Changes in Sleep Duration and Sleep Timing in the General Population from before to during the First COVID-19 Lockdown: A Systematic Review and Meta-Analysis.

BACKGROUND: The COVID-19 lockdown had a profound effect on everyday life, including sleep health. This systematic review and meta-analysis evaluated changes in quantitative sleep parameters during the first lockdown compared with pre-lockdown in the general population. METHODS: A search in scientific databases was performed to identify eligible observational studies from inception to 8 February 2023. We performed a random effects meta-analysis of those studies reporting (a) means of sleep duration, time in bed (TIB), and sleep timing (bedtime and wake-up time); (b) the percentages of atypical sleep duration before and during the lockdown; (c) the percentages of change in sleep duration and sleep timing. RESULTS: A total of 154 studies were included. A small increase in sleep duration (0.25 standardized mean difference, 95% CI 0.180-0.315) was found, with 55.0% of the individuals reporting changes, predominantly an increase (35.2%). The pooled relative risk for sleeping more than 8/9 h per night was 3.31 (95% IC 2.60-4.21). There was a moderately significant delay in sleep timing and a surge in napping. CONCLUSION: An increase in sleep duration and napping, and delayed sleep timing were observed. High-quality studies should evaluate whether these parameters have now become chronic or have returned to pre-lockdown values.

Circadian misalignment proxies, BMI, and chronic conditions: the role for weekday to weekend sleep differences.

OBJECTIVE: To evaluate whether social jet lag (SJL) and weekend catch-up sleep (CUS), proxies of circadian misalignment, were associated with BMI and chronic conditions. METHODS: Participants (n = 2,050,18-65y) were part of a virtual cross-sectional and population-based research. We examined CUS and SJL as continuous and categorical (< 1 h,1-2 h, > 2 h). Linear regression analyses were performed to assess the differences in BMI (outcome) associated with CUS and SJL. Restricted cubic splines were performed to explore the shape of the relationship between weekday-to-weekend variability in sleep duration, midpoint, wake time, and bedtime. Logistic regression models were used to estimate ORs(95%CIs) for chronic conditions and overweight related to CUS and SJL. Analyses were adjusted for sleep duration, biological and behavior-related variables. RESULTS: We found a positive association of SJL and CUS with BMI. The effects remained even after adjustment for weekly sleep duration and demonstrated a proportional increase with the magnitude of sleep variability. Among participants with SJL > 2 h, BMI increased by 2.29 kg/m2 (95%CI:0.84;3.74,p:0.002). They also had 129% higher odds of chronic conditions (95%CI:1.16;4.52, p:0.01) and 119% higher odds of overweight (95%CI: 1.20;3.98,p:0.01). Individuals with CUS > 2 h presented 78% higher odds of overweight (95%CI:1.27;2.50,p:0.001) and an increase of 1.61 kg/m2 in BMI (95%CI: 0.81; 2.40,p < 0.001). CONCLUSIONS: Our findings, which demonstrate that even a slight weekend sleep extension and variability of just 1 h is associated with higher values of BMI, suggest incorporating measures for sleep consistency and regularity into clinical protocols and public health guidelines to prevent and treat obesity and related diseases.

Changes in rest-activity rhythms in adolescents as they age: associations with brain changes and behavior in the ABCD study.

Background: Adolescents with disrupted rest-activity rhythms (RAR) including shorter sleep duration, later sleep timing and low physical activity levels have higher risk for mental and behavioral problems. However, it remains unclear whether the same associations can be observed for within-subject changes in RAR. Methods: Our longitudinal investigation on RAR used Fitbit data from the Adolescent Brain Cognitive Development (ABCD) Study at the 2-year (FL2: aged 10-13 years) and 4-year follow-up (FL4: aged 13-16 years). 963 youths had good-quality Fitbit data at both time points. In this study we examined changes in RAR from FL2 to FL4, their environmental and demographic contributors as well as brain and behavioral correlates. Results: From FL2 to FL4, adolescents showed decreases in sleep duration and physical activity as well as delayed sleep timing (Cohen's d .44-.75). The contributions of environmental and demographic factors to RAR changes were greatest to sleep timing (explained 10% variance) and least to sleep duration (explained 1% variance). Delays in sleep timing had stronger correlations with behavioral problems including greater impulsivity and poor academic performance than reductions in sleep duration or physical activity. Additionally, the various brain measures differed in their sensitivity to RAR changes. Reductions in sleep duration were associated with decreased brain functional connectivity between subcortical regions and sensorimotor and cingulo-opercular networks and with enhanced functional connectivity between sensorimotor, visual and auditory networks. Delays in sleep timing were mainly associated with grey matter changes in subcortical regions. Conclusions: The current findings corroborate the role of sleep and physical activity in adolescent's brain neurodevelopment and behavior problems. RAR might serve as biomarkers for monitoring behavioral problems in adolescents and to serve as potential therapeutic targets for mental disorders.

Assessment of cognitive function and sleep-wake rhythms in community-dwelling older adults.

Disruption of the circadian rhythm and sleep-wake cycles is a consequence of aging and is associated with the cognitive decline and many neurodegenerative conditions. We investigated the bedtime, wake-up time, sleep timing (midpoint between bedtime and wake-up time), and sleep timing standard deviation (SD) using the actigraphy among 80 consecutive volunteers aged ≥ 60 years. Global cognitive function and executive function of detailed cognitive domains were evaluated using the mini-mental state examination (MMSE) and Wisconsin card sorting test (WCST) and subjective daytime sleepiness was assessed using the Epworth Sleepiness Scale (ESS). The category achievement (CA), total errors (TE), perseverative errors of Nelson (PEN), non-perseverative errors (NPE), and difficulties in maintaining set (DMS) on the WCST were significantly correlated with sleep timing SD (CA: r = - 0.276, p = 0.013, TE: r = 0.311, p = 0.005, PEN: r = 0.241, p = 0.032, NPE: r = 0.250, p = 0.025, DMS: r = 0.235, p = 0.036), but not with the MMSE score. Multiple regression analyses with the stepwise forward selection method including age, ESS score, bedtime, sleep timing, and sleep timing SD, revealed that the ESS score, and sleep timing SD were significant factors related to CA on the WCST (ESS score: ß = - 0.322, p = 0.004; sleep timing SD: ß = - 0.250, p = 0.022). Assessment of sleep-wake rhythms, daytime sleepiness, and cognitive function using the MMSE and WCST is valuable for the prediction of cognitive decline in the geriatric population.

Sleep duration and social jetlag in healthy adolescents. Association with anxiety, depression, and chronotype: a pilot study.

PURPOSE: Misalignment between sleep opportunity and chronotype preference during adolescence may affect sleep and mental health. The aim of this study was to objectively evaluate sleep duration and social jetlag (SJL) to observe if there is a relationship with anxiety, depression, or chronotype. METHODS: Community based cohort study (n = 65) was conducted in Northern Europe. Participants recorded their sleep during the regular school schedule for 3 school nights and 2 free nights with FDA-cleared/EU Medical Device Directive (CE-02862) compliant home sleep test. They also completed validated questionnaires to assess (Morningness Eveningness Questionnaire; MEQ), sleepiness (Epworth Sleepiness Scale; ESS), and insomnia (Insomnia Severity Index; ISI), anxiety (General Anxiety Disorder-7; GAD-7), and depression symptoms (Beck's Depression Inventory-II; BDI-II). Data were collected during the last week of February and the first 2 weeks of March, 2023. RESULTS: Average sleep duration on school nights was 7 h, 15 min, with 18% of participants on average sleeping ≥ 8 h. Average sleep onset was significantly later on free nights (1 hour, 47 minutes; p < 0.0001) causing a high prevalence of moderate-severe SJL, in 71% of participants. Evening chronotypes (prevalence 15.4%) fell asleep later on free nights, causing them to have significantly more SJL (2 hours, 58 minutes) than morning chronotypes (1 hour, 32 minutes) and intermediary chronotypes (1 hour, 36 minutes). Evening chronotypes also had more severe insomnia (ISI + 4.4, p = 0.006; + 4.0, p = 0.001) and greater depressive symptoms (BDI-II + 21.6, p < 0.0001; + 17.1, p < 0.0001). A significant negative correlation was observed between MEQ scores and ESS (r = - 0.287; p = 0.001), ISI (r = - 0.343, p < 0.0001), GAD-7 (r = - 0.185, p < 0.0001), BDI-II (r = - 0.501, p = 0.0001), and suicidal thoughts (r = - 0.294, p = 0.017). CONCLUSION: Adolescents are sleep-deprived and have a high prevalence of SJL that is positively correlated with depressive symptoms and evening chronotype. That evening chronotypes have shorter sleep duration, more severe SJL, and significantly more sleepiness and insomnia, anxiety, and depressive symptoms may indicate possible benefits in identifying this group with the aim to assist them in improving their sleep habits with potentially positive effects on mental health.

Assessing the Accuracy of Generative Conversational Artificial Intelligence in Debunking Sleep Health Myths: Mixed Methods Comparative Study With Expert Analysis.

BACKGROUND: Adequate sleep is essential for maintaining individual and public health, positively affecting cognition and well-being, and reducing chronic disease risks. It plays a significant role in driving the economy, public safety, and managing health care costs. Digital tools, including websites, sleep trackers, and apps, are key in promoting sleep health education. Conversational artificial intelligence (AI) such as ChatGPT (OpenAI, Microsoft Corp) offers accessible, personalized advice on sleep health but raises concerns about potential misinformation. This underscores the importance of ensuring that AI-driven sleep health information is accurate, given its significant impact on individual and public health, and the spread of sleep-related myths. OBJECTIVE: This study aims to examine ChatGPT's capability to debunk sleep-related disbeliefs. METHODS: A mixed methods design was leveraged. ChatGPT categorized 20 sleep-related myths identified by 10 sleep experts and rated them in terms of falseness and public health significance, on a 5-point Likert scale. Sensitivity, positive predictive value, and interrater agreement were also calculated. A qualitative comparative analysis was also conducted. RESULTS: ChatGPT labeled a significant portion (n=17, 85%) of the statements as "false" (n=9, 45%) or "generally false" (n=8, 40%), with varying accuracy across different domains. For instance, it correctly identified most myths about "sleep timing," "sleep duration," and "behaviors during sleep," while it had varying degrees of success with other categories such as "pre-sleep behaviors" and "brain function and sleep." ChatGPT's assessment of the degree of falseness and public health significance, on the 5-point Likert scale, revealed an average score of 3.45 (SD 0.87) and 3.15 (SD 0.99), respectively, indicating a good level of accuracy in identifying the falseness of statements and a good understanding of their impact on public health. The AI-based tool showed a sensitivity of 85% and a positive predictive value of 100%. Overall, this indicates that when ChatGPT labels a statement as false, it is highly reliable, but it may miss identifying some false statements. When comparing with expert ratings, high intraclass correlation coefficients (ICCs) between ChatGPT's appraisals and expert opinions could be found, suggesting that the AI's ratings were generally aligned with expert views on falseness (ICC=.83, P<.001) and public health significance (ICC=.79, P=.001) of sleep-related myths. Qualitatively, both ChatGPT and sleep experts refuted sleep-related misconceptions. However, ChatGPT adopted a more accessible style and provided a more generalized view, focusing on broad concepts, while experts sometimes used technical jargon, providing evidence-based explanations. CONCLUSIONS: ChatGPT-4 can accurately address sleep-related queries and debunk sleep-related myths, with a performance comparable to sleep experts, even if, given its limitations, the AI cannot completely replace expert opinions, especially in nuanced and complex fields such as sleep health, but can be a valuable complement in the dissemination of updated information and promotion of healthy behaviors.

Actigraphic sleep dimensions and associations with academic functioning among adolescents.

STUDY OBJECTIVES: There is mixed evidence regarding associations of sleep duration with academic functioning in adolescents and a lack of research on other sleep dimensions, particularly using objective sleep measures. We examined associations of multiple actigraphic sleep dimensions with academic functioning among adolescents. METHODS: Data were from the sleep sub-study of the age 15 wave of the Future of Families and Child Wellbeing Study (n = 774-782; 52% female), a national, diverse sample of teens. Adolescents wore wrist-actigraphs for ~1 week and completed a survey reporting academic performance and school-related behavioral problems. Regression models assessed whether average sleep duration, timing, maintenance efficiency, and SD-variability were associated with self-reported academic functioning in cross-sectional analyses adjusted for demographic characteristics, depressive symptoms, and anxious symptoms. RESULTS: Later sleep timing (hours) and greater sleep variability (SD-hours) were associated with poorer academic outcomes, including sleep onset variability with higher odds of receiving a D or lower (OR = 1.29), sleep onset (ß = -.07), sleep offset (ß = -.08), and sleep duration variability (ß = -.08) with fewer A grades, sleep offset with lower GPA (ß = -.07), sleep offset (OR = 1.11), sleep duration variability (OR = 1.31), and sleep onset variability (OR = 1.42) with higher odds of being suspended or expelled in the past 2 years, and sleep duration variability with greater trouble at school (ß = .13). Sleep duration, sleep maintenance efficiency, and sleep regularity index were not associated with academic functioning. CONCLUSIONS: Later sleep timing and greater sleep variability are risk factors for certain academic problems among adolescents. Promoting sufficient, regular sleep timing across the week may improve adolescent academic functioning.

Sleep timing behaviour, sleep duration and adherence to obesogenic dietary patterns from pre-school to school age: results from the Portuguese birth cohort Generation XXI.

In an obesogenic environment, short sleeping may increase opportunistic eating. The timing of sleep might also influence the drive to eat. This study investigated the prospective association of sleep timing and duration with diet in 5286 children from the Portuguese birth cohort Generation XXI, evaluated at 4 and 7 years of age. At 4 years, sleep duration was categorised into ≤10 and >10 h. Four sleep timing categories were generated based on the median split for sleep-onset and -offset times: 'Early Sleep-Early Wake'; 'Early Sleep-Late Wake'; 'Late Sleep-Early Wake'; 'Late Sleep-Late Wake'. At 7 years, diet was obtained by a food frequency questionnaire and three dietary patterns were included: 'Healthier', 'Energy-Dense Foods (EDF)' and 'Snacking'. The Healthy Eating Index was used to evaluate diet quality. Multinomial logistic regression models and generalised linear models were performed. Children who had a late sleep, independently of the time of waking up, had higher odds of following the 'EDF' pattern, compared with the 'Healthier'. Boys who had late sleep and/or late wake had also higher odds of following the 'Snacking' pattern and had poorer diet quality. In both sexes, a late sleep or late wake were associated with a lower diet quality, compared to the group 'Early Sleep-Early Wake', and independently of nap behaviour. In boys, shorter sleep duration was associated with a poorer diet. In conclusion, pre-schoolers with late bedtimes or wake-up times have worse dietary patterns and poorer diet quality at the age of 7 years, which seems to be independent of sleep duration.

Sleep deficiency among people living with human immunodeficiency virus: A growing challenge.

PURPOSE OF REVIEW: The purpose of this narrative review is to consolidate and summarize the existing literature on sleep deficiency among people living with human immunodeficiency virus (HIV; PLWH), to discuss the potential impact of antiretroviral therapy on sleep deficiency and to identify priorities for future research in this area. RECENT FINDINGS: Three important domains of sleep deficiency include alterations in sleep quality (including sleep disorders), duration and timing. The existing HIV and sleep deficiency literature, which is robust for sleep quality but sparser for sleep duration or sleep timing, has identified epidemiological correlates and outcomes associated with sleep deficiency including sociodemographic factors, HIV-specific factors, aspects of physical and mental health and cognition. SUMMARY: Sleep deficiency is a common problem among PLWH and is likely underdiagnosed, although more high-quality research is needed in this area. Sleep quality has received the most attention in the literature via methodologies that assess subjective/self-reported sleep quality, objective sleep quality or both. There is significantly less research on sleep duration and minimal research on sleep timing. Use of certain antiretroviral therapy drugs may be associated with sleep deficiency for some individuals. Future research should utilize larger, longitudinal studies with consistent, comprehensive and validated methods to assess both subjective and objective measures of sleep deficiency to better understand the prevalence, correlates and clinical implications of sleep deficiency in PLWH.

'It's satisfying but destructive': A qualitative study on the experience of bedtime procrastination in new career starters.

BACKGROUND: Bedtime procrastination, the volitional delay of going to bed without any external circumstances causing the delay, is linked to multiple indicators of inadequate sleep. Intervening to reduce bedtime procrastination may be an important avenue to improve sleep outcomes, yet the phenomenon remains poorly understood in populations at risk for bedtime procrastination. New career starters, those who have graduated from tertiary education and started a new full-time job within the past 12 months, may be susceptible to problematic bedtime procrastination and are at an opportune time for a 'fresh start' to change behaviour. AIMS: The objectives of this study were to understand how bedtime procrastination is experienced and perceived by new career starters, to identify the enablers and barriers to behaviour change in new career starters and to explore themes for future interventions. MATERIALS & METHODS: Data were collected through in-depth semi-structured interviews with 28 participants. RESULTS: Inductive thematic analysis was used to find seven themes: (1) negative feelings before and during bedtime procrastination; (2) wanting to versus knowing I shouldn't; (3) difficulty falling asleep; (4) influence of automatic processes; (5) consequences of bedtime procrastination; (6) lack of self-control and (7) technology captures late-night attention. Participants emphasised the need for me-time, self-negotiation to continue procrastinating and knowledge of the value of sleep. DISCUSSION & CONCLUSION: Findings suggest that bedtime procrastination involves both reflective and automatic cognitive processes. Future interventions would benefit from a dual-process approach, using cognitive and behavioural techniques to reduce bedtime procrastination.

Multidimensional sleep health and diabetic retinopathy: Systematic review and meta-analysis.

Diabetic retinopathy (DR) is one of the most prevalent microvascular diabetic complications. Poor sleep health and obstructive sleep apnea (OSA) are risk factors for diabetes and poor glycemic control. Recent studies have suggested associations between poor sleep health/OSA and DR. Furthermore, there have been suggestions of melatonin dysregulation in the context of DR. We conducted a systematic review and meta-analysis exploring the associations between multidimensional sleep health (duration, satisfaction, efficiency, timing/regularity and alertness), OSA and melatonin with DR. Forty-two studies were included. Long, but not short sleep, was significantly associated with DR, OR 1.41 (95%CI 1.21, 1.64). Poor sleep satisfaction was also significantly associated with DR, OR 2.04 (1.41, 2.94). Sleep efficiency and alertness were not associated with DR, while the evidence on timing/regularity was scant. Having OSA was significantly associated with having DR, OR 1.34 (1.07, 1.69). Further, those with DR had significantly lower melatonin/melatonin metabolite levels than those without DR, standardized mean difference -0.94 (-1.44, -0.44). We explored whether treating OSA with continuous positive airway pressure (CPAP) led to improvement in DR (five studies). The results were mixed among studies, but potential benefits were observed in some. This review highlights the association between poor multidimensional sleep health and DR.

Is evening chronotype associated with higher alcohol consumption? A systematic review and meta-analysis.

A broader understanding of whether and to what extent chronotype should be considered a risk factor for alcohol consumption is needed. The aim of this systematic review was to summarize the evidence on the association between evening chronotype and alcohol consumption. A systematic search of observational studies on this association was conducted in the PubMed, Scopus, Web of Science, Cochrane Library and PsycINFO databases up to April 30th, 2023. Random-effect models estimated the pooled odds ratio (OR) of alcohol consumption according to chronotype. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines and Quality Assessment tool for Observational Cohorts and Cross-sectional Studies from the National Heart, Lung and Blood Institute were followed. A total of 33 studies involving 28 207 individuals (age range: 18-93 years) were included in this review. Overall, most studies indicated a higher volume and frequency of alcohol consumption in evening-type individuals than in individuals with different chronotypes. Additionally, a meta-analysis including 13 studies showed that evening-type individuals were 41% more likely to consume alcohol than those with other chronotypes (OR = 1.41, 95% confidence interval: 1.16-1.66; I2 = 38.0%). Limitations of the present findings are the predominance of cross-sectional studies and varied definitions of alcohol consumption. The available evidence supports an association between the evening chronotype and alcohol consumption. The evening-type population, especially young adults, is a specific target for educational interventions for preventing or reducing alcohol consumption.PROSPERO number: CRD42022343778.

The associations between sleep timing and night sleep duration with dyslipidemia in a rural population: The Henan Rural Cohort Study.

Evidence linking sleep timing and night sleep duration to dyslipidemia was limited and inconclusive, especially among low- and middle-income adults. The aims were to evaluate the associations between sleep timing, night sleep duration and dyslipidemia in a rural population. Based on the Henan Rural Cohort Study, a total of 37 164 participants were included. The Pittsburgh Sleep Quality Index was used to collect sleep information. Logistic regression and restrictive cubic splines were conducted to explore the associations. Of the 37 164 enrolled participants, 13881 suffered from dyslipidemia. Compared to the reference groups, people who went to sleep after 23:00 or woke up after 7:30 had higher prevalence of dyslipidemia, the adjusted odds ratios (ORs) and 95% confidence intervals (CIs)were 1.30 (1.20-1.41) and 1.34 (1.19-1.50). The adjusted OR (95%CI) of participants in the Late-sleep/Late-rise category compared to the Early-sleep/Early-rise category was 1.55 (1.08-1.23). Compared to the reference (7~≤8 h), the adjusted OR (95%CI) was 1.11 (1.03-1.20) for longer (>9 h) night sleep duration. Moreover, the combined effects of sleep duration (>9 h) with sleep time (22:00~) (OR = 1.46, 95%CI: 1.16-1.84), sleep duration (>9 h) with wake-up time (≥7:30) (OR = 1.28, 95%CI: 1.08-1.51), and sleep duration (>9 h) with the Late-sleep/Late-rise category (OR = 1.41, 95%CI: 1.14-1.75) increased the prevalence of dyslipidemia. Accordingly, our results indicate that delayed sleep timing and longer night sleep duration had independent and joint effects on higher risks of dyslipidemia in rural population.

Disparities in sleep-wake patterns by labor force status: Population-based findings.

Sleep disturbances have been associated with unemployment, but variation in sleep-wake patterns by labor force status has rarely been examined. With a population-based sample, we investigated differences in sleep-wake patterns by labor force status (employed, unemployed, and not-in-the-labor-force) and potential disparities by sociodemographic variables. The analysis included 130,602 adults aged 25-60 y, who participated in the American Time Use Survey between 2003 and 2019. Individual sleep-wake pattern was extracted from time use logs in a strict 24-h period (04:00 h-03:59 h). Functional nonparametric regression models based on dimensionality reduction and neighborhood matching were applied to model the relationship between sleep-wake patterns and labor force status. Specifically, we predicted changes in intra-person sleep-wake patterns under hypothetical changes of labor force status from employed to unemployed or not-in-the-labor-force. We then studied moderations of this association by gender, race/ethnicity and educational attainment. In comparison to the employed state, unemployed and not-in-the-labor-force states were predicted to have later wake-times, later bedtimes, and higher tendency for taking midday naps. Changes in labor force status led to more apparent shifts in wake-times than in bedtimes. Additionally, sleep schedules of Hispanics and those with higher education level were more vulnerable to the change of labor force status from employed to unemployed.

Late, but Not Early, Night Sleep Loss Compromises Neuroendocrine Appetite Regulation and the Desire for Food.

OBJECTIVE: There is evidence that reduced sleep duration increases hunger, appetite, and food intake, leading to metabolic diseases, such as type 2 diabetes and obesity. However, the impact of sleep timing, irrespective of its duration and on the regulation of hunger and appetite, is less clear. We aimed to evaluate the impact of sleep loss during the late vs. early part of the night on the regulation of hunger, appetite, and desire for food. METHODS: Fifteen normal-weight ([mean ± SEM] body-mass index: 23.3 ± 0.4 kg/m2) healthy men were studied in a randomized, balanced, crossover design, including two conditions of sleep loss, i.e., 4 h sleep during the first night-half ('late-night sleep loss'), 4 h sleep during the second night-half ('early-night sleep loss'), and a control condition with 8h sleep ('regular sleep'), respectively. Feelings of hunger and appetite were assessed through visual analogue scales, and plasma ghrelin and leptin were measured from blood samples taken before, during, and after night-time sleep. RESULTS: Ghrelin and feelings of hunger and appetite, as well as the desire for food, were increased after 'late-night sleep loss', but not 'early-night sleep loss', whereas leptin remained unaffected by the timing of sleep loss. CONCLUSIONS: Our data indicate that timing of sleep restriction modulates the effects of acute sleep loss on ghrelin and appetite regulation in healthy men. 'Late-night sleep loss' might be a risk factor for metabolic diseases, such as obesity and type 2 diabetes. Thereby, our findings highlight the metabolic relevance of chronobiological sleep timing.

Evening chronotype, insufficient weekday sleep, and weekday-weekend gap in sleep times: What is really to blame for a reduction in self-perceived health among university students?

The association of insufficient sleep with reduced self-perceived health was previously well established. Moreover, it was sometimes shown that the indicators of poorer health were significantly related to chronotype and weekday-weekend gaps in sleep timing and duration. It remains to be elucidated, however, whether chronotype and these gaps can contribute to the reduced health self-ratings independently from shortened sleep duration or, alternatively, their relationship with health can be simply explained by their association with insufficient sleep on weekdays. In an online survey, we tested whether the self-rated health of university students can be predicted by several individual characteristics of the sleep-wake cycles, such as chronotype, weekday and weekend sleep times, weekday-weekend gap in sleep times, sleepability and wakeability at different times of the day, etc. Responses to a question about general health and to items of several questionnaires for chronobiological assessment were collected from smartphones of 1582 university students (mean age ± standard deviation was 19.5 ± 1.7 y). The results of regression analyses suggested that lower odds of having good self-rated health were significantly associated with an earlier weekday risetime, a later weekday bedtime, and, consequently, a shorter weekday time in bed. After accounting for weekday sleep, self-rated health showed significant association with neither chronotype nor weekday-weekend differences in sleep duration and timing. Besides, the adverse health effects of reduced weekday sleep were independent from the significant adverse effects of several other individual sleep-wake characteristics including poorer nighttime sleepability and lower daytime wakeability. We concluded that university students perceive the negative health impacts of losing sleep by waking up early on weekdays irrespective of their night sleep quality and daytime level of alertness. Their chronotype and weekday-weekend difference in sleep times might not be among significant contributors to this perception. It is of practical importance to consider the reduction of weekday sleep losses among the interventions aimed at preventing sleep and health problems.

Mindfulness, Subjective Cognitive Functioning, Sleep Timing and Time Expansion during COVID-19 Lockdown: A Longitudinal Study in Italy.

During the COVID-19 lockdown, a distortion of time passage has been widely reported in association with a change in daily rhythm. However, several variables related to these changes have not been considered. The purpose of the present study was to assess the changes in dispositional mindfulness, time experience, sleep timing and subjective memory functioning. A longitudinal study was conducted on 39 Italian adults (53.85% males; 35.03 ± 14.02 years) assessing mindfulness, ad hoc questions of sleep habits during workdays and free days, chronotypes, subjective time experience, and memory functioning before (December 2019-March 2020) and during (April 2020-May 2020) the first Italian COVID-19 lockdown. Participants reported delayed sleep timing, a slowdown in the perception of the present time, a decrease of time pressure, and an increase in the feeling of time expansion/boredom. In addition to correlations between mindfulness, memory functioning, and subjective sleep duration during workdays, a mediation model showed that changes in the dispositional mindfulness determined a delay of bedtime during workdays through the mediation effect of increased feeling of time expansion/boredom. This finding highlighted the role of mindfulness in reducing the feeling of time expansion/boredom for regulating the sleep timing. The theoretical and practical implications of the findings are discussed.

Sociodemographic, temporal and bedtime routine correlates of sleep timing and duration in South Asian and white children: A Born in Bradford study.

Objective: The study aimed to examine sociodemographic, temporal and bedtime routine correlates of parent-reported sleep duration and timing in a biethnic sample of 18 month and 36 month old children from a disadvantaged location. Methods: Between October 2010 and September 2012, parents completed a bespoke three day sleep diary when their child was approximately 18 months (n = 276) and 36 months of age (n = 262) (45.1% South Asian; 54.9% white). Parents reported their child's overnight sleep duration (h/day), the time their child fell asleep, their wake time and their child's bedtime and napping routines. Data were available at both time points for 135 children. Results: In line with previous literature, South Asian children had shorter overnight sleep duration and later sleep and wake times than white children. In both ethnic groups, children slept and woke up later on weekends, and children went to bed earlier and slept longer in winter. In white children only, napping duration was associated with overnight sleep period. No significant associations were found between napping frequency and overnight sleep duration. Based on parent-reported data, children who consistently adhered to regular bedtimes and had set times for sleeping tended to go to sleep earlier, wake earlier and have longer overnight sleep. Conclusions: The data showed parent-reported variation in sleep patterns between two ethnic groups within a single geographical and deprived area. It is important that researchers, clinicians and early years workers are considerate of cultural norms in sleep practices.

Sleep from Infancy Through Adolescence.

This article describes the changes in normal sleep regulation, structure, and organization and sleep-related changes in respiration from infancy to adolescence. The first 2 years of age are striking, with more time asleep than awake. With development, the electroencephalogram architecture has a marked reduction in rapid eye movement sleep and the acquisition of K-complexes, sleep spindles, and slow-wave sleep. During adolescence there is a reduction in slow-wave sleep and a delay in the circadian phase. Infants have a more collapsible upper airway and lower lung volumes than older children, which predisposes them to obstructive sleep apnea and sleep-related hypoxemia.

Temporal associations between nightly sleep with daytime eating and activity levels in free-living young adults.

STUDY OBJECTIVES: This study aimed to quantify the temporal associations between nightly sleep quantity and timing with daytime eating behavior and activity levels in free-living (i.e. non-experimental) settings. METHODS: Generally healthy young adults (N = 63; 28.9 ± 7.1 years) completed concurrent sleep (wrist actigraphy), eating (photo-assisted diet records), and activity (waist actigraphy) assessments over 14 days. Multilevel models quantified the associations between nightly sleep (total sleep time, timing of sleep and wake onset) with next-day eating behavior (diet quality, caloric intake, timing of eating onset/offset, eating window duration) and activity levels (total physical activity, sedentary time). Associations in the reverse direction (i.e. eating and activity predicting sleep) were explored. Models adjusted for demographic and behavioral confounders and accounted for multiple testing. RESULTS: At within- and between-subject levels, nights with greater-than-average total sleep time predicted a shorter eating window the next day (all p ≤ 0.002). Later-than-average sleep and wake timing predicted within- and between-subject delays in next-day eating onset and offset, and between-subject reductions in diet quality and caloric intake (all p ≤ 0.008). At within- and between-subject levels, total sleep time was bidirectionally, inversely associated with sedentary time (all p < 0.001), while later-than-average sleep and wake timing predicted lower next-day physical activity (all p ≤ 0.008). CONCLUSIONS: These data underscore the complex interrelatedness between sleep, eating behavior, and activity levels in free-living settings. Findings also suggest that sleep exerts a greater influence on next-day behavior, rather than vice versa. While testing in more diverse samples is needed, these data have potential to enhance health behavior interventions and maximize health outcomes.