Combined effects of sleep timing and nighttime sleep duration on non-alcoholic fatty liver disease.

BACKGROUND: While short sleep duration is linked to higher risk of non-alcoholic fatty liver disease (NAFLD), the combined effects of sleep timing and sleep duration on NAFLD are less explored. METHODS: In this cross-sectional study of 39,471 participants from Beijing-Tianjin-Hebei region of China, self-reported sleep information and ultrasonography-diagnosed NAFLD were obtained from Jan 2018 to Jan 2020. Sleep timing was categorized based on sleep midpoint: early-type (before 2:00 AM), intermediate-type (2:00-2:30 AM), and late-type (after 2:30 AM). We used multivariable logistic regression to explore the relationship between sleep timing, duration, and NAFLD. We analyzed sleep midpoint and duration categorically and continuously, and conducted stratification analyses by age, sex, body mass index, hypertension, diabetes, and dyslipidemia. RESULTS: Intermediate-type (OR: 1.15, 95% confidence interval: 1.05-1.26) and late-type sleep timing (OR: 1.08, 1.00-1.16) were associated with higher NAFLD risk compared to early-type. Additionally, longer sleep duration was linked to lower risk (OR: 0.92, 0.90-0.95 per hour increase). Notably, intermediate to late-type sleepers with normal sleep duration (7 to <8 h) exhibited a 20% higher NAFLD risk compared to early-type sleepers with the same duration (OR: 1.20, 95% CI: 1.04-1.39). The increased NAFLD risk associated with intermediate to late sleep timing was particularly evident in men, hypertension, and prediabetes or diabetes participants. CONCLUSIONS: Intermediate to late sleep timing, even with normal sleep duration, is associated with increased NAFLD risk. These findings underscore the importance of considering both sleep timing and sleep duration for NAFLD prevention, especially in men and individuals with cardiometabolic conditions.

Weekday and weekend sleep times across the human lifespan: a model-based simulation.

PURPOSE: The shifts in the opposite directions, toward later and earlier sleep timing, occur during the transition through adolescence and adulthood, respectively. Such a n-shape of age-associated change in sleep timing does not resemble the inverse relationship of sleep duration with ages. Age-associated variation in the parameters of the mechanisms of circadian and homeostatic regulation of sleep would underlie these different shapes of relationship of sleep times with ages. Here, we searched for a parsimonious explanation of these different shapes by simulating sleep times on weekdays and weekends with one of the variants of the two-process model of sleep regulation. METHODS: Using mean age of a sample with reported sleep times on weekdays and weekends, the whole set of 1404 such samples was subdivided into 15 age subsets. Simulations of sleep times in these subsets were performed with and without the suggestion of age-associated variation in the circadian phase. RESULTS: Simulations showed that the age-associated decay of slow-wave activity can parsimoniously explain not only the parallel decreases in weekend sleep duration and rate of the buildup of sleep pressure during the wake phase of the sleep-wake cycle, but also both the delay and advance of sleep timing during the transition through adolescence and adulthood, respectively. CONCLUSION: The almost functional relationships were revealed between the age-related changes in sleep duration, rate of the buildup of sleep pressure, and slow-wave activity that is a good electrophysiological marker of cortical metabolic rate and synaptic density, strength and efficacy.

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.

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.

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.

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.

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 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.

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.

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.

The Impact of Sleep Disorders on Cardiovascular Health: Mechanisms and Interventions.

This comprehensive review article explores the intricate mechanisms at work and possible remedies for the connection between sleep issues and cardiovascular health. Sleep disorders, which include conditions like insomnia and sleep apnea, are drawing increasing amounts of attention due to their serious detrimental consequences on cardiovascular health. This article carefully examines the body of existing evidence to explain the intricate mechanisms that connect sleep disruptions to cardiovascular issues. Mechanisms include inflammation, disruption of the autonomic nervous system, endothelial dysfunction, and aberrant metabolic processes all have an impact on these pathways. The study also looks at a variety of existing and novel therapeutic modalities that aim to minimize the detrimental effects of sleep disruptions on cardiovascular health. This includes evaluating the effectiveness of lifestyle changes, pharmaceutical interventions, and behavioural therapy for enhancing sleep quality and hence preserving cardiovascular health. By synthesising and presenting the most recent study data, this article offers valuable insights into the complex relationships between sleep patterns, cardiovascular function, and potential therapeutics. These results provide a solid foundation for guiding future research endeavours and clinical judgements. Pharmacotherapy is a possibility for momentary relief. Cardiovascular illness has been linked to the sensorimotor problem known as restless legs syndrome (RLS), which causes a strong impulse to move the legs. Sleep disruption caused by RLS-related leg movements leads to sympathetic activation, elevated blood pressure, impaired vascular function, and potential iron deficiency. Treating the underlying iron deficiency, when present, and medications targeting dopamine receptors or regulating calcium channels are the primary interventions for RLS. In conclusion, sleep disorders significantly impact cardiovascular health through multiple mechanisms. Early detection, accurate diagnosis, and appropriate interventions are crucial for mitigating associated cardiovascular risks. Multidisciplinary approaches including lifestyle modifications, behavioral interventions, and targeted pharmacotherapy have shown promise in improving sleep quality and cardiovascular outcomes. Further research is needed to enhance our understanding of the complex interplay between sleep disorders and cardiovascular health, leading to the development of more effective interventions and improved patient outcomes.

Sleep-wake patterns and disturbances in Portuguese primary school children: a comparison between 1995 and 2016.

Purpose: It is often assumed sleep duration has decreased and sleep schedules have delayed over the last decades, as society modernized. We aimed to investigate changes in the sleep patterns of school-age children over time. Methods: We compared the sleep timings, durations, and disturbances of primary school-age children in 1995 and roughly two decades later, in 2016. Data from 666 children attending the 3rd and 4th grades of basic education were combined from two different cross-sectional school-based studies conducted within the same educational region of mainland Portugal using the same parent-report questionnaire (Children's Sleep-wake Patterns Questionnaire). Results: Mean sleep duration did not differ significantly between the two time points (schooldays: t = .118, p = .906; free days: t = 1.310, p = .191), albeit the percentage of children sleeping the recommended number of hours decreased significantly in 2016 when compared to 1995 (schooldays: χ2 = 4.406, p = .036; free days: χ2 = 16.859, p < .001). Wake-times advanced on free days in 2016. Difficulties on settling to sleep alone and returning to sleep were more prevalent in 2016, as well as fearing the dark and needing lights on or parent's presence to fall asleep. Conclusions: Sleep onset-related disturbances appear to have increased from 1995 to 2016. One possible explanation for this increase might be the change in parental practices preventing children from learning to fall asleep autonomously.

Chronotype ontogeny related to gender

Chronotype is an established concept designed to identify distinct phase relationships between the expression of circadian rhythms and external synchronizers in humans. Although it has been widely accepted that chronotype is subjected to ontogenetic modulation, there is no consensus on the interaction between age and gender. This study aimed to determine the relationship between age- and gender-related changes in the morningness-eveningness character in a large sample of people. A total of 14,650 volunteers were asked to complete the Brazilian version of the Horne and Östberg chronotype questionnaire. The data demonstrated that, on average, women were more morning-oriented than men until the age of 30 and there were no significant differences between men and women from 30 to 45 years of age. In contrast to the situation observed until the age of 30, women older than 45 years were more evening-oriented than men. These results suggest that the ontogenetic development of the circadian timekeeping system is more plastic in men, as represented by the larger amplitude of chronotype changes throughout their aging process. The phase delay of adolescence and phase advance of the elderly seem to be phenomena that are more markedly present in men than in women. Thus, our data, for the first time, provide support that sharply opposes the view that there is a single path toward morningness as a function of age, regardless of gender.