-pituitary-adrenal axis and cognitive measures as biomarkers for recovery sleep health. Support (if any) NASA NNX14AN49G, 80NSSC20K0243 (NG)

Impact of heat exposure on sleep health and its population vulnerability in the United States

Later sleep timing is associated with an increased risk of preterm birth in nulliparous women

We aimed to investigate the effect of increased sleep pressure and shortened sleep duration on subjective sleep perception in relation to electroencephalographic sleep measures. We analyzed the data from a study in which 14 healthy male volunteers had completed a baseline assessment with 8hr time in bed, a sleep deprivation (40hr of wakefulness) and a sleep restriction protocol with 5hr time in bed during 7 nights. In this work, we assessed perception index, derived through dividing the subjectively perceived total sleep time, wake after sleep onset and sleep latency duration by the objectively measured one at each condition. We found that total sleep time was subjectively underestimated at baseline and shifted towards overestimation during sleep restriction and after deprivation. This change in accuracy of subjective estimates was not associated with any changes in sleep architecture or sleep depth. Wake after sleep onset was significantly underestimated only during sleep restriction. Sleep latency was always overestimated subjectively without any significant change in this misperception across conditions. When comparing accuracy of subjective and actimetry estimates, subjective estimates regarding total sleep time and wake after sleep onset deviated less from electroencephalography derived measures during sleep restriction and after deprivation. We conclude that self-assessments and actimetry data of patients with chronic sleep restriction should be interpreted cautiously. The subjectively decreased perception of wake after sleep onset could lead to overestimated sleep efficiency in such individuals, whereas the underestimation of sleep time and overestimation of wake after sleep onset by actimetry could lead to further underestimated sleep duration.

Introduction Characterizing habitual sleep patterns in children and adolescents is challenging due to the well-documented variability inherent in standard assessment methods, which often yield poor to moderate internal consistency. This quality control study aimed to evaluate the internal consistency of habitual sleep assessment methods (questionnaire, sleep diary, and accelerometry) using data from the Interacting Mechanisms of SLeep and Endurance Exercise in Pediatrics (iSLEEP) study, an ancillary project of the UCI pediatric Molecular Transducers of Physical Activity Consortium (MoTrPAC). Additionally, it examined whether incorporating sleep/wake pattern parameters into sleep continuity measures improve internal consistency. Methods Seventy-seven healthy children and adolescents (Mage=15.0±2.3 years, 62.3%f) completed the iSLEEP MoTrPAC ancillary study including questionnaire [School Sleep Habit Survey (SSHS)] and 7-14 days of accelerometry (Actiwatch) with daily sleep diaries. Sleep continuity variables [i.e., sleep onset/offset times, midsleep time, total sleep time (TST), and sleep efficiency (SE)], were derived from SSHS, diary, and accelerometry (using standardized scoring approaches that include the diary). Behavioral sleep/wake patterns were estimated using UP/DOWN times/slopes, deriving from Shape Language Modeling (SLM) using minute-by-minute activity counts. Internal consistency (Cronbach’s alpha) and reliability coefficients were computed. Factor analyses identified latent structures which were correlated between measurement approaches, and the contribution of sleep/wake pattern correlation metrics to traditional sleep continuity measures from accelerometry was evaluated. Results Sleep continuity measures from diaries (α=0.63) and accelerometry (α=0.65) demonstrated similar moderate internal consistency, while questionnaire showed expected poor consistency (α=0.21). Behavioral sleep/wake pattern variables (UP/DOWN times/slopes) showed good and acceptable internal consistency (α=0.78). Factor analyses identified two key components solutions for sleep continuity measures in diaries and accelerometry: Factor 1: sleep timing (onset, offset, midsleep; p’s< 0.001) and Factor 2: TST and SE (p’s< 0.001). Factors were significantly correlated between the measurement approaches (timing factor, r=0.87; TST/SE factor, r=0.50, p’s< 0.001). Integrating behavioral sleep/wake pattern variables with the traditional accelerometry-derived sleep continuity measures resulted in strong internal consistency (α=0.83). Conclusion Diary and accelerometry exhibited comparable internal structure and validity of habitual sleep pattern characterization in children and adolescents. Incorporating behavioral sleep/wake activity patterns alongside traditional sleep continuity measures enhances validity measures. Support (if any) Support: R01 HL153807, U01 AR071158, PERC Systems Biology Program.

Longitudinal studies of sleep during normal pregnancy and post-partum are rare, and interpretation of the findings is often hampered by methodological issues. Consequentially, there is still limited information on what constitutes normal sleep quality and quantity across pregnancy and early post-partum, for both nulliparous and multiparous women. To quantify the change and variability in sleep duration and quality across pregnancy and post-partum for healthy nulliparous and multiparous women. Nineteen women (eight nulliparous and 11 multiparous) wore an actigraph and completed a sleep diary to objectively measure sleep for seven nights during the second trimester, one week prior to delivery, and at one and six weeks post-partum. Mixed model analysis of variance and logistic regression were used to investigate changes in sleep across this timeframe. The largest changes in sleep occurred in the first week post-partum (1.5 h less sleep than during pregnancy, three times more sleep episodes in 24 h, 70% of women regularly napping during the day, and greatest day-to-day variability in sleep). Compared to multiparas, nulliparas generally had less efficient sleep, spent more time in bed and had greater wake after sleep onset in the second trimester, and spent less time in bed and had fewer sleep episodes a day at one week post-partum. These changes should be used to inform women about the extent of change in sleep, particularly early post-partum, and to help health-care providers identify women experiencing severe sleep loss and disruption and discuss possible coping strategies with them.

Sleep is essential for recovery in hospitalized patients, yet frequent disruptions from medical care make rest difficult. Most prior efforts have focused on environmental modifications, often overlooking patients' role in advocating for their sleep. This study evaluated the effectiveness of the Inpatient Sleep Loss: Educating and Empowering Patients (I-SLEEP) intervention in improving sleep duration and reducing medical care disruptions among hospitalized patients. In this single-center randomized controlled trial (NCT04151251), general medicine patients at the University of Chicago were randomized to either I-SLEEP (sleep education, advocacy questions, and a sleep kit) or standard care (sleep kit alone) between July 2019 and March 2023. The primary outcome was patient-reported sleep duration. Secondary outcomes included actigraphy-measured sleep duration and continuity (efficiency and wake after sleep onset), as well as patient-reported sleep disruptions. Mixed effects models adjusted for covariates were used for analysis. A total of 194 participants were enrolled. There were no significant differences in demographic characteristics between groups. Sleep duration and continuity did not differ significantly between groups. However, patients receiving I-SLEEP reported fewer disruptions from vital sign monitoring (63% vs. 75%, p = .004), medication administration (49% vs. 61%, p = .003), and laboratory draws (57% vs. 68%, p = .009). These findings remained significant after adjusting for covariates. I-SLEEP did not increase sleep duration or continuity but reduced medical care disruptions. These findings suggest that patient education and empowerment may be effective strategies for reducing preventable care-related sleep disruptions in hospitals. Further research should examine implementation at scale and potential long-term benefits.

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Only few epidemiologic studies examined sleep characteristics in relation to dietary behaviour. Our aim was to analyse associations of sleep duration, midpoint of sleep and sleep quality with dietary intake among the Bavarian population. Within the cross-sectional Bavarian Food Consumption Survey II, 1050 subjects aged 13-81 years were recruited. Dietary intake was assessed with three 24-h dietary recalls by telephone (EPIC-Soft). In our study, 814 participants aged 18 years or older, who completed at least two 24-h dietary recalls and who had complete and plausible information on sleep characteristics were analysed. Dietary intake was described by the consumption of main food groups, energy-proving nutrients and energy intake. Sleep was measured by the Pittsburgh Sleep Quality Index Questionnaire, from which categories of self-reported usual sleep duration in half-h-steps per night, midpoint of sleep and overall sleep quality were derived. Sleep duration was associated with intake of non-alcoholic beverages (P<0.01), carbonated beverages (P=0.04), water (P=0.04) and coffee/black tea (P=0.01) with higher intake among short duration sleepers. No association was found between the consumption of other main food groups, energy-proving nutrients or total daily energy intake and sleep duration. Midpoint of sleep was associated with intake of carbonated beverages (P=0.02, highest intake among subjects with early midpoint of sleep). No association between sleep quality and dietary intake was detected. Our findings demonstrate only specific associations between sleep characteristics and dietary intake, and mainly sleep duration was associated with beverage intake.

Introduction Implementation of electronic health records (EHR) across healthcare systems linking clinical to survey data has enabled systematic assessments of longitudinal relationships between sleep traits and diseases classified by PheWAS codes where ICD-9/10 codes are collapsed to categories based on clinical similarity. In the Partners Biobank, a hospital-based virtual cohort from Mass General Brigham in greater Boston, MA, we aimed to assess associations between sleep traits and incident diseases. Methods Self-reported weekday/weekend bed and wake times from a survey at consent were used to derive sleep traits. Incident diseases were defined as two incident PheWAS codes on separate dates ≥1y after consent. Cox proportional hazards models compared short (&amp;lt;7h) and long (≥9h) sleep duration, with 7-8h (referent group), adjusted for age, gender, race/ethnicity, and employment status, then further adjusted for BMI. Similarly, sleep midpoint (midpoint between weekend wake/bed times), sleep debt (difference in weekend/weekday sleep duration), and social jetlag (difference in weekend/weekday sleep midpoint) were assessed. Results The analytical sample consisted of 24,065 adults (mean sleep duration =8.12h) seeking regular care with sleep data. Participants had a total of 7,513,649 ICD codes of which incident 323,946 ICD codes mapped to 137,137 PheWAS codes. Over a median follow-up of 2.73 years (interquartile range: 1.82-3.98), participants sleeping &amp;lt;7h had a significantly higher risk of incident Acute pain [hazard ratio(95% confidence interval)=1.46(1.2-1.78)], Tobacco use disorder [1.42(1.18-1.71)], Sciatica [1.72(1.3-2.27)], and Edema [1.69(1.25-2.28)]. Each additional hour of later sleep midpoint and increased sleep debt and social jetlag associated with higher risk of incident Major depressive disorder [midpoint:1.30(1.14-1.49); debt:1.23(1.09-1.38); jetlag:1.54(1.27-1.84)]. Associations retained significance upon further adjustment for BMI, except for Edema, and no other associations were observed at the Bonferroni threshold (P=0.0125). Conclusion Our findings in a large hospital-based virtual cohort support unique inter-relationships between sleep duration/timing on somatic, behavioral, and mental health outcomes. Support H.S.D. and R.S. are supported by NIDDK grant R01DK107859. B.C. is supported by K01-HL135405-01. S.R. and R.S. are partially supported by R35 NHLBI HL 135816.

To evaluate the effects of adjunctive pregabalin 300 mg/day versus placebo on polysomnographic (PSG) variables in patients with well controlled partial seizures and subjectively reported sleep disturbance. An exploratory, 4-week, double-blind, randomized study in patients with well controlled partial seizures on AED monotherapy and subjective sleep disturbance over the previous 6 months. Mean changes from baseline to endpoint in PSG and subjective sleep variables (MOS Sleep Scale, Groningen Sleep Questionnaire) in patients on adjunctive pregabalin 300 mg/day (n=8) were compared with patients on placebo (n=7). Baseline PSGs showed sleep fragmentation. Mean sleep efficiency improved significantly in both treatment groups in the mean baseline to endpoint change; there was no significant between-group difference. Pregabalin treatment was associated with a significant reduction in number of awakenings (p = 0.02), and improvement in wake time after sleep onset approached significance (p = 0.055), suggesting improvement in sleep continuity that was not observed in the placebo group. Pregabalin was also associated with significant improvements in the MOS sleep disturbance and sleep quantity subscales compared with placebo (p < or =0.03). There were no changes in self-reported seizure control. This exploratory pilot study suggests that pregabalin may improve sleep continuity in patients with clinically relevant sleep disturbance. The effect on disturbed sleep appears independent of seizure control. The effects of pregabalin on disturbed sleep and seizures and their interrelationships warrant further study.

Introduction The majority of adolescents report consuming a caffeinated beverage on a typical day, which has been linked to poor sleep health in cross-sectional studies. However, it is unknown whether poor sleep predicts caffeine consumption, and/or whether caffeine consumption predicts poor sleep, particularly when sleep is measured objectively. The current study examined within- and between-person associations of actigraphic sleep dimensions with caffeinated beverage consumption in adolescents. Methods Data were collected from a micro-longitudinal substudy of the age 15 wave of the Fragile Families and Child Wellbeing Study (n=589). Adolescents wore a wrist-actigraphy device and completed daily surveys for approximately one week (mean=5.6 days). Daily surveys assessed sleep quality and caffeinated beverage consumption (0=no caffeine, 1=any caffeine). Separate mixed models assessed whether actigraphy-measured sleep duration, timing, maintenance efficiency, and subjective quality predicted next-day caffeinated beverage consumption within and between adolescents. Variability of sleep duration and timing (SD), sleep regularity index, and social jetlag were tested as additional between-person predictors. Lagged models tested whether daily caffeinated beverage consumption predicted sleep that night (n=458; mean=5.2 days). Results Between-person results showed that adolescents who had more variable actigraphic sleep duration (OR=1.21, p=.042) and sleep midpoint (OR=1.27, p=.045) had greater odds of consuming caffeinated beverages compared to others. Within-person results showed that on days when adolescents consumed ≥1 caffeinated beverage, they had later sleep onset by (b±SEM) 17±6 mins (p=.003) that night and later wake time by 19±7 mins (p= .011) the next morning, compared to days when they did not consume caffeine. Sleep duration, timing, maintenance efficiency, and subjective quality did not predict next-day caffeinated beverage consumption (all p&amp;gt;.10). Conclusion Greater variability in sleep duration and timing and later sleep timing are risk factors for poor emotional and cardiometabolic health. Curbing caffeinated beverage consumption may aid in the maintenance of regular sleep schedules and advance sleep timing in adolescents, potentially improving physical and psychological health. Support (If Any) R01HD073352