Frequent Napping Research Articles

Impact of Breakfast Consumption and Sleep Habits on Morning Attention and Concentration Among Health Professional Students.

Background Breakfast consumption and sleep habits are known to affect cognitive performance, yet their specific impact on health professional students' morning attention is underresearched. Objective The study's objective was to assess the influence of sleeping habits and breakfast eating habits on health professional students' morning attention span. Methodology A cross-sectional study was conducted with 323 undergraduate health professional students from medical colleges in Lahore, Pakistan. Participants completed an online questionnaire that gathered data on demographic characteristics, breakfast consumption patterns, sleep habits, and morning attention levels. Morning attention was measured using a self-reported scale where students rated their ability to concentrate during morning lectures on a five-point Likert scale ranging from "very poor" to "very good." Additional questions assessed the frequency and quality of breakfast consumption, sleep duration, sleep quality (using the Pittsburgh Sleep Quality Index), and daytime napping habits. Statistical analyses, including descriptive statistics and multiple regression analysis, were conducted using the IBM SPSS Statistics for Windows, Version 23 (Released 2015; IBM Corp., Armonk, New York, United States) to explore the relationships between breakfast and sleep habits and their effects on self-reported attention during morning lectures. Results Of the 323 participants, 78 (24.14%) never skipped breakfast, while 71 (22.93%) skipped breakfast regularly. Breakfast skippers exhibited poorer attention, with a coefficient of -0.45 (p = 0.0002). Students consuming a more nutritious breakfast demonstrated improved attention, with a coefficient of 0.32 (p < 0.0001). Regarding sleep, 196 students (60.68%) slept four to six hours; those with longer sleep durations had better attention (coefficient = 0.21, p = 0.020). Conversely, 271 participants (83.90%) reported that frequent daytime napping and poor sleep quality, including frequent nighttime awakenings, had a negative impact on attention, with coefficients of -0.30 (p = 0.007) and -0.28 (p = 0.005), respectively. Additionally, 161 students (49.84%) reported difficulty concentrating during morning lectures. Conclusion Regular consumption of a nutritious breakfast and sufficient sleep are crucial for maintaining optimal morning attention and cognitive performance among health professional students.

Multidimensional Sleep Profiles via Machine learning and Risk of Dementia and Cardiovascular Disease.

Sleep health comprises several dimensions such as duration and fragmentation of sleep, circadian activity, and daytime behavior. Yet, most research has focused on individual sleep characteristics. Studies are needed to identify sleep profiles incorporating multiple dimensions and to assess how different profiles may be linked to adverse health outcomes. To identify actigraphy-based 24-hour sleep/circadian profiles in older men and to investigate whether these profiles are associated with the incidence of dementia and cardiovascular disease (CVD) events over 12 years. Data came from a prospective sleep study with participants recruited between 20032005 and followed until 2015-2016. Multicenter population-based cohort study. Among the 3,135 men enrolled, we excluded 331 men with missing or invalid actigraphy data and 137 with significant cognitive impairment at baseline, leading to a sample of 2,667 participants. Leveraging 20 actigraphy-derived sleep and circadian activity rhythm variables, we determined sleep/circadian profiles using an unsupervised machine learning technique based on multiple coalesced generalized hyperbolic mixture modeling. Incidence of dementia and CVD events. We identified three distinct sleep/circadian profiles: active healthy sleepers (AHS; n=1,707 (64.0%); characterized by normal sleep duration, higher sleep quality, stronger circadian rhythmicity, and higher activity during wake periods), fragmented poor sleepers (FPS; n=376 (14.1%); lower sleep quality, higher sleep fragmentation, shorter sleep duration, and weaker circadian rhythmicity), and long and frequent nappers (LFN; n=584 (21.9%); longer and more frequent naps, higher sleep quality, normal sleep duration, and more fragmented circadian rhythmicity). Over the 12-year follow-up, compared to AHS, FPS had increased risks of dementia and CVD events (Hazard Ratio (HR)=1.35, 95% confidence interval (CI)=1.02-1.78 and HR=1.32, 95% CI=1.08-1.60, respectively) after multivariable adjustment, whereas LFN showed a marginal association with increased CVD events risk (HR=1.16, 95% CI=0.98-1.37) but not with dementia (HR=1.09, 95%CI=0.86-1.38). We identified three distinct multidimensional profiles of sleep health. Compared to healthy sleepers, older men with overall poor sleep and circadian activity rhythms exhibited worse incident cognitive and cardiovascular health. These results highlight potential targets for sleep interventions and the need for more comprehensive screening of poor sleepers for adverse outcomes.

Causal relationship between sleep phenotype and idiopathic normal pressure hydrocephalus: a two-sample bidirectional Mendelian randomization study

To explore the causal relationship between sleep phenotype and idiopathic normal pressure hydrocephalus (iNPH) using two-sample bidirectional Mendelian randomization. The exposure data including 8 sleep phenotypes used in this study were obtained from GWAS catalog, FinnGenR10 and MRCIEU GWAS. The outcome data for idiopathic normal-pressure hydrocephalus were obtained from FinnGen R10. We used the inverse-variance weighted (IVW) method to perform the principal analyses. Cochrane Q-statistics test was used to assess the heterogeneity and MR Egger‑intercept test performed to evaluate the pleiotropy for sensitivity analyses. IVW result showed that frequent daytime nap was associated with higher odds of iNPH (OR=3.3393, 95 CI% : 1.0646-10.4742, P=0.0270). Cochrane Q-statistics test and MR Egger‑intercept test showed that the MR analysis had no pleiotropy or heterogeneity (P > 0.05). The external validation reproduced this result (OR=2.5660, 95 CI% : 1.1680-5.6373, P=0.0189; OR=4.0424, 95 CI% : 1.5709-10.4024, P=0.0038). Reverse Mendelian randomization suggested that iNPH did not have significant impact on sleep phenotype. The frequency of daytime naps is causally associated with iNPH, and reducing the frequency of weekly daytime naps can reduce the risk of iNPH in the elderly population.

From the Workroom to the Bedroom: Work-to-Home Spillover as a Mechanism Linking Work Characteristics to Sleep Health.

Work may influence the home domain and subsequently impact employee sleep. Past work found that negative spillover mediated the relationship between perceived unfairness about work and insomnia symptoms across 20 years. As an extension of past work, this study investigated whether negative spillover and positive spillover mediate the relationship between job demands (perceived unfairness, job discrimination) and job resources (coworker and supervisor support) on multidimensional sleep health. Two waves of survey data from a subset of full-time workers were obtained from the Midlife in the United States Study approximately 10 years apart. A sleep health composite captured irregularity, dissatisfaction, nap frequency, inefficiency, and suboptimal sleep duration (higher=more sleep health problems). PROCESS Macro evaluated cross-sectional (T1) and sequential (T1 exposureaT1 mediatoraT2 outcome) mediation pathways, adjusting for sociodemographic characteristics, physical health, neuroticism, and work hours. Both cross-sectionally and prospectively, higher negative spillover mediated the association of higher unfairness with more sleep health problems, and the association between higher discrimination and more sleep health problems. There was no support for positive spillover as a mediator between job resources and sleep health cross-sectionally or prospectively. Findings suggest that organizations should reduce the amount of negative spillover by limiting instances of unfairness and discrimination at work to promote specific aspects of employee sleep health such as sleep irregularity, dissatisfaction, efficiency, and nap frequency.

Daytime napping and the incidence of Parkinson’s disease: a prospective cohort study with Mendelian randomization

BackgroundThe causal relationship between daytime napping and the risk of Parkinson’s disease (PD) remains unclear, with prospective studies providing limited evidence. This study investigated the association between daytime napping frequency and duration and PD incidence and explored the causality relationship between this association by conducting Mendelian randomization (MR) analysis.MethodsThis prospective cohort study included 393,302 participants, and accelerometer-measured daytime napping data were available only for 78,141 individuals. Cox proportional hazards regression was used to estimate the association between the daytime napping frequency and duration and the PD risk. The role of the systemic immune-inflammation index (SII) in the association between daytime napping frequency and PD risk was assessed through mediation analyses. Moreover, the causal association between the daytime napping frequency and the PD risk was preliminarily explored by conducting two-sample MR analyses.ResultsThe median follow-up duration was 12.18 years. The participants who reported napping sometimes or usually exhibited a significantly higher PD risk than those who never/rarely napped during the day [sometimes: hazard ratio (HR), 1.13; 95% confidence interval (CI), 1.03–1.23; usually: HR, 1.33; 95% CI, 1.14–1.55], and SII played a mediating role in this association. However, the MR analyses did not indicate that the daytime napping frequency and PD risk were significantly associated. The participants napping for over 1 h exhibited a significantly elevated PD risk (HR, 1.54; 95% CI, 1.11–2.16). Moreover, no significant interaction was identified between napping frequency or duration and genetic susceptibility to PD (P for interaction > 0.05).ConclusionsIn this study, increased daytime napping frequency and duration were associated with an increased PD risk, but no causal relationship was observed between napping frequency and PD risk in the MR analysis. Larger GWAS-based cohort studies and MR studies are warranted to explore potential causal relationships.

No genetic association between sleep traits and periodontitis: A bidirectional two-sample Mendelian randomization study

ABSTRACT Objective This study aimed to investigate the potential genetic link between sleep traits and periodontitis. Methods A two-sample bidirectional Mendelian randomization (MR) analysis was conducted using publicly available genome-wide association studies data on chronotype, daytime sleepiness, daytime napping frequency, insomnia, sleep duration, snoring, and the apnea-hypopnea index (AHI), along with a separate dataset on periodontitis. Results Chronotype (OR = 0.929, 95% CI = 0.788–1.095), daytime sleepiness (OR = 0.492, 95% CI = 0.186–1.306), daytime napping frequency (OR = 1.178, 95% CI = 0.745–1.863), sleep duration (OR = 0.868, 95% CI = 0.644–1.169), AHI (OR = 1.124, 95% CI = 0.980–1.289), insomnia (OR = 0.832, 95% CI = 0.440–1.573), and snoring (OR = 0.641, 95% CI = 0.198–2.075) had no effect on periodontitis. Similarly, periodontitis demonstrated no significant effect on sleep traits. Conclusions There is no evidence of a bidirectional genetic relationship between sleep traits and the risk of periodontitis.

Association of night-time sleep and daytime napping with painful temporomandibular disorder.

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. This study aimed to further explore the association of night-time sleep and daytime napping with painful TMD. 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. 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. 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.

Sleep duration, napping behaviors and restless legs syndrome during pregnancy and the trajectories of ultrasonographic measures of fetal growth: Findings from the NICHD Fetal Growth Studies–Singletons

ObjectivesGiven 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. MethodsThe 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. ResultsFrom 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. ConclusionsOur 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.

Sleep disorders in chronic kidney disease.

Sleep disorders are highly prevalent in chronic kidney disease (CKD) but are often under-recognized. Restless legs syndrome, which is common in CKD owing to issues with dopamine metabolism and is exacerbated by iron deficiency and uraemia, can lead to poor sleep quality and increased daytime fatigue. Insomnia is also prevalent in CKD, particularly in patients requiring dialysis, with increased sleep latency and sleep fragmentation being reported. The cause of insomnia in CKD is multifactorial - poor sleep habits and frequent napping during dialysis, uraemia, medications and mood disorders have all been suggested as potential contributing factors. Sleep apnoea and CKD are also now recognized as having a bi-directional relationship. Sleep apnoea is a risk factor for accelerated progression of CKD, and fluid overload, which is associated with kidney failure, can lead to both obstructive and central sleep apnoea. The presence of obstructive sleep apnoea in CKD can exacerbate the already heightened cardiovascular morbidity and mortality in these patients, as well as leading to daytime fatigue and reduced quality of life. Increased awareness, timely diagnosis and appropriate therapeutic interventions are essential to reduce the negative impact of sleep disorders in patients with kidney disease.

The relationship between daytime napping and glycemic control in people with type 2 diabetes.

To examine the association between napping characteristics and glycemic control in people with type 2 diabetes. This study used a cross-sectional design. A convenience sample of people with type 2 diabetes (N=226) were included. Glycemic control was indicated by HbA1c which was measured by A1C Now®+. Napping characteristics including napping frequency, duration, timing, and type were measured by validated questionnaires. Other variables, such as insomnia, cognitive impairment, and depression were measured by the Insomnia Severity Index, Montreal Cognitive Assessment, and Patient Health Questionnaire-9, respectively. Multivariate linear regression analyses were performed. The sample consisted of 122 women (54.0%), with a median age of 67 years. Their median HbA1c was 6.8%. No significant relationship was found between napping frequency and HbA1c. Among nappers, after controlling for covariates, long napping duration (≥60 min) and morning napping were both associated with poorer glycemic control. Compared with appetitive napping, restorative napping was associated with better glycemic control. Daytime napping (e.g., duration and type) is an important modifiable factor for glycemic control in people with type 2 diabetes. This study provides new insights into the relationship between napping and glucose management among people with diabetes.

Shorter self-reported sleep duration is associated with worse virtual spatial navigation performance in men.

Sleep has been shown to impact navigation ability. However, it remains unclear how different sleep-related variables may be independently associated with spatial navigation performance, and as to whether gender may play a role in these associations. We used a mobile video game app, Sea Hero Quest (SHQ), to measure wayfinding ability in US-based participants. Wayfinding performance on SHQ has been shown to correlate with real-world wayfinding. Participants were asked to report their sleep duration, quality, daytime sleepiness and nap frequency and duration on a typical night (n = 766, 335 men, 431 women, mean age = 26.5years, range = 18-59years). A multiple linear regression was used to identify which self-reported sleep variables were independently associated with wayfinding performance. Shorter self-reported sleep durations were significantly associated with worse wayfinding performance in men only. Other self-reported sleep variables showed non-significant trends of association with wayfinding performance. When removing non-typical sleepers (< 6 or > 9h of sleep on a typical night), the significant association between sleep duration and spatial navigation performance in men was no longer present. These findings from U.S.-based participants suggest that a longer self-reported sleep duration may be an important contributor to successful navigation ability in men.

Association between daytime napping and incident arrhythmias: A prospective cohort study and mendelian randomization analysis

BackgroundEmerging evidence has linked daytime napping with the risk of cardiovascular events. Cardiac arrhythmias are considered an early clinical stage for cardiovascular diseases. However, whether napping frequency is associated with incident arrhythmias remains unknown. ObjectiveThis study aimed to prospectively investigate the association between napping frequency and cardiac arrhythmias. MethodsDaytime napping frequency was self-reported in response to touchscreen questionnaires. The primary outcomes were incident arrhythmias including atrial fibrillation/flutter (AF/Af), ventricular arrhythmia, and bradyarrhythmia. Cox regression analysis was conducted on the basis of 491,117 participants free of cardiac arrhythmias from the UK Biobank. The 2-sample mendelian randomization (MR) and 1-sample MR were used to ensure a causal effect of genetically predicted daytime napping on the risk of arrhythmias. ResultsDuring a median follow-up of 11.91 years, 28,801 incident AF/Af cases, 4132 incident ventricular arrhythmias, and 11,616 incident bradyarrhythmias were documented. Compared with never/rarely napping, usually napping was significantly associated with higher risks of AF/Af (hazard ratio, 1.141; 95% CI, 1.083–1.203) and bradyarrhythmia (hazard ratio, 1.138; 95% CI, 1.049–1.235) but not ventricular arrhythmia after adjustment for various covariates. The 2-sample MR and 1-sample MR analysis showed that increased daytime napping frequency was likely to be a potential causal risk factor for AF/Af in FinnGen (odds ratio, 1.626; 95% CI, 1.061–2.943) and bradyarrhythmia in the UK Biobank (odds ratio, 1.005; 95% CI, 1.002–1.008). ConclusionThe results of this study add to the burgeoning evidence of an association between daytime napping frequency and an increased risk of cardiac arrhythmias including AF/Af, ventricular arrhythmia, and bradyarrhythmia.

The relationship between daytime napping and anxiety level of medical faculty students of universitas Muhammadiyah Purwokerto

Introduction: Anxiety and sleep deprivation are common concerns among medical students, affecting their essential cognitive and psychomotor skills. One effective solution is incorporating daytime napping, which improves performance, productivity, and mental well-being. Objectives: Analyzing the relationship between the frequency and duration of naps and the level of anxiety among students of the Faculty of Medicine, Universitas Muhammadiyah Purwokerto. Methods Materials: A cross-sectional study was conducted on medical students at the Faculty of Medicine, Universitas Muhammadiyah Purwokerto. The quality of daytime napping was assessed based on a questionnaire about the frequency and duration of daytime naps, and the anxiety levels of the respondents were evaluated using the Hamilton Anxiety Rating Scale (HARS). Results: Among 185 respondents, the majority had a daytime napping habit (93%), with a frequency of 1-3 times per week (56.2%), lasting for 31-60 minutes per day (44.9%). Fisher's analysis results indicate that respondents with a daytime napping habit with a frequency of 4-6 times (p = 0.018) and a duration of 1-30 minutes per week (p = 0.022) tend to have lower anxiety levels. Conclusion: Based on the analysis and discussion conducted, it can be concluded that there is a very strong relationship between daytime napping habits and anxiety levels in the Faculty of Medicine, Muhammadiyah Purwokerto University students.

SLEEP AND SEXUALITY AMONG CAREGIVERS AND THEIR PARTNERS

Abstract Older adult caregivers have increased risk of disturbed sleep, which is associated with declines in sexual frequency. Spousal caregivers engage in less sexual activity than caregivers of non-spouses. We examined whether the associations between sleep behaviors (duration, napping frequency, feeling rested) and couples’ sexual frequency, quality, and pleasure were similar among dyads in which one spouse was providing care to a spouse (n = 146) or a parent or other care recipient (n = 211). Using Wave 2 of the NSHAP and actor-partner interdependence models, we found significant differences (p &amp;lt;.01) between dyads. For all spouses, only frequency of sharing a bed was related to frequency of sexual activity in the previous 12 months. Sleep duration was not associated with any outcomes. In both groups, frequency of sharing a bed was positively associated with reports of physical pleasure (b’s ranged from .20 to .50). In spousal caregiver couples, caregivers’ greater napping frequency was negatively associated (b = -.29, p &amp;lt;.01) with their partner’s reports of a physically pleasurable relationship, and their reports of feeling rested were positively (b = .17, p &amp;lt; .01) associated with their own reports of pleasure. For couples in which the caregiver was caring for a non-spouse, there were actor effects for caregivers’ and noncaregivers’ napping frequency on lower reports of sexual relationship quality (b = .19 and .49, respectively), and a partner effect for non-caregivers (b = .25). These results point to the importance of understanding the context of caregiving, sleep behaviors, and sexual relationships.

SLEEP TIGHT, STAY HEALTHY? MULTIDIMENSIONAL SLEEP HEALTH AND CHRONIC CONDITION DEVELOPMENT OVER ONE DECADE

Abstract Chronic conditions affect half of adults and are the leading cause of death in the United States. Healthy sleep is a modifiable risk factor, but greater information is needed about specific sleep experiences linked to chronic condition development. The present study aims to (1) identify within-person patterns of various sleep experiences (i.e., sleep health phenotypes describing sleep duration, regularity, sleep onset latency, insomnia symptoms, daytime tiredness, and nap frequency) and (2) understand the connection between transitions in sleep health phenotypes and chronic condition development. We use self-report data from a national sample of adults (N=5,026) taken from the Midlife in the United States (MIDUS) study across two waves (II and III) separated by about ten years. Latent transition analysis revealed four sleep phenotypes: good sleepers (optimal sleep across dimensions), insomnia sleepers (short duration, long sleep onset latency, high daytime tiredness, frequent insomnia symptoms), weekend catch-up sleepers (long sleep duration on weekends compared to weekdays), and nappers (frequent naps). For cardiovascular conditions, consistent insomnia sleepers (i.e., insomnia sleeper -&amp;gt; insomnia sleeper) were at 72% higher risk (CI:[1.04, 2.82]) than consistently good sleepers. For diabetes, consistent insomnia sleepers again were at higher risk (188%; CI:[1.72,4.79]) as were consistent nappers (128%; CI:[1.26,4.09]) and weekend catch-up sleepers -&amp;gt; nappers (137%; CI:[1.21,4.60]). For cancers, only nappers -&amp;gt; insomnia sleepers exhibited higher risk (45%; CI:[1.16,1.83]). We newly identify two sleep health phenotypes (napper and, especially, insomnia sleeper) as risks for developing life-threatening chronic conditions.

ToSleep Dreaming Medals: Sleep Characteristics, Napping Behavior, and Sleep-Hygiene Strategies in Elite Track-and-Field Athletes Facing the Olympic Games of Tokyo 2021.

Few data are available on sleep characteristics of elite track-and-field athletes. Our study aimed to assess (1)differences in sleep between sexes and among different track-and-field disciplines, (2)the effect of individualized sleep-hygiene strategies on athletes' sleep parameters, and (3)daytime nap characteristics in track-and-field athletes. Sleep characteristics of 16 elite Olympic-level track-and-field athletes (male: n = 8; female: n = 8) were assessed during the preseason period, at baseline (T0), and during the in-season period, after the adoption of individualized sleep-hygiene strategies (T1). Sleep parameters were objectively monitored by actigraphy for a minimum of 10 days, for each athlete, at both T0 and T1. A total of 702 nights were analyzed (T0 = 425; T1 = 277). Female athletes displayed better sleep efficiency (88.69 [87.69-89.68] vs 91.72 [90.99-92.45]; P = .003, effect size [ES]: 0.44), lower sleep latency (18.99 [15.97-22.00] vs 6.99 [5.65-8.32]; P < .001, ES: 0.65), higher total sleep time (07:03 [06:56-07:11] vs 07:18 [07:10-07:26]; P = .030, ES: 0.26), earlier bedtime (00:24 [00:16-00:32] vs 00:13 [00:04-00:22]; P = .027, ES: 0.18), and lower nap frequency (P < .001) than maleathletes. Long-distance runners had earlier bedtime (00:10 [00:03-00:38] vs 00:36 [00:26-00:46]; P < .001, ES: 0.41) and wake-up time (07:41 [07:36-07:46] vs 08:18 [08:07-08:30]; P < .001, ES: 0.61), higher nap frequency, but lower sleep efficiency (88.79 [87.80-89.77] vs 91.67 [90.95-92.38]; P = .013, ES: 0.44), and longer sleep latency (18.89 [15.94-21.84] vs 6.69 [5.33-8.06]; P < .001, ES: 0.67) than athletes of short-term disciplines. Furthermore, sleep-hygiene strategies had a positive impact on athletes' total sleep time (429.2 [423.5-434.8] vs 451.4 [444.2-458.6]; P < .001, ES: 0.37) and sleep latency (14.33 [12.34-16.32] vs 10.67 [8.66-12.68]; P = .017, ES: 0.19). Sleep quality and quantity were suboptimal at baseline in Olympic-level track-and-field athletes. Large differences were observed in sleep characteristics between sexes and among different track-and-field disciplines. Given the positive effect of individualized sleep-hygiene strategies on athlete's sleep, coaches should implement sleep education sessions in the daily routine of top-level athletes.

Early morning naps are correlated with incident Alzheimer’s Dementia in older adults

AbstractBackgroundPrevious findings suggest that frequent and longer naps during daytime are associated with elevated risks of Alzheimer’s dementia among older adults. This study aims to further examine whether naps during a particular time of a day are differentially linked to risk of Alzheimer’s dementia.MethodA total of 1,203 participants from the Rush Memory and Aging Project (mean age at actigraphy = 80.85±7.30 years; 77% female) wore accelerometers (Actical) for up to 14 (mean = 9.57±1.17) days and completed annual neurocognitive assessment for up to 17 (mean = 6.92±4.12) years. A validated algorithm was used to identify daytime naps between 9am and 7pm. We categorized participants into those who napped versus those who did not nap during each time period, i.e., morning (9‐11am), noon (11am‐1pm), early afternoon (1‐3pm), late afternoon (3‐5pm), and early evening (5‐7pm). We conducted Cox proportional hazards models to test whether napping at a specific time of day is correlated with incident Alzheimer’s dementia, adjusting for age, sex, education years, length of actigraphy recording, body mass index, intradaily variability of rest‐activity rhythms, and nighttime sleep duration.ResultAmong all participants, 357 developed Alzheimer’s dementia during follow‐up (mean time to incidents = 6.34±3.98 years). Compared to those who did not nap in the morning (9‐11am), participants who napped in the morning had 1.4‐fold (HR[95%CI] = 1.43 [1.07‐1.93], p = 0.01) risk for developing Alzheimer’s dementia. This association was attenuated after further adjusting for total nap duration and frequency (HR[95%CI] = 1.32[0.97‐1.79], p = 0.07). However, napping during other time periods was not associated with risk for Alzheimer’s dementia, after adjusting for the covariates (noon: HR[95%CI] = 1.26[0.94‐1.68], p = 0.12; early afternoon: HR[95%CI] = 1.22[0.81‐1.84], p = 0.33; late afternoon: HR[95%CI] = 1.22[0.81‐1.84], p = 0.34; early evening: HR[95%CI] = 0.84[0.62‐1.13], p = 0.24).ConclusionNapping in the morning may link to an increased risk of Alzheimer’s dementia in older adults. A potential explanation is that individuals who nap more in the morning are more likely to experience disturbances in sleep‐wake regulation. Future studies should investigate this underlying mechanism and test whether interventions to reduce morning naps or consolidate naps can benefit neurocognitive outcomes.

Associations between afternoon napping, left amygdala volume and cognitive performance in elderly with normal cognitive function

BackgroundThe relationship between afternoon napping and cognitive function in the elderly is very complex and the mechanism is unknown. MethodsIn the current study, 194 community elders with normal cognitive functions were included. All subjects completed baseline clinical assessment, baseline neuropsychological test as well as baseline structural MRI. Based on their napping status, these 194 participants were divided into the napping group (n = 88) and the non-napping group (n = 106). We then compared the differences in cognitive performance and structural magnetic resonance between the two groups. ResultsIn the intergroup analysis, we found that the nappers showed poorer cognitive performance on both overall cognitive function and domain specific cognitive function; while on the whole sample, we found a significant negative association (F = 20.27, p<0.001) between afternoon napping and left amygdala volume. However, we did not find any effect of night sleep length or napping frequency on cognitive performance or left amygdala volume. ConclusionsIn community elders with normal cognitive functions, afternoon napping is associated with cognitive performance, and left amygdala may play an important role in this process.

Sleep disturbances among cancer survivors

PurposeWe investigated sleep disturbances among cancer survivors compared to similarly aged women without cancer history. MethodsWe identified 2067 women with a history of cancer other than breast or non-melanoma skin cancer at enrollment in the Sister Study, a US-wide cohort of women with a family history of breast cancer. Cancer survivors were matched with up to 5 cancer-free women (N = 9717) on age at enrollment. An index age (for covariate classification) was defined as the age at cancer diagnosis for survivors and the same age for their matched comparators. Sleep disturbances included duration, sleep medication usage, insomnia symptoms, long sleep-latency onset (≥30 min to fall asleep), frequent night awakenings (waking ≥3/night, ≥ 3 times/week), frequent napping (≥ 3 times/week), and a composite outcome of ≥ 1sleep disturbance. Multivariable linear regression (effect estimate, 95% confidence interval (CI)) and logistic regression (odds ratio, OR, 95% CI) were used for continuous and dichotomous outcomes, respectively. ResultsAt enrollment, cancer survivors were on average 13.8 years (range=0, 62) from diagnosis. After adjustment for age at enrollment and depression, diabetes, hypertension, and menopausal status prior to the index age, sleep disturbances were generally not more common among cancer survivors compared to those without cancer. However, among cancer survivors, those > 2 years from diagnosis were more likely to report ≥ 1 sleep disturbance (OR=1.44; 1.07, 1.93) compared to survivors 0–2 years from diagnosis. ConclusionAddressing sleep disturbances may improve well-being for cancer survivors.

Assessing the daily association of sleep hygiene behaviours with sleep: A between and within persons approach

Sleep hygiene behaviours are recommendations given to both clinical and non-clinical populations with a focus on modifying behaviours to maximise sleep outcomes. However, methodological issues present in sleep hygiene research make it difficult to conclusively determine the impact of each behaviour. This study aimed to address these issues by adopting a two-week, repeated measures design which incorporated objective sleep measures and used linear mixed effect modelling to assess the daily association of a wide range of sleep hygiene behaviours on sleep in a non-clinical, university sample. Between-persons effects revealed that bedtime and frequency of daytime napping, alcohol use, and social media use were negatively related to sleep duration while waketime and frequency of too much water consumption were positively related to sleep duration. Within-person effects revealed that later than usual bedtime, earlier than usual waketime, no sunlight exposure, poor ventilation, having an unpleasant conversation before bed were negatively associated with sleep duration whereas using alcohol to deliberately help full asleep was positively related to sleep duration. In contrast, disproportionately more behaviours were not significantly related to either sleep outcome, only some of which could be explained by individual differences, which suggests that more research is needed to determine the conditions under which these behaviours affect sleep, if at all.