Less screen time and more physical activity is associated with more stable sleep patterns among Icelandic adolescents

Longitudinal analysis of the bidirectional relationship between screen time and sleep: Exploring the role of physical activity

BACKGROUND

Excessive screen time and poor sleep duration have significant implications for children's health and well-being. Understanding the dynamic relationship between screen time and sleep duration, as well as the impact of physical activity in this relationship, is essential for promoting healthy behaviours. The aims of this study were to: 1) investigate the bidirectional relationship between screen time and sleep duration in children, and 2) explore the mediating role of physical activity in these associations.

METHODS

Data were from 2064 children (47 % girls) who responded to time-use diaries at waves 3 (age 5), 6 (age 10), and 7 (age 12) of the Longitudinal Study of Australian Children (LSAC). Cross-lagged panel modelling was conducted to test bidirectional associations between screen time and sleep duration, with the mediating role of physical activity assessed using a lagged mediation model.

RESULTS

A bidirectional association between screen time and sleep duration across ages 10 to 12 was observed. Screen time at 10 years of age was associated with sleep duration at 12 years of age (β = -0.071 [95%CI, -0.114 to -0.015]), and sleep duration at 10 years of age was associated with screen time at 12 years of age (β = -0.048 [95%CI, -0.087 to -0.002]). Moreover, increased levels of physical activity at age 12 reduced the negative impact of both screen time on sleep duration and sleep duration on screen time during the ages of 10 and 12.

CONCLUSION

Findings highlight a cyclical influence where each factor impacts the other over time. Interventions aimed at reducing screen time and increasing physical activity may help mitigate the negative effects of excessive screen time on sleep.

Exploring β-caryophyllene: a non-psychotropic cannabinoid's potential in mitigating cognitive impairment induced by sleep deprivation

Sleep deprivation or sleep loss, a prevalent issue in modern society, is linked to cognitive impairment, leading to heightened risks of errors and accidents. Chronic sleep deprivation affects various cognitive functions, including memory, attention, and decision-making, and is associated with an increased risk of neurodegenerative diseases, cardiovascular issues, and metabolic disorders. This review examines the potential of β-caryophyllene, a dietary non-psychotropic cannabinoid, and FDA-approved flavoring agent, as a therapeutic solution for sleep loss-induced cognitive impairment. It highlights β-caryophyllene's ability to mitigate key contributors to sleep loss-induced cognitive impairment, such as inflammation, oxidative stress, neuronal death, and reduced neuroplasticity, by modulating various signaling pathways, including TLR4/NF-κB/NLRP3, MAPK, Nrf2/HO-1, PI3K/Akt, and cAMP/PKA/CREB. As a naturally occurring, non-psychotropic compound with low toxicity, β-caryophyllene emerges as a promising candidate for further investigation. The review underscores the therapeutic potential of β-caryophyllene for sleep loss-induced cognitive impairment and provides mechanistic insights into its action on crucial pathways, suggesting that β-caryophyllene could be a valuable addition to strategies aimed at combating cognitive impairment and other health issues due to sleep loss.

SmartSense-D: A safety, feasibility, and acceptability pilot study of digital phenotyping in young people with major depressive disorder

Background

Digital assessment of behaviours, including physical activity, sleep, and social interactions could be associated with changes in mood and other mental health symptoms. This study assessed the safety, feasibility, acceptability, and potential predictive value of passive and active sensing in young people with major depressive disorder (MDD).

Methods

Over eight weeks, passive (smartphone sensing, actigraphy) and active (ecological momentary assessment; EMA) data were collected from 40 young participants with MDD (aged 16-25 years). We assessed the safety, feasibility, and acceptability of daily active and passive sensing in this population. Additionally, linear mixed models and correlation analysis explored associations between passive and active sensing measures.

Results

Of the 48 young participants, 83% (n = 40) completed the full protocol. No adverse events were reported. Over eight weeks, participants averaged 35.9 days (65.3%) with EMAs and 37.9 days (69%) with actigraphy data. Smartphone sensors recorded communication for 21.1 days (38.4%), location for 43.1 days (78.4%), maximum unlock duration for 43.4 days (79%), social media use for 34.8 days (63.3%), and inter-key delay for 32.8 days (59.6%). Regarding acceptability, 83.1% found the application usable and comfortable. Secondary measures showed significant correlations between sleep and physical activity, and between location and phone use sensors. There was a significant negative association between daily positive mood ratings and QIDS total scores (Beta coefficient [95% CI]: 2.66 [-3.98, -1.34]; p = 0.002).

Conclusion

Passive and active sensing methods were safe, and acceptable among young people with MDD.

Association between social jetlag and leisure-time physical activity and muscle strengthening exercise in young adults: findings from a nationally representative sample in South Korea

OBJECTIVES

Social jetlag (SJL), which is characterised by a misalignment between biological and social time, is associated with cardiometabolic risk factors. This study investigated the relationship between SJL, leisure-time physical activity (LTPA) and muscle strengthening exercise (MSE) in young adults.

STUDY DESIGN

This was a cross-sectional study.

METHODS

This cross-sectional study included a nationally representative sample of young adults aged 19-29 years (n = 2113). SJL was calculated as the difference in the midpoint of sleep onset and offset time between weekdays and weekends. The dependent variables were engagement in ≥150 min/week of moderate-to-vigorous LTPA and engagement in MSE ≥2 days/week based on guidelines provided by the World Health Organisation. Logistic regression analysis was performed to estimate odds ratios (ORs) and 95% confidence intervals (CIs). Non-linear relationships were estimated using restricted cubic spline regression.

RESULTS

The study population comprised 975 men and 1138 women. Among participants, 4.6% had <0 min, 41.9% had 0-59 min, 25.7% had 60-119 min and 27.7% had ≥120 min SJL. Those with ≥120 min SJL had a reduced likelihood of achieving the recommended level of LTPA (OR: 0.71, 95% CI: 0.52-0.95) and MSE (OR: 0.73, 95% CI: 0.55-0.97). In the non-linear model, an inverse U-shaped association was observed, wherein the highest probability of meeting the recommended level of LTPA and MSE was observed in those with 45 min SJL, decreasing after this threshold.

CONCLUSIONS

Individuals with ≥120 min SJL were less likely to engage in the recommended level of both aerobic and anaerobic exercise. Although future studies using a longitudinal design are required to elucidate the causal relationship between SJL and physical activity, the current findings suggest that physical inactivity during leisure time may play an important role in the increased risk of cardiometabolic abnormalities in young adults with SJL.

Inflammatory markers, somatic complaints, use of medication and health care in 11-year-old children at familial high risk of schizophrenia or bipolar disorder compared with population-based controls. The Danish High Risk and Resilience Study - via 11

PURPOSE

Patients with schizophrenia or bipolar disorder are at increased risk of somatic illnesses and have more somatic complaints compared with the general population. Schizophrenia and bipolar disorder are highly heritable. Already during childhood, children at familial high risk of schizophrenia (FHR-SZ) or bipolar disorder (FHR-BD) are at increased risk of psychiatric disorders and cognitive and social impairments. Knowledge about physical conditions is sparse.

MATERIALS AND METHODS

Through blood tests (n = 293), interviews, and questionnaires, we assessed inflammatory markers, somatic complaints, medication - and health care use in 11-year-old children at FHR-SZ, FHR-BD, and population-based controls (PBC).

RESULTS

Children at FHR-SZ had higher concentrations of leucocytes (mean 6.41, SD 0.73) compared with PBC (mean 5.78, SD 0.27, p = 0.005) and of neutrophilocytes (FHR-SZ: mean 3.11, SD 1.32, PBC: mean 2.70, SD 0.96, p = 0.024). Compared with PBC (26.6%), more children at FHR-SZ (40.5%, p = 0.007) reported somatic complaints. So did caregivers and teachers to children at FHR-BD. Somatic complaints, higher concentrations of leucocytes, and neutrophilocytes were associated with lower levels of physical activity. Children at FHR-BD with psychiatric disorders reported more somatic complaints compared with those without.

CONCLUSION

Children at FHR-SZ had higher concentrations of leucocytes and neutrophilocytes than PBC. Children at FHR-SZ or FHR-BP displayed more somatic complaints than controls. Our study highlights rarely explored disadvantage of being born to parents with schizophrenia or bipolar disorder. To enhance understanding of how physical conditions in childhood may interplay with later transition to mental disorders in children at FHR-SZ and FHR-BD, further research is needed.

When and what: A longitudinal study on the role of screen time and activities in adolescent sleep

OBJECTIVES

Previous research has highlighted a link between electronic media use and sleep outcomes, but the nuanced impacts of screen use at different time of day and activities on adolescent sleep are underexplored.

METHODS

831 participants underwent online assessment three times with interval of three months regarding their screen time and activities at specific times of the day, daytime sleepiness was assessed with the Epworth Sleepiness Scale, and sleep outcomes were assessed with the Pittsburgh Sleep Quality Index and Insomnia Severity Index. The associations between time spent on various screen activities, and sleep outcomes were examined respectively after controlling for inter-individual differences using the Random Intercept Cross-Lagged Panel Model models and LMMs.

RESULTS

The RI_CLPM model revealed that both electronic screen time during daytime and after lights off in the evening in Wave1 negatively predicted the sleep quality in Wave2; the nighttime screen time before lights off in Wave1 significantly negatively predicted the seventy of insomnia in Wave2. Whereas no cross-lag and predictive effects of sleep outcomes on screen time were revealed. Moreover, daytime screen exposure, including T.V. watching and social media use, and nighttime music listening were negatively associated with sleep quality. Conversely, nighttime screen time of shopping and working/studying positively influenced sleep quality. Additionally, daytime screen time of T.V. viewing was positively associated with increased insomnia severity, whereas nighttime work/study-related screen time negatively affected insomnia severity. Nighttime screen time of music listening negatively predicted daytime sleepiness.

CONCLUSIONS

The current findings contributed to the existing literature suggesting that the effects of electronic screen time on sleep depended on both the time of day and type of screen activities.

Interactive Screen-Based Activities Predict Worse Actigraphic Sleep Health That Night Among Adolescents

PURPOSE

To determine the micro-longitudinal effects of duration and timing of screen-based activities on sleep within and between adolescents.

METHODS

Daily survey and actigraphy data from the age 15 wave of the Future of Families and Child Wellbeing Study were analyzed using multilevel modeling. Four hundred seventy five adolescents provided three or more days of valid daily survey and nighttime sleep data.

RESULTS

Within-person results showed that on days when adolescents played video games more than their daytime average ± SE (1.3 ± 1.2 hours), sleep onset (6 ± 2 minutes, p < .01) and midpoint (4 ± 2 minutes, p < .02) were delayed for each additional hour of gaming. Between-person results showed that for each hour adolescents used screens to communicate with friends across the day, sleep onset was later (11 ± 3 minutes, p < .01), sleep midpoint was later (8 ± 3 minutes, p < .01), and sleep duration was shorter (-5 ± 2 minutes, p < .03). Adolescents who used screens to communicate with friends or play video games in the hour before bed had later sleep onset (30 ± 14 minutes, p < .03) and midpoint (25 ± 13 minutes, p < .05).

DISCUSSION

Among adolescents, passive screen usage such as browsing the Internet or watching videos may not affect sleep timing or duration, but limiting interactive screen-based activities could protect adolescent sleep health and well-being.

Modifiable behavioral risk factors for NCDs and sleep in Brazilian adolescents

OBJECTIVE

To analyze the association between modifiable behavioral risk factors for non-communicable diseases and sleep parameters in Brazilian adolescents.

METHODS

This was a cross-sectional study that used data from the RPS Cohort Consortium, São Luís, Brazil for the follow-up of adolescents aged 18-19 years (n = 2,515). The outcomes were excessive daytime sleepiness (Epworth Sleepiness Scale - ESS) and sleep quality (Pittsburgh Sleep Quality Index - PSQI). The exposures of interest were the behavioral risk factors for non-communicable diseases (NCDs): screen time, physical inactivity, alcohol, smoking, illicit drugs, caffeine intake, and consumption of sugar-sweetened beverages. Excess weight was considered a possible mediator of this association between the exposures of interest and the outcomes. The models were analyzed by modeling with structural equations.

RESULTS

Physical inactivity (standardized coefficient, SC = 0.112; p = 0.001), higher consumption of alcohol (SC = 0.168; p = 0.019) and of sugar-sweetened beverages (SC = 0.128; p < 0.001) were associated with excessive daytime sleepiness in adolescents; better socioeconomic status was also associated with this outcome (SC = 0.128; p < 0.001). Physical inactivity (SC = 0.147; p < 0.001) and higher consumption of sugar-sweetened beverages (SC = 0.089; p = 0.003) were also associated with poor sleep quality. Overweight was neither a mediator nor associated with sleep quality or excessive daytime sleepiness.

CONCLUSIONS

The main modifiable behavioral risk factors for NCDs are associated with worse sleep parameters already in adolescence, which serves as a warning toward the accumulation of risks for sleep disorders in the future.

A National Survey of U.S. Adolescent Sleep Duration, Timing, and Social Jetlag During the COVID-19 Pandemic

OBJECTIVES

To assess changes in duration, timing, and social jetlag in adolescent sleep during the COVID-19 pandemic and evaluate the impact of mood, physical activity, and social interactions on sleep.

STUDY DESIGN

An online survey queried adolescents' sleep before (through retrospective report) and during the initial phase of COVID-19 in May 2020. Adolescents (N = 3,494), 13-19 years old, in the United States (U.S.) answered questions about their current and retrospective (prior to COVID-19) sleep, chronotype, mood, and physical and social activities. Linear regression models were fit for time in bed, reported bed and wake times, and social jetlag during COVID-19, accounting for pre-COVID-19 values.

RESULTS

Total reported time in bed (a proxy for sleep duration) increased on weekdays by an average of 1.3 ± 1.8 hours (p < .001) during COVID-19, compared to retrospective report of time in bed prior to COVID-19. During COVID-19, 81.3% of adolescents reported spending 8 hours or more in bed on weekdays compared to only 53.5% prior to COVID-19. On weekdays, bedtimes were delayed on average by 2.5 hours and wake times by 3.8 hours during COVID-19 compared to prior to COVID-19. On weekends, bedtimes were delayed on average by 1.6 hours and waketimes by 1.5 hours (all p's < 0.001). Social jetlag of >2 hours decreased to 6.3% during COVID-19 compared to 52.1% prior to COVID-19. Anxiety and depression symptoms and a decline in physical activity during COVID-19 were associated with delayed bed and wake times during COVID-19.

CONCLUSIONS

During COVID-19, adolescents reported spending more time in bed, with most adolescents reporting 8 hours of sleep opportunity and more consistent sleep schedules. As schools return to in-person learning, additional research should examine how sleep schedules may change due to school start times and what lessons can be learned from changes that occurred during COVID-19 that promote favorable adolescent sleep.

Sleep variability and regularity as contributors to obesity and cardiometabolic health in adolescence

OBJECTIVE

Adolescence is a developmental stage of critical changes in sleep and its circadian timing when the contribution of abnormal sleep variability (amount) and sleep regularity (timing) to obesity and its associated adverse cardiometabolic health outcomes appears to increase. The aim of this study was to summarize findings from studies conducted in adolescents examining both sleep variability and regularity in relation to obesity and cardiometabolic health. Gaps in research and potential causal pathways that future studies should examine are highlighted.

RESULTS

Nightly deviations in sleep duration and sleep midpoint appear to contribute to the development of obesity and associated adverse cardiometabolic outcomes in youth. Studies show that increased sleep variability and irregularity are associated with obesity, decreased physical activity, dysregulated eating and inadequate diet, metabolic dysfunction, impaired cardiac autonomic balance, and elevated blood pressure in adolescents.

CONCLUSIONS

A stable circadian timing of sleep is essential to the overall physical well-being of youth. Emerging evidence supports that sleep variability and circadian misalignment, including sleep irregularity, contribute to adverse obesity-related health outcomes early on in adolescence. Future studies should focus on the underlying behavioral and biological mechanisms in the causal pathway between day-to-day deviations in the amount and timing of sleep and obesity.

Moderate-Vigorous Physical Activity, Screen Time and Sleep Time Profiles: A Cluster Analysis in Spanish Adolescents

The study had two aims: (1) To classify the adolescents according to their levels of moderate-vigorous physical activity, screen time and sleep time, and (2) to analyze, in a descriptive and correlational manner, the profiles of moderate-vigorous physical activity, screen time and sleep time of each cluster according to the sex and grade of the adolescents. The study design was cross-sectional, with descriptive and correlational analysis. The sample consisted of 663 adolescents in Compulsory Secondary Education from Soria (Spain). The Four by One-Day Physical Activity Questionnaire was used to measure levels of physical activity, screen time and sleep time. The results showed that the young people had an average of 67.99 ± min/day of moderate-vigorous physical activity, 112.56 min/day of screen time and 548.63 min/day of sleep time. Adolescents were classified into three clusters according to their levels of physical activity, screen time and sleep time (F_MANOVA (6,1318) = 314.439; p ≤ 0.001; β = 1; f = 1.177). In conclusion, only 28.21% of the young people accomplished the recommendations for physical activity practice, screen time and sleep time. Moreover, these results vary according to the sex and grade of the adolescents.

The Relationships between Physical Activity, Screen Time and Sleep Time According to the Adolescents' Sex and the Day of the Week

This study had two aims: (1) to identify the levels of physical activity, screen time and sleep time of adolescents according to the sex of the participant and the day of the week; (2) to find out the relationships between physical activity, screen time and sleep time according to the sex of the participant and the day of the week. The study design was non-experimental, descriptive-correlational and cross-sectional. The sample consisted of 694 adolescents in Compulsory Secondary Education from Soria (Spain). Four by One-Day Physical Activity Questionnaires were used to measure levels of physical activity, screen time and sleep time. Levene’s test and Student’s t-test were used to calculate the difference between the means of the variables. Pearson’s test was used to calculate bivariate correlations between variables. Results showed higher levels of screen time in males (136.93 min/day ± 81.548). Screen time, sleep time and moderate−vigorous physical activity are higher during the weekend. Positive relationships were found between screen time and light physical activity (rmales = 0.274; p ≤ 0.01; rfemales = 0.065; p > 0.05). The correlations between moderate−vigorous physical activity and screen time were negative (rmales = −0.282; p ≤ 0.01; rfemales = −0.187; p ≤ 0.05). The relationship between screen time and sleep time was negative in males (r = −0.135; p ≤ 0.05). In conclusion, the levels of physical activity, screen time and sleep time vary according to the sex of the participants and the day of the week.

An Explanatory Model of the Relationships between Physical Activity, Social Support and Screen Time among Adolescents

Effective physical activity studies are necessary to understand how factors involved in physical activity mediate behaviour. Therefore, more reliable explanatory models can be generated in order to design effective actions to promote physical activity. The study had two aims: (1) to develop an explanatory model to identify and establish the relationships between physical activity, social support and screen time among adolescents; and (2) to contrast the explanatory structural model by means of a multi-group analysis according to sex. The study design was cross-sectional with descriptive and correlational analysis. The research was carried out with a representative sample of adolescents from the province of Soria (mean age 14.06 ± 1.27 years). The instruments used were: Four by One-Day Physical Activity Questionnaire, Parent Support Scale and Peer Support Scale. The results show that social support had a negative relationship with screen time (r = −0.178; p ≤ 0.001); males had a positive relationship between physical activity and screen time (r = 0.118; p ≤ 0.05); and peer support had more influence on social support than parental support. In conclusion, the proposed model was effective in triangulating the relationships between physical activity, social support and screen time in a novel way, while allowing us to discriminate these results according to participants’ sex.

Sleeping through a Lockdown: How Adolescents and Young Adults Struggle with Lifestyle and Sleep Habits Upheaval during a Pandemic

OBJECTIVES

The objective of the present study was to investigate the relationship between chronotype, lifestyle habits during the pandemic, and changes in sleep timing during the first wave of the COVID-19 pandemic in youth.

METHOD

An online survey of adolescents and young adults (N = 449) was conducted in June 2020. Multivariate hierarchical regressions assessed the contribution of chronotype and changes in lifestyle habits to sleep timing during the COVID-19 pandemic in two age groups (12 to 17 years old and 18 to 25 years old).

RESULTS

Chronotype was a significant predictor of changes in sleep habits during the pandemic in both age groups. In adolescents, electronic device usage during the pandemic was a significant predictor of bedtimes and wake times on weekdays, and caffeine during the pandemic was a predictor of weekday wake times. The number of hours worked during the pandemic was a significant predictor of weekday wake times in both age groups. In young adults, cannabis consumption during the pandemic was a predictor of weekend bedtimes. A later chronotype, along with higher usage of electronic devices, fewer hours worked, as well as higher caffeine and cannabis consumption during the pandemic were associated with delayed sleep timing during the pandemic in youth.

CONCLUSION

These results highlight the importance of assessing lifestyle habits when exploring changes in sleep habits in youth.

Association between free-living sleep and memory and attention in healthy adolescents

In laboratory studies, imposed sleep restriction consistently reduces cognitive performance. However, the association between objectively measured, free-living sleep and cognitive function has not been studied in older adolescents. To address this gap, we measured one week of sleep with a wrist-worn GT3X+ actigraph in 160 adolescents (96 girls, 17.7 ± 0.3 years) followed by assessment of working memory with an n-back task and visual attention with a Posner cue-target task. Over the week, participants spent 7.1 ± 0.8 h/night in bed and slept 6.2 ± 0.8 h/night with 88.5 ± 4.8% efficiency and considerable intra-participant night-to-night variation, with a standard deviation in sleep duration of 1.2 ± 0.7 h. Sleep measures the night before cognitive testing were similar to weekly averages. Time in bed the night before cognitive testing was negatively associated with response times during the most challenging memory task (3-back; p = 0.005). However, sleep measures the night before did not correlate with performance on the attention task and weekly sleep parameters were not associated with either cognitive task. Our data suggests shorter acute free-living sleep may negatively impact difficult memory tasks, however the relationship between free-living sleep and cognitive task performance in healthy adolescents is less clear than that of laboratory findings, perhaps due to high night-to-night sleep variation.