Child routines moderate a brief behavioral intervention to enhance sleep in school-aged children.

OBJECTIVE: To examine whether child routines (the consistency or variation in children's daily routines, household responsibilities, discipline routines, and homework routines) moderated the effectiveness of a brief behavioral intervention to enhance sleep in school-aged children. METHODS: Secondary analysis was conducted with a subset of 66 families with short sleeping (≤9.5 hr/day) children, 8-11 years old (female = 68%; mean age = 9.76, SD = 1.02) who completed the Child Routines Inventory at baseline and were then randomized to receive a behavioral sleep intervention (n = 32) or to control (n = 34). Sleep period was objectively measured using wrist actigraphy at baseline and 2 months post-randomization. Moderation analysis was performed using ordinary least squares regression using the PROCESS macro for SPSS. RESULTS: Controlling for sleep period at baseline, treatment condition was significantly related to the sleep period at 2 months post-randomization, with the intervention group achieving a longer sleep period compared to the usual sleep period group (control) (b = 46.30, p < .01). Intervention response was moderated by child routines (b = 1.43, p < .05). Specifically, the intervention produced the greatest change in sleep period for children who engaged in greater routine behaviors at baseline than those who engaged in fewer routine behaviors. CONCLUSIONS: Families that engage in routine behaviors may be better equipped to adopt the behavioral modifications required to get a good night's sleep. The findings highlight the importance of working with families to establish routine behaviors to improve responses to behavioral sleep interventions.

Randomized controlled trial to enhance children's sleep, eating, and weight.

BACKGROUND: The present study assessed the efficacy of a behavioral intervention to enhance children's sleep and reduce caloric intake and body mass index (BMI) change. METHODS: Seventy-eight children 8-11 years old who slept 9.5 h/night or less were randomized to the sleep intervention or to no treatment control. The primary outcome was 2-month change in the actigraph-estimated sleep period; changes in reported caloric intake, percent calories from fat, and BMI/BMI z-score (BMIz) were assessed. RESULTS: Children randomized to intervention enhanced their sleep period by 40 ± 7 min/night relative to control (p < 0.001), and were more likely to increase their sleep period by 30 min/night or more (52% versus 15%, p = 0.003). No differences were observed for reported dietary intake or BMI/BMIz. However, in post-hoc analyses collapsing across groups, those who increased sleep by 30 min/night or more had lower BMI (-0.31 kg/m2, p = 0.01) and BMIz (-0.07, p = 0.03) and reported fewer percent calories from fat at 2 months (-2.2%, p = 0.04). CONCLUSIONS: A brief behavioral intervention can enhance children's sleep, but did not result in changes in caloric intake or weight status. Enhancing sleep by 30 min/night or more may be beneficial for weight regulation. IMPACT: A brief behavioral intervention improved children's nocturnal sleep relative to no treatment control. Given the many benefits of a good night's sleep across domains of functioning, findings have significant implications for children's health and wellbeing. There were no differences between groups on eating behaviors or BMI. However, across groups, children who increased their sleep period by at least 30 min/night, reported reduced intake from fat and evidenced lower BMI at 2 months. Thus, a brief intervention can improve sleep and may have potential benefits for weight regulation.

Sleep Problems and Autism Impairments in a Large Community Sample of Children and Adolescents.

Sleep problems are common in individuals with autism spectrum disorder (ASD). How sleep problems reflect specific ASD phenotypes is unclear. We studied whether sleep problems indexed functional impairment in a heterogeneous community sample of individuals with ASD. We analyzed 977 probands (233 females; age = 11.27 ± 4.13 years) from the Rhode Island Consortium for Autism Research and Treatment dataset, a unique public-private-academic collaboration involving all major points of service for families in Rhode Island. We found that individuals with a confirmed diagnosis of ASD were more likely to have sleep problems. However, across the whole sample and above and beyond a formal diagnosis, sleep problems were dimensionally associated with worse social impairment and poorer adaptive functioning. By using a large dataset reflective of the diversity of presentations in the community, this study underscores the importance of considering sleep problems in clinical practice to improve adaptive functioning in individuals with ASD.

Naps not as effective as a night of sleep at dissipating sleep pressure.

The two-process model of sleep posits that two processes interact to regulate sleep and wake: a homeostatic (Process S) and a circadian process (Process C). Process S compensates for sleep loss by increasing sleep duration and intensity. Process C gates the timing of sleep/wake favouring sleep during the circadian night in humans. In this study, we examined whether taking six naps throughout a 24-hr period would result in the same amount of dissipation of homeostatic pressure at the end of the day as a night of sleep, when time in bed is equivalent. Data from 46 participants (10-23 years; mean = 14.5 [±â€…2.9]; 25 females) were analysed. Slow-wave energy, normalized to account for individual differences in slow-wave activity, was used as a measure of sleep homeostasis. In the nap condition, slow-wave energy of six naps distributed equally during a 24-hr period was calculated. In the baseline condition, slow-wave energy was measured after 9-hr time in bed. A paired t-test was used to compare nap and baseline conditions. A linear regression was used to examine whether slow-wave energy varied as a function of age. Slow-wave energy was greater during baseline than the nap condition (p < .001). No association between age and slow-wave energy was found for baseline or nap conditions. Our findings indicate that multiple naps throughout the day are not as effective at dissipating sleep pressure as a night of sleep. This is likely due to the influence of the circadian system, which staves off sleep during certain times of the day.

Day-to-day associations between sleep characteristics and affect in community dwelling adults.

Despite the high co-occurrence of sleep and mood disturbances, day-to-day associations between sleep characteristics (sleep duration, continuity, and timing) and dimensions of mood (positive affect and negative affect) remain unclear. The present study aimed to test whether there is a daily, bidirectional association between these sleep characteristics and affective states, while addressing methodological limitations in the extant literature by using actiography and ecological momentary assessment methods. Participants were community dwelling, midlife adults (aged 30-54 years, N = 462, 47% male) drawn from the Adult Health and Behavior Project-Phase 2 study. Participants' sleep patterns were assessed with actiography over a 7-day monitoring period, and on 4 of those days, participants completed an ecological momentary assessment protocol that included hourly assessments of positive affect and negative affect during their wake intervals. Using hierarchical linear modelling, we tested whether participants' sleep characteristics on a given night predicted next-day affect and vice versa. We also explored whether nocturnal sleep characteristics would differentially associate with affect at different times of day (morning, afternoon, and evening) while controlling for multiple health behaviours. We found that when participants reported higher positive affect on a given day, they slept later that night (B = 0.22, p = .010). Although we found no other statistically significant associations in our primary analyses (all p > .05), we found several sleep-affect associations specific to time of day (B ranges: 0.01-0.18, all p ≤ .02), which warrants further study. Overall, our findings suggest that healthy adults may be resilient to daily fluctuations in their sleep and mood.

In-person vs home schooling during the COVID-19 pandemic: Differences in sleep, circadian timing, and mood in early adolescence.

During the COVID-19 pandemic, schools around the world rapidly transitioned from in-person to remote learning, providing an opportunity to examine the impact of in-person vs remote learning on sleep, circadian timing, and mood. We assessed sleep-wake timing using wrist actigraphy and sleep diaries over 1-2 weeks during in-person learning (n = 28) and remote learning (n = 58, where n = 27 were repeat assessments) in adolescents (age M ± SD = 12.79 ± 0.42 years). Circadian timing was measured under a single condition in each individual using salivary melatonin (Dim Light Melatonin Onset; DLMO). Online surveys assessed mood (PROMIS Pediatric Anxiety and Depressive Symptoms) and sleepiness (Epworth Sleepiness Scale - Child and Adolescent) in each condition. During remote (vs in-person) learning: (i) on school days, students went to sleep 26 minutes later and woke 49 minutes later, resulting in 22 minutes longer sleep duration (all P < .0001); (ii) DLMO time did not differ significantly between conditions, although participants woke at a later circadian phase (43 minutes, P = .03) during remote learning; and (iii) participants reported significantly lower sleepiness (P = .048) and lower anxiety symptoms (P = .006). Depressive symptoms did not differ between conditions. Changes in mood symptoms were not mediated by sleep. Although remote learning continued to have fixed school start times, removing morning commutes likely enabled adolescents to sleep longer, wake later, and to wake at a later circadian phase. These results indicate that remote learning, or later school start times, may extend sleep and improve some subjective symptoms in adolescents.

Editorial Perspective: Adolescents' fragile sleep-shining light on a time of risk to mental health.

As many other facets of life-biological, behavioral, psychological, cognitive, and social-undergo change during adolescence, so too does sleep. The context of sleep behavior is modified by alterations to underlying bioregulatory processes that challenge sleep's timing, regularity, and quantity. The buildup of sleep pressure during the day gets slower, opening the door for youth to stay awake later; however, the amount of sleep required does not diminish. Further, the circadian timing system delays, again providing the biological impetus for later sleep. When these changes meet societal demands for early wake, most teens cannot find a way to get enough sleep at a consistent time from night to night. Insufficient and irregular sleep provides a fragile foundation to support mental health.

Genome-wide DNA methylation patterns associated with sleep and mental health in children: a population-based study.

BACKGROUND: DNA methylation (DNAm) has been implicated in the biology of sleep. Yet, how DNAm patterns across the genome relate to different sleep outcomes, and whether these associations overlap with mental health is currently unknown. Here, we investigated associations of DNAm with sleep and mental health in a pediatric population. METHODS: This cross-sectional study included 465 10-year-old children (51.3% female) from the Generation R Study. Genome-wide DNAm levels were measured using the Illumina 450K array (peripheral blood). Sleep problems were assessed from self-report and mental health outcomes from maternal questionnaires. Wrist actigraphy was used in 188 11-year-old children to calculate sleep duration and midpoint sleep. Weighted gene co-expression network analysis was used to identify highly comethylated DNAm 'modules', which were tested for associations with sleep and mental health outcomes. RESULTS: We identified 64 DNAm modules, one of which associated with sleep duration after covariate and multiple testing adjustment. This module included CpG sites spanning 9 genes on chromosome 17, including MAPT - a key regulator of Tau proteins in the brain involved in neuronal function - as well as genes previously implicated in sleep duration. Follow-up analyses suggested that DNAm variation in this region is under considerable genetic control and shows strong blood-brain concordance. DNAm modules associated with sleep did not overlap with those associated with mental health. CONCLUSIONS: We identified one DNAm region associated with sleep duration, including genes previously reported by recent GWAS studies. Further research is warranted to examine the functional role of this region and its longitudinal association with sleep.

An update on adolescent sleep: New evidence informing the perfect storm model.

The maturation of sleep regulatory systems during adolescence in combination with psychosocial and societal pressures culminate in a "Perfect Storm" of short and ill-timed sleep and the associated consequences for many youngsters. This model, first described by Carskadon in 2011, guides our current thinking of adolescent sleep behavior. Since the original description, the field has moved forward with remarkable pace, and this review aims to summarize recent progress and describe how this new work informs our understanding of sleep regulation and sleep behavior during this developmental time frame.

The Influence of Circadian Timing on Olfactory Sensitivity.

Olfactory sensitivity has traditionally been viewed as a trait that varies according to individual differences but is not expected to change with one's momentary state. Recent research has begun to challenge this position and time of day has been shown to alter detection levels. Links between obesity and the timing of food intake further raise the issue of whether odor detection may vary as a function of circadian processes. To investigate this question, 37 (21 male) adolescents (M age = 13.7 years) took part in a 28-h forced desynchrony (FD) protocol with 17.5 h awake and 10.5 h of sleep, for 7 FD cycles. Odor threshold was measured using Sniffin' Sticks 6 times for each FD cycle (total threshold tests = 42). Circadian phase was determined by intrinsic period derived from dim light melatonin onsets. Odor threshold showed a significant effect of circadian phase, with lowest threshold occurring on average slightly after the onset of melatonin production, or about 1.5○ (approximately 21:08 h). Considerable individual variability was observed, however, peak olfactory acuity never occurred between 80.5○ and 197.5○ (~02:22-10:10 h). These data are the first to show that odor threshold is differentially and consistently influenced by circadian timing, and is not a stable trait. Potential biological relevance for connections between circadian phase and olfactory sensitivity are discussed.

An experimental study of adolescent sleep restriction during a simulated school week: changes in phase, sleep staging, performance and sleepiness.

This laboratory study investigated the impact of restricted sleep during a simulated school week on circadian phase, sleep stages and daytime functioning. Changes were examined across and within days and during a simulated weekend recovery. Participants were 12 healthy secondary school students (six male) aged 15-17 years [mean = 16.1 years, standard deviation (SD) = 0.9]. After 2 nights with 10 h (21:30-07:30 hours), time in bed was restricted to 5 h for 5 nights (02:30-07:30 hours), then returned to 10 h time in bed for 2 nights (21:30-07:30 hours). Saliva was collected in dim light on the first and last sleep restriction nights to measure melatonin onset phase. Sleep was recorded polysomnographically, and the Psychomotor Vigilance Task (PVT) and Karolinska Sleepiness Scale were undertaken 3-hourly while awake. Average phase delay measured by melatonin was 3 h (SD = 50 min). Compared to baseline, sleep during the restriction period contained a smaller percentage of Stages 1 and 2 and rapid eye movement (REM) and a greater percentage of Stage 4. PVT lapses increased significantly during sleep restriction and did not return to baseline levels during recovery. Subjective sleepiness showed a similar pattern during restriction, but returned to baseline levels during recovery. Results suggest that sustained attention in adolescents is affected negatively by sleep restriction, particularly in the early morning, and that a weekend of recovery sleep is insufficient to restore performance. The discrepancy between sleepiness ratings and performance may indicate a lack of perception of this residual impairment.

An approach to understanding sleep and depressed mood in adolescents: person-centred sleep classification.

Depressive mood in youth has been associated with distinct sleep dimensions, such as timing, duration and quality. To identify discrete sleep phenotypes, we applied person-centred analysis (latent class mixture models) based on self-reported sleep patterns and quality, and examined associations between phenotypes and mood in high-school seniors. Students (n = 1451; mean age = 18.4 ± 0.3 years; 648 M) completed a survey near the end of high-school. Indicators used for classification included school night bed- and rise-times, differences between non-school night and school night bed- and rise-times, sleep-onset latency, number of awakenings, naps, and sleep quality and disturbance. Mood was measured using the total score on the Center for Epidemiologic Studies-Depression Scale. One-way anova tested differences between phenotype for mood. Fit indexes were split between 3-, 4- and 5-phenotype solutions. For all solutions, between phenotype differences were shown for all indicators: bedtime showed the largest difference; thus, classes were labelled from earliest to latest bedtime as 'A' (n = 751), 'B' (n = 428) and 'C' (n = 272) in the 3-class solution. Class B showed the lowest sleep disturbances and remained stable, whereas classes C and A each split in the 4- and 5-class solutions, respectively. Associations with mood were consistent, albeit small, with class B showing the lowest scores. Person-centred analysis identified sleep phenotypes that differed in mood, such that those with the fewest depressive symptoms had moderate sleep timing, shorter sleep-onset latencies and fewer arousals. Sleep characteristics in these groups may add to our understanding of how sleep and depressed mood associate in teens.

Stage 2 Sleep EEG Sigma Activity and Motor Learning in Childhood ADHD: A Pilot Study.

Attention deficit hyperactivity disorder (ADHD) is associated with deficits in motor learning and sleep. In healthy adults, overnight improvements in motor skills are associated with sleep spindle activity in the sleep electroencephalogram (EEG). This association is poorly characterized in children, particularly in pediatric ADHD. Polysomnographic sleep was monitored in 7 children with ADHD and 14 typically developing controls. All children were trained on a validated motor sequence task (MST) in the evening with retesting the following morning. Analyses focused on MST precision (speed-accuracy trade-off). NREM Stage 2 sleep EEG power spectral analyses focused on spindle-frequency EEG activity in the sigma (12-15 Hz) band. The ADHD group demonstrated a selective decrease in power within the sigma band. Evening MST precision was lower in ADHD, yet no difference in performance was observed following sleep. Moreover, ADHD status moderated the association between slow sleep spindle activity (12-13.5 Hz) and overnight improvement; spindle-frequency EEG activity was positively associated with performance improvements in children with ADHD but not in controls. These data highlight the importance of sleep in supporting next-day behavior in ADHD while indicating that differences in sleep neurophysiology may contribute to deficits in this population.

Estimating sleep from multisensory armband measurements: validity and reliability in teens.

Given the recognition that sleep may influence obesity risk, there is increasing interest in measuring sleep parameters within obesity studies. The goal of the current analyses was to determine whether the SenseWear(®) Pro3 Armband (armband), typically used to assess physical activity, is reliable at assessing sleep parameters. The armband was compared with the AMI Motionlogger(®) (actigraph), a validated activity monitor for sleep assessment, and with polysomnography, the gold standard for assessing sleep. Participants were 20 adolescents (mean age = 15.5 years) with a mean body mass index percentile of 63.7. All participants wore the armband and actigraph on their non-dominant arm while in-lab during a nocturnal polysomnographic recording (600 min). Epoch-by-epoch sleep/wake data and concordance of sleep parameters were examined. No significant sleep parameter differences were found between the armband and polysomnography; the actigraph tended to overestimate sleep and underestimate wake compared with polysomnography. Both devices showed high sleep sensitivity, but lower wake detection rates. Bland-Altman plots showed large individual differences in armband sleep parameter concordance rates. The armband did well estimating sleep overall, with group results more similar to polysomnography than the actigraph; however, the armband was less accurate at an individual level than the actigraph.

What Role Does Sleep Play in Weight Gain in the First Semester of University?

We hypothesized that shorter sleep durations and greater variability in sleep patterns are associated with weight gain in the first semester of university. Students (N = 132) completed daily sleep diaries for 9 weeks, completed the MEQ (chronotype) and CES-D (depressed mood) at week 9, and self-reported weight/height (weeks 1 & 9). Mean and variability scores were calculated for sleep duration (TST, TSTv), bedtime (BT, BTv), and wake time (WT, WTv). An initial hierarchical regression evaluated (block 1) sex, ethnicity; (block 2) depressed mood, chronotype; (block 3) TST; (block 4) BT, WT; and (block 5; R(2) change = 0.09, p = 0.005) TSTv, BTv, WTv with weight change. A sex-by-TSTv interaction was found. A final model showed that ethnicity, TST, TSTv, and BTv accounted for 31% of the variance in weight change for males; TSTv was the most significant contributor (R(2) change = 0.21, p < 0.001). Daily variability in sleep duration contributes to males' weight gain. Further investigation needs to examine sex-specific outcomes for sleep and weight.

Acute Changes in Sleep Duration on Eating Behaviors and Appetite-Regulating Hormones in Overweight/Obese Adults.

There is considerable interest in the role of sleep in weight regulation, yet few studies have examined this relationship in overweight/obese (OW/OB) adults. Using a within-subject, counterbalanced design, 12 OW/OB women were studied in lab with two nights of short (5 hr time in bed [TIB]) and two nights of long (9 hr TIB) sleep. Hunger, consumption at a buffet, and fasting hormone levels were obtained. Significant polysomnographic differences occurred between conditions in total sleep time and sleep architecture (ps < .001). Percent energy from protein at the buffet increased following short sleep. No differences were observed for total energy intake or measured hormones. Further research is needed to determine how lengthening sleep impacts weight regulation in OW/OB adults.

Sleep patterns are associated with common illness in adolescents.

This prospective, field-based study examined the association between actigraphically measured total sleep time and incident illness including cold, flu, gastroenteritis and other common infectious diseases (e.g., strep throat) in adolescents during the course of a school semester. Participants were 56 adolescents ages 14-19 years (mean = 16.6, standard deviation = 1.2, 39% male) from five high schools in Rhode Island. Beginning in late January, adolescents wore actigraphs [mean 91 (19) days, range 16-112 days] and were assigned post-hoc to longer or shorter sleep groups based on median splits. Adolescents were interviewed weekly across as many as 16 weeks (modal number of interviews = 13) using a structured protocol that included 14 health event questions. Illness events and illness-related school absences were coded for 710 completed interviews, with 681 illness events and 90 school absences reported. Outcomes (illness bouts, illness duration and absences) were compared among sex, sleep and academic year groups using non-parametric regression. In a subset of 18 subjects, mean actigraphically estimated total sleep time six nights before matched illness/wellness events was compared using multivariate analysis of variance (manova). Longer sleepers and males reported fewer illness bouts; total sleep time effects were more apparent in males than females. A trend was found for shorter total sleep time before ill events. The present findings in this small naturalistic sample indicate that acute illnesses were more frequent in otherwise healthy adolescents with shorter sleep, and illness events were associated with less sleep during the previous week than comparable matched periods without illness.

Chronotype is associated with the timing of the circadian clock and sleep in toddlers.

Chronotype is a construct reflecting individual differences in diurnal preference. Although chronotype has been studied extensively in school-age children, adolescents and adults, data on young children are scarce. This study describes chronotype and its relationship to the timing of the circadian clock and sleep in 48 healthy children aged 30-36 months (33.4 ± 2.1 months; 24 males). Parents completed the Children's Chronotype Questionnaire (CCTQ) ~2 weeks before the start of the study. The CCTQ provides three measures of chronotype: midsleep time on free days, a multi-item morningness/eveningness score and a single item chronotype score. After 5 days of sleeping on their habitual schedule (assessed with actigraphy and sleep diaries), children participated in an in-home salivary dim light melatonin onset assessment. Average midsleep time on free days was 1:47 ± 0:35, and the average morningness/eveningness score was 26.8 ± 4.3. Most toddlers (58.4%) were rated as 'definitely a morning type' or 'rather morning than evening type', while none (0%) were rated as 'definitely evening type'. More morning types (midsleep time on free days and morningness/eveningness score, respectively) had earlier melatonin onset times (r = 0.45, r = 0.26), earlier habitual bedtimes (r = 0.78, r = 0.54), sleep onset times (r = 0.80, r = 0.52), sleep midpoint times (r = 0.90, r = 0.53) and wake times (r = 0.74, r = 0.34). Parent ratings using the single-item chronotype score were associated with melatonin onset (r = 0.32) and habitual bedtimes (r = 0.27), sleep onset times (r = 0.33) and sleep midpoint times (r = 0.27). Morningness may best characterize circadian preference in early childhood. Associations between chronotype and circadian physiology and sleep timing suggest adequate validity for the CCTQ in this age group. These findings have important implications for understanding the marked variability in sleep timing during the early years of life.

Sleep Physiology and Neurocognition Among Adolescents With Attention-Deficit/Hyperactivity Disorder.

OBJECTIVE: Few studies have characterized the nature of sleep problems among adolescents with attention-deficit/hyperactivity disorder (ADHD) using polysomnography (PSG). Additionally, although adolescents with ADHD and adolescents with sleep disturbances display similar neurocognitive deficits, the role of sleep in contributing to neurocognitive impairment in adolescent ADHD is unknown. This study investigated differences in PSG-measured sleep among adolescents with ADHD compared with non-psychiatric controls and associations with neurocognition. METHOD: Medication-free adolescents aged 13 to 17 (N = 62, n = 31 with ADHD; mean age = 15.3 years; 50% female) completed a diagnostic evaluation, 3 nights of ambulatory PSG, the Cambridge Neuropsychological Test Automated Battery, and subjective reports of sleep and executive functioning. Linear regressions covarying for age, sex, and pubertal status examined group differences in sleep indices, and partial Pearson correlations assessed relations between sleep and neurocognition. RESULTS: Although adolescents with ADHD did not exhibit differences in PSG-measured sleep duration, awakenings, or latency (ps > .05) compared with non-psychiatric controls, they displayed lower slow wave sleep percentage (ß = -.40) and non-rapid eye movement (NREM) electroencephalogram (EEG) delta power (ß = -.29). They also exhibited greater stage 2 percentage (ß = .41), NREM EEG sigma power (ß = .41), and elevated self-reported sleep disturbances (ps < .05). Lower NREM EEG delta power, increased high-frequency power, and slower decline in NREM EEG delta power overnight were associated with poorer neurocognition among adolescents with ADHD. CONCLUSIONS: Adolescents with ADHD reported more sleep disturbances than non-psychiatric controls and exhibited differences in sleep stage distribution and NREM sleep EEG frequency. Sleep-EEG spectral indices were associated with impaired neurocognition, suggesting that physiological sleep processes may underlie neurocognitive deficits in ADHD. Future studies may clarify whether sleep plays a causal role in neurocognitive impairments in adolescent ADHD and whether interventions normalizing sleep improve neurocognition. CLINICAL TRIAL REGISTRATION INFORMATION: Sleep Dysfunction and Neurocognitive Outcomes in Adolescent ADHD; https://clinicaltrials.gov/; NCT02897362. DIVERSITY & INCLUSION STATEMENT: We worked to ensure sex and gender balance in the recruitment of human participants. We worked to ensure race, ethnic, and/or other types of diversity in the recruitment of human participants. We worked to ensure that the study questionnaires were prepared in an inclusive way. One or more of the authors of this paper self-identifies as a member of one or more historically underrepresented sexual and/or gender groups in science. We actively worked to promote sex and gender balance in our author group. While citing references scientifically relevant for this work, we also actively worked to promote sex and gender balance in our reference list.

Altered sleep architecture following consecutive nights of presleep alcohol.

STUDY OBJECTIVES: Alcohol consumption before sleep decreases sleep latency, explaining the common use of alcohol as a sleep aid. The full impact of alcohol on sleep architecture is not well understood, particularly the potential cumulative effects of presleep alcohol consumption across consecutive nights. Here, we describe the effects of presleep alcohol on sleep architecture across three consecutive nights. METHODS: Thirty adult participants took part in a crossover, within-participants study consisting of two sets of three consecutive nights of in-lab polysomnography. For each series of nights, participants drank one of the two beverages: a mixer only or a mixer plus alcohol (targeting a BrAC of 0.08 mg/L), ending 1 hour before lights out. Polysomnography (PSG) was used to stage sleep, and standard sleep variables were extracted. Linear mixed-effect analysis and generalized additive modeling were used to examine the effect of alcohol on sleep architecture. RESULTS: Alcohol before sleep increased the rate of slow wave sleep (SWS) accumulation across all three nights and decreased the rate of rapid eye movement (REM) sleep accumulation at the start of each night. Alcohol also decreased the total amount of REM sleep but did not affect the total amount of SWS each night. CONCLUSIONS: These data indicate that drinking alcohol before sleep substantially affects sleep architecture, including changes to the rate of accumulation of SWS and REM sleep. We show that alcohol disrupts normal sleep architecture, leading to a significant decrease in REM sleep; thus, the use of alcohol as a sleep aid remains a public health concern.