Direct comparison of two new actigraphs and polysomnography in children and adolescents

The temporal and bi-directional relationship between physical activity and sleep in ambulatory children with cerebral palsy

PURPOSE

Exploring the temporal and bi-directional relationship between device-based measures of physical activity and sleep in ambulatory children with cerebral palsy (CP).

MATERIALS AND METHODS

24-hour activity data were collected from children with CP (n = 51, 43% girls, mean age (range); 6.8 (3-12) years; Gross Motor Function Classification System levels I to III). Nocturnal sleep parameters and daily physical activity were measured for seven consecutive days and nights using ActiGraph GT3X accelerometers. Linear mixed models were constructed to explore the relationships between sleep and activity.

RESULTS

Light and moderate-to-vigorous activity were negatively associated with sleep efficiency (SE) (resp. p = 0.04, p = 0.010) and total sleep time (TST) (resp. p = 0.007, p = 0.016) the following night. Sedentary time was positively associated with SE and TST the following night (resp. p = 0.014, p = 0.004). SE and TST were positively associated with sedentary time (resp. p = 0.011, p = 0.001) and negatively with moderate-to-vigorous physical activity (resp. p < 0.001, p = 0.002) the following day. Total bedtime and TST were negatively associated with light physical activity (resp. p = 0.046, p = 0.004) the following day.

CONCLUSIONS

The findings from this study suggest that ambulatory children with CP may not sleep better after physical activity, and vice versa, indicating that the relationship is complex and needs further investigation.

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.

A school-based physical activity intervention in primary school: effects on physical activity, sleep, aerobic fitness, and motor competence

Objective

The "Super Quinas" project evaluated the effectiveness of an intervention program to improve physical activity, aerobic fitness, sleep, and motor competence on children in primary school.

Methods

The experimental group (n = 19) enrolled in a 12-week intervention program (one more extra-curricular activity class of 60 min per week) compared to the CG (n = 19), all aged 9-10 years. Physical activity (PA) and sleep were measured by accelerometry, and aerobic fitness was measured by Children's Yo-Yo test (YYIR1C) during the 1st week (PRE), the 6th week (DUR), and the 12th week (POST) of the intervention program. Motor Competence in PRE and POST intervention was also assessed by the Motor Competence Assessment (MCA) instrument. Heart rate (HR, assessed using HR monitors), and enjoyment level were recorded during all intervention program classes. A linear mixed model analysis (i.e., within-subject analyses) was performed.

Results

Comparing the EG and CG in DUR and POST, the EG spent ~18 min and ~ 34 min more time in moderate to vigorous physical activity (MVPA) per day (p < 0.001); had ~44 min and ~ 203 min less sedentary time per day (p < 0.001); performed more 44 and 128 m in the Children's Yo-Yo test compared to CG (p < 0.001) and slept more 17 and 114 min per night (p < 0.001). In POST motor competence was significantly better (27%) in the EG compared to CG (p < 0.001). The %HRmax during the extra-curricular classes ranged between 65 and 81% (i.e., light to moderate intensities), and the enjoyment between fun and great fun.

Conclusion

Our findings suggest that adding one more extra-curricular activity class of 60 min per week for 12 weeks effectively increased the levels of physical activity, aerobic fitness, sleep duration, and motor competence in children aged 9-10 years.

Sleepy and grumpy go hand in hand for US Navy Sailors

Study Objectives

The study explores how sleep, sleep-related practices, and behaviors, in addition to various demographic and occupational characteristics, are related to overall mood of US Navy sailors when they are underway.

Methods

Longitudinal assessment of US Navy sailors performing their underway duties (N = 873, 79.2% males, median age 25 years). Participants completed standardized questionnaires, wore wrist-worn actigraphs, and completed daily activity logs.

Results

Sailors who reported worse profile of mood states (POMS) total mood disturbance scores had shorter sleep duration, worse sleep quality, and more episodes of split sleep. The group with worse mood also reported more symptoms of excessive daytime sleepiness as well as more symptoms of insomnia. In addition to sleep results, sailors with worse mood also tended to be younger, more likely to use nicotine and tobacco products, and less likely to have an exercise routine when compared to sailors with better POMS scores. Finally, the group with worse POMS scores included more enlisted personnel, tended to work more hours per day, and were more likely to stand watch-especially on rotating watch schedules.

Conclusions

The results found significant associations between the sleep practices and mood of sailors aboard US Navy ships. Numerous other demographic and occupational factors were also strongly associated with mood. This paper is part of the Sleep and Circadian Rhythms: Management of Fatigue in Occupational Settings Collection.

Does a self-reported sleep duration reflect actigraphy reported sleep duration in female football players?

Sleep is often compromised in female athletes, and the monitoring of female athletes' sleep is an important preventative and educational tool. With self-reporting of sleep common practice for athletes as part of a daily wellness assessment, there is a need to understand whether sleep indices are being reported accurately, and thus whether self-report data are useful. This study aimed to compare the agreement between self-reported and actigraphy reported sleep duration in female football players, with the intention of informing best practice for athlete monitoring. Twenty-two female footballers (mean age 19.5 ± 1.3 years) provided a daily self-report across 7 days, whilst also wearing an actigraph across the same testing period. Agreement between the two measures was assessed using Bland-Altman limits of agreement, with acceptable limits of agreement defined as <30 minutes. Results showed evident disagreement between the two methods, with a mean bias of -0.54 (32 min, 95% CI -0.66 to -0.43) and a potential disagreement range of over 2 h (Lower 95% limits of agreement -1.49 to upper 95% limits of agreement 0.40). Coaches using self-reported sleep durations as a monitoring tool for female footballers should interpret the results with caution and be aware of the potential for inaccuracies in this measure. As such, where possible, coaches should consider other methods of sleep monitoring, rather than solely relying on a self-report, to ensure they are operating with optimal practice within situational constraints.

Ethical considerations in using sensors to remotely assess pediatric health behaviors

Sensors, including accelerometer-based and electronic adherence monitoring devices, have transformed health data collection. Sensors allow for unobtrusive, real-time sampling of health behaviors that relate to psychological health, including sleep, physical activity, and medication-taking. These technical strengths have captured scholarly attention, with far less discussion about the level of human touch involved in implementing sensors. Researchers face several subjective decision points when collecting health data via sensors, with these decisions posing ethical concerns for users and the public at large. Using examples from pediatric sleep, physical activity, and medication adherence research, we pose critical ethical questions, practical dilemmas, and guidance for implementing health-based sensors. We focus on youth given that they are often deemed the ideal population for digital health approaches but have unique technology-related vulnerabilities and preferences. Ethical considerations are organized according to Belmont principles of respect for persons (e.g., when sensor-based data are valued above the subjective lived experiences of youth and their families), beneficence (e.g., with sensor data management and sharing), and justice (e.g., with sensor access and acceptability among minoritized pediatric populations). Recommendations include the need to increase transparency about the extent of subjective decision making with sensor data management. Without greater attention to the human factors involved in sensor research, ethical risks could outweigh the scientific promise of sensors, thereby negating their potential role in improving child health and care. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

The association between cortical gyrification and sleep in adolescents and young adults

Study objectives

Healthy sleep is important for adolescent neurodevelopment, and relationships between brain structure and sleep can vary in strength over this maturational window. Although cortical gyrification is increasingly considered a useful index for understanding cognitive and emotional outcomes in adolescence, and sleep is also a strong predictor of such outcomes, we know relatively little about associations between cortical gyrification and sleep.

Methods

Using Local gyrification index (lGI) of 34 bilateral brain regions and regularized regression for feature selection, we examined gyrification-sleep relationships in the Neuroimaging and Pediatric Sleep databank (252 participants; 9-26 years; 58.3% female) and identified developmentally invariant (stable across age) or developmentally specific (observed only during discrete age intervals) brain-sleep associations. Naturalistic sleep characteristics (duration, timing, continuity, and regularity) were estimated from wrist actigraphy.

Results

For most brain regions, greater lGI was associated with longer sleep duration, earlier sleep timing, lower variability in sleep regularity, and shorter time awake after sleep onset. lGI in frontoparietal network regions showed associations with sleep patterns that were stable across age. However, in default mode network regions, lGI was only associated with sleep patterns from late childhood through early-to-mid adolescence, a period of vulnerability for mental health disorders.

Conclusions

We detected both developmentally invariant and developmentally specific ties between local gyrification and naturalistic sleep patterns. Default mode network regions may be particularly susceptible to interventions promoting more optimal sleep during childhood and adolescence.

Habitual sleep and intraindividual variability of sleep in gifted children: an actigraphy study

STUDY OBJECTIVES

Giftedness is a multidimensional condition. It is increasingly put forward that gifted children (GC) could be a population at high risk for sleep problems. The current study investigated GC and typically developing children for their habitual sleep, night-to-night sleep variability, and parental reports of child sleep.

METHODS

The sample consisted of 62 GC (31 girls; mean age = 9.63 ± 1.71 years) and 62 typically developing children (31 girls; mean age = 9.68 ± 1.68 years). Groups were age and sex matched. Giftedness was identified using Renzulli's 3-factor definition of giftedness. Sleep duration, quality, and night-to-night variability were assessed using actigraphy. Parents were asked to complete the short-form version of the Children's Sleep Habits Questionnaire to report on their child's sleep. Groups were compared with independent sample t-tests and chi-square analyses.

RESULTS

GC displayed lower sleep efficiencies, more wake time after sleep onset, and more night-to-night sleep variability than typically developing children. GC were found to experience less social jetlag compared to typically developing children, and they also showed more clinically significant sleep problems as reported by parents.

CONCLUSIONS

Sleep maintenance and stability tend to be challenged in GC. While there is growing evidence that greater sleep variability is associated with poorer physical and emotional health, studies have yet to examine these associations in GC specifically to get a better understanding of giftedness. Overall, there is a need for research focused on both predictors and consequences of sleep patterns and sleep variability in GC.

CITATION

Bastien L, Théoret R, Bernier A, Godbout R. Habitual sleep and intraindividual variability of sleep in gifted children: an actigraphy study. J Clin Sleep Med. 2023;19(5):925-934.

Sleep Signal Analysis for Early Detection of Alzheimer's Disease and Related Dementia (ADRD)

OBJECTIVE

Alzheimer's Disease and Related Dementia (ADRD) is growing at alarming rates, putting research and development of diagnostic methods at the forefront of the biomedical research community. Sleep disorder has been proposed as an early sign of Mild Cognitive Impairment (MCI) in Alzheimer's disease. Although several clinical studies have been conducted to assess sleep and association with early MCI, reliable and efficient algorithms to detect MCI in home-based sleep studies are needed in order to address both healthcare costs and patient discomfort in hospital/lab-based sleep studies.

METHODS

In this paper, an innovative MCI detection method is proposed using an overnight recording of movements associated with sleep combined with advanced signal processing and artificial intelligence. A new diagnostic parameter is introduced which is extracted from the correlation between high frequency, sleep-related movements and respiratory changes during sleep. The newly defined parameter, Time-Lag (TL), is proposed as a distinguishing criterion that indicates movement stimulation of brainstem respiratory regulation that may modulate hypoxemia risk during sleep and serve as an effective parameter for early detection of MCI in ADRD. By implementing Neural Networks (NN) and Kernel algorithms with choosing TL as the principle component in MCI detection, high sensitivity (86.75% for NN and 65% for Kernel method), specificity (89.25% and 100%), and accuracy (88% and 82.5%) have been achieved.

Opal Actigraphy (Activity and Sleep) Measures Compared to ActiGraph: A Validation Study

Physical activity and sleep monitoring in daily life provide vital information to track health status and physical fitness. The aim of this study was to establish concurrent validity for the new Opal Actigraphy solution in relation to the widely used ActiGraph GT9X for measuring physical activity from accelerometry epic counts (sedentary to vigorous levels) and sleep periods in daily life. Twenty participants (age 56 + 22 years) wore two wearable devices on each wrist for 7 days and nights, recording 3-D accelerations at 30 Hz. Bland-Altman plots and intraclass correlation coefficients (ICCs) assessed validity (agreement) and test-retest reliability between ActiGraph and Opal Actigraphy sleep durations and activity levels, as well as between the two different versions of the ActiGraph. ICCs showed excellent reliability for physical activity measures and moderate-to-excellent reliability for sleep measures between Opal versus Actigraph GT9X and between GT3X versus GT9X. Bland-Altman plots and mean absolute percentage error (MAPE) also show a comparable performance (within 10%) between Opal and ActiGraph and between the two ActiGraph monitors across activity and sleep measures. In conclusion, physical activity and sleep measures using Opal Actigraphy demonstrate performance comparable to that of ActiGraph, supporting concurrent validation. Opal Actigraphy can be used to quantify activity and monitor sleep patterns in research and clinical studies.

Sleep Disturbances in Adolescents with Attention-Deficit/Hyperactivity Disorder

Introduction

Delayed sleep phase syndrome (DSPS) and insomnia disorders are prevalent in adolescents and are comorbid with attention-deficit/hyperactivity disorder (ADHD), but only limited information is available regarding the prevalence of DSPS and insomnia in adolescents with ADHD. Moreover, previous studies comparing objective sleep parameters averaged the findings across all participants of each group (ADHD, control) regardless of each individual's level of reported sleep disturbance. This might have resulted in inconsistency between information obtained by objective and subjective sleep measures in adolescents with ADHD. The objectives of the present study were 1) to compare the prevalence of risk for DSPS and insomnia in adolescents with ADHD and control adolescents in our samples; 2) to compare objectively measured sleep characteristics of adolescents with ADHD and controls while taking into consideration their levels of risk for DSPS or their level of insomnia; and 3) to compare the ADHD symptom levels of adolescents with moderate/high and low risk for DSPS or insomnia.

Methods

Seventy-three adolescents (37 ADHD, 36 controls) aged 12-15 years participated in a cross-sectional study. Actigraphy was used to characterize objective sleep parameters and parents' or adolescents' reports were used to characterize subjective sleep parameters.

Results

Of the participants in the ADHD and control groups, 33.33% and 27%, respectively, had moderate/high levels of risk for DSPS. Adolescents in the high-risk group for DSPS had an objectively measured delayed sleep schedule and more variable sleep duration, time in bed, and sleep efficiency compared to adolescents in the low-risk group for DSPS, regardless of their ADHD diagnosis. Adolescents with higher levels of insomnia spent more time in bed and had more variable sleep efficiency compared to adolescents with no insomnia, regardless of their diagnosis.

Conclusion

The prevalence of moderate/high risk for DSPS was similarly high in adolescents with ADHD and controls. Participants' subjective reports of sleep disturbances were consistent with their objective sleep parameters when the type and level of subjectively defined sleep disturbance were considered. ADHD symptom levels were not different in adolescents with moderate/high or low risk for DSPS or insomnia.

Comparison of the usability of an automatic sleep staging program via portable 1-channel electroencephalograph and manual sleep staging with traditional polysomnography

Automatic algorithms are a proposed alternative to manual assessment of polysomnography data for analyzing sleep structure; however, none are acceptably accurate for clinical use. We investigated the feasibility of an automated sleep stage scoring system called Sleep Scope, which is intended for use with portable 1-channel electroencephalograph, and compared it with the traditional polysomnography scoring method. Twenty-six outpatients and fourteen healthy volunteers underwent Sleep Scope and polysomnography assessments simultaneously. Polysomnography records were manually scored by three sleep experts. Sleep Scope records were scored using a dedicated auto-staging algorithm. Sleep parameters, including total sleep time, sleep latency, wake after sleep onset, and sleep efficiency, were calculated. The epoch-by-epoch pairwise concordance based on the classification of sleep into five stages (i.e., wake, rapid eye movement, N1, N2, and N3) was also evaluated after validating homogeneity and bias between Sleep Scope and polysomnography. Compared with polysomnography, Sleep Scope seemed to overestimate sleep latency by approximately 3 min, but there was no consistent tendency in bias in other sleep parameters. The Κ values ranged from 0.66 to 0.75 for experts' inter-rater polysomnography scores and from 0.62 to 0.67 for Sleep Scope versus polysomnography scores, which indicated sufficient agreement in the determination of sleep stages based on the Landis and Koch criteria. We observed sufficient concordance between Sleep Scope and polysomnography despite lower concordance in sleep disorder patients. Thus, this auto-staging system might serve as a novel clinical tool for reducing the time and expenses required of medical staff and patients.

Supplementary Information

The online version contains supplementary material available at 10.1007/s41105-022-00421-5.

Validation of Fitbit Charge 4 for assessing sleep in Chinese patients with chronic insomnia: A comparison against polysomnography and actigraphy

Our research aims to assess the performance of a new generation of consumer activity trackers (Fitbit Charge 4^TM: FBC) to measure sleep variables and sleep stage classifications in patients with chronic insomnia, compared to polysomnography (PSG) and a widely used actigraph (Actiwatch Spectrum Pro: AWS). We recruited 37 participants, all diagnosed with chronic insomnia disorder, for one night of sleep monitoring in a sleep laboratory using PSG, AWS, and FBC. Epoch-by-epoch analysis along with Bland–Altman plots was used to evaluate FBC and AWS against PSG for sleep-wake detection and sleep variables: total sleep time (TST), sleep efficiency (SE), waking after sleep onset (WASO), and sleep onset latency (SOL). FBC sleep stage classification of light sleep (LS), deep sleep (DS), and rapid eye movement (REM) was also compared to that of PSG. When compared with PSG, FBC notably underestimated DS (-41.4, p < 0.0001) and SE (-4.9%, p = 0.0016), while remarkably overestimating LS (37.7, p = 0.0012). However, the TST, WASO, and SOL assessed by FBC presented no significant difference from that assessed by PSG. Compared with PSG, AWS and FBC showed great accuracy (86.9% vs. 86.5%) and sensitivity (detecting sleep; 92.6% vs. 89.9%), but comparatively poor specificity (detecting wake; 35.7% vs. 62.2%). Both devices showed better accuracy in assessing sleep than wakefulness, with the same sensitivity but statistically different specificity. FBC supplied equivalent parameters estimation as AWS in detecting sleep variables except for SE. This research shows that FBC cannot replace PSG thoroughly in the quantification of sleep variables and classification of sleep stages in Chinese patients with chronic insomnia; however, the user-friendly and low-cost wearables do show some comparable functions. Whether FBC can serve as a substitute for actigraphy and PSG in patients with chronic insomnia needs further investigation.

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.

Cognitive Function Decline in the Third Trimester of Pregnancy Is Associated with Sleep Fragmentation

During late pregnancy, sleep deterioration is regularly observed. In concert with these observations, in previous studies by other researchers, a slight objective cognitive decline in pregnant women has been found. Sleep is essential for memory consolidation. The hypothesis of the study was that cognitive impairment could be related to sleep deterioration during pregnancy. The study included 19 pregnant women in their third trimester of pregnancy (28−40 weeks, median 33 weeks (IQR 32−37)) recruited at the Department of Gynecology and Obstetrics, Medical University of Warsaw, and 20 non-pregnant women as controls. The assessment was performed using the vocabulary subtest from the Wechsler Adult Intelligence Scale (WAIS), D2 Test of Attention, OSPAN task (Operational Span Task) to assess cognitive performance, actigraphy to examine sleep parameters, and a set of self-report instruments: Athens Insomnia Scale (AIS), Beck Depression Inventory (BDI), Ford Insomnia Response to Stress (FIRST), Regenstein Hyperarousal Scale (HS), and Epworth Sleepiness Scale (ESS). Although there were no differences between the groups in WAIS (p = 0.18), pregnant women had worse scores in working memory capacity (overall number of remembered letters: p = 0.012, WM span index: p = 0.004) and a significantly lower score in attention (p = 0.03). Pregnant women also had lower sleep efficiency (p = 0.001), more awakenings from sleep (p = 0.001), longer average awakenings (p < 0.0001), longer wake after sleep onset (WASO, p < 0.0001), and longer total time in bed (p < 0.0001). In psychological assessment, pregnant women had only a higher FIRST score (p = 0.02). Using mediation analysis, we found that frequent awakening might be the major factor contributing to deterioration in working memory performance, explaining almost 40% of the total effect. In conclusion, sleep fragmentation in the third trimester of pregnancy may impair working memory consolidation. Pregnant women often complain about poor daily performance as well as non-restorative sleep. In this study, we showed that there is a relationship between lower sleep quality in pregnancy and worse cognitive functioning. We can expect a cognitive decline in women with sleep disturbances in pregnancy. Therefore, we should pay more attention to the treatment of sleep disorders in pregnancy.

Comparing in-lab full polysomnography for diagnosing sleep apnea in children to home sleep apnea tests (HSAT) with an online video attending technician

The main study aim was to compare the validity of children sleep apnea data obtained from standard polysomnography (PSG) to a home sleep apnea test (HSAT) accompanied by an attending online video technician. Our study population was comprised of 100 children, 54 boys and 46 girls, ages 3–11 (average age 5.2, SD 1.2) assigned randomly either to in-lab full PSG or to a HSAT with real-time, online technical support to rule out obstructive sleep apnea (OSA). A t test comparison did not yield significant differences between data obtained from the in-lab PSG and HSAT with real-time, online, technical support for any of the following measures: Apnea–Hypopnea Index, Oxygen desaturation Index, baseline O2, or minimum O2 parameters. However, a significant difference was found for time in bed and total sleep time, which was significantly longer in the HAST. Online HSAT can provide a safe, convenient and a reliable way to perform sleep studies in young children for diagnosing OSA in their familiar home environment.

[Comparison and correlation analysis of sleep parameters between watch-type sleep monitor (Actiwatch) and polysomnography]

OBJECTIVE

With the rapid development of sleep medicine, there are various methods for detecting sleep diseases. This study compared the correlation between the lightweight watch-type sleep monitor (Actiwatch) and the "gold standard" polysomnography (PSG) in the Chinese population, in order to provide a basis for clinical application.

METHODS

From August 2018 to December 2019, 121 subjects who simultaneously performed sleep breathing monitoring (PSG) and wearing a watch-type sleep monitor (Actiwatch) in the Sleep Center of Peking University People's Hospital were enrolled. All subjects received PSG and Actiwatch at the same time, and filled out the sleep diary next morning. Monitoring indicators were collected for linear correlation analysis and paired t test to compare the differences.

RESULTS

Under low sensitivity conditions, the correlation coefficient of total sleep time (TST) between PSG and Actiwatch was 0.53 (P < 0.05). Paired t test analysis showed that there was no significant difference between the TSTs of Actiwatch and PSG (t=-0.890, P=0.36). According to age stratification, the smaller the age, the stronger the correlation between the TSTs of Actiwatch and PSG, and the coefficient could be up to 0.92 (P < 0.05). Paired t test showed that there was no significant difference between them (t=-1.057, P=0.35). According to the stratification by diagnosis, the correlation coefficient between the TSTs of Actiwatch and PSG in normal PSG group could be as high as 0.79 (P < 0.05), the results of paired t test showed that there was no significant difference between the TSTs of Actiwatch and PSG in normal PSG group (t=-0.784, P=0.44).

CONCLUSION

As a wearable home recorder, when the analysis parameters of Actiwatch were set as low sensitivity, PSG and Actiwatch had the highest TST correlation. The younger the age, the stronger correlation between the TSTs of Actiwatch and PSG. The PSG and Actiwatch subjects with normal PSG presentation had a higher TST correlation.

Protocol for targeting insomnia in school-aged children with autism spectrum disorder without intellectual disability: a randomised control trial

INTRODUCTION

Insomnia affects up to 80% of children with autism spectrum disorder (ASD). Negative consequences of insomnia in ASD include decreased quality of life (QOL), impaired learning and cognition, increased stereotypic and challenging behaviours, and increased parental stress. Cognitive behavioural treatment for childhood insomnia (CBT-CI) is a promising treatment for dealing with insomnia and its negative consequences but has not yet been studied in school-aged children with ASD and comorbid insomnia. Access to healthcare is another challenge for children with ASD, particularly in rural and underserved regions. Previous studies indicate that ASD and insomnia share common arousal-based underpinnings, and we hypothesise that CBT-CI will reduce the hyperarousal associated with insomnia and ASD. This trial will be the first to examine CBT-CI adapted for children with ASD and will provide new information about two different modes of delivery across a variety of primary and secondary child and parent sleep and related outcomes. Knowledge obtained from this trial might allow us to develop new or modify current treatments to better target childhood insomnia and ASD.

METHODS AND ANALYSIS

Children (N=180) 6-12 years of age with ASD and insomnia will be recruited from an established autism database, a paediatric clinic and community outreach in the Columbia, MO and surrounding areas. Participants will be randomised to CBT-CI adapted for children with ASD (in-person or remote using computers with cameras) or Sleep Hygiene and Related Education. Participants will be assessed at baseline, post-treatment, 6-month and 12-month follow-ups. The following assessments will be completed regarding the children: objective and subjective sleep, daytime functioning (adaptive functioning, attention, challenging behaviours, anxiety), QOL and physiological arousal (heart rate variability) and parents: objective and subjective sleep, daytime functioning (anxiety, depression, fatigue), QOL, physiological arousal and parental burden/stress.

ETHICS AND DISSEMINATION

Ethics approval was obtained in January 2020 from the University of Missouri. Ethics approval was obtained in July 2020 from the US Army Medical Research and Development Command, Office of Research Protections and Human Research Protection Office. All data are expected to be collected by 2024. Full trial results are planned to be published by 2025. Secondary analyses of baseline data will be subsequently published.

TRIAL REGISTRATION NUMBER

NCT04545606; Pre-results.

Objective Behavioral Measures in Children before, during, and after the COVID-19 Lockdown in Israel

Studies using questionnaires report that COVID-19 restrictions resulted in children spending significantly less time outdoors. This study used objective measures to assess the impact of pandemic-related restrictions on children’s behavior. A total of 19 healthy 8–12-year-old boys were observed before and during social restriction periods. Of these, 11 boys were reassessed after restrictions were lifted. For each session, Actiwatches were dispensed for measures of time outdoors, activity, and sleep. Changes overall and by school status were assessed using signed-rank test and Wilcoxon rank sum tests. During restrictions, children spent significantly less time outdoors (p = 0.001), were less active (p = 0.001), and spent less time engaged in moderate-to-vigorous physical activity (p = 0.004). Sleep duration was not significantly different between sessions (p > 0.99), but bedtime and wake time shifted to a later time during restrictions (p < 0.05 for both). Time outdoors and activity returned close to pre-pandemic levels after restrictions were lifted (p > 0.05 for both). Children’s behaviors significantly changed during the COVID-19 pandemic. The reduction in outdoor light exposure is of importance due to the role of light in the etiology of myopia and vitamin D production. The reduction in physical activity may have negative health effects in terms of obesity and depression, although further research is required to ascertain the long-term effects.

Later sleep timing predicts accelerated summer weight gain among elementary school children: a prospective observational study

OBJECTIVES AND BACKGROUND

Social demands of the school-year and summer environment may affect children's sleep patterns and circadian rhythms during these periods. The current study examined differences in children's sleep and circadian-related behaviors during the school-year and summer and explored the association between sleep and circadian parameters and change in body mass index (BMI) during these time periods.

METHODS

This was a prospective observational study with 119 children ages 5 to 8 years with three sequential BMI assessments: early school-year (fall), late school-year (spring), and beginning of the following school-year in Houston, Texas, USA. Sleep midpoint, sleep duration, variability of sleep midpoint, physical activity, and light exposure were estimated using wrist-worn accelerometry during the school-year (fall) and summer. To examine the effect of sleep parameters, physical activity level, and light exposure on change in BMI, growth curve modeling was conducted controlling for age, race, sex, and chronotype.

RESULTS

Children's sleep midpoint shifted later by an average of 1.5 h during summer compared to the school-year. After controlling for covariates, later sleep midpoints predicted larger increases in BMI during summer, (γ = .0004, p = .03), but not during the school-year. Sleep duration, sleep midpoint variability, physical activity levels, and sedentary behavior were not associated with change in BMI during the school-year or summer. Females tended to increase their BMI at a faster rate during summer compared to males, γ = .06, p = .049. Greater amounts of outdoor light exposure (γ = -.01, p = .02) predicted smaller increases in school-year BMI.

CONCLUSIONS

Obesity prevention interventions may need to target different behaviors depending on whether children are in or out of school. Promotion of outdoor time during the school-year and earlier sleep times during the summer may be effective obesity prevention strategies during these respective times.

Physical activity, lung function, and sleep outcomes in urban children with asthma

OBJECTIVES

To examine (1) whether daily declines in physical activity (PA) level and/or in lung function (FEV1) predict an asthma exacerbation in a sample of urban children with asthma, and (2) the association between number of sleep awakenings and decline in daytime PA in this group.

METHODS

In this sample of urban children aged 7-9 years with persistent asthma (N = 147), objective methods assessing lung function via a handheld spirometer and moderate-to-vigorous physical activity (MVPA) via accelerometry were measured over a 4-week period during the fall and early winter of each year as part of a larger 5-year study.

RESULTS

In the entire sample, a significant association between PA and lung function was noted such that a greater decline in daily MVPA was associated with lower odds of exacerbation. Ethnic group differences showed that this association was also significant only among Latino children (odds ratio [OR] = 0.98; 95% confidence interval [CI]:0.97-0.99). A greater number of sleep awakenings were associated with greater declines in daily MVPA among Latinos only (p = .05).

CONCLUSIONS

Results suggest that declining MVPA may contribute to lower risk for an exacerbation. Reasons for declining MVPA need to be further explored in this group. Children with asthma may avoid or be fearful of engaging in PA or may face early symptoms which influence patterns of PA, and this may minimize risk for an exacerbation. Results also suggest reasons for night-time disruptions may need to be targeted in further research or interventions as they can contribute to PA avoidance in this high-risk group.

Associations of the residential built environment with adolescent sleep outcomes

STUDY OBJECTIVES

Over 75% of US high school students obtain insufficient sleep, placing them at risk for adverse health outcomes. Identification of modifiable determinants of adolescent sleep is needed to inform prevention strategies, yet little is known about the influence of the built environment on adolescent sleep.

METHODS

In this prospective study, actigraphy was used to assess sleep outcomes among 110 adolescents for 14 days each in eighth and ninth grades: duration (hours/night), onset and offset, and sleeping ≥8 hours. Home addresses were linked to built environment exposures: sound levels, tree canopy cover, street density, intersection density, population density, and housing density. Mixed-effects regression estimated associations of built environment measures with sleep outcomes, adjusting for sex, race, parent education, household income, household size, grade, weeknight status, and neighborhood poverty.

RESULTS

A 1-standard deviation (SD) increase in neighborhood sound was associated with 16 minutes later sleep onset (β = 0.28; 95% confidence interval (CI): 0.06, 0.49) and 25% lower odds of sleeping for ≥8 hours (odds ratio (OR) = 0.75, 95% CI: 0.59, 0.96). A 1-SD increase in neighborhood tree canopy was associated with 18 minutes earlier sleep onset (β = -0.31, 95% CI: -0.49, -0.13) and 10 minutes earlier sleep offset (β= -0.17, 95% CI: -0.28, -0.05). No associations were observed for density-based exposures.

CONCLUSIONS

Higher neighborhood sound level was associated with lower odds of sufficient sleep, while higher tree canopy cover was associated with more favorable sleep timing. Neighborhood sound levels and tree canopy cover are potential targets for policies and interventions to support healthier sleep among adolescents.

Sleep in New Zealand children aged 7-9: associations with ethnicity, socioeconomic status, and achievement in reading and mathematics

STUDY OBJECTIVES

The aims were (1) to investigate differences by ethnicity and socioeconomic status (SES) in objective measures of sleep in children aged 7-9 years and (2) determine whether measures of sleep predict child achievement in reading or mathematics after controlling for ethnicity and SES.

METHODS

Four groups of parent-child dyads were recruited: Māori, low-SES schools (n = 18); Māori, high-SES schools (n = 17); New Zealand European, low-SES schools (n = 18); New Zealand European, high-SES schools (n = 17). Child sleep was measured by actigraphy. Parents and teachers reported child daytime sleepiness and behavior, and children completed a self-report of anxiety symptoms. Teachers also reported on child achievement in reading and mathematics.

RESULTS

Children from low-SES schools went to bed later on school nights (F[1,68] = 12.150, P = .001) and woke later (F[1,68] = 15.978, P < .001) than children from high-SES schools but had similar sleep duration. There were no differences related to ethnicity. Children from low-SES schools were almost 3 times more likely to be below national standards for mathematics. Children not meeting academic standards in mathematics had a later sleep start time, lower sleep period efficiency, and a decreased total sleep time. However, when SES and sleep period efficiency were modeled together neither were found to significantly influence achievement in mathematics.

CONCLUSIONS

In this study, SES influenced sleep timing but not the quality and quantity of sleep in 7- to 9-year-old children, and a significant independent effect of sleep efficiency on learning could not be demonstrated.

Similarities and differences between actigraphy and parent-reported sleep in a Hispanic and non-Hispanic White sample

OBJECTIVE

Despite concerns about the inaccuracy of parents' reports of children's sleep, it remains unclear whether the bias of parents' reports varies across racial/ethnic groups. To address this limitation, the current study systematically investigated the concordance among parent-reported sleep questionnaires, sleep diaries, and actigraphy-based sleep in a sample of Hispanic and non-Hispanic White children.

METHODS

Parents of 51 Hispanic and 38 non-Hispanic White children (N = 89; M_age = 6.46, SD = 0.62; 50.6% male) reported their child's bedtime and wake time on school days using sleep diaries and questionnaires. Children's sleep also was assessed with actigraphy for five consecutive school days.

RESULTS

Parents reported longer sleep duration, earlier bedtime, and later wake time using sleep diaries and questionnaires compared to actigraphy-based assessments. Larger discrepancies between diaries and actigraphy of sleep duration, and between questionnaires and actigraphy of wake time were found in non-Hispanic White children, compared to Hispanic children.

CONCLUSIONS

Although parents tended to overestimate their child's sleep as compared to actigraphy, parents of Hispanic children may be more accurate in some estimates of children's sleep than parents of non-Hispanic White children. Researchers, clinicians, and parents should be aware of the potential biases in parents' reports and estimates of their child's sleep and that the degree of bias could vary across racial/ethnic groups.

A Comparison of Self- and Proxy-Reported Subjective Sleep Durations With Objective Actigraphy Measurements in a Survey of Wisconsin Children 6-17 Years of Age

Children's sleep quality and duration are important to overall development, health, and wellbeing. However, measuring children's sleep is challenging, especially in situations where objective assessment is impractical. This study aimed to assess age and proxy effects in comparing subjective sleep duration with objective measures, in a community-based sample of Wisconsin children (aged 6-17 years), recruited from 2014-2017. The sample participants had a mean age of 11.4 (standard deviation, 3.3) years and 52% of them were male. We used linear mixed effects models to test for age effects in proxy- and self-report groups separately, and a quasiexperimental regression discontinuity approach to compare subjective sleep duration with objective actigraphy estimates across proxy- and self-report groups. We found evidence of systematic overestimation of sleep duration when using subjective measurements but did not find evidence of age effects in either group. Based on these analyses, we found evidence of differential overestimation by proxy- or self-report condition. Proxy reporters overestimated sleep duration by 2.3 hours (95% confidence interval: 2.2, 2.4), compared with 1.0 hour (95% confidence interval: 0.7, 1.2) for self-reporters. These findings suggest that proxy- versus self-reporting conditions are an important consideration when designing a study, and that it might be beneficial to reduce the age at which children self-report.

Validation Framework for Sleep Stage Scoring in Wearable Sleep Trackers and Monitors with Polysomnography Ground Truth

The rapid growth of point-of-care polysomnographic alternatives has necessitated standardized evaluation and validation frameworks. The current average across participant validation methods may overestimate the agreement between wearable sleep tracker devices and polysomnography (PSG) systems because of the high base rate of sleep during the night and the interindividual difference across the sampling population. This study proposes an evaluation framework to assess the aggregating differences of the sleep architecture features and the chronologically epoch-by-epoch mismatch of the wearable sleep tracker devices and the PSG ground truth. An AASM-based sleep stage categorizing method was proposed to standardize the sleep stages scored by different types of wearable trackers. Sleep features and sleep stage architecture were extracted from the PSG and the wearable device's hypnograms. Therefrom, a localized quantifier index was developed to characterize the local mismatch of sleep scoring. We evaluated different commonly used wearable sleep tracking devices with the data collected from 22 different subjects over 30 nights of 8-h sleeping. The proposed localization quantifiers can characterize the chronologically localized mismatches over the sleeping time. The outperformance of the proposed method over existing evaluation methods was reported. The proposed evaluation method can be utilized for the improvement of the sensor design and scoring algorithm.

Engineering a mobile platform to promote sleep in the pediatric primary care setting

Study Objectives

Pediatricians lack tools to support families at home for the promotion of childhood sleep. We are using the Multiphase Optimization Strategy (MOST) framework to guide the development of a mobile health platform for childhood sleep promotion. The objective of this study is to demonstrate feasibility of a mobile health platform towards treating children with insufficient sleep.

Methods

Children aged 10–12 years were enrolled (Study #1: N = 30; Study #2: N = 43). Participants wore a sleep tracker to measure sleep duration. Data were retrieved by a mobile health platform, programmed to send introductory messages during run-in (2 weeks) and goal achievement messages during intervention (7 weeks) periods. In study #1, participants were randomized to control, gain-framed incentive or loss-framed incentive arms. In study #2, participants were randomized to control, loss-framed incentive, normative feedback or loss-framed incentive plus normative feedback arms.

Results

In study #1, 1514 nights of data were captured (69%) and sleep duration during the intervention was higher by an average of 21 (95% CI: −8, 51) and 34 (95% CI: 7, 61) minutes per night for the gain-framed and loss-framed arms, respectively, compared to controls. In study #2, 2,689 nights of data were captured (81%), with no major differences in average sleep duration between the control and the loss-framed or normative feedback arms.

Conclusions

We have developed and deployed a mobile health platform that can capture sleep data and remotely communicate with families. Promising candidate intervention components will be further investigated under the optimization phase of the MOST framework.

Clinical Trials

Both studies included in this manuscript were registered at clinicaltrials.gov:

-Study #1: NCT03263338

-Study #2: NCT03426644

Comparison of multichannel and single-channel wrist-based devices with polysomnography to measure sleep in children and adolescents

STUDY OBJECTIVES

To compare sleep parameters produced by the Fitbit Charge 3 (Fitbit) and Actigraph GT9X accelerometer (Actigraph) to polysomnography in children and adolescents.

METHODS

Participants (n = 56, ages 9.2 ± 3.3 years) wore a Fitbit and an Actigraph on their nondominant wrist concurrently with polysomnography during an overnight observation at a children's sleep laboratory. Total sleep time, sleep efficiency, wake after sleep onset, sleep onset, and sleep offset were extracted from the Fitabase and Actilife software packages, respectively, with the Sadeh algorithm. Bland-Altman plots were used to assess the agreement between wearable devices and polysomnography.

RESULTS

Seventy-nine percent of participants were diagnosed with OSA. Compared with polysomnography, the Fitbit and the Actigraph underestimated total sleep time by 6.1 minutes (absolute mean bias [AMB] = 27.7 minutes) and 31.5 minutes (AMB = 38.2 minutes), respectively. The Fitbit overestimated sleep efficiency by 3.0% (AMB = 6.3%), and the Actigraph underestimated sleep efficiency by 12.9% (AMB = 13.2%). The Fitbit overestimated wake after sleep onset by 18.8 minutes (AMB = 23.9 minutes), and the Actigraph overestimated wake after sleep onset by 56.1 minutes (AMB = 54.7 minutes). In addition, the Fitbit and the Actigraph underestimated sleep onset by 1.2 minutes (AMB = 13.9 minutes) and 10.2 minutes (AMB = 18.1 minutes), respectively. Finally, the Fitbit and the Actigraph overestimated sleep offset by 6.0 minutes (AMB = 12.0 minutes) and 10.5 minutes (AMB = 12.6 minutes). Linear regression indicated significant trends, with the Fitbit underestimating wake after sleep onset and sleep efficiency at higher values.

CONCLUSIONS

The Fitbit provided comparable and in some instances better sleep estimates with polysomnography compared to the Actigraph. Findings support the use of multichannel devices to measure sleep in children and adolescents. Additional studies are needed in healthy children over several nights and in free-living settings.

Validity of a Novel Research-Grade Physical Activity and Sleep Monitor for Continuous Remote Patient Monitoring

In the midst of the COVID-19 pandemic, Remote Patient Monitoring technologies are highly important for clinicians and researchers. These connected-health technologies enable monitoring of patients and facilitate remote clinical trial research while reducing the potential for the spread of the novel coronavirus. There is a growing requirement for monitoring of the full 24 h spectrum of behaviours with a single research-grade sensor. This research describes a free-living and supervised protocol comparison study of the Verisense inertial measurement unit to assess physical activity and sleep parameters and compares it with the Actiwatch 2 actigraph. Fifteen adults (11 males, 23.4 ± 3.4 years and 4 females, 29 ± 12.6 years) wore both monitors for 2 consecutive days and nights in the free-living study while twelve adults (11 males, 23.4 ± 3.4 years and 1 female, 22 ± 0 years) wore both monitors for the duration of a gym-based supervised protocol study. Agreement of physical activity epoch-by-epoch data with activity classification of sedentary, light and moderate-to-vigorous activity and sleep metrics were evaluated using Spearman's rank-order correlation coefficients and Bland-Altman plots. For all activity, Verisense showed high agreement for both free-living and supervised protocol of r = 0.85 and r = 0.78, respectively. For physical activity classification, Verisense showed high agreement of sedentary activity of r = 0.72 for free-living but low agreement of r = 0.36 for supervised protocol; low agreement of light activity of r = 0.42 for free-living and negligible agreement of r = -0.04 for supervised protocol; and moderate agreement of moderate-to-vigorous activity of r = 0.52 for free-living with low agreement of r = 0.49 for supervised protocol. For sleep metrics, Verisense showed moderate agreement for sleep time and total sleep time of r = 0.66 and 0.54, respectively, but demonstrated high agreement for determination of wake time of r = 0.83. Overall, our results showed moderate-high agreement of Verisense with Actiwatch 2 for assessing epoch-by-epoch physical activity and sleep, but a lack of agreement for activity classifications. Future validation work of Verisense for activity cut-point potentially holds promise for 24 h continuous remote patient monitoring.

Sleep Assessments for Children With Severe Cerebral Palsy: A Scoping Review

Objectives

To identify the sleep-based instruments in postural care intervention research and examine whether the instruments are suitable as postural care outcome measures specifically for children with severe cerebral palsy.

Data Sources

Investigators searched the electronic databases from 2 university library systems, including OVID Medline, CINAHL, OT Search, Cochrane Database of Systematic Reviews, and Health and Psychosocial Instruments for articles published between 2000 and October 2019.

Study Selection

The initial search yielded 1928 abstracts. Two independent investigators identified 8 English-language peer-reviewed articles that published postural care intervention study results.

Data Extraction

Investigators screened the 8 articles and found that 6 included sleep as a primary or secondary intervention outcome. The principal investigator then fully reviewed these 6 publications, recorded their sleep-related instruments, and applied Coster’s published guidelines (2013) to analyze the sleep-based instruments' suitability as outcome measures.

Data Synthesis:

Collectively, the 6 studies used 8 distinct measures, 6 of which (actigraphy, Chailey Sleep Questionnaire, Pediatric Sleep Questionnaire, polysomnography, sleep diary, and Sleep Disturbance Scale for Children) underwent analysis. As stand-alone instruments, none completely met criteria for suitability as outcome measures for those with severe cerebral palsy.

Conclusions

Combined use of the Sleep Disturbance Scale for Children and actigraphy may be favorable for assessing the sleep-related domains relevant to children with severe cerebral palsy. However, rehabilitation professionals should test sensitivity and specificity to understand the instruments’ ability for capturing changes in sleep from postural care intervention.

Actigraphy-Based Assessment of Sleep Parameters

Actigraphy, a method for inferring sleep/wake patterns based on movement data gathered using actigraphs, is increasingly used in population-based epidemiologic studies because of its ability to monitor activity in natural settings. Using special software, actigraphic data are analyzed to estimate a range of sleep parameters. To date, despite extensive application of actigraphs in sleep research, published literature specifically detailing the methodology for derivation of sleep parameters is lacking; such information is critical for the appropriate analysis and interpretation of actigraphy data. Reporting of sleep parameters has also been inconsistent across studies, likely reflecting the lack of consensus regarding the definition of sleep onset and offset. In addition, actigraphy data are generally underutilized, with only a fraction of the sleep parameters generated through actigraphy routinely used in current sleep research. The objectives of this paper are to review existing algorithms used to estimate sleep/wake cycles from movement data, demonstrate the rules/methods used for estimating sleep parameters, provide clear technical definitions of the parameters, and suggest potential new measures that reflect intraindividual variability. Utilizing original data collected using Motionlogger Sleep Watch (Ambulatory Monitoring Inc., Ardsley, NY), we detail the methodology and derivation of 29 nocturnal sleep parameters, including those both widely and rarely utilized in research. By improving understanding of the actigraphy process, the information provided in this paper may help: ensure appropriate use and interpretation of sleep parameters in future studies; enable the recalibration of sleep parameters to address specific goals; inform the development of new measures; and increase the breadth of sleep parameters used.

Developmental effects on sleep-wake patterns in infants receiving a cow's milk-based infant formula with an added prebiotic blend: a Randomized Controlled Trial

BACKGROUND

Few studies have evaluated nutritive effects of prebiotics on infant behavior state, physiology, or metabolic status.

METHODS

In this double-blind randomized study, infants (n = 161) received cow's milk-based infant formula (Control) or similar formula with an added prebiotic blend (polydextrose and galactooligosaccharides [PDX/GOS]) from 14-35 to 112 days of age. Infant wake behavior (crying/fussing, awake/content) and 24-h sleep-wake actograms were analyzed (Baseline, Days 70 and 112). Salivary cortisol was immunoassayed (Days 70 and 112). In a subset, exploratory stool 16S ribosomal RNA-sequencing was analyzed (Baseline, Day 112).

RESULTS

One hundred and thirty-one infants completed the study. Average duration of crying/fussing episodes was similar at Baseline, significantly shorter for PDX/GOS vs. Control at Day 70, and the trajectory continued at Day 112. Latency to first and second nap was significantly longer for PDX/GOS vs. Control at Day 112. Cortisol awakening response was demonstrated at Days 70 and 112. Significant stool microbiome beta-diversity and individual taxa abundance differences were observed in the PDX/GOS group.

CONCLUSIONS

Results indicate faster consolidation of daytime waking state in infants receiving prebiotics and support home-based actigraphy to assess early sleep-wake patterns. A prebiotic effect on wake organization is consistent with influence on the gut-brain axis and warrants further investigation.

IMPACT

Few studies have evaluated nutritive effects of prebiotics on infant behavior state, cortisol awakening response, sleep-wake entrainment, and gut microbiome. Faster consolidation of daytime waking state was demonstrated in infants receiving a prebiotic blend in infant formula through ~4 months of age. Shorter episodes of crying were demonstrated at ~2 months of age (time point corresponding to age/developmental range associated with peak crying) in infants receiving formula with added prebiotics. Results support home-based actigraphy as a suitable method to assess early sleep-wake patterns. Prebiotic effect on wake organization is consistent with influence on the gut-brain axis and warrants further investigation.

The Validity, Reliability, and Feasibility of Measurement Tools Used to Assess Sleep of Pre-school Aged Children: A Systematic Rapid Review

Background: Sleep of pre-school aged children is important for their health and development, but there are currently no standards for measuring sleep in this age group. We aimed to examine the validity, reliability and feasibility of tools used to assess sleep of pre-school aged children. Methods: Studies were eligible for inclusion if they examined the validity and/or reliability and/or feasibility of a measurement tool used to examine sleep of pre-school aged children (aged 3-7 years). We systematically searched six electronic databases, grey literature and trial registries. We manually searched topic specific journals, reference and citations of included studies, and reference lists of existing reviews. We extracted data and conducted a risk of bias assessment on the included studies using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) risk of bias checklist. We used a narrative synthesis to present the results. Results: Sixteen studies met the inclusion criteria: these explored accelerometers (n = 3) and parental reported tools (n = 13; nine questionnaires, six diaries). Studies assessed construct validity (n = 3), criterion validity (n = 1), convergent validity (n = 13), test-retest reliability (n = 2), internal consistency (n = 4) and feasibility (n = 12). Most studies assessed the convergent validity of questionnaires and diaries compared with accelerometers, but the validity of accelerometers for sleep in this age group is unknown. Of studies with a low risk of bias, one sleep diary was shown to be valid for measuring sleep duration. No measurement tools were appropriate for determining sleep quality. Reporting of reliability and feasibility was minimal. Discussion: The evidence base in this field is limited, and most studies had high risk of bias. Future research on sleep in pre-school aged children should focus on assessing the validity, reliability and feasibility of accelerometers, which in turn will improve the quality of studies that assess questionnaires and diaries against accelerometers. Systematic Review Registration: https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021230900; PROSPERO: CRD42021230900.

Multi-Night Validation of a Sleep Tracking Ring in Adolescents Compared with a Research Actigraph and Polysomnography

BACKGROUND

Wearable devices have tremendous potential for large-scale longitudinal measurement of sleep, but their accuracy needs to be validated. We compared the performance of the multisensor Oura ring (Oura Health Oy, Oulu, Finland) to polysomnography (PSG) and a research actigraph in healthy adolescents.

METHODS

Fifty-three adolescents (28 females; aged 15-19 years) underwent overnight PSG monitoring while wearing both an Oura ring and Actiwatch 2 (Philips Respironics, USA). Measurements were made over multiple nights and across three levels of sleep opportunity (5 nights with either 6.5 or 8h, and 3 nights with 9h). Actiwatch data at two sensitivity settings were analyzed. Discrepancies in estimated sleep measures as well as sleep-wake, and sleep stage agreements were evaluated using Bland-Altman plots and epoch-by-epoch (EBE) analyses.

RESULTS

Compared with PSG, Oura consistently underestimated TST by an average of 32.8 to 47.3 minutes (Ps < 0.001) across the different TIB conditions; Actiwatch 2 at its default setting underestimated TST by 25.8 to 33.9 minutes. Oura significantly overestimated WASO by an average of 30.7 to 46.3 minutes. It was comparable to Actiwatch 2 at default sensitivity in the 6.5, and 8h TIB conditions. Relative to PSG, Oura significantly underestimated REM sleep (12.8 to 19.5 minutes) and light sleep (51.1 to 81.2 minutes) but overestimated N3 by 31.5 to 46.8 minutes (Ps < 0.01). EBE analyses demonstrated excellent sleep-wake accuracies, specificities, and sensitivities - between 0.88 and 0.89 across all TIBs.

CONCLUSION

The Oura ring yielded comparable sleep measurement to research grade actigraphy at the latter's default settings. Sleep staging needs improvement. However, the device appears adequate for characterizing the effect of sleep duration manipulation on adolescent sleep macro-architecture.

Changes in Sleep Duration and Timing During the Middle-to-High School Transition

PURPOSE

The purpose of the study was to quantify changes in sleep during the middle-to-high school transition and determine if changes in sleep differ by sociodemographic characteristics.

METHODS

Adolescents were enrolled in eighth grade and followed into ninth grade (N = 110; 2,470 nights observed). The outcomes were actigraphy-estimated sleep duration, sleep onset, sleep offset, and sleep sufficiency (≥8 hours of sleep). The exposures were school grade (eighth or ninth), school night status (school or nonschool), sex (female or male), and race (white, black, or other).

RESULTS

On school nights, sleep duration declined by 25.8 minutes per night (p < .001) from eighth to ninth grade. There was no change in sleep duration on nonschool nights. Timing of sleep onset was 22.2 minutes later on school nights (p < .001) and 17.4 minutes later on nonschool nights (p < .001) in ninth grade. Timing of sleep offset did not change on school mornings but was 22.2 minutes later on nonschool mornings (p < .001) in ninth grade. The proportion of school nights (and nonschool nights) with sleep duration ≥8 hours was 9.4% (38.3%) in eighth grade and 5.7% (35.9%) in ninth grade. The odds of sleeping ≥8 hours per night was 42% lower in ninth grade, compared toeighth grade (odds ratio = .58; 95% confidence interval: .37, .91). Males were 59% less likely to sleep ≥8 hours per night. Black adolescents were 51% less likely to sleep ≥8 hours per night.

CONCLUSIONS

Insufficient sleep is highly prevalent, especially on school nights and among male and black adolescents, and this problem worsens with the transition to high school.

Experimental sleep loss, racial bias, and the decision criterion to shoot in the Police Officer's Dilemma task

Violent behavior, police brutality, and racial discrimination are currently at the forefront of society’s attention, and they should be. We investigated whether mild sleep loss—as typical for many adults throughout the work week—could aggravate the socio-emotional-cognitive processes contributing to violence and discrimination. In a sample of 40 healthy young adults, we either experimentally restricted participants’ sleep for four nights (6.2 h/night) or let participants obtain normal sleep (7.7 h/night)—and then had them complete the Police Officer’s Dilemma Task. In this computerized task, the participant must rapidly decide to shoot or not shoot at White and Black men who either are or are not holding a gun. Results showed significant racial biases, including more and quicker shooting of Black targets compared to White targets. Furthermore, signal detection analyses demonstrated that mild sleep restriction changed participants’ decision criterion, increasing the tendency to shoot, even when controlling for psychomotor vigilance, fluid intelligence, and self-reported desirability to behave in a socially acceptable manner. The increased tendency to shoot was also observed in participants who reported believing that they had adapted to the sleep loss. Future experimental research using trained police officers will help establish the generalizability of these laboratory effects. Importantly, sleep loss is modifiable via organization-level changes (e.g., shift scheduling, light entrainment) and individual-level interventions (e.g., sleep hygiene education, incentives for behavioral change), suggesting that if sleep loss is corrected, it could save lives—including Black lives.

Sleep assessment by means of a wrist actigraphy-based algorithm: agreement with polysomnography in an ambulatory study on older adults

The purpose of the present work is to examine, on a clinically diverse population of older adults (N = 46) sleeping at home, the performance of two actigraphy-based sleep tracking algorithms (i.e., Actigraphy-based Sleep algorithm, ACT-S1 and Sadeh's algorithm) compared to manually scored electroencephalography-based PSG (PSG-EEG). ACT-S1 allows for a fully automatic identification of sleep period time (SPT) and within the identified sleep period, the sleep-wake classification. SPT detected by ACT-S1 did not differ statistically from using PSG-EEG (bias = -9.98 min; correlation 0.89). In sleep-wake classification on 30-s epochs within the identified sleep period, the new ACT-S1 presented similar or slightly higher accuracy (83-87%), precision (86-89%) and F1 score (90-92%), significantly higher specificity (39-40%), and significantly lower, but still high, sensitivity (96-97%) compared to Sadeh's algorithm, which achieved 99% sensitivity as the only measure better than ACT-S1's. Total sleep times (TST) estimated with ACT-S1 and Sadeh's algorithm were higher, but still highly correlated to PSG-EEG's TST. Sleep quality metrics of sleep period efficiency and wake-after-sleep-onset computed by ACT-S1 were not significantly different from PSG-EEG, while the same sleep quality metrics derived by Sadeh's algorithm differed significantly from PSG-EEG. Agreement between ACT-S1 and PSG-EEG reached was highest when analyzing the subset of subjects with least disrupted sleep (N = 28). These results provide evidence of promising performance of a full-automation of the sleep tracking procedure with ACT-S1 on older adults. Future longitudinal validations across specific medical conditions are needed. The algorithm's performance may further improve with integrating multi-sensor information.

Engineering a Mobile Platform to Promote Sleep in the Pediatric Primary Care Setting

Background

Pediatricians lack tools to support families at home for the promotion of childhood sleep. We are using the Multiphase Optimization Strategy (MOST) framework to guide the development of a mobile health platform for childhood sleep promotion.

Purpose

Under the preparation phase of the MOST framework, to demonstrate feasibility of a mobile health platform towards treating children with insufficient sleep.

Methods

Children aged 10-12y were enrolled (Study #1: N=30; Study #2: N=43). Participants wore a sleep tracker to measure sleep duration. Data were retrieved by a mobile health platform, programmed to send introductory messages during run-in (2 weeks) and goal achievement messages during intervention (7 weeks) periods. In study #1, participants were randomized to control, gain-framed incentive or loss-framed incentive arms. In study #2, participants were randomized to control, loss-framed incentive, normative feedback or loss-framed incentive plus normative feedback arms.

Results

In study #1, 1,514 nights of data were captured (69%) and sleep duration during the intervention was higher by an average of 21 (95% CI: -8, 51) and 34 (95% CI: 7, 61) minutes per night for the gain-framed and loss-framed arms, respectively, compared to controls. In study #2, 2,689 nights of data were captured (81%), with no major differences in average sleep duration between the control and the loss-framed or normative feedback arms.

Conclusion

We have developed and deployed a mobile health platform that can capture sleep data and remotely communicate with families. Promising candidate intervention components will be further investigated under the optimization phase of the MOST framework.

Sleep Tracking of a Commercially Available Smart Ring and Smartwatch Against Medical-Grade Actigraphy in Everyday Settings: Instrument Validation Study

BACKGROUND

Assessment of sleep quality is essential to address poor sleep quality and understand changes. Owing to the advances in the Internet of Things and wearable technologies, sleep monitoring under free-living conditions has become feasible and practicable. Smart rings and smartwatches can be employed to perform mid- or long-term home-based sleep monitoring. However, the validity of such wearables should be investigated in terms of sleep parameters. Sleep validation studies are mostly limited to short-term laboratory tests; there is a need for a study to assess the sleep attributes of wearables in everyday settings, where users engage in their daily routines.

OBJECTIVE

This study aims to evaluate the sleep parameters of the Oura ring along with the Samsung Gear Sport watch in comparison with a medically approved actigraphy device in a midterm everyday setting, where users engage in their daily routines.

METHODS

We conducted home-based sleep monitoring in which the sleep parameters of 45 healthy individuals (23 women and 22 men) were tracked for 7 days. Total sleep time (TST), sleep efficiency (SE), and wake after sleep onset (WASO) of the ring and watch were assessed using paired t tests, Bland-Altman plots, and Pearson correlation. The parameters were also investigated considering the gender of the participants as a dependent variable.

RESULTS

We found significant correlations between the ring's and actigraphy's TST (r=0.86; P<.001), WASO (r=0.41; P<.001), and SE (r=0.47; P<.001). Comparing the watch with actigraphy showed a significant correlation in TST (r=0.59; P<.001). The mean differences in TST, WASO, and SE of the ring and actigraphy were within satisfactory ranges, although there were significant differences between the parameters (P<.001); TST and SE mean differences were also within satisfactory ranges for the watch, and the WASO was slightly higher than the range (31.27, SD 35.15). However, the mean differences of the parameters between the watch and actigraphy were considerably higher than those of the ring. The watch also showed a significant difference in TST (P<.001) between female and male groups.

CONCLUSIONS

In a sample population of healthy adults, the sleep parameters of both the Oura ring and Samsung watch have acceptable mean differences and indicate significant correlations with actigraphy, but the ring outperforms the watch in terms of the nonstaging sleep parameters.

Kids' Outcomes And Long-term Abilities (KOALA): protocol for a prospective, longitudinal cohort study of mild traumatic brain injury in children 6 months to 6 years of age

INTRODUCTION

Mild traumatic brain injury (mTBI) is highly prevalent, especially in children under 6 years. However, little research focuses on the consequences of mTBI early in development. The objective of the Kids' Outcomes And Long-term Abilities (KOALA) study is to document the impact of early mTBI on children's motor, cognitive, social and behavioural functioning, as well as on quality of life, stress, sleep and brain integrity.

METHODS AND ANALYSES

KOALA is a prospective, multicentre, longitudinal cohort study of children aged 6 months to 6 years at the time of injury/recruitment. Children who sustain mTBI (n=150) or an orthopaedic injury (n=75) will be recruited from three paediatric emergency departments (PEDs), and compared with typically developing children (community controls, n=75). A comprehensive battery of prognostic and outcome measures will be collected in the PED, at 10 days, 1, 3 and 12 months postinjury. Biological measures, including measures of brain structure and function (magnetic resonance imaging, MRI), stress (hair cortisol), sleep (actigraphy) and genetics (saliva), will complement direct testing of function using developmental and neuropsychological measures and parent questionnaires. Group comparisons and predictive models will test the a priori hypotheses that, compared with children from the community or with orthopaedic injuries, children with mTBI will (1) display more postconcussive symptoms and exhibit poorer motor, cognitive, social and behavioural functioning; (2) show evidence of altered brain structure and function, poorer sleep and higher levels of stress hormones. A combination of child, injury, socioenvironmental and psychobiological factors are expected to predict behaviour and quality of life at 1, 3 and 12 months postinjury.

ETHICS AND DISSEMINATION

The KOALA study is approved by the Sainte-Justine University Hospital, McGill University Health Centre and University of Calgary Conjoint Health Research Ethics Boards. Parents of participants will provide written consent. Dissemination will occur through peer-reviewed journals and an integrated knowledge translation plan.

Performance of a commercial multi-sensor wearable (Fitbit Charge HR) in measuring physical activity and sleep in healthy children

PURPOSE

This study sought to assess the performance of the Fitbit Charge HR, a consumer-level multi-sensor activity tracker, to measure physical activity and sleep in children.

METHODS

59 healthy boys and girls aged 9-11 years old wore a Fitbit Charge HR, and accuracy of physical activity measures were evaluated relative to research-grade measures taken during a combination of 14 standardized laboratory- and field-based assessments of sitting, stationary cycling, treadmill walking or jogging, stair walking, outdoor walking, and agility drills. Accuracy of sleep measures were evaluated relative to polysomnography (PSG) in 26 boys and girls during an at-home unattended PSG overnight recording. The primary analyses included assessment of the agreement (biases) between measures using the Bland-Altman method, and epoch-by-epoch (EBE) analyses on a minute-by-minute basis.

RESULTS

Fitbit Charge HR underestimated steps (~11.8 steps per minute), heart rate (~3.58 bpm), and metabolic equivalents (~0.55 METs per minute) and overestimated energy expenditure (~0.34 kcal per minute) relative to research-grade measures (p< 0.05). The device showed an overall accuracy of 84.8% for classifying moderate and vigorous physical activity (MVPA) and sedentary and light physical activity (SLPA) (sensitivity MVPA: 85.4%; specificity SLPA: 83.1%). Mean estimates of bias for measuring total sleep time, wake after sleep onset, and heart rate during sleep were 14 min, 9 min, and 1.06 bpm, respectively, with 95.8% sensitivity in classifying sleep and 56.3% specificity in classifying wake epochs.

CONCLUSIONS

Fitbit Charge HR had adequate sensitivity in classifying moderate and vigorous intensity physical activity and sleep, but had limitations in detecting wake, and was more accurate in detecting heart rate during sleep than during exercise, in healthy children. Further research is needed to understand potential challenges and limitations of these consumer devices.

Toward standardizing the clinical testing protocols of point-of-care devices for obstructive sleep apnea diagnosis

PURPOSE

In recent years, point-of-care (POC) devices, especially smart wearables, have been introduced to provide a cost-effective, comfortable, and accessible alternative to polysomnography (PSG)-the current gold standard-for the monitoring, screening, and diagnosis of obstructive sleep apnea (OSA). Thorough validation and human subject testing are essential steps in the translation of these device technologies to the market. However, every device development group tests their device in their own way. No standard guidelines exist for assessing the performance of these POC devices. The purpose of this paper is to critically distill the key aspects of the various protocols reported in the literature and present a protocol that unifies the best practices for testing wearable and other POC devices for OSA.

METHODS

A limited review and graphical descriptive analytics of literature-including journal articles, web sources, and clinical manuscripts by authoritative agencies in sleep medicine-are performed to glean the testing and validation methods employed for POC devices, specifically for OSA.

RESULTS

The analysis suggests that the extent of heterogeneity of the demographics, the performance metrics, subject survey, hypotheses, and statistical analyses need to be carefully considered in a systematic protocol for testing POC devices for OSA.

CONCLUSION

We provide a systematic method and list specific recommendations to extensively assess various performance criteria for human subject testing of POC devices. A rating scale of 1-3 is provided to encourage studies to put a focus on addressing the key elements of a testing protocol.

Wearable Device-Independent Next Day Activity and Next Night Sleep Prediction for Rehabilitation Populations

Wearable sensor-based devices are increasingly applied in free-living and clinical settings to collect fine-grained, objective data about activity and sleep behavior. The manufacturers of these devices provide proprietary software that labels the sensor data at specified time intervals with activity and sleep information. If the device wearer has a health condition affecting their movement, such as a stroke, these labels and their values can vary greatly from manufacturer to manufacturer. Consequently, generating outcome predictions based on data collected from patients attending inpatient rehabilitation wearing different sensor devices can be challenging, which hampers usefulness of these data for patient care decisions. In this article, we present a data-driven approach to combining datasets collected from different device manufacturers. With the ability to combine datasets, we merge data from three different device manufacturers to form a larger dataset of time series data collected from 44 patients receiving inpatient therapy services. To gain insights into the recovery process, we use this dataset to build models that predict a patient's next day physical activity duration and next night sleep duration. Using our data-driven approach and the combined dataset, we obtained a normalized root mean square error prediction of 9.11% for daytime physical activity and 11.18% for nighttime sleep duration. Our sleep result is comparable to the accuracy we achieved using the manufacturer's sleep labels (12.26%). Our device-independent predictions are suitable for both point-of-care and remote monitoring applications to provide information to clinicians for customizing therapy services and potentially decreasing recovery time.

Sleep in Myopic and Non-Myopic Children

Purpose

To examine differences in sleep between myopic and non-myopic children.

Methods

Objective measurements of sleep, light exposure, and physical activity were collected from 91 children, aged 10 to 15 years, for two 14-day periods approximately 6 months apart. Sleep parameters were analyzed with respect to refractive error, season, day of the week, age, and sex.

Results

Myopic children exhibited differences in sleep duration by day of the week (P < 0.001) and season (P = 0.007). Additionally, myopic children exhibited shorter sleep latency than non-myopic children (P = 0.04). For all children, wake time was later (P < 0.001) and sleep duration was longer (P = 0.03) during the cooler season compared with the warmer season. On weekends, children went to bed later (P < 0.001), woke up later (P < 0.001), and had increased sleep duration (P < 0.001) than on weekdays. Younger children exhibited earlier bedtime (P = 0.005) and wake time (P = 0.01) than older children. Time spent outdoors was positively associated with sleep duration (P = 0.03), and daily physical activity was negatively associated with wake time (P < 0.001).

Conclusions

Myopic children tended to have more variable sleep duration and shorter latency than non-myopic children. Sleep patterns were influenced by season, day of the week, age, time outdoors, and activity.

Translational Relevance

Myopic children tended to have more variable sleep duration and shorter latency than non-myopic children, which may reflect previously reported differences in environmental and behavioral factors between refractive error groups.

Actigraphy in sleep research with infants and young children: Current practices and future benefits of standardized reporting

Actigraphy is a cost‐efficient method to estimate sleep–wake patterns over long periods in natural settings. However, the lack of methodological standards in actigraphy research complicates the generalization of outcomes. A rapidly growing methodological diversity is visible in the field, which increasingly necessitates the detailed reporting of methodology. We address this problem and evaluate the current state of the art and recent methodological developments in actigraphy reporting with a special focus on infants and young children. Through a systematic literature search on PubMed (keywords: sleep, actigraphy, child *, preschool, children, infant), we identified 126 recent articles (published since 2012), which were classified and evaluated for reporting of actigraphy. Results show that all studies report on the number of days/nights the actigraph was worn. Reporting was good with respect to device model, placement and sleep diary, whereas reporting was worse for epoch length, algorithm, artefact identification, data loss and definition of variables. In the studies with infants only (n = 58), the majority of articles (62.1%) reported a recording of actigraphy that was continuous across 24 hr. Of these, 23 articles (63.9%) analysed the continuous 24‐hr data and merely a fifth used actigraphy to quantify daytime sleep. In comparison with an evaluation in 2012, we observed small improvements in reporting of actigraphy methodology. We propose stricter adherence to standards in reporting methodology in order to streamline actigraphy research with infants and young children, to improve comparability and to facilitate big data ventures in the sleep community.

Disentangling the Direction of Associations between Sleep and Temperament in Toddlers

OBJECTIVES/BACKGROUND

Although much research has investigated the associations between children's sleep and their temperament, the direction of these associations remains unclear, largely due to a lack of longitudinal studies with repeated assessments of both sleep and temperament. Aiming to clarify the temporal precedence of these two constructs, the current study investigated reciprocal associations between toddlers' sleep and temperament with a longitudinal design.

PARTICIPANTS

The sample consisted of 82 toddlers (39 girls) assessed twice.

METHODS

At both 2 (M = 25.23 months; SD = 1.11) and 3 years of age (M = 36.81 months; SD = 0.91), toddlers' sleep duration and quality were assessed using actigraphy and their temperament was reported by their mothers with the Toddler Behavior Assessment Questionnaire.

RESULTS

Shorter nighttime sleep duration (ß = - .28, p = .03) and lower sleep efficiency (ß = - .33, p = .01) at 2 years predicted more temperamental proneness to anger at 3 years, while greater temperamental social fear at 2 years was predictive of shorter 24-hour (ß = - .44, p = .02) and nighttime (ß = - .36, p = .04) sleep duration at 3 years. Associations between temperamental activity level and sleep variables were non-significant.

CONCLUSION

The direction of the associations between toddlers' sleep and their temperament may vary according to which dimension of temperament is considered. These findings should encourage practitioners to identify the beginning of the causal chain leading to sleep or temperamental difficulties so as to develop well-tailored intervention plans.

Associations Between Objective Sleep Behaviors and Blood Glucose Variability in Young Children With Type 1 Diabetes

BACKGROUND

Young children with Type 1 diabetes (T1D) are at risk for extreme blood glucose variability, a risk factor for suboptimal glycated hemoglobin A1c (HbA1c) and long-term health complications. We know that a reciprocal relationship exists between sleep and glycemic outcomes in older youth with T1D; however, little research has examined objective sleep in young children (<7 years) with T1D.

PURPOSE

This study examines bidirectional associations between sleep behaviors and glycemic variability in young children with T1D.

METHODS

Thirty-nine young children with T1D (Mage 4.33 ± 1.46 years; MHbA1c 8.10 ± 1.06%) provided accelerometry data to objectively measure sleep onset latency, number of nighttime awakenings, and total sleep time. We also assessed HbA1c, average blood glucose, and glycemic variability (i.e., standard deviation of blood glucose from device downloads). We evaluated bidirectional relationships using multilevel modeling in SAS, with weekday/weekend as a Level 2 moderator.

RESULTS

Children averaged 8.5 ± 1.44 hr of sleep per night, but only 12.8% met current sleep recommendations. Children experienced more nighttime awakenings, higher blood glucose, and more glycemic variability on weekends. Sleep onset latency and nighttime awakenings predicted greater glycemic variability on weekends, and weekend glycemic variability predicted increased nighttime awakenings.

CONCLUSIONS

Most young children with T1D did not meet sleep recommendations. Young children experienced more nighttime awakenings, higher blood glucose, and increased glycemic variability on weekends only, when routines may be less predictable. Findings suggest that one way families of young children with T1D may be able to decrease glycemic variability is to keep consistent routines on weekdays and weekends.