Development of infant and toddler sleep patterns: real‐world data from a mobile application

The aim of this study was to investigate the development of infant and toddler sleep patterns. Data were collected on 841 children (aged from birth to 36 months) via a free, publicly available, commercially sponsored iPhone app. Analyses were conducted on caregiver recordings of 156 989 sleep sessions across a 19‐month period. Detailed visualizations of the development of sleep across the first 3 years of life are presented. In the first 3 months, sleep sessions primarily lasted less than 3.5 h throughout the day. Between 3 and 7 months old, sleep consolidated into two naps of about 1.5 h in length and a night‐time sleep session of about 10.5 h. Across age groups, a negative relationship was observed between the start of bedtime and the length of the night‐time sleep session (i.e. later bedtime is associated with a shorter night‐time sleep period). The length of daytime sleep sessions (naps) varied with age, decreasing between 1 and 5 months old, and then increasing monotonically through 28 months. Morning wake time was observed to be invariant in children aged 5–36 months. Sleep patterns are ever‐changing across the first few years with wide individual variability. Sleep patterns start to develop more clearly at 5–6 months, when longer night‐time sleep duration begins and sleep consolidation occurs. Daytime sleep patterns appeared to become more consistent and consolidated later in age than night‐time sleep. Finally, there is greater variability in bedtimes than wake times, with bedtimes having a greater influence on night‐time sleep duration.     

Reference values and changes in infant sleep–wake behaviour during the first 12 months of life: a systematic review

This paper is a systematic review on the reference values and changes in infant sleep–wake behaviour during the first 12 months of life. This systematic review was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta‐Analysis (PRISMA). Seventy‐four papers were included, and the reference values and changes in sleep–wake behaviour during the first 12 months of life were identified. Sleep duration during the 24‐h period, and day and sleep periods during the night decreased over the first 12 months of life. Night wakings and bedtime/sleep‐onset time decreased, while the longest sleep period increased at night during the first 6 months. High discrepancy was noted between studies in the reference values of sleep–wake behaviour, while more congruence was noted regarding changes, especially those occurring in the first 6 months of life. Several methodological differences were identified between studies and may partially explain inconsistencies in the results, including the assessment of different sleep–wake behaviours, the focus on specific ages or age ranges, the use of self‐report, observational or direct measures, the recruitment of small or large representative samples, and the countries where the research was conducted. These aspects should be considered in future research and caution should be taken when generalizing results from studies with diverse methodological characteristics. Nonetheless, this review identifies normative reference values and the changes occurring in infant sleep–wake behaviour, and could inform both practitioners and researchers, helping them identify infants with sleep delays or problems.     

Association between sleep duration,fat mass,lean mass and obesity in Korean adults: the fourth and fifth Korea National Health and Nutrition Examination Surveys

This study investigated the association between sleep duration, fat mass, lean mass and obesity. Participants of this cross‐sectional study were 16 905 adults included into the 4th and 5th Korea National Health and Nutrition Examination Surveys. Sleep duration was assessed by self‐reported survey and categorized into ≤ 5, 6, 7, 8 and ≥ 9 h per day. The group reporting 7 h of sleep per day (comprised of those sleeping 7–8 h per day) was used as the reference group. Body composition was measured by dual X‐ray absorptiometry (DEXA). Obesity was defined based on the criteria from the Korean Society for the Study of Obesity. Least‐squares means of fat mass index (FMI) and lean mass index (LMI) adjusted for age, employment status, comorbidities and physical activity were used to assess the relation between sleep duration and body composition. Multivariable logistic regression was used to calculate the adjusted odds ratios (aOR) and 95% confidence intervals (95% CI) of obesity according to sleep duration after adjusting for sociodemographic and health‐related factors. After adjustment, FMI increased with fewer hours of sleep (P for trend: < 0.001) and LMI decreased with more hours of sleep (P for trend: 0.011). Compared to the reference group, sleep‐deprived individuals were 1.22 times more likely to have general obesity (aOR: 1.22; 95% CI: 1.03–1.45) and 1.32 times more likely to have abdominal obesity (aOR: 1.32; 95% CI: 1.10–1.58). Our findings suggest that sleep deprivation might be related to an increase of fat mass and obesity, while oversleeping could be linked to a reduction of lean mass.     

Night‐shift work is associated with poorer glycaemic control in patients with type 2 diabetes

The circadian system plays a role in regulating metabolism. Night‐shift work, a form of circadian misalignment, is associated with increased type 2 diabetes risk. This study aimed to determine if night‐shift workers with type 2 diabetes experience poorer glycaemic control than non‐shift workers. Patients with type 2 diabetes (104 unemployed, 85 day workers and 60 night‐shift workers) participated. Sleep duration, sleep quality, morningness–eveningness preference, depressive symptoms and dietary intake were assessed using standardized questionnaires. Haemoglobin A1c levels were measured. Night‐shift workers had significantly higher haemoglobin A1c levels compared with others, while there were no differences between day workers and unemployed participants (median 7.86% versus 7.24% versus 7.09%, respectively). Additionally, night‐shift workers were younger, had a higher body mass index, and consumed more daily calories than others. Among night‐shift workers, there were no significant differences in haemoglobin A1c levels between those performing rotating versus non‐rotating shifts (P = 0.856), or those with clockwise versus counterclockwise shift rotation (P = 0.833). After adjusting for age, body mass index, insulin use, sleep duration, morningness–eveningness preference and percentage of daily intake from carbohydrates, night‐shift work, compared with day work, was associated with significantly higher haemoglobin A1c (B = 0.059, P = 0.044), while there were no differences between unemployed participants and day workers (B = 0.016, P = 0.572). In summary, night‐shift work is associated with poorer glycaemic control in patients with type 2 diabetes.     

The effect on sleep of being on‐call: an experimental field study

The aim of this study was to: (i) gain more insight into the relationship between being on‐call and sleep and (ii) investigate the role of stress in this relationship. Data were collected by means of an experimental field study with a within‐subject design (two conditions, random order). Ninety‐six students participated during two consecutive nights: a reference night and a simulated on‐call night without an actual call. Participants were told they could be called at any time during the on‐call night. In the case of a call, participants had to perform online tasks for approximately 30 min. Self‐reported sleep quality and the extent to which participants experienced stress during the on‐call period were assessed by means of short questionnaires. Actigraphy was used to obtain objective sleep measures. Results for actigraphy data revealed no significant within‐person differences between conditions. However, participants reported longer sleep onset latencies, more awakenings and more wake after sleep onset during the on‐call night than during the reference night. They also reported more sleep problems and a lower overall sleep quality, and felt less recuperated after the on‐call night. Perceived stress moderated the relationship between being on‐call, on one hand, and the number of awakenings, wake after sleep onset, sleep problems and overall sleep quality, on the other hand. Results show that, even in the absence of an actual call, sleep during on‐call nights is of lower quality and has less restorative value – especially when being on‐call is experienced as stressful.     

Time‐of‐night variations in the story‐like organization of dream experience developed during rapid eye movement sleep

This study aimed to investigate the cycles (2nd/4th) and duration‐related (5/10 min) variations in the story‐like organization of dream experience elaborated during rapid eye movement (REM) sleep. Dream reports were analysed using story grammar rules. Reports were provided by those subjects (14 of 22) capable of reporting a dream after each of the four awakenings provoked in 2 consecutive nights during REM sleep of the 2nd and 4th cycles, after periods of either 5 or 10 min, counterbalanced across the nights. Two researchers who were blind as to the sleep condition scored the dream reports independently. The values of the indicators of report length (measured as value of total word count) and of story‐like organization of dream reports were matched taking time‐of‐night (2nd and 4th cycles) and REM duration (5 versus 10 min) as factors. Two‐way analyses of variance showed that report length increased significantly in 4th‐cycle REM sleep and nearly significantly for longer REM duration, whereas the number of dream‐stories per report did not vary. The indices of sequential (number of statements describing the event structure developed in the story) and hierarchical (number of episodes per story) organization increased significantly only in dream‐stories reported after 10 min of 4th‐cycle REM sleep. These findings indicate that the characteristics of structural organization of dream‐stories vary along with time of night, and suggest that the elaboration of a long and complex dream‐story requires a fairly long time and the availability of a great amount of cognitive resources to maintain its continuity and coherence.     

Delay discounting and response disinhibition moderate associations between actigraphically measured sleep parameters and body mass index

Previous research suggests that the sleep–obesity association varies significantly across individuals. This study examined the associations between actigraphically measured sleep parameters and body mass index and hypothesized that the associations would be stronger in individuals with greater delay discounting, the devaluation of future rewards and response disinhibition and the difficulty in withholding previously rewarded responses. Seventy‐eight college students carried a wrist‐worn actigraph and completed diaries reporting bedtime, wake time and covariates including physical activity, alcohol and caffeine consumption, daytime nap duration and perceived stress for 7 days and completed the delay discounting and go/no‐go response disinhibition tasks. Their height and weight were measured. Only bedtime variability was significantly associated with body mass index in the main effect model controlling for all covariates (B = 0.03, P = 0.001). Delay discounting moderated associations of bedtime (B = 0.03, P < 0.001), sleep duration variability (B = 0.05, P = 0.002), bedtime variability (B = 0.03, P = 0.002) and wake time variability (B = 0.02, P < 0.001) with body mass index; these associations were significant only when the delay discounting rate was high. Response disinhibition moderated the association between bedtime variability and body mass index in a similar pattern (B = 0.01, P = 0.004). The findings suggest that, using actigraphy measures of sleep, circadian desynchrony rather than sleep duration is a risk factor for higher body mass index. The findings support the hypothesis that delay discounting and response disinhibition moderate the associations between sleep and body mass index. Delay discounting and response disinhibition might characterize individuals who are vulnerable to the influence of circadian desynchrony on weight.     

Sleep patterns and insomnia among adolescents: a population‐based study

The aim of the current study was to examine sleep patterns and rates of insomnia in a population‐based study of adolescents aged 16–19 years. Gender differences in sleep patterns and insomnia, as well as a comparison of insomnia rates according to DSM‐IV, DSM‐V and quantitative criteria for insomnia (Behav. Res. Ther., 41 , 2003, 427), were explored. We used a large population‐based study in Hordaland county in Norway, conducted in 2012. The sample included 10 220 adolescents aged 16–18 years (54% girls). Self‐reported sleep measurements included bedtime, rise time, time in bed, sleep duration, sleep efficiency, sleep onset latency, wake after sleep onset, rate and frequency and duration of difficulties initiating and maintaining sleep and rate and frequency of tiredness and sleepiness. The adolescents reported short sleep duration on weekdays (mean 6:25 hours), resulting in a sleep deficiency of about 2 h. A majority of the adolescents (65%) reported sleep onset latency exceeding 30 min. Girls reported longer sleep onset latency and a higher rate of insomnia than boys, while boys reported later bedtimes and a larger weekday–weekend discrepancy on several sleep parameters. Insomnia prevalence rates ranged from a total prevalence of 23.8 (DSM‐IV criteria), 18.5 (DSM‐V criteria) and 13.6% (quantitative criteria for insomnia). We conclude that short sleep duration, long sleep onset latency and insomnia were prevalent in adolescents. This warrants attention as a public health concern in this age group.     

Actigraphy‐assessed sleep during school and vacation periods: a naturalistic study of restricted and extended sleep opportunities in adolescents

School‐related sleep restriction in adolescents has been identified by studies comparing weekday and weekend sleep. This study compared weekday and vacation sleep to assess restricted and extended sleep opportunities. One‐hundred and forty‐six adolescents (47.3% male) aged 16.2 ± 1.0 years (M ± SD) from the general community wore an actigraph continuously for 4 weeks: the last week of a school term (Time‐E), the following 2‐week vacation, and the first week of the next term. Self‐reported sleep was assessed for each of the three time intervals, and chronotype was assessed using the Morningness–Eveningness Questionnaire at Time‐E. Daily actigraphy bedtime, rise‐time, time‐in‐bed, total sleep time, sleep onset latency, sleep efficiency, and % wake after sleep onset were analysed using latent growth curve modelling. The removal of school‐related sleep restriction was associated with an abrupt delay in sleep timing and increase in sleep duration. Subsequently, bedtime and rise‐time showed further linear delays throughout the vacation, while changes in time‐in‐bed were non‐significant. Sleep onset latency increased linearly, peaking in the middle of the second vacation week. Across the first vacation week, total sleep time and sleep efficiency linearly decreased, while % wake after sleep onset increased. These changes stabilized during the second vacation week. Older age and eveningness were associated with later bedtime and rise‐time, whilst females had longer time‐in‐bed, total sleep time and sleep onset latency. Compared with school days, sleep during the vacation was characterized by later timing, longer duration, lower quality and greater variability. Recovery from school‐related sleep restriction appeared to be completed within the 2 weeks of naturalistic extended sleep.     

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.     

Integrating nap and night‐time sleep into sleep patterns reveals differential links to health‐relevant outcomes

Both night‐time sleep and nap behaviour have been linked consistently to health outcomes. Although reasons for napping are usually tied to night‐time sleep, the majority of studies assess their effects independently. The current study thus aimed to examine the health relevance of patterns of sleep behaviour that take into account both night‐time and daytime sleep habits. Night‐time sleep, recorded during 7 days via actigraphy from 313 participants (aged 34–82 years) of the Midlife in the United States II Biomarker study, was assessed. Blood and urine specimens were assayed for noradrenaline, interleukin‐6 and C‐reactive protein. Participants self‐reported nap behaviour, depressive symptoms, perceived chronic stress and the presence of medical symptoms and conditions. Overall, nappers (n = 208) showed elevated waist–hip ratios, C‐reactive protein and interleukin‐6 levels compared to non‐nappers and reported more physiological symptoms and conditions (all P ≤ 0.019). Within nappers, cluster analysis revealed three patterns of sleep behaviour—infrequent nappers with good night‐time sleep, frequent nappers with good night‐time sleep and nappers with poor night‐time sleep. Nappers with poor night‐time sleep thereby exhibited elevated noradrenaline levels, depressive symptoms and perceived stress scores compared to other groups (all P ≤ 0.041). These findings support the idea that nap–health relationships are complex, in that frequency of napping and accumulation of nap sleep is not related linearly to health consequences. Assessing nap behaviour in conjunction with night‐time sleep behaviour appeared crucial to elucidate further the health relevance of napping, particularly in terms of psychological health outcomes, including chronic stress and depressive symptoms.     

Acute sleep restriction increases dietary intake in preschool‐age children

Epidemiological findings suggest short sleep duration is associated with overweight and obesity across the lifespan. In adults, experimental sleep loss increases caloric intake more than total daily energy needs, thus leading to weight gain. To date, little is known about the relationship between sleep restriction and dietary intake in preschool children. Healthy children (n = 10; 41.2 ± 5.4 months; 5 females) followed a strict sleep schedule for 5 days before each experimental condition: 1 day of baseline sleep (nap and scheduled bedtime/wake time) and 1 day of sleep restriction (no‐nap and ~2.3 h bedtime delay). Standardized parent‐report dietary intake measures were obtained on baseline, sleep restriction and sleep recovery (ad libitum sleep opportunity in the 24‐h following sleep restriction) days. As designed, children slept ~3 h less on the sleep restriction than the baseline day (P < 0.001), with no significant differences in sleep between baseline and recovery days (verified with actigraphy). Repeated‐measures anova s indicated differences across conditions in total kilocalories, sugar, carbohydrate and fat intake (all P < 0.05; no differences in protein). Post hoc tests revealed that compared with baseline, children consumed 21% more kilocalories, 25% more sugar and 26% more carbohydrates on the day of sleep restriction, as well as 14% more kilocalories and 23% more fat on the day of sleep recovery (all P < 0.05). Findings suggest that acute sleep loss increases dietary intake in preschoolers both on the day of and the day after sleep restriction. Increased kilocalorie intake may promote weight gain over time and be a mechanism through which short sleep contributes to childhood obesity risk.     

Sleep patterns and insomnia in a large population‐based study of middle‐aged and older adults: The Tromsø study 2015–2016

Epidemiological studies assessing adult sleep duration have yielded inconsistent findings and there are still large variations in estimation of insomnia prevalence according to the most recent diagnostic criteria. Our objective was to describe sleep patterns in a large population of middle‐aged and older adults, by employing accurate measures of both sleep duration and insomnia. Data stem from the Tromsø Study (2015–2016), an ongoing population‐based study in northern Norway comprising citizens aged 40 years and older (n = 21,083, attendance = 64.7%). Sleep parameters were reported separately for weekdays and weekends and included bedtime, rise time, sleep latency and total sleep time. Insomnia was defined according to recent diagnostic criteria (International Classification of Sleep Disorders; ICSD‐3). The results show that 20% (95% confidence interval,19.4–20.6) fulfilled the inclusion criteria for insomnia. The prevalence was especially high among women (25%), for whom the prevalence also increased with age. For men, the prevalence was around 15% across all age groups. In all, 42% of the women reported sleeping <7 hr (mean sleep duration of 7:07 hr), whereas the corresponding proportion among males was 52% (mean sleep duration of 6:55 hr). We conclude that the proportion of middle‐aged and older adults not getting the recommended amount of sleep is worryingly high, as is also the observed prevalence of insomnia. This warrants attention as a public health problem in this population.     

Blue‐blocking glasses as additive treatment for mania: Effects on actigraphy‐derived sleep parameters

Improvement of sleep is a central treatment goal for patients in a manic state. Blue‐blocking (BB) glasses as adjunctive treatment hasten overall recovery from mania. This method is an evolvement from dark therapy and builds on the discovery of the blue‐light‐sensitive retinal ganglion cell that signals daytime to the brain. We report effects of adjunctive BB glasses on actigraphy‐derived sleep parameters for manic inpatients as compared to placebo. Hospitalized patients with bipolar disorder in a manic state aged 18–70 years were recruited from five clinics in Norway from February 2012 to February 2015. The participants were randomly allocated to wearing BB glasses or placebo (clear glasses) as an adjunctive treatment from 18:00 to 08:00 hours for seven consecutive nights. Sleep and wake were monitored by actigraphy. From 32 eligible patients, 10 patients in each group qualified for the group analyses. The BB group's mean sleep efficiency was significantly higher at night 5 as compared to the placebo group (92.6% vs. 83.1%, p = .027). The 95% confidence interval (CI) was 89.4%–95.8% in the BB group and 75.9%–90.3% in the placebo group. There were fewer nights of interrupted sleep in the BB group: 29.6% versus 43.8% in the placebo group. The BB group received less‐intensive sleep‐promoting pharmacological treatment and showed significantly higher sleep efficiency and more consolidated sleep as compared to the placebo group. Our findings suggest sleep‐promoting effects through deactivating mechanisms. Adjunctive BB glasses seem to be useful for improving sleep for manic patients in the hospital setting.     

Subjective–objective sleep discrepancy among older adults: associations with insomnia diagnosis and insomnia treatment

Discrepancy between subjective and objective measures of sleep is associated with insomnia and increasing age. Cognitive behavioural therapy for insomnia improves sleep quality and decreases subjective–objective sleep discrepancy. This study describes differences between older adults with insomnia and controls in sleep discrepancy, and tests the hypothesis that reduced sleep discrepancy following cognitive behavioural therapy for insomnia correlates with the magnitude of symptom improvement reported by older adults with insomnia. Participants were 63 adults >60 years of age with insomnia, and 51 controls. At baseline, participants completed sleep diaries for 7 days while wearing wrist actigraphs. After receiving cognitive behavioural therapy for insomnia, insomnia patients repeated this sleep assessment. Sleep discrepancy variables were calculated by subtracting actigraphic sleep onset latency and wake after sleep onset from respective self‐reported estimates, pre‐ and post‐treatment. Mean level and night‐to‐night variability in sleep discrepancy were investigated. Baseline sleep discrepancies were compared between groups. Pre–post‐treatment changes in Insomnia Severity Index score and sleep discrepancy variables were investigated within older adults with insomnia. Sleep discrepancy was significantly greater and more variable across nights in older adults with insomnia than controls, P ≤ 0.001 for all. Treatment with cognitive behavioural therapy for insomnia was associated with significant reduction in the Insomnia Severity Index score that correlated with changes in mean level and night‐to‐night variability in wake after sleep onset discrepancy, P < 0.001 for all. Study of sleep discrepancy patterns may guide more targeted treatments for late‐life insomnia.     

Duration of sleep at 3 years of age is associated with fat and fat‐free mass at 4 years of age: the Southampton Women's Survey

Many studies have shown that shorter sleep duration in childhood is associated with higher body mass index (BMI), and have proposed that it is due to an effect of sleep on adiposity. There is little evidence about the association of sleep with fat‐free mass. This study examined the association between child's sleep duration at age 3 years and fat and fat‐free mass at 4 years of age in a prospective cohort study of 302 boys and 285 girls. Study participants were taking part in the Southampton Women's Survey, a longitudinal study of mothers and children from preconception onwards. Total sleep duration at age 3 years was derived from parental report of night sleep and nap duration. Body composition was assessed by Dual‐energy X‐ray Absorptiometry (DXA) at 4 years. Mean total sleep duration was 11.5 hours. In linear regression analyses, adjusted for potentially confounding factors (maternal educational attainment, prepregnancy BMI, smoking during pregnancy, child's gestational age at birth, age at DXA, sex, age last breastfed, dietary quality at 3 years, TV watching and hours actively on the move and parental social class), shorter sleep in hours was associated with higher BMI (kg/m²) [β: ?0.2340, 95% confidence interval (CI): ?0.373 to ?0.096], a greater fat mass index (kg) (β: ?0.1182, 95% CI: ?0.218 to ?0.018) and a greater fat‐free mass index (kg) (β: ?0.100, 95% CI: ?0.185 to ?0.015). Previous research suggested that the association between shorter sleep and higher body mass index is due to an effect on adiposity. Our findings are novel, suggesting that the relationship between sleep and BMI is also determined by an effect on muscle.     

The impact of prolonged violent video‐gaming on adolescent sleep: an experimental study

Video‐gaming is an increasingly prevalent activity among children and adolescents that is known to influence several areas of emotional, cognitive and behavioural functioning. Currently there is insufficient experimental evidence about how extended video‐game play may affect adolescents' sleep. The aim of this study was to investigate the short‐term impact of adolescents' prolonged exposure to violent video‐gaming on sleep. Seventeen male adolescents (mean age = 16 ± 1 years) with no current sleep difficulties played a novel, fast‐paced, violent video‐game (50 or 150 min) before their usual bedtime on two different testing nights in a sleep laboratory. Objective (polysomnography‐measured sleep and heart rate) and subjective (single‐night sleep diary) measures were obtained to assess the arousing effects of prolonged gaming. Compared with regular gaming, prolonged gaming produced decreases in objective sleep efficiency (by 7 ± 2%, falling below 85%) and total sleep time (by 27 ± 12 min) that was contributed by a near‐moderate reduction in rapid eye movement sleep (Cohen's d = 0.48). Subjective sleep‐onset latency significantly increased by 17 ± 8 min, and there was a moderate reduction in self‐reported sleep quality after prolonged gaming (Cohen's d = 0.53). Heart rate did not differ significantly between video‐gaming conditions during pre‐sleep game‐play or the sleep‐onset phase. Results provide evidence that prolonged video‐gaming may cause clinically significant disruption to adolescent sleep, even when sleep after video‐gaming is initiated at normal bedtime. However, physiological arousal may not necessarily be the mechanism by which technology use affects sleep.     

Reliability of sleep spindle measurements in adolescents: How many nights are necessary?

Evidence of night‐to‐night variation in adolescent sleep spindle characteristics is lacking. Twelve adolescents (M = 15.8 ± 0.8 years, eight males) participated in a laboratory study involving 9 nights with 10 hr sleep opportunity. Sleep electroencephalograph was analysed and intra‐class coefficients calculated to determine the reliability of sleep spindles across multiple nights of recording. Slow spindle amplitude and fast spindle density, duration and amplitude characteristics all had acceptable reliability within a single night of sleep recording. Slow spindle density and duration measurements needed a minimum of 4 and 2 nights, respectively, for reliable estimation. Theoretical and methodological implications are discussed.     

Effect of physical fitness and body composition on sleep and sleep-related hormone concentrations

The study assessed the effect of physical fitness and body composition on sleep and the nighttime secretion of the hormones, human growth hormone (hGH), prolactin, and cortisol. Two groups of 17 subjects, one of fit athletes and the other of unfit nonathletes, were selected so that the groups were matched for weight, height, lean body mass (LBM), and fat levels. Subjects slept in a sleep laboratory for 3 nonconsecutive nights: 1 adaptation night and 2 experimental nights. On 1 experimental night blood samples were collected; on the other, baseline sleep was assessed and the catheter was not inserted. Weight and height were measured and LBM assessed by 24 h urinary creatinine. The effect of physical fitness was tested by a comparison of the two groups; body composition was assessed by correlation analyses. Physical fitness did not have a significant effect on either sleep or hormone levels, although in the latter case the results were marginal. In contrast, body composition was related to both sleep and hGH. Percentage LBM was negatively correlated with slow-wave sleep and positively correlated with hGH levels. These results were significant for all subjects combined and for the fit group, although not the unfit group alone.     

Validity,potential clinical utility,and comparison of consumer and research‐grade activity trackers in Insomnia Disorder I: In‐lab validation against polysomnography

Consumer activity trackers claiming to measure sleep/wake patterns are ubiquitous within clinical and consumer settings. However, validation of these devices in sleep disorder populations are lacking. We examined 1 night of sleep in 42 individuals with insomnia (mean = 49.14 ± 17.54 years) using polysomnography, a wrist actigraph (Actiwatch Spectrum Pro: AWS) and a consumer activity tracker (Fitbit Alta HR: FBA). Epoch‐by‐epoch analysis and Bland?Altman methods evaluated each device against polysomnography for sleep/wake detection, total sleep time, sleep efficiency, wake after sleep onset and sleep latency. FBA sleep stage classification of light sleep (N1 + N2), deep sleep (N3) and rapid eye movement was also compared with polysomnography. Compared with polysomnography, both activity trackers displayed high accuracy (81.12% versus 82.80%, AWS and FBA respectively; ns) and sensitivity (sleep detection; 96.66% versus 96.04%, respectively; ns) but low specificity (wake detection; 39.09% versus 44.76%, respectively; p = .037). Both trackers overestimated total sleep time and sleep efficiency, and underestimated sleep latency and wake after sleep onset. FBA demonstrated sleep stage sensitivity and specificity, respectively, of 79.39% and 58.77% (light), 49.04% and 95.54% (deep), 65.97% and 91.53% (rapid eye movement). Both devices were more accurate in detecting sleep than wake, with equivalent sensitivity, but statistically different specificity. FBA provided equivalent estimates as AWS for all traditional actigraphy sleep parameters. FBA also showed high specificity when identifying N3, and rapid eye movement, though sensitivity was modest. Thus, it underestimates these sleep stages and overestimates light sleep, demonstrating more shallow sleep than actually obtained. Whether FBA could serve as a low‐cost substitute for actigraphy in insomnia requires further investigation.