Interindividual and intraindividual variability in adolescent sleep patterns across an entire school term: A pilot study

Sleep health, its intraindividuality, and perceived stress in college students during the COVID-19 pandemic

Objective: To describe the changes in sleep health domains and examine the associations between the repeated measures and intraindividual variability (IIV) of these domains and perceived stress. Participants: A diverse racial and ethnic group of first-year college students (N = 23, 78.3% female, aged 17-18) attending in-person classes during the COVID-19 pandemic. Methods: Sleep health domains were determined using 7-day wrist actigraph and daily sleep diaries, and perceived stress scale was completed at 1-month intervals across 3 months. Results: Sleep timing, regularity, and alertness during daytime demonstrated statistically significant changes between three timepoints. Greater stress was associated with more irregularity (B = 2.25 [.87-3.62], p < .001), more dissatisfaction in sleep (B = .04 [.02-.19], p < .01), alertness during daytime (B = .18 [.05-.31], p < .001), and greater IIV (ie, fluctuations) in sleep satisfaction (B = .083 [.02, .15], p < .01). Conclusion: These findings offer insights for future researchers to facilitate intervention development to promote mental and sleep health among college students.

Seasonal and Weekly Patterns of Korean Adolescents' Web Search Activity on Insomnia: Retrospective Study

BACKGROUND

Sleep deprivation in adolescents is a common but serious public health issue. Adolescents often have a progressive circadian delay and suffer from insufficient sleep during weekdays due to the school schedule. Temporal patterns in internet search activity data can provide relevant information for understanding the characteristic sleep problems of the adolescent population.

OBJECTIVE

We aimed to reveal whether adolescents exhibit distinct temporal seasonal and weekly patterns in internet search activity on insomnia compared to adults.

METHODS

We hypothesized that adolescents exhibit larger variations in the internet search volume for insomnia, particularly in association with the school schedule (e.g., academic vacations and weekends). We extracted the daily search volume for insomnia in South Korean adolescents (13-18 years old), adults (19-59 years old), and young adults (19-24 years old) during the years 2016-2019 using NAVER DataLab, the most popular search engine in South Korea. The daily search volume data for each group were normalized with the annual median of each group. The time series of the search volume was decomposed into slow fluctuation (over a year) and fast fluctuation (within a week) using fast Fourier transform. Next, we compared the normalized search volume across months in a year (slow fluctuation) and days in a week (fast fluctuation).

RESULTS

In the annual trend, 2-way ANOVA revealed a significant (group) × (month) interaction (P<.001). Adolescents exhibited much greater seasonal variations across a year than the adult population (coefficient of variation=0.483 for adolescents vs 0.131 for adults). The search volume for insomnia in adolescents was notably higher in January, February, and August, which are academic vacation periods in South Korea (P<.001). In the weekly pattern, 2-way ANOVA revealed a significant (group) × (day) interaction (P<.001). Adolescents showed a considerably increased search volume on Sunday and Monday (P<.001) compared to adults. In contrast, young adults demonstrated seasonal and weekly patterns similar to adults.

CONCLUSIONS

Adolescents demonstrate distinctive seasonal and weekly patterns in internet searches on insomnia (ie, increased search in vacation months and weekend-weekday transitions), which are closely associated with the school schedule. Adolescents' sleep concerns might be potentially affected by the disrupted daily routine and the delayed sleep phase during vacations and weekends. As we demonstrated, comparing various age groups in infodemiology and infoveillance data might be helpful in identifying distinctive features in vulnerable age groups.

The influence of a permanent double-shift school start time on adolescent sleep and chronotype across different age groups

The main objective of this study was to explore the differences in sleep habits and chronotype across different age groups in Mexican adolescents attending a permanent double-shift school system. This cross-sectional study consisted of 1,969 (1,084 girls) students from public elementary, secondary, and high schools, as well as undergraduate university students from Mexico. Age range was 10-22 [15.33 ± 3.28 (mean ± SD)] years, 988 morning shift and 981 afternoon shift students. Questions regarding usual self-reported bedtime and rise time were collected, and from that, estimates for time in bed, midpoint of sleep, social jetlag, and chronotype were evaluated. Afternoon shift students reported later rise times, bedtimes, midpoint of sleep, and longer time in bed on school days than morning shift students, as well as less social jetlag. Overall, afternoon shift students reported a later chronotype than morning shift students. Peak lateness of chronotype in afternoon shift students was at age 15, with girls peaking at age 14 and boys at age 15. Meanwhile, morning shift students reported peak lateness of chronotype around age 20. In this study, adolescents from different age ranges attending an extremely delayed school start time reported adequate sleep compared with adolescents attending a fixed morning school start time. In addition, the analysis presented in this study seems to suggest that the peak of late chronotype may be influenced by school start times.

Children's activity and diet behaviours in the summer holidays versus school year

BACKGROUND

Evidence shows children gain more weight during the summer holidays versus the school year.

OBJECTIVES

To examine within-child differences in activity and diet behaviours during the summer holidays versus the school year.

METHODS

Children (mean age 9.4 years; 37% male) wore accelerometers (GENEActiv; n = 133), reported activities (Multimedia Activity Recall for Children and Adolescents; n = 133) and parents reported child diet (n = 133) at five timepoints over 2 years capturing school and summer holiday values. Mixed-effects models were used to compare school and summer holiday behaviours.

RESULTS

Children spent less time in moderate- to vigorous-physical activity (-12 min/day; p = 0.001) and sleep (-12 min/day; p < 0.001) and more time sedentary (+27 min/day; p < 0.001) during summer holidays versus the school year. Screentime (+70 min/day; p < 0.001), domestic/social activities (+43 min/day; p = <0.001), self-care (+24 min/day; p < 0.001), passive transport (+22 min/day; p = 0.001) and quiet time (+16 min/day; p = 0.012) were higher during the summer holidays, compensating for less time in school-related activities (-164 min/day; p < 0.001). Diet quality was lower (-4 points; p < 0.001) and children consumed fewer serves of fruit (-0.4 serves; p < 0.001) during the summer holidays versus the school year.

CONCLUSIONS

Children are displaying poorer activity and diet behaviours during the summer holidays, which may contribute to accelerated weight gain over the holiday period.

Associations of Changes in Sleep and Emotional and Behavioral Problems From Late Childhood to Early Adolescence

Importance

Sleep problems and psychopathology symptoms are highly comorbid and bidirectionally correlated across childhood and adolescence. Whether these associations are specific to discrete profiles of sleep problems and specific internalizing and externalizing phenomena is currently unclear.

Objective

To characterize individual changes in profiles of sleep problems and their prospective associations with psychopathology symptoms across the transition from childhood to adolescence.

Design, Setting, and Participants

This observational cohort study used baseline data (participant age of 9 to 11 years) and 2-year follow-up data (participant age of 11 to 13 years) from the community-setting, multicenter Adolescent Brain Cognitive Development (ABCD) study. Individuals were assessed for a range of sleep problems at both waves and categorized into profiles via latent profile analysis. The stability and change in these profiles over time was assessed via latent transition analysis. Logistic regression models examined whether psychopathology symptoms were cross-sectionally associated with profile membership and whether transitions between profiles were associated with changes psychopathology symptoms over time. Data were collected from September 2016 to January 2020, and data were analyzed from August 2021 to July 2022.

Exposures

Sleep problems were assessed at both baseline and follow-up via the parent-reported Sleep Disturbance Scale for Children (SDSC).

Main Outcomes and Measures

Psychopathology symptoms at both baseline and follow-up were assessed using the internalizing and externalizing dimension scores derived from the parent-reported Child Behavior Checklist.

Results

A total of 10 313 individuals (4913 [47.6%] were female) were categorized into 4 latent profiles of sleep problems at both baseline and follow-up: a low disturbance profile, a sleep onset/maintenance problems profile, a moderate and nonspecific disturbance profile (termed mixed disturbance), and a high disturbance profile. Individuals in the 3 more severe problem profiles displayed greater risk of concurrent internalizing symptoms (sleep onset/maintenance problems: odds ratio [OR], 1.30; 95% CI, 1.25-1.35; P < .001; mixed disturbance: OR, 1.29; 95% CI, 1.25-1.33; P < .001; high disturbance: OR, 1.44; 95% CI, 1.40-1.49; P < .001) and externalizing symptoms (sleep onset/maintenance problems: OR, 1.20; 95% CI, 1.16-1.23; P < .001; mixed disturbance: OR, 1.17; 95% CI, 1.14-1.20; P < .001; high disturbance: OR, 1.24; 95% CI, 1.21-1.28; P < .001). Transitions between sleep profiles over time were associated with prospective internalizing and externalizing symptoms, but not vice versa.

Conclusions and Relevance

There are substantial changes in sleep problems across the transition to adolescence that are associated with later internalizing and externalizing symptoms. Sleep profiles could be targeted in future intervention and treatment programs to improve sleep-related and mental health-related outcomes across development.

Separating the influences of means and daily variations of sleep on the stress-induced salivary cortisol response

BACKGROUND

Previous research regarding the effects of sleep quality and quantity on the acute stress response has yielded inconsistent findings. This may be attributed to various factors, including composite sleep components (i.e., means and daily variations) and mixed cortisol stress response (i.e., reactivity and recovery). Thus, this study aimed to separate the effects of means and daily variations of sleep on the reactivity and recovery of cortisol responses to psychological challenges.

METHODS

In study 1, we recruited 41 healthy participants (24 women; age range, 18-23 years), monitored their sleep during seven consecutive days via wrist actigraphy and sleep diaries, and adopted the Trier Social Stress Test (TSST) paradigm to induce acute stress. Study 2 consisted of a validation experiment using the ScanSTRESS paradigm, which included 77 additional healthy individuals (35 women; age range, 18-26 years). Similarly to the TSST, the ScanSTRESS induces acute stress using uncontrollability and social evaluation. In both studies, saliva samples from the participants were collected before, during, and after the acute stress task.

RESULTS

Using residual dynamic structural equation modeling, both study 1 and study 2 demonstrated that higher means of objective sleep efficiency, and longer means of objective sleep duration were related to greater cortisol recovery. In addition, fewer daily variations in objective sleep duration were associated with greater cortisol recovery. However, there was no correlation between sleep variables and cortisol reactivity, except for the daily variations in objective sleep duration in study 2. No correlation was observed between subjective sleep and cortisol response to stress.

CONCLUSIONS

The present study separated two features of multi-day sleep patterns and two components of cortisol stress response, providing a more comprehensive picture of the effect of sleep on the stress-induced salivary cortisol response, and contributing to the future development of targeted interventions for stress-related disorders.

Bidirectional associations between sedentary time and sleep duration among 12- to 14-year-old adolescents

Background

The aim of this study was to investigate bidirectional associations between (prolonged) sitting time and sleep duration in 12- to 14-year-old adolescents using a between-subjects and within-subjects analyses approach.

Methods

Observational data were used from 108 adolescents (53% girls; mean age 12.9 (SD 0.7) years) from six schools in Flanders, Belgium. The Axivity AX3 triaxial accelerometer, worn on the thigh, was used to assess daily total sitting time and daily time spent in sedentary bouts of ≥30 min (as a proxy for prolonged sitting time). The Fitbit Charge 3 was used to assess nightly sleep duration. Both monitors were worn on schooldays only (ranging from 4 to 5 days). Linear mixed models were conducted to analyse the associations, resulting in four models. In each model, the independent variable (sleep duration, sitting time or prolonged sitting time) was included as within- as well as between-subjects factor.

Results

Within-subjects analyses showed that when the adolescents sat more and when the adolescents spent more time sitting in bouts of ≥30 min than they usually did on a given day, they slept less during the following night (p = 0.01 and p = 0.05 (borderline significant), respectively). These associations were not significant in the other direction. Between-subjects analyses showed that adolescents who slept more on average, spent less time sitting (p = 0.006) and less time sitting in bouts of ≥30 min (p = 0.004) compared with adolescents who slept less on average. Conversely, adolescents who spent more time sitting on average and adolescents who spent more time sitting in bouts of ≥30 min on average, slept less (p = 0.02 and p = 0.003, respectively).

Conclusions

Based on the between-subjects analyses, interventions focusing on reducing or regularly breaking up sitting time could improve adolescents’ sleep duration on a population level, and vice versa. However, the within-subjects association was only found in one direction and suggests that to sleep sufficiently during the night, adolescents might limit and regularly break up their sitting time the preceding day.

Trial registration

Data have been used from our trial registered at ClinicalTrials.gov (NCT04327414; registered on March 11, 2020).

Supplementary Information

The online version contains supplementary material available at 10.1186/s12889-021-11694-9.

Dynamics of sleep, sedentary behavior, and moderate-to-vigorous physical activity on school versus nonschool days

STUDY OBJECTIVES

Studies examining time-use activity behaviors (sleep, sedentary behavior, and physical activity) on school days compared with nonschool days have examined these behaviors independently, ignoring their interrelated nature, limiting our ability to optimize the health benefits of these behaviors. This study examines the associations of school-day (vs. nonschool day) with time-use activity behaviors.

METHODS

Time series data (6,642 days) from Fitbits (Charge-2) were collected (n = 196, 53% female, 5-10 years). We used a variable-centered dynamic structural equation modeling approach to estimate day-to-day associations of time-use activity behaviors on school days for each child. We then used person-centered cluster analyses to group individuals based on these estimates.

RESULTS

Within-participant analysis showed that on school days (vs. nonschool days), children (1) slept less (β = -0.17, 95% CI = -0.21, -0.13), (2) were less sedentary (β = -0.05, 95% CI = -0.09, -0.02), and (3) had comparable moderate-to-vigorous physical activity (MVPA; β = -0.05, 95% CI = -0.11, 0.00). Between-participant analysis showed that, on school days, children with higher sleep carryover experienced greater decreases in sleep (β = 0.44, 95% CI = 0.08, 0.71), children with higher body mass index z-score decreased sedentary behavior more (β = -0.41, 95% CI = -0.64, -0.13), and children with lower MVPA increased MVPA more (β = -0.41, 95% CI -0.64, -0.13). Cluster analysis demonstrated four distinct patterns of connections between time-use activity behaviors and school (High Activity, Sleep Resilient, High Sedentary, and Dysregulated Sleep).

CONCLUSIONS

Using a combination of person-centered and more traditional variable-centered approaches, we identified patterns of interrelated behaviors that differed on school, and nonschool days. Findings can inform targeted intervention strategies tailored to children's specific behavior patterns.

A meta-analysis of accelerometer sleep outcomes in healthy children based on the Sadeh algorithm: the influence of child and device characteristics

STUDY OBJECTIVES

Children often experience sleep problems, with a negative impact on mood, behavior, cognitive function, and other aspects of mental and physical health. Accelerometers are widely used to assess sleep, but general reference values for healthy children do not yet exist. The aim of this meta-analysis was to determine mean values for wake after sleep onset (WASO), sleep efficiency (SE), total sleep time (TST) and sleep onset latency (SOL), and to determine the effect of child and accelerometer-characteristics.

METHODS

A search included studies with healthy children, 0-18 years, reporting WASO, SE, TST, and/or SOL, calculated with the Sadeh algorithm. Meta-analyses with random effects produced pooled estimate means per outcome. Meta-regression analyses determined the effect of age, sex, placement site and accelerometer type.

RESULTS

Eighty-three studies (9,068 participants) were included. Pooled means were 63 min (95% CI 57 to 69) for WASO, 88% (95% CI 87 to 89) for SE, 477 min (95% CI 464 to 491) for TST and 19 min (95% CI 17 to 22) for SOL. Heterogeneity was high (95%-99%). TST decreased with age and there was an age-effect on SOL. SE differed between wrist and ankle (used in age 0-24 months) placement, and between piezoelectric and MEMS-type accelerometers. No differences were found between boys and girls, although this number of studies was small.

CONCLUSIONS

We found differences in almost all investigated outcomes and heterogeneity was high. Therefore, we advise to use a study-specific control sample until more robust reference values are available. Future research should narrow the methodological heterogeneity and produce larger datasets, needed to establish these reference values.

Day-to-day variability in sleep parameters and depression risk: a prospective cohort study of training physicians

While 24-h total sleep time (TST) is established as a critical driver of major depression, the relationships between sleep timing and regularity and mental health remain poorly characterized because most studies have relied on either self-report assessments or traditional objective sleep measurements restricted to cross-sectional time frames and small cohorts. To address this gap, we assessed sleep with a wearable device, daily mood with a smartphone application and depression through the 9-item Patient Health Questionnaire (PHQ-9) over the demanding first year of physician training (internship). In 2115 interns, reduced TST (b = -0.11, p < 0.001), later bedtime (b = 0.068, p = 0.015), along with increased variability in TST (b = 0.4, p = 0.0012) and in wake time (b = 0.081, p = 0.005) were associated with more depressive symptoms. Overall, the aggregated impact of sleep variability parameters and of mean sleep parameters on PHQ-9 were similar in magnitude (both r² = 0.01). Within individuals, increased TST (b = 0.06, p < 0.001), later wake time (b = 0.09, p < 0.001), earlier bedtime (b = - 0.07, p < 0.001), as well as lower day-to-day shifts in TST (b = -0.011, p < 0.001) and in wake time (b = -0.004, p < 0.001) were associated with improved next-day mood. Variability in sleep parameters substantially impacted mood and depression, similar in magnitude to the mean levels of sleep parameters. Interventions that target sleep consistency, along with sleep duration, hold promise to improve mental health.

Influence of Training Schedules on Objective Measures of Sleep in Adolescent Academy Football Players

Brown, GA, Veith, S, Sampson, JA, Whalan, M, and Fullagar, HHK. Influence of training schedules on objective measures of sleep in adolescent academy football players. J Strength Cond Res 34(9): 2515-2521, 2020-Football academy settings may pose risks to adolescent athletes achieving sufficient sleep because of the contextual challenges these players face (e.g., psychosocial pressure, changes in training, competition, and academic stress). Given the importance of sleep to overall health as well as physical athletic development and injury risk, this study aimed to investigate whether differences in training schedules (morning vs. evening training sessions) affected objective measures of sleep in adolescent academy football (soccer) players. Twelve academy players (mean age 14.18 ± 1.36 years) wore an ActiGraph accelerometer on nights before, and nights of, training days in 2 separate weeks where morning (09:00-11:00 hours) and evening (18:00-20:00 hours) training occurred. Objective sleep parameters and training load data were collected. Night-time sleep periods were categorized as sleep preceding morning training, preceding evening training, or after evening training. One-way univariate and multivariate analyses of variance for repeated measures were performed to determine the impact of the training schedule on sleep. Significance levels were set at p < 0.05. The total sleep time was below the recommended guidelines (<8 hours) across conditions. A large significant effect of the training schedule on time attempted to fall asleep (p = 0.004, effect size [ES] = 0.40) and time of sleep (p = 0.003, ES = 0.41) was present, with post-evening sessions resulting in the latest times. Overall, the players' sleep behavior was resilient to changes in training schedules. However, the low sleep durations (and potential risks to physical performance/injury) suggest that sleep education coupled with practical interventions are required in this cohort.

Measuring sleep duration in adolescence: Comparing subjective and objective daily methods

OBJECTIVES

This study provides the first investigation into the correspondence between self-reported and actigraph-measured nighttime sleep duration in adolescents that disambiguates between- versus within-person associations. Moderators were evaluated to determine if between- and within-person correspondence vary by participant characteristics.

METHODS

One hundred fifty adolescents (14-21 years) reported sleep time for 1 week, while wearing an actigraph, and reported on moderators, including demographics (i.e., sex, age, ethnicity, and socioeconomic status), depressive symptoms, and perceived stress. Mixed effects models evaluated within- and between-person associations between self-reported and actigraph-measured sleep, and examined whether these associations differed by possible moderators.

RESULTS

Results indicated significant between- (b = 0.77, SE = 0.08, P < .001) and within-person (b = 0.51, SE = 0.04, P < .001) associations between self-reported and actigraph-measured sleep duration, with no significant moderation effects.

CONCLUSIONS

Our results support the use of either self-reports or actigraphs to examine within-person nighttime sleep duration in adolescent community samples.