UNASSIGNED: Stroke can result in or exacerbate various sleep disorders. The presence of behaviors such as daytime sleepiness poststroke can indicate underlying sleep disorders which can significantly impact functional recovery and thus require prompt detection and monitoring for improved care. Actigraphy, a quantitative measurement technology, has been primarily validated for nighttime sleep in healthy adults; however, its validity for daytime sleep monitoring is currently unknown. Therefore this study aims to identify the best-performing actigraphy sensor and algorithm for detecting daytime sleep in poststroke individuals.
UNASSIGNED: Participants wore Actiwatch Spectrum and ActiGraph wGT3X-BT on their less-affected wrist, while trained observers recorded daytime sleep occurrences and activity levels (active, sedentary, and asleep) during non-therapy times. Algorithms, Actiwatch (Autoscore AMRI) and ActiGraph (Cole-Kripke, Sadeh), were compared with on-site observations and assessed using F2 scores, emphasizing sensitivity to detect daytime sleep.
UNASSIGNED: Twenty-seven participants from an inpatient stroke rehabilitation unit contributed 173.5 hours of data. The ActiGraph Cole-Kripke algorithm (minute sleep time = 15 minutes, bedtime = 10 minutes, and wake time = 10 minutes) achieved the highest F2 score (0.59). Notably, when participants were in bed, the ActiGraph Cole-Kripke algorithm continued to outperform Sadeh and Actiwatch AMRI, with an F2 score of 0.69.
UNASSIGNED: The study demonstrates both Actiwatch and ActiGraph\'s ability to detect daytime sleep, particularly during bed rest. ActiGraph (Cole-Kripke) algorithm exhibited a more balanced sleep detection profile and higher F2 scores compared to Actiwatch, offering valuable insights for optimizing daytime sleep monitoring with actigraphy in stroke patients.

Two researchers independently assessed studies published up to February 5, 2023, across PubMed, Web of Science, Embase, and Cochrane Library, to investigate the associations of sleep traits with cardiometabolic risk factors, as well as with cardiovascular diseases. Fourteen systematic reviews consisting of 23 meta-analyses, and 11 Mendelian randomization (MR) studies were included in this study. Short sleep duration was associated with a higher risk of obesity, type 2 diabetes (T2D), hypertension, stroke, and coronary heart disease (CHD) in observational studies, while a causal role was only demonstrated in obesity, hypertension, and CHD by MR. Similarly, long sleep duration showed connections with a higher risk of obesity, T2D, hypertension, stroke, and CHD in observational studies, none was supported by MR analysis. Both observational and MR studies indicated heightened risks of hypertension, stroke, and CHD in relation to insomnia. Napping was linked to elevated risks of T2D and CHD in observational studies, with MR analysis confirming a causal role in T2D. Additionally, snoring was correlated with increased risks of stroke and CHD in both observational and MR studies. This work consolidates existing evidence on a causal relationship between sleep characteristics and cardiometabolic risk factors, as well as cardiovascular diseases.

BACKGROUND: The aim of the study is to estimate the prevalence and associated factors of insomnia among older adults in the Philippines.
METHODS: In all, 5206 cross-sectional nationally representative data from older adults (≥ 60 years) of the 2018 Longitudinal Study on Ageing and Health in the Philippines (LSAHP) was analysed. Napping frequency and duration were assessed by self-report.
RESULTS: The prevalence of regular nappers was 35.7%, low or moderate napping (1-59 min) was 10.5% and long napping (≥ 60 min) duration was 25.2%. In the final adjusted model, older age was not significantly associated with low or moderate napping duration but older age was positively associated with long napping duration. High wealth status, physical activity and late insomnia were positively associated with low or moderate napping duration. High wealth status, urban residence, daily activity limitations, and physical activity were positively associated, and currently working status, poor self-rated health status and current alcohol use were negatively associated with long napping duration.
CONCLUSIONS: One in four older adults reported long napping duration. Sociodemographic, health status and behaviour and sleep parameters were associated with low or moderate and/or long napping duration.

OBJECTIVE: Napping is a common habit in many countries. Nevertheless, studies about the chronic effects of napping on obesity are contradictory, and the molecular link between napping and metabolic alterations has yet to be studied. We aim to identify molecular mechanisms in adipose tissue (AT) that may connect napping and abdominal obesity.
METHODS: In this cross-sectional study, we extracted the RNA repeatedly across 24h from cultured AT explants and performed RNA sequencing. Circadian rhythms were analyzed using 6 consecutive time points across 24 hours. We also assessed global gene expression in each group (nappers vs. non-nappers).
RESULTS: With napping, there was a loss of rhythmicity in 88% of genes that showed circadian rhythmicity among non-nappers, a reduction in rhythm amplitudes of 29%, and significant phase changes from a coherent unimodal acrophase in non-nappers, towards a scattered and bimodal acrophase in nappers. Those genes that lost rhythmicity with napping were mainly involved in pathways of glucose and lipid metabolism, and of the circadian clock. Additionally, we found differential global gene expression between nappers and non-nappers with 34 genes down- and 32 genes up-regulated in nappers. The top up-regulated gene (IER3) and top down-regulated pseudogene (VDAC2P2) in nappers have been previously shown to be involved in inflammation.
CONCLUSIONS: These new findings may have implications for our understanding of napping\'s effects on obesity and metabolic disorders.

BACKGROUND: Painful temporomandibular disorder (TMD) is the common cause of chronic oro-facial pain, which may interfere with sleep. Previous studies have documented an association between sleep and TMD.
OBJECTIVE: This study aimed to further explore the association of night-time sleep and daytime napping with painful TMD.
METHODS: A total of 419 patients (aged 31.88 ± 11.54 years with women forming 85.4%) from a TMD/Orofacial Pain center were enrolled. Patients\' sleep conditions were evaluated with the Pittsburgh Sleep Quality Index (PSQI) questionnaire, and information on night-time sleep duration, napping duration and napping frequency was interviewed. TMD was diagnosed according to the Diagnostic Criteria for TMD protocol and stratified into myalgia (muscle pain), arthralgia (joint pain) and combined (muscle and joint pain) subgroups. The severity of TMD was measured with the Fonseca Anamnestic Index (FAI) questionnaire. Restricted cubic spline (RCS) regression models were established to explore relationships between sleep and painful TMD subgroups.
RESULTS: Patients with poor sleep quality (PSQI≥6) had higher FAI scores (median 60, p < .001) and higher proportions of painful TMDs. The myalgia subgroup had higher PSQI scores (median 8, p < .001) than the arthralgia subgroup. The RCS models indicated a non-linear relationship between night-time sleep duration and myalgia (p < .001), which was not observed in arthralgia. However, there were no significant findings concerning napping and painful TMD subgroups.
CONCLUSIONS: This study found that the association between sleep and TMD is mainly related to painful TMD conditions, which are associated with night-time sleep duration.

OBJECTIVE: Given the plausible mechanisms and the lacking of empirical evidence, the study aims to investigate how gestational sleep behaviors and the development of sleep disorders, such as restless legs syndrome, influence ultrasonographic measures of fetal growth.
METHODS: The study included 2457 pregnant women from the NICHD Fetal Growth Studies - Singletons (2009-2013), who were recruited between 8-13 gestational weeks and followed up to five times during pregnancy. Women were categorized into six groups based on their total sleep hours and napping frequency. The trajectory of estimated fetal weight from 10-40weeks was derived from three ultrasonographic measures. Linear mixed effect models were applied to model the estimated fetal weight in relation to self-reported sleep-napping behaviors and restless legs syndrome status, adjusting for age, race and ethnicity, education, parity, prepregnancy body mass index category, infant sex, and prepregnancy sleep-napping behavior.
RESULTS: From enrollment to near delivery, pregnant women\'s total sleep duration and nap frequency declined and restless legs syndrome symptoms frequency increased generally. No significant differences in estimated fetal weight were observed by sleep-napping group or by restless legs syndrome status. Results remained similar in sensitivity analyses and stratified analyses by women\'s prepregnancy body mass index category (normal vs. overweight/obese) or by infant sex.
CONCLUSIONS: Our data indicate that there is no association between sleep during pregnancy-assessed as total sleep duration and napping frequency, nor restless legs syndrome symptoms-and fetal growth from weeks 10 to 40 in healthy pregnant women.

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.
CONCLUSIONS: 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.

[This corrects the article DOI: 10.3389/fendo.2024.1294638.].

As the incidence of type 2 diabetes mellitus (T2DM) is increasing rapidly and its consequences are severe, effective intervention and prevention, including sleep-related interventions, are urgently needed. As a component of sleep architecture, naps, alone or in combination with nocturnal sleep, may influence the onset and progression of T2DM. Overall, napping is associated with an increased risk of T2DM in women, especially in postmenopausal White women. Our study showed that napping >30 minutes (min) increased the risk of T2DM by 8-21%. In addition, non-optimal nighttime sleep increases T2DM risk, and this effect combines with the effect of napping. For nondiabetic patients, napping >30 min could increase the risks of high HbA1c levels and impaired fasting glucose (IFG), which would increase the risk of developing T2DM later on. For diabetic patients, prolonged napping may further impair glycemic control and increase the risk of developing diabetic complications (e.g., diabetic nephropathy) in the distant future. The following three mechanisms are suggested as interpretations for the association between napping and T2DM. First, napping >30 min increases the levels of important inflammatory factors, including interleukin 6 and C-reactive protein, elevating the risks of inflammation, associated adiposity and T2DM. Second, the interaction between postmenopausal hormonal changes and napping further increases insulin resistance. Third, prolonged napping may also affect melatonin secretion by interfering with nighttime sleep, leading to circadian rhythm disruption and further increasing the risk of T2DM. This review summarizes the existing evidence on the effect of napping on T2DM and provides detailed information for future T2DM intervention and prevention strategies that address napping.

BACKGROUND: Sleep and physical performance are strongly related and mutually influence each other. Athletes, particularly in disciplines like offshore sailing and ultra-endurance sports, often suffer from sleep deprivation due to factors like irregular training times, travel, and the extended duration of events like 100-mile mountain races. Despite growing interest in sleep\'s role in sports science, few studies have specifically investigated the sleep patterns of ultramarathon runners. This study aimed to investigate sleep patterns and sleep management strategies in ultramarathons, and the repercussions of sleep deprivation during and after races.
METHODS: This cross-sectional study using e-survey was conducted on 1154 runners from two ultramarathons (a 165 km race with 9,576 m positive elevation; 2018 finish time [23:18:48-66:04:00], and a 111 km race with 6,433 m elevation; [15:34:56 - 41:54:16]).
RESULTS: The results revealed that 58% of the runners reported implementing sleep management strategies before or during the race. Most runners began the race with some level of sleep debt (-50 min a week before the race). During the races, 77% of runners slept, with the cumulative sleep duration varying based on race duration and the number of nights spent on the race (76 min at 165 km and 27 min at 111 km). Short naps lasting less than 30 min were the most popular strategy. The prevalence of symptoms attributed to sleep deprivation during the race was high (80%), with reported falls and hallucinations. After the race, runners reported recovering a normal state of wakefulness relatively quickly (within two days); 22% believed that sleep deprivation during the race increased the risk of accidents in everyday life.
CONCLUSIONS: This study provides valuable insights into sleep patterns and strategies in ultramarathon running and emphasizes the importance of adequate sleep management for performance and post-race recovery.